Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
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Alpha Momentum Trade - AMT (QUAD Financial)The "Alpha Momentum Trend" indicator was conceived by Tiago Friedrich and programmed by Conrado Villaça.
The indicator description applies to the daily chart. When used on other timeframes, the indicator also changes its signals based on the timeframe used.
It has five fields, from top to bottom:
1. "ATR Multiple MA" greater than multiple: shows how many candles the asset stayed 7 times the ATR (average true range) above the 50-period simple moving average (SMA) in the last 126 candles. The purpose is to identify the strength of the asset because the more times it stayed at this distance from the SMA 50, the greater the acceleration of its prices tends to be, indicating a high momentum asset. You can change the period of the SMA in the indicator settings.
2. ATR% Multiple from MA: shows the multiple of ATR that the asset is from the same SMA as in the upper field. The default is the SMA 50, and the indicator helps identify interesting regions to take profits from long positions. When the asset is more than 7 ATRs above the SMA 50, the asset is considered "stretched," and a correction or price consolidation becomes likely. For high beta assets with a very strong trend, you can use a multiple of 10 ATRs for this purpose.
3. ATR% Multiple from 52w Low: shows the multiple of ATR that the asset is in relation to the 52-week low price. The higher the number, the more the asset has risen relative to its volatility standards, indicating a stronger trend. For momentum traders, it's ideal for the asset to be at least 15 ATRs above the minimum for this period to ensure that it's in a strong uptrend and far from the lows.
4. Longest streak above SMA: within the last 126 candles, it shows the longest streak of days when the asset didn't close below a specific simple moving average. The default definition is with the 10-day SMA, but you can change it in the indicator settings. The more consecutive days the asset can stay above the SMA10, the sign that its trend is consistent and not very volatile, which is desirable. Ideally, an asset should have previously formed an uptrend by staying at least 20 consecutive days above the SMA10.
5. Longest streak above EMA: within the last 126 candles, it shows the longest streak of days when the asset didn't close below a specific exponential moving average. The default definition is with the 21-day EMA, but you can change it in the indicator settings. The more consecutive days the asset can stay above the EMA21, the sign that its trend is consistent and not very volatile, which is desirable. Ideally, an asset should have previously formed an uptrend by staying at least 35 consecutive days above the EMA21.
It's also possible to visualize on the chart the moving averages used for the calculation of the "ATR Multiple MA," "Longest streak above SMA," and "Longest streak above EMA". In the default configuration, this results in a simple 50-day moving average, a simple 10-day moving average, and an exponential 21-day moving average being displayed on the chart, respectively.
Stochastic Momentum Channel with Volume Filter [IkkeOmar]A stochastic version of my momentum channel volume filter
The "Stochastic Momentum" indicator combines the concepts of Stochastic and Bollinger Bands to provide insights into price momentum and potential trend reversals. It can be used to identify overbought and oversold conditions, as well as potential bullish and bearish signals.
The indicator calculates a Stochastic RSI using the RSI (Relative Strength Index) of a given price source. It applies smoothing to the Stochastic RSI values using moving averages to generate two lines: the %K line and the %D line. The %K line represents the current momentum, while the %D line represents a filtered version of the momentum.
Additionally, the indicator plots Bollinger Bands around the moving average of the Stochastic RSI. The upper and lower bands represent levels where the price is considered relatively high or low compared to its recent volatility. The distance between the bands reflects the current market volatility.
Here's how the indicator can be interpreted:
Stochastic Momentum (%K and %D lines):
When the %K line crosses above the %D line, it suggests a potential upward move or bullish momentum.
When the %K line crosses below the %D line, it indicates a potential downward move or bearish momentum.
The color of the plot changes based on the relationship between the %K and %D lines. Green indicates %K > %D, while red indicates %K < %D.
Bollinger Bands (Upper and Lower Bands):
When the price crosses above the upper band, it suggests an overbought condition, indicating a potential reversal or pullback.
When the price crosses below the lower band, it suggests an oversold condition, indicating a potential reversal or bounce.
To identify potential upward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses above the lower band, it may signal a potential upward move or bounce.
If the %K line crosses above the %D line while the %K line is below the upper band, it may indicate a potential upward move.
To identify potential downward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses below the upper band, it may signal a potential downward move or pullback.
If the %K line crosses below the %D line while the %K line is above the lower band, it may indicate a potential downward move.
Code explanation
Input Variables:
The input function is used to create customizable input variables that can be adjusted by the user.
smoothK and smoothD are inputs for the smoothing periods of the %K and %D lines, respectively.
lengthRSI represents the length of the RSI calculation.
lengthStoch is the length parameter for the stochastic calculation.
volumeFilterLength determines the length of the volume filter used to filter the RSI.
Source Definition:
The src variable is an input that defines the price source used for the calculations.
By default, the close price is used, but the user can choose a different price source.
RSI Calculation:
The rsi1 variable calculates the RSI using the ta.rsi function.
The RSI is a popular oscillator that measures the strength and speed of price movements.
It is calculated based on the average gain and average loss over a specified period.
In this case, the RSI is calculated using the src price source and the lengthRSI parameter.
Volume Filter:
The code calculates a volume filter to filter the RSI values based on the average volume.
The volumeAvg variable calculates the simple moving average of the volume over a specified period (volumeFilterLength).
The filteredRsi variable stores the RSI values that meet the condition of having a volume greater than or equal to the average volume (volume >= volumeAvg).
Stochastic Calculation:
The k variable calculates the %K line of the Stochastic RSI using the ta.stoch function.
The ta.stoch function takes the filtered RSI values (filteredRsi) as inputs and calculates the %K line based on the length parameter (lengthStoch).
The smoothK parameter is used to smooth the %K line by applying a moving average.
The d variable represents the %D line, which is a smoothed version of the %K line obtained by applying another moving average with a period defined by smoothD.
Momentum Calculation:
The kd variable calculates the average of the %K and %D lines, representing the momentum of the Stochastic RSI.
Bollinger Bands Calculation:
The ma variable calculates the moving average of the momentum values (kd) using the ta.sma function with a period defined by bandLength.
The offs variable calculates the offset by multiplying the standard deviation of the momentum values with a factor of 1.6185.
The up and dn variables represent the upper and lower bands, respectively, by adding and subtracting the offset from the moving average.
The Bollinger Bands provide a measure of volatility and can indicate potential overbought and oversold conditions.
Color Assignments:
The colors for the plot and Bollinger Bands are assigned based on certain conditions.
If the %K line is greater than the %D line, the plotCol variable is set to green. Otherwise, it is set to red.
The upCol and dnCol variables are set to different colors based on whether the fast moving average (fastMA) is above or below the upper and lower bands, respectively.
Plotting:
The Stochastic Momentum (%K) is plotted using the plot function with the assigned color (plotCol).
The upper and lower Bollinger Bands are plotted using the plot function with the respective colors (upCol and dnCol).
The fast moving average (fastMA) is plotted in black color to distinguish it from the bands.
The hline function is used to plot horizontal lines representing the upper and lower bands of the Stochastic Momentum.
The code combines the Stochastic RSI, Bollinger Bands, and color logic to provide visual representations of momentum and potential trend reversals. It allows traders to observe the interaction between the Stochastic Momentum lines, the Bollinger Bands, and price movements, enabling them to make informed trading decisions.
Multi Time Frame Trend, Volume and Momentum ProfileWHAT DOES THIS INDICATOR DO?
I created this indicator to address some of the significant inconveniences when analyzing a security, such as continually switching between different time frames to determine the trend and potential pullbacks, adding volume or volume-derived indicators, and finally, something that would help me determine the strength of the trend (maybe two additional indicators here). So I decided to code this all-in-one indicator that you can add multiple times to your chart depending on the settings you want to use, or just optimize the parameters for the particular asset and then switch between the options.
As the name suggests, it consists of three main sections - Trend , Volume , and Momentum . You have complete control over the parameters, including the Time Frames you want to use for each one (they can be different). So, let me explain each section in more detail.
HOW DOES THE INDICATOR WORK?
1. Trend Settings
In order to determine the trend, you need to set up two Moving Averages. You have a wide choice here - SMA, EMA, WMA, RMA, HMA, DEMA, TEMA, VWMA, and ALMA. Since the indicator does not plot the moving averages on the chart, I strongly suggest using this indicator along with the free "Trend Indicator for Directional Trading(main)" , which you can find in the Public Library. Once you set up the Trend Resolution, the Types of MAs, and their lengths, the indicator will generate a histogram of their convergences and divergences.
The change in colors should help you more easily determine the trend:
a) Bright Green - bull trend and price trending up (a good place to open long)
b) Dark Green - bull trend and price trending down (stay flat or open a long position with great caution)
c) Bright Red - bear trend and price trending down (a good place to open short)
d) Dark Red - bear trend and price trending up (stay flat or open a short position with great caution)
e) In addition, you can change the color palette to reflect the bull/bear trend momentum by scrolling to the bottom and selecting "Color Based on Bull/Bear Momentum", but I will discuss this in more detail below.
This part of the indicator is useful for opening a trade in the direction of the trend or for spotting a potential divergence. Both cases are illustrated below.
2. Volume Settings
The calculations for this part of the indicator are partially taken from "Multi Time Frame Effective Volume Profile" . I will quickly outline the specifics here, but if you want a more thorough understanding of how it works, please check the description of the MTF Effective Volume Profile indicator .
You have three elements with the following default settings - Resolution (5-min), Lookback (100), and Average (1). This means that the indicator will analyze the last one hundred 5-min bars and will plot a sum of only those that are at least 1 times bigger than the average. Those that are smaller than the average will be left out from the calculation. What you get is a trend line showing you accumulation/distribution based on modified volume parameters.
This part of the indicator is useful for spotting exhaustions and increased buying/selling volume that is opposite to the price trend. As you will see in the picture below, in frame 1 the selling pressure is decreasing, while buying volume is increasing. At one point supply dries out and the bulls take control, thus reverting the price. In frame 2, however, you can see that the higher high is not met with nearly as much buying volume as in the previous peak, showing that the bulls are exhausted and maybe a trend change will follow or at the very least that the bull trend will take a break.
3. Momentum Settings
The final part is an RSI smoothed through a Moving Average with the addition of some minor optimizations. Thus, the parameters you have to configure here aside from the resolution are the RSI length, the moving average that will be used, and its length. Out of the three, this is the most lagging component, but it's also the most accurate one. I must mention that due to the modified nature of this RSI, overbought and oversold levels carry less weight to the trading signals. Rather, pay attention to the change of colors, as they do so when the RSI changes direction based on preset parameters. The picture below shows such instances.
4. Additional Settings
This section consists of 4 elements:
a) Length of Trend - filters out the noise and gives a signal only when the trend becomes more established
b) ADX Threshold - filters out trading ranges and indecision zones when it's not recommended to open a trade
c) Select Analysis - choose what part of the indicator you want to see from a drop-down menu
d) Color Based on Bull/Bear Momentum - a global setting that will override the preset coloring of each indicator and will replace it with colors based on bull/bear strength and momentum - green for bulls, red for bears, and gray for non-trading zones.
The last part of this indicator is a combination of all of the above and is called a Points-Based System . It generates 3 rows of dots that go light green when bull criteria are met, orange when bear criteria are met, or gray when it's neither of the two. When you get a column of 3 green dots you get a buy signal. Similarly, a column of 3 orange dots gives you a sell signal. Grey zones are non-tradeable. It goes without saying that the frequency and quality of the signals you get will almost entirely depend on your settings, so feel free to experiment and adjust the indicator to catch the best moves for the given security.
In terms of indicator adjustments, I have left almost every part open to configuration. That is 15 parameters and 35 adjustable colors.
HOW MUCH DOES THE INDICATOR COST ?
As much as I would like to offer it for free (as some of my other ones), a great deal of work, trading logic, and testing have gone into creating this indicator. More than a few hundred iterations and a few dozen branches were required to reach the end result which is a precise combination of usefulness, simplicity, and practicality. Furthermore, this indicator will continue to be updated and user-requested features that improve its performance will be added.
Disclaimer: The purpose of all indicators is to indicate potential setups, which may lead to profitable results. No indicator is perfect and certainly, no indicator has a 100% success rate. They are subject to flaws, wrongful interpretation, bugs, etc. This indicator makes no exception. It must be used with a sound money management plan that puts the main emphasis on protecting your capital. Please, do not rely solely on any single indicator to make trading decisions instead of you. Indicators are storytellers, not fortune tellers. They help you see the bigger picture, not the future.
To find out more about how to gain access to this indicator, please use the provided information below or just message me. Thank you for your time.
Volatility Based Momentum Oscillator (VBMO)There is a frequent and definitive pattern in price movement, whereby price will steadily drift lower, then accelerate before bottoming out. Similarly, price will often steadily rise, then accelerate into a climax top.
The Volatility Based Momentum Oscillator (VBMO) is designed to delineate between steady versus more accelerated and climactic price movements.
VBMO is calculated using a short-term moving average, the distance of price from this moving average, and the trading instrument’s historical volatility. Even though VBMO’s calculation is relatively simple, the resulting values can help traders identify, analyze and act upon many scenarios, such as climax tops, reversals, and capitulation. Moreover, since the units and scale for VBMO are always the same, the indicator can be used in a consistent manner across multiple timeframes and instruments.
For more details, there is an article further describing VBMO and its applicability.
VMDM - Volume, Momentum & Divergence Master [BullByte]VMDM - Volume, Momentum and Divergence Master
Educational Multi-Layer Market Structure Analysis System
Multi-factor divergence engine that scores RSI momentum, volume pressure, and institutional footprints into one non-repainting confluence rating (0-100).
WHAT THIS INDICATOR IS
VMDM is an educational indicator designed to teach traders how to recognize high-probability reversal and continuation patterns by analyzing four independent market dimensions simultaneously. Instead of relying on a single indicator that may produce frequent false signals, VMDM creates a confluence-based scoring system that weights multiple confirmation factors, helping you understand which setups have stronger technical backing and which are lower quality.
This is NOT a trading system or signal generator. It is a learning tool that visualizes complex market structure concepts in an accessible format for both coders and non-coders.
THE PROBLEM IT SOLVES
Most traders face these common challenges:
Challenge 1 - Indicator Overload: Running RSI, volume analysis, and divergence detection separately creates chart clutter and conflicting signals. You waste time cross-referencing multiple windows trying to determine if all factors align.
Challenge 2 - False Divergences: Standard divergence indicators trigger on every minor pivot, creating noise. Many divergences fail because they lack supporting evidence from volume or market structure.
Challenge 3 - Missed Context: A bullish RSI divergence means nothing if it occurs during weak volume or in the middle of strong distribution. Context determines quality.
Challenge 4 - Repainting Confusion: Many divergence scripts repaint, showing perfect historical signals that never actually triggered in real-time, leading to false confidence.
Challenge 5 - Institutional Pattern Recognition: Absorption zones, stop hunts, and exhaustion patterns are taught in trading education but difficult to identify systematically without manual analysis.
VMDM addresses all five challenges by combining complementary analytical layers into one transparent, non-repainting, confluence-weighted system with visual clarity.
WHY THIS SPECIFIC COMBINATION - MASHUP JUSTIFICATION
This indicator is NOT a random mashup of popular indicators. Each of the four layers serves a specific analytical purpose and together they create a complete market structure assessment framework.
THE FOUR ANALYTICAL LAYERS
LAYER 1 - RSI MOMENTUM DIVERGENCE (Trend Exhaustion Detection)
Purpose: Identifies when price momentum is weakening before price itself reverses.
Why RSI: The Relative Strength Index measures momentum on a bounded 0-100 scale, making divergence detection mathematically consistent across all assets and timeframes. Unlike raw price oscillators, RSI normalizes momentum regardless of volatility regime.
How It Contributes: Divergence between price pivots and RSI pivots reveals early momentum exhaustion. A lower price low with a higher RSI low (bullish regular divergence) signals sellers are losing strength even as price makes new lows. This is the PRIMARY signal generator in VMDM.
Limitation If Used Alone: RSI divergence by itself produces many false signals because momentum can remain weak during continued trends. It needs confirmation from volume and structural evidence.
LAYER 2 - VOLUME PRESSURE ANALYSIS (Buying vs Selling Intensity)
Purpose: Quantifies whether the current bar's volume reflects buying pressure or selling pressure based on where price closed within the bar's range.
Methodology: Instead of just measuring volume size, VMDM calculates WHERE in the bar range the close occurred. A close near the high on high volume indicates strong buying absorption. A close near the low indicates selling pressure. The calculation accounts for wick size (wicks reduce pressure quality) and uses percentile ranking over a lookback period to normalize pressure strength on a 0-100 scale.
Formula Concept:
Buy Pressure = Volume × (Close - Low) / (High - Low) × Wick Quality Factor
Sell Pressure = Volume × (High - Close) / (High - Low) × Wick Quality Factor
Net Pressure = Buy Pressure - Sell Pressure
Pressure Strength = Percentile Rank of Net Pressure over lookback period
Why Percentile Ranking: Absolute volume varies by asset and session. Percentile ranking makes 85th percentile pressure on low-volume crypto comparable to 85th percentile pressure on high-volume forex.
How It Contributes: When a bullish divergence occurs at a pivot low AND pressure strength is above 60 (strong buying), this adds 25 confluence points. It confirms that the divergence is occurring during actual accumulation, not just weak selling.
Limitation If Used Alone: Pressure analysis shows current bar intensity but cannot identify trend exhaustion or reversal timing. High buying pressure can exist during a strong uptrend with no reversal imminent.
LAYER 3 - BEHAVIORAL FOOTPRINT PATTERNS (Volume Anomaly Detection)
CRITICAL DISCLAIMER: The terms "institutional footprint," "absorption," "stop hunt," and "exhaustion" used in this indicator are EDUCATIONAL LABELS for specific price and volume behavioral patterns. These patterns are detected through technical analysis of publicly available price, volume, and bar structure data. This indicator does NOT have access to actual institutional order flow, market maker data, broker stop-loss locations, or any non-public data source. These pattern names are used because they are common terminology in trading education to describe these technical behaviors. The analysis is interpretive and based on observable price action, not privileged information.
Purpose: Detect volume anomalies and price patterns that historically correlate with potential reversal zones or trend continuation failure.
Pattern Type 1 - Absorption (Labeled as "ACCUMULATION" or "DISTRIBUTION")
Detection Criteria: Volume is more than 2x the moving average AND bar range is less than 50 percent of the average bar range.
Interpretation: High volume compressed into a tight range suggests large participants are absorbing supply (accumulation) or distribution (distribution) without allowing price to move significantly. This often precedes directional moves once absorption completes.
Visual: Colored box zone highlighting the absorption area.
Pattern Type 2 - Stop Hunt (Labeled as "BULL HUNT" or "BEAR HUNT")
Detection Criteria: Price penetrates a recent 10-bar high or low by a small margin (0.2 percent), then closes back inside the range on above-average volume (1.5x+).
Interpretation: Price briefly spikes beyond recent structure (likely triggering stop losses placed just beyond obvious levels) then reverses. This is a classic false breakout pattern often seen before reversals.
Visual: Label at the wick extreme showing hunt direction.
Pattern Type 3 - Exhaustion (Labeled as "SELL EXHAUST" or "BUY EXHAUST")
Detection Criteria: Lower wick is more than 2.5x the body size with volume above 1.8x average and RSI below 35 (sell exhaustion), OR upper wick more than 2.5x body size with volume above 1.8x average and RSI above 65 (buy exhaustion).
Interpretation: Large wicks with high volume and extreme RSI suggest aggressive buying or selling was met with equally aggressive rejection. This exhaustion often marks short-term extremes.
Visual: Label showing exhaustion type.
How These Contribute: When a divergence forms at a pivot AND one of these behavioral patterns is active, the confluence score increases by 20 points. This confirms the divergence is occurring during structural anomaly activity, not just normal price flow.
Limitation If Used Alone: These patterns can occur mid-trend and do not indicate direction without momentum context. Absorption in a strong uptrend may just be continuation accumulation.
LAYER 4 - CONFLUENCE SCORING MATRIX (Quality Weighting System)
Purpose: Translate all detected conditions into a single 0-100 quality score so you can objectively compare setups.
Scoring Breakdown:
Divergence Present: +30 points (primary signal)
Pressure Confirmation: +25 points (volume supports direction)
Behavioral Footprint Active: +20 points (structural anomaly present)
RSI Extreme: +15 points (RSI below 30 or above 70 at pivot)
Volume Spike: +10 points (current volume above 1.5x average)
Maximum Possible Score: 100 points
Why These Weights: The weights reflect reliability hierarchy based on backtesting observation. Divergence is the core signal (30 points), but without volume confirmation (25 points) many fail. Behavioral patterns add meaningful context (20 points). RSI extremes and volume spikes are secondary confirmations (15 and 10 points).
Quality Tiers:
90-100: TEXTBOOK (all factors aligned)
75-89: HIGH QUALITY (strong confluence)
60-74: VALID (meets minimum threshold)
Below 60: DEVELOPING (not displayed unless threshold lowered)
How It Contributes: The confluence score allows you to filter noise. You can set your minimum quality threshold in settings. Higher thresholds (75+) show fewer but higher-quality patterns. Lower thresholds (50-60) show more patterns but include lower-confidence setups. This teaches you to distinguish strong setups from weak ones.
Limitation: Confluence scoring is historical observation-based, not predictive guarantee. A 95-point setup can still fail. The score represents technical alignment, not future certainty.
WHY THIS COMBINATION WORKS TOGETHER
Each layer addresses a limitation in the others:
RSI Divergence identifies WHEN momentum is exhausting (timing)
Volume Pressure confirms WHETHER the exhaustion is accompanied by opposite-side accumulation (confirmation)
Behavioral Footprint shows IF structural anomalies support the reversal hypothesis (context)
Confluence Scoring weights ALL factors into an objective quality metric (filtering)
Using only RSI divergence gives you timing without confirmation. Using only volume pressure gives you intensity without directional context. Using only pattern detection gives you anomalies without trend exhaustion context. Using all four together creates a complete analytical framework where each layer compensates for the others' weaknesses.
This is not a mashup for the sake of combining indicators. It is a structured analytical system where each component has a defined role in a multi-dimensional market assessment process.
HOW TO READ THE INDICATOR - VISUAL ELEMENTS GUIDE
VMDM displays up to five visual layer types. You can enable or disable each layer independently in settings under "Visual Layers."
VISUAL LAYER 1 - MARKET STRUCTURE (Pivot Points and Lines)
What You See:
Small labels at swing highs and lows marked "PH" (Pivot High) and "PL" (Pivot Low) with horizontal dashed lines extending right from each pivot.
What It Means:
These are CONFIRMED pivots, not real-time. A pivot low appears AFTER the required right-side confirmation bars pass (default 3 bars). This creates a delay but prevents repainting. The pivot only appears once it is mathematically confirmed.
The horizontal lines represent support (from pivot lows) and resistance (from pivot highs) levels where price previously found significant rejection.
Color Coding:
Green label and line: Pivot Low (potential support)
Red label and line: Pivot High (potential resistance)
How To Use:
These pivots are the foundation for divergence detection. Divergence is only calculated between confirmed pivots, ensuring all signals are non-repainting. The lines help you see historical structure levels.
VISUAL LAYER 2 - PRESSURE ZONES (Background Color)
What You See:
Subtle background color shading on bars - light green or light red tint.
What It Means:
This visualizes volume pressure strength in real-time.
Color Coding:
Light Green Background: Pressure Strength above 70 (strong buying pressure - price closing near highs on volume)
Light Red Background: Pressure Strength below 30 (strong selling pressure - price closing near lows on volume)
No Color: Neutral pressure (pressure between 30-70)
How To Use:
When a bullish divergence pattern appears during green pressure zones, it suggests the divergence is forming during accumulation. When a bearish divergence appears during red zones, distribution is occurring. Pressure zones help you filter divergences - those forming in supportive pressure environments have higher probability.
VISUAL LAYER 3 - DIVERGENCE LINES (Dotted Connectors)
What You See:
Dotted lines connecting two pivot points (either two pivot lows or two pivot highs).
What It Means:
A divergence has been detected between those two pivots. The line connects the price pivots where RSI showed opposite behavior.
Color Coding:
Bright Green Line: Bullish divergence (regular or hidden)
Bright Red Line: Bearish divergence (regular or hidden)
How To Use:
The divergence line appears ONLY after the second pivot is confirmed (delayed by right-side confirmation bars). This is intentional to prevent repainting. When you see the line appear, it means:
For Bullish Regular Divergence:
Price made a lower low (second pivot lower than first)
RSI made a higher low (RSI at second pivot higher than first)
Interpretation: Downtrend losing momentum
For Bullish Hidden Divergence:
Price made a higher low (second pivot higher than first)
RSI made a lower low (RSI at second pivot lower than first)
Interpretation: Uptrend continuation likely (pullback within uptrend)
For Bearish Regular Divergence:
Price made a higher high (second pivot higher than first)
RSI made a lower high (RSI at second pivot lower than first)
Interpretation: Uptrend losing momentum
For Bearish Hidden Divergence:
Price made a lower high (second pivot lower than first)
RSI made a higher high (RSI at second pivot higher than first)
Interpretation: Downtrend continuation likely (bounce within downtrend)
If "Show Consolidated Analysis Label" is disabled, a small label will appear on the divergence line showing the divergence type abbreviation.
VISUAL LAYER 4 - BEHAVIORAL FOOTPRINT MARKERS
What You See:
Boxes, labels, and markers at specific bars showing pattern detection.
ABSORPTION ZONES (Boxes):
Colored rectangular boxes spanning one or more bars.
Purple Box: Accumulation absorption zone (high volume, tight range, bullish close)
Red Box: Distribution absorption zone (high volume, tight range, bearish close)
If absorption continues for multiple consecutive bars, the box extends and a counter appears in the label showing how many bars the absorption lasted.
What It Means: Large volume is being absorbed without significant price movement. This often precedes directional breakouts once the absorption phase completes.
STOP HUNT MARKERS (Labels):
Small labels below or above wicks labeled "BULL HUNT" or "BEAR HUNT" (may show bar count if consecutive).
What It Means:
BULL HUNT : Price spiked below recent lows then reversed back up on volume - likely triggered sell stops before reversing
BEAR HUNT : Price spiked above recent highs then reversed back down on volume - likely triggered buy stops before reversing
EXHAUSTION MARKERS (Labels):
Labels showing "SELL EXHAUST" or "BUY EXHAUST."
What It Means:
SELL EXHAUST : Large lower wick with high volume and low RSI - aggressive selling met with strong rejection
BUY EXHAUST : Large upper wick with high volume and high RSI - aggressive buying met with strong rejection
How To Use:
These markers help you identify WHERE structural anomalies occurred. When a divergence signal appears AT THE SAME TIME as one of these patterns, the confluence score increases. You are looking for alignment - divergence + behavioral pattern + pressure confirmation = high-quality setup.
VISUAL LAYER 5 - CONSOLIDATED ANALYSIS LABEL (Main Pattern Signal)
What You See:
A large label appearing at pivot points (or in real-time mode, at current bar) containing full pattern analysis.
Label Appearance:
Depending on your "Use Compact Label Format" setting:
COMPACT MODE (Single Line):
Example: "BULLISH REGULAR | Q:HIGH QUALITY C:82"
Breakdown:
BULLISH REGULAR: Divergence type detected
Q:HIGH QUALITY: Pattern quality tier
C:82: Confluence score (82 out of 100)
FULL MODE (Multi-Line Detailed):
Example:
PATTERN DETECTED
-------------------
BULLISH REGULAR
Quality: HIGH QUALITY
Price: Lower Low
Momentum: Higher Low
Signal: Weakening Downtrend
CONFLUENCE: 82/100
-------------------
Divergence: 30
Pressure: 25
Institutional: 20
RSI Extreme: 0
Volume: 10
Breakdown:
Top section: Pattern type and quality
Middle section: Divergence explanation (what price did vs what RSI did)
Bottom section: Confluence score with itemized breakdown showing which factors contributed
Label Position:
In Confirmed modes: Label appears AT the pivot point (delayed by confirmation bars)
In Real-time mode: Label appears at current bar as conditions develop
Label Color:
Gold: Textbook quality (90+ confluence)
Green: High quality (75-89 confluence)
Blue: Valid quality (60-74 confluence)
How To Use:
This is your primary decision-making label. When it appears:
Check the divergence type (regular divergences are reversal signals, hidden divergences are continuation signals)
Review the quality tier (textbook and high quality have better historical win rates)
Examine the confluence breakdown to see which factors are present and which are missing
Look at the chart context (trend, support/resistance, timeframe)
Use this information to assess whether the setup aligns with your strategy
The label does NOT tell you to buy or sell. It tells you a technical pattern has formed and provides the quality assessment. Your trading decision must incorporate risk management, market context, and your strategy rules.
UNDERSTANDING THE THREE DETECTION MODES
VMDM offers three signal detection modes in settings to accommodate different trading styles and learning objectives.
MODE 1: "Confluence Only (Real-Time)"
How It Works: Displays signals AS THEY DEVELOP on the current bar without waiting for pivot confirmation. The system calculates confluence score from pressure, volume, RSI extremes, and behavioral patterns. Divergence signals are NOT required in this mode.
Delay: ZERO - signals appear immediately.
Use Case: Real-time scanning for high-confluence zones without divergence requirement. Useful for intraday traders who want immediate alerts when multiple factors align.
Tradeoff: More frequent signals but includes setups without confirmed divergence. Higher false signal rate. Signals can change as the bar develops (not repainting in historical bars, but current bar updates).
Visual Behavior: Labels appear at the current bar. No divergence lines unless divergence happens to be present.
MODE 2: "Divergence + Confluence (Confirmed)" - DEFAULT RECOMMENDED
How It Works: Full system engagement. Signals appear ONLY when:
A pivot is confirmed (requires right-side confirmation bars to pass)
Divergence is detected between current pivot and previous pivot
Total confluence score meets or exceeds your minimum threshold
Delay: Equal to your "Pivot Right Bars" setting (default 3 bars). This means signals appear 3 bars AFTER the actual pivot formed.
Use Case: Highest-quality, non-repainting signals for swing traders and learners who want to study confirmed pattern completion.
Tradeoff: Delayed signals. You will not receive the signal until confirmation occurs. In fast-moving markets, price may have already moved significantly by the time the signal appears.
Visual Behavior: Labels appear at the historical pivot location (in the past). Divergence lines connect the two pivots. This is the most educational mode because it shows completed, confirmed patterns.
Non-Repainting Guarantee: Yes. Once a signal appears, it never disappears or changes.
MODE 3: "Divergence + Confluence (Relaxed)"
How It Works: Same as Confirmed mode but with adaptive thresholds. If confluence is very high (10 points above threshold), the signal may appear even if some factors are weak. If divergence is present but confluence is slightly below threshold (within 10 points), it may still appear.
Delay: Same as Confirmed mode (right-side confirmation bars).
Use Case: Slightly more signals than Confirmed mode for traders willing to accept near-threshold setups.
Tradeoff: More signals but lower average quality than Confirmed mode.
Visual Behavior: Same as Confirmed mode.
DASHBOARD GUIDE - READING THE METRICS
The dashboard appears in the corner of your chart (position selectable in settings) and provides real-time market state analysis.
You can choose between four dashboard detail levels in settings: Off, Compact, Optimized (default), Full.
DASHBOARD ROW EXPLANATIONS
ROW 1 - Header Information
Left: Current symbol and timeframe
Center: "VMDM "
Right: Version number
ROW 2 - Mode and Delay
Shows which detection mode you are using and the signal delay.
Example: "CONFIRMED | Delay: 3 bars"
This reminds you that signals in confirmed mode appear 3 bars after the pivot forms.
ROW 3 - Market Regime
Format: "TREND UP HV" or "RANGING NV"
First Part - Trend State:
TREND UP: 20 EMA above 50 EMA with strong separation
TREND DOWN: 20 EMA below 50 EMA with strong separation
RANGING: EMAs close together, low trend strength
TRANSITION: Between trending and ranging states
Second Part - Volatility State:
HV: High Volatility (current ATR more than 1.3x the 50-bar average ATR)
NV: Normal Volatility (current ATR between 0.7x and 1.3x average)
LV: Low Volatility (current ATR less than 0.7x average)
Third Column: Volatility ratio (example: "1.45x" means current ATR is 1.45 times normal)
How To Use: Regime context helps you interpret signals. Reversal divergences are more reliable in ranging or transitional regimes. Continuation divergences (hidden) are more reliable in trending regimes. High volatility means wider stops may be needed.
ROW 4 - Pressure
Shows current volume pressure state.
Format: "BUYING | ██████████░░░░░░░░░"
States:
BUYING : Pressure strength above 60 (closes near highs)
SELLING : Pressure strength below 40 (closes near lows)
NEUTRAL : Pressure strength between 40-60
Bar Visualization: Each block represents 10 percentile points. A full bar (10 filled blocks) = 100th percentile pressure.
Color: Green for buying, red for selling, gray for neutral.
How To Use: When pressure aligns with divergence direction (bullish divergence during buying pressure), confluence is stronger.
ROW 5 - Volume and RSI
Format: "1.8x | RSI 68 | OB"
First Value: Current volume ratio (1.8x = volume is 1.8 times the moving average)
Second Value: Current RSI reading
Third Value: RSI state
OB: Overbought (RSI above 70)
OS: Oversold (RSI below 30)
Blank: Neutral RSI
How To Use: Volume spikes (above 1.5x) during divergence formation add confluence. RSI extremes at pivots add confluence.
ROW 6 - Behavioral Footprint
Format: "BULL HUNT | 2 bars"
Shows the most recent behavioral pattern detected and how long ago.
States:
ACCUMULATION / DISTRIBUTION: Absorption detected
BULL HUNT / BEAR HUNT: Stop hunt detected
SELL EXHAUST / BUY EXHAUST: Exhaustion detected
SCANNING: No recent pattern
NOW: Pattern is active on current bar
How To Use: When footprint activity is recent (within 50 bars) or active now, it adds context to divergence signals forming in that area.
ROW 7 - Current Pattern
Shows the divergence type currently detected (if any).
Examples: "BULLISH REGULAR", "BEARISH HIDDEN", "Scanning..."
Quality: Shows pattern quality (TEXTBOOK, HIGH QUALITY, VALID)
How To Use: This tells you what type of signal is active. Regular divergences are reversal setups. Hidden divergences are continuation setups.
ROW 8 - Session Summary
Format: "14 events | A3 H8 E3"
First Value: Total institutional events this session
Breakdown:
A: Absorption events
H: Stop hunt events
E: Exhaustion events
How To Use: High event counts suggest an active, volatile session with frequent structural anomalies. Low counts suggest quiet, orderly price action.
ROW 9 - Confluence Score (Optimized/Full mode only)
Format: "78/100 | ████████░░"
Shows current real-time confluence score even if no pattern is confirmed yet.
How To Use: Watch this in real-time to see how close you are to pattern formation. When it exceeds your threshold and divergence forms, a signal will appear (after confirmation delay).
ROW 10 - Patterns Studied (Optimized/Full mode only)
Format: "47 patterns | 12 bars ago"
First Value: Total confirmed patterns detected since chart loaded
Second Value: How many bars since the last confirmed pattern appeared
How To Use: Helps you understand pattern frequency on your selected symbol and timeframe. If many bars have passed since last pattern, market may be trending without reversal opportunities.
ROW 11 - Bull/Bear Ratio (Optimized/Full mode only)
Format: "28:19 | BULL"
Shows count of bullish vs bearish patterns detected.
Balance:
BULL: More bullish patterns detected (suggests market has had more bullish reversals/continuations)
BEAR: More bearish patterns detected
BAL: Equal counts
How To Use: Extreme imbalances can indicate directional bias in the studied period. A heavily bullish ratio in a downtrend might suggest frequent failed rallies (bearish continuation). Context matters.
ROW 12 - Volume Ratio Detail (Optimized/Full mode only)
Shows current volume vs average volume in absolute terms.
Example: "1.4x | 45230 / 32300"
How To Use: Confirms whether current activity is above or below normal.
ROW 13 - Last Institutional Event (Full mode only)
Shows the most recent institutional pattern type and how many bars ago it occurred.
Example: "DISTRIBUTION | 23 bars"
How To Use: Tracks recency of last anomaly for context.
SETTINGS GUIDE - EVERY PARAMETER EXPLAINED
PERFORMANCE SECTION
Enable All Visuals (Master Toggle)
Default: ON
What It Does: Master kill switch for ALL visual elements (labels, lines, boxes, background colors, dashboard). When OFF, only plot outputs remain (invisible unless you open data window).
When To Change: Turn OFF on mobile devices, 1-second charts, or slow computers to improve performance. You can still receive alerts even with visuals disabled.
Impact: Dramatic performance improvement when OFF, but you lose all visual feedback.
Maximum Object History
Default: 50 | Range: 10-100
What It Does: Limits how many of each object type (labels, lines, boxes) are kept in memory. Older objects beyond this limit are deleted.
When To Change: Lower to 20-30 on fast timeframes (1-minute charts) to prevent slowdown. Increase to 100 on daily charts if you want more historical pattern visibility.
Impact: Lower values = better performance but less historical visibility. Higher values = more history visible but potential slowdown on fast timeframes.
Alert Cooldown (Bars)
Default: 5 | Range: 1-50
What It Does: Minimum number of bars that must pass before another alert of the same type can fire. Prevents alert spam when multiple patterns form in quick succession.
When To Change: Increase to 20+ on 1-minute charts to reduce noise. Decrease to 1-2 on daily charts if you want every pattern alerted.
Impact: Higher cooldown = fewer alerts. Lower cooldown = more alerts.
USER EXPERIENCE SECTION
Show Enhanced Tooltips
Default: ON
What It Does: Enables detailed hover-over tooltips on labels and visual elements.
When To Change: Turn OFF if you encounter Pine Script compilation errors related to tooltip arguments (rare, platform-specific issue).
Impact: Minimal. Just adds helpful hover text.
MARKET STRUCTURE DETECTION SECTION
Pivot Left Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the LEFT of the center bar that must be higher (for pivot low) or lower (for pivot high) than the center bar for a pivot to be valid.
Example: With value 3, a pivot low requires the center bar's low to be lower than the 3 bars to its left.
When To Change:
Increase to 5-7 on noisy timeframes (1-minute charts) to filter insignificant pivots
Decrease to 2 on slow timeframes (daily charts) to catch more pivots
Impact: Higher values = fewer, more significant pivots = fewer signals. Lower values = more frequent pivots = more signals but more noise.
Pivot Right Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the RIGHT of the center bar that must pass for confirmation. This creates the non-repainting delay.
Example: With value 3, a pivot is confirmed 3 bars AFTER it forms.
When To Change:
Increase to 5-7 for slower, more confirmed signals (better for swing trading)
Decrease to 2 for faster signals (better for intraday, but still non-repainting)
Impact: Higher values = longer delay but more reliable confirmation. Lower values = faster signals but less confirmation. This setting directly controls your signal delay in Confirmed and Relaxed modes.
Minimum Confluence Score
Default: 60 | Range: 40-95
What It Does: The threshold score required for a pattern to be displayed. Patterns with confluence scores below this threshold are not shown.
When To Change:
Increase to 75+ if you only want high-quality textbook setups (fewer signals)
Decrease to 50-55 if you want to see more developing patterns (more signals, lower average quality)
Impact: This is your primary signal filter. Higher threshold = fewer, higher-quality signals. Lower threshold = more signals but includes weaker setups. Recommended starting point is 60-65.
TECHNICAL PERIODS SECTION
RSI Period
Default: 14 | Range: 5-50
What It Does: Lookback period for RSI calculation.
When To Change:
Decrease to 9-10 for faster, more sensitive RSI that detects shorter-term momentum changes
Increase to 21-28 for slower, smoother RSI that filters noise
Impact: Lower values make RSI more volatile (more frequent extremes and divergences). Higher values make RSI smoother (fewer but more significant divergences). 14 is industry standard.
Volume Moving Average Period
Default: 20 | Range: 10-200
What It Does: Lookback period for calculating average volume. Current volume is compared to this average to determine volume ratio.
When To Change:
Decrease to 10-14 for shorter-term volume comparison (more sensitive to recent volume changes)
Increase to 50-100 for longer-term volume comparison (smoother, less sensitive)
Impact: Lower values make volume ratio more volatile. Higher values make it more stable. 20 is standard.
ATR Period
Default: 14 | Range: 5-100
What It Does: Lookback period for Average True Range calculation used for volatility measurement and label positioning.
When To Change: Rarely needs adjustment. Use 7-10 for faster volatility response, 21-28 for slower.
Impact: Affects volatility ratio calculation and visual label spacing. Minimal impact on signals.
Pressure Percentile Lookback
Default: 50 | Range: 10-300
What It Does: Lookback period for calculating volume pressure percentile ranking. Your current pressure is ranked against the pressure of the last X bars.
When To Change:
Decrease to 20-30 for shorter-term pressure context (more responsive to recent changes)
Increase to 100-200 for longer-term pressure context (smoother rankings)
Impact: Lower values make pressure strength more sensitive to recent bars. Higher values provide more stable, long-term pressure assessment. Capped at 300 for performance reasons.
SIGNAL DETECTION SECTION
Signal Detection Mode
Default: "Divergence + Confluence (Confirmed)"
Options:
Confluence Only (Real-time)
Divergence + Confluence (Confirmed)
Divergence + Confluence (Relaxed)
What It Does: Selects which detection logic mode to use (see "Understanding The Three Detection Modes" section above).
When To Change: Use Confirmed for learning and non-repainting signals. Use Real-time for live scanning without divergence requirement. Use Relaxed for slightly more signals than Confirmed.
Impact: Fundamentally changes when and how signals appear.
VISUAL LAYERS SECTION
All toggles default to ON. Each controls visibility of one visual layer:
Show Market Structure: Pivot markers and support/resistance lines
Show Pressure Zones: Background color shading
Show Divergence Lines: Dotted lines connecting pivots
Show Institutional Footprint Markers: Absorption boxes, hunt labels, exhaustion labels
Show Consolidated Analysis Label: Main pattern detection label
Use Compact Label Format
Default: OFF
What It Does: Switches consolidated label between single-line compact format and multi-line detailed format.
When To Change: Turn ON if you find full labels too large or distracting.
Impact: Visual clarity vs. information density tradeoff.
DASHBOARD SECTION
Dashboard Mode
Default: "Optimized"
Options: Off, Compact, Optimized, Full
What It Does: Controls how much information the dashboard displays.
Off: No dashboard
Compact: 8 rows (essential metrics only)
Optimized: 12 rows (recommended balance)
Full: 13 rows (every available metric)
Dashboard Position
Default: "Top Right"
Options: Top Right, Top Left, Bottom Right, Bottom Left
What It Does: Screen corner where dashboard appears.
HOW TO USE VMDM - PRACTICAL WORKFLOW
STEP 1 - INITIAL SETUP
Add VMDM to your chart
Select your detection mode (Confirmed recommended for learning)
Set your minimum confluence score (start with 60-65)
Adjust pivot parameters if needed (default 3/3 is good for most timeframes)
Enable the visual layers you want to see
STEP 2 - CHART ANALYSIS
Let the indicator load and analyze historical data
Review the patterns that appear historically
Examine the confluence scores - notice which patterns had higher scores
Observe which patterns occurred during supportive pressure zones
Notice the divergence line connections - understand what price vs RSI did
STEP 3 - PATTERN RECOGNITION LEARNING
When a consolidated analysis label appears:
Read the divergence type (regular or hidden, bullish or bearish)
Check the quality tier (textbook, high quality, or valid)
Review the confluence breakdown - which factors contributed
Look at the chart context - where is price relative to structure, trend, etc.
Observe the behavioral footprint markers nearby - do they support the pattern
STEP 4 - REAL-TIME MONITORING
Watch the dashboard for real-time regime and pressure state
Monitor the current confluence score in the dashboard
When it approaches your threshold, be alert for potential pattern formation
When a new pattern appears (after confirmation delay), evaluate it using the workflow above
Use your trading strategy rules to decide if the setup aligns with your criteria
STEP 5 - POST-PATTERN OBSERVATION
After a pattern appears:
Mark the level on your chart
Observe what price does after the pattern completes
Did price respect the reversal/continuation signal
What was the confluence score of patterns that worked vs. those that failed
Learn which quality tiers and confluence levels produce better results on your specific symbol and timeframe
RECOMMENDED TIMEFRAMES AND ASSET CLASSES
VMDM is timeframe-agnostic and works on any asset with volume data. However, optimal performance varies:
BEST TIMEFRAMES
15-Minute to 1-Hour: Ideal balance of signal frequency and reliability. Pivot confirmation delay is acceptable. Sufficient volume data for pressure analysis.
4-Hour to Daily: Excellent for swing trading. Very high-quality signals. Lower frequency but higher significance. Recommended for learning because patterns are clearer.
1-Minute to 5-Minute: Works but requires adjustment. Increase pivot bars to 5-7 for filtering. Decrease max object history to 30 for performance. Expect more noise.
Weekly/Monthly: Works but very infrequent signals. Increase confluence threshold to 70+ to ensure only major patterns appear.
BEST ASSET CLASSES
Forex Majors: Excellent volume data and clear trends. Pressure analysis works well.
Crypto (Major Pairs): Good volume data. High volatility makes divergences more pronounced. Works very well.
Stock Indices (SPY, QQQ, etc.): Excellent. Clean price action and reliable volume.
Individual Stocks: Works well on high-volume stocks. Low-volume stocks may produce unreliable pressure readings.
Commodities (Gold, Oil, etc.): Works well. Clear trends and reactions.
WHAT THIS INDICATOR CANNOT DO - LIMITATIONS
LIMITATION 1 - It Does Not Predict The Future
VMDM identifies when technical conditions align historically associated with potential reversals or continuations. It does not predict what will happen next. A textbook 95-confluence pattern can still fail if fundamental events, news, or larger timeframe structure override the setup.
LIMITATION 2 - Confirmation Delay Means You Miss Early Entry
In Confirmed and Relaxed modes, the non-repainting design means you receive signals AFTER the pivot is confirmed. Price may have already moved significantly by the time you receive the signal. This is the tradeoff for non-repainting reliability. You can use Real-time mode for faster signals but sacrifice divergence confirmation.
LIMITATION 3 - It Does Not Tell You Position Sizing or Risk Management
VMDM provides technical pattern analysis. It does not calculate stop loss levels, take profit targets, or position sizing. You must apply your own risk management rules. Never risk more than you can afford to lose based on a technical signal.
LIMITATION 4 - Volume Pressure Analysis Requires Reliable Volume Data
On assets with thin volume or unreliable volume reporting, pressure analysis may be inaccurate. Stick to major liquid assets with consistent volume data.
LIMITATION 5 - It Cannot Detect Fundamental Events
VMDM is purely technical. It cannot predict earnings reports, central bank decisions, geopolitical events, or other fundamental catalysts that can override technical patterns.
LIMITATION 6 - Divergence Requires Two Pivots
The indicator cannot detect divergence until at least two pivots of the same type have formed. In strong trends without pullbacks, you may go long periods without signals.
LIMITATION 7 - Institutional Pattern Names Are Interpretive
The behavioral footprint patterns are named using common trading education terminology, but they are detected through technical analysis, not actual institutional data access. The patterns are interpretations based on price and volume behavior.
CONCEPT FOUNDATION - WHY THIS APPROACH WORKS
MARKET PRINCIPLE 1 - Momentum Divergence Precedes Price Reversal
Price is the final output of market forces, but momentum (the rate of change in those forces) shifts first. When price makes a new low but the momentum behind that move is weaker (higher RSI low), it signals that sellers are losing strength even though they temporarily pushed price lower. This precedes reversal. This is a fundamental principle in technical analysis taught by Charles Dow, widely observed in market behavior.
MARKET PRINCIPLE 2 - Volume Reveals Conviction
Price can move on low volume (low conviction) or high volume (high conviction). When price makes a new low on declining volume while RSI shows improving momentum, it suggests the new low is not confirmed by participant conviction. Adding volume pressure analysis to momentum divergence adds a confirmation layer that filters false divergences.
MARKET PRINCIPLE 3 - Anomalies Mark Structural Extremes
When volume spikes significantly but range contracts (absorption), or when price spikes beyond structure then reverses (stop hunt), or when aggressive moves are met with large-wick rejection (exhaustion), these anomalies often mark short-term extremes. Combining these structural observations with momentum analysis creates context.
MARKET PRINCIPLE 4 - Confluence Improves Probability
No single technical factor is reliable in isolation. RSI divergence alone fails frequently. Volume analysis alone cannot time entries. Combining multiple independent factors into a weighted system increases the probability that observed patterns have structural significance rather than random noise.
THE EDUCATIONAL VALUE
By visualizing all four layers simultaneously and breaking down the confluence scoring transparently, VMDM teaches you to think in terms of multi-dimensional analysis rather than single-indicator reliance. Over time, you will learn to recognize these patterns manually and understand which combinations produce better results on your traded assets.
INSTITUTIONAL TERMINOLOGY - IMPORTANT CLARIFICATION
This indicator uses the following terms that are common in trading education:
Institutional Footprint
Absorption (Accumulation / Distribution)
Stop Hunt
Exhaustion
CRITICAL DISCLAIMER:
These terms are EDUCATIONAL LABELS for specific price action and volume behavior patterns detected through technical analysis of publicly available chart data (open, high, low, close, volume). This indicator does NOT have access to:
Actual institutional order flow or order book data
Market maker positions or intentions
Broker stop-loss databases
Non-public trading data
Proprietary institutional information
The patterns labeled as "institutional footprint" are interpretations based on observable price and volume behavior that educational trading literature often associates with potential large-participant activity. The detection is algorithmic pattern recognition, not privileged data access.
When this indicator identifies "absorption," it means it detected high volume within a small range - a condition that MAY indicate large orders being filled but is not confirmation of actual institutional participation.
When it identifies a "stop hunt," it means price briefly penetrated a structural level then reversed - a pattern that MAY have triggered stop losses but is not confirmation that stops were specifically targeted.
When it identifies "exhaustion," it means high volume with large rejection wicks - a pattern that MAY indicate aggressive participation meeting strong opposition but is not confirmation of institutional involvement.
These are technical analysis interpretations, not factual statements about market participant identity or intent.
DISCLAIMER AND RISK WARNING
EDUCATIONAL PURPOSE ONLY
This indicator is designed as an educational tool to help traders learn to recognize technical patterns, understand multi-factor analysis, and practice systematic market observation. It is NOT a trading system, signal service, or financial advice.
NO PERFORMANCE GUARANTEE
Past pattern behavior does not guarantee future results. A pattern that historically preceded price movement in one direction may fail in the future due to changing market conditions, fundamental events, or random variance. Confluence scores reflect historical technical alignment, not future certainty.
TRADING INVOLVES SUBSTANTIAL RISK
Trading financial instruments involves substantial risk of loss. You can lose more than your initial investment. Never trade with money you cannot afford to lose. Always use proper risk management including stop losses, position sizing, and portfolio diversification.
NO PREDICTIVE CLAIMS
This indicator does NOT predict future price movement. It identifies when technical conditions align in patterns that historically have been associated with potential reversals or continuations. Market behavior is probabilistic, not deterministic.
BACKTESTING LIMITATIONS
If you backtest trading strategies using this indicator, ensure you account for:
Realistic commission costs
Realistic slippage (difference between signal price and actual fill price)
Sufficient sample size (minimum 100 trades for statistical relevance)
Reasonable position sizing (risking no more than 1-2 percent of account per trade)
The confirmation delay inherent in the indicator (you cannot enter at the exact pivot in Confirmed mode)
Backtests that do not account for these factors will produce unrealistic results.
AUTHOR LIABILITY
The author (BullByte) is not responsible for any trading losses incurred using this indicator. By using this indicator, you acknowledge that all trading decisions are your sole responsibility and that you understand the risks involved.
NOT FINANCIAL ADVICE
Nothing in this indicator, its code, its description, or its visual outputs constitutes financial, investment, or trading advice. Consult a licensed financial advisor before making investment decisions.
FREQUENTLY ASKED QUESTIONS
Q: Why do signals appear in the past, not at the current bar
A: In Confirmed and Relaxed modes, signals appear at confirmed pivots, which requires waiting for right-side confirmation bars (default 3). This creates a delay but prevents repainting. Use Real-time mode if you want current-bar signals without pivot confirmation.
Q: Can I use this for automated trading
A: You can create alert-based automation, but understand that Confirmed mode signals appear AFTER the pivot with delay, so your entry will not be at the pivot price. Real-time mode signals can change as the current bar develops. Automation requires careful consideration of these factors.
Q: How do I know which confluence score to use
A: Start with 60. Observe which patterns work on your symbol/timeframe. If too many false signals, increase to 70-75. If too few signals, decrease to 55. Quality vs. quantity tradeoff.
Q: Do regular divergences mean I should enter a reversal trade immediately
A: No. Regular divergences indicate momentum exhaustion, which is a WARNING sign that trend may reverse, not a confirmation that it will. Use confluence score, market context, support/resistance, and your strategy rules to make entry decisions. Many divergences fail.
Q: What's the difference between regular and hidden divergence
A: Regular divergence = price and momentum move in opposite directions at extremes = potential reversal signal. Hidden divergence = price and momentum move in opposite directions during pullbacks = potential continuation signal. Hidden divergence suggests the pullback is just a correction within the larger trend.
Q: Why does the pressure zone color sometimes conflict with the divergence direction
A: Pressure is real-time current bar analysis. Divergence is confirmed pivot analysis from the past. They measure different things at different times. A bullish divergence confirmed 3 bars ago might appear during current selling pressure. This is normal.
Q: Can I use this on stocks without volume data
A: No. Volume is required for pressure analysis and behavioral pattern detection. Use only on assets with reliable volume reporting.
Q: How often should I expect signals
A: Depends on timeframe and settings. Daily charts might produce 5-10 signals per month. 1-hour charts might produce 20-30. 15-minute charts might produce 50-100. Adjust confluence threshold to control frequency.
Q: Can I modify the code
A: Yes, this is open source. You can modify for personal use. If you publish a modified version, please credit the original and ensure your publication meets TradingView guidelines.
Q: What if I disagree with a pattern's confluence score
A: The scoring weights are based on general observations and may not suit your specific strategy or asset. You can modify the code to adjust weights if you have data-driven reasons to do so.
Final Notes
VMDM - Volume, Momentum and Divergence Master is an educational multi-layer market analysis system designed to teach systematic pattern recognition through transparent, confluence-weighted signal detection. By combining RSI momentum divergence, volume pressure quantification, behavioral footprint pattern recognition, and quality scoring into a unified framework, it provides a comprehensive learning environment for understanding market structure.
Use this tool to develop your analytical skills, understand how multiple technical factors interact, and learn to distinguish high-quality setups from noise. Remember that technical analysis is probabilistic, not predictive. No indicator replaces proper education, risk management, and trading discipline.
Trade responsibly. Learn continuously. Risk only what you can afford to lose.
-BullByte
Reduced-Lag Chande Momentum Oscillator [BOSWaves]Reduced-Lag Chande Momentum Oscillator – Adaptive Momentum Geometry with Reduced-Latency Reversion Logic
Overview
The Reduced-Lag Chande Momentum Oscillator represents a sophisticated extension of the classical Chande Momentum Oscillator, preserving the foundational measurement of net directional pressure while addressing inherent limitations in lag, noise, and signal clarity. The traditional CMO provides reliable snapshots of upward versus downward force but reacts slowly to rapid market accelerations and can obscure meaningful momentum inflections with delayed readings. This iteration integrates a dual-stage reduced-lag filter, optional advanced smoothing, and acceleration-based analytics, producing a real-time, multi-dimensional representation of market momentum.
The design reframes classical momentum using a layered curvature and gradient structure - main, midline, and shadow - to show trajectory, velocity, and intensity in one view. Instead of the usual ±70/30 extremes, it uses ±50 as a statistically grounded threshold where one side of the market begins exerting true dominance. This captures structural imbalance more reliably, exposing exhaustion and actionable inflection without amplifying noise.
This visualization gives traders a continuous, responsive read on market structure, revealing not just direction but rate of change, acceleration alignment, and curvature behavior. The oscillator becomes a momentum map, expressing both probability and intensity behind directional shifts.
Where conventional oscillators mislabel short-lived swings as signals, the Reduced-Lag CMO separates baseline shifts from high-conviction transitions, enabling cleaner, more decisive signal interpretation.
Theoretical Foundation
The classical Chande Momentum Oscillator, created by Tushar Chande, calculates the normalized net difference between consecutive upward and downward price changes over a defined window, generating readings from –100 to +100. While effective for capturing basic directional pressure, the unmodified CMO suffers from signal latency and sensitivity to abrupt market swings, which can obscure actionable inflection points.
The Reduced-Lag CMO augments this foundation with three key mechanisms:
Reduced-Lag Filtering : A dual-EMA structure eliminates inertial lag, aligning the oscillator curve closely with real-time market momentum without producing overshoot artifacts.
Smoothing Architecture : Optional SMA, EMA, or WMA smoothing is applied post-filter, balancing noise reduction with trajectory fidelity. A multi-layer line system (shadow → midline → main) communicates depth, curvature, and gradient dynamics.
Acceleration Integration : First and second derivatives of the smoothed curve quantify velocity and acceleration, allowing the indicator to identify not only momentum flips but the force behind each shift, forming the basis for the strong-signal overlay.
The combination of these mechanisms produces an oscillator that respects the original CMO framework while delivering real-time, context-sensitive intelligence. The ±50 boundaries are selected as the statistically validated pressure zones where directional dominance exceeds neutral oscillation. Crosses and rejections at these boundaries are not arbitrary overbought/oversold events, but measurable imbalances with actionable significance.
How It Works
The Reduced-Lag CMO is constructed through a multi-stage process:
Momentum Estimation Core : Raw CMO values are calculated and then passed through a reduced-lag filter to remove delay, creating a curve that closely tracks instantaneous directional pressure.
Smoothing & Layered Representation : The filtered curve can be smoothed and split into three layers - shadow, midline, and main - giving visual depth, trajectory clarity, and curvature instead of a single-line oscillator.
Gradient-Based Pressure Mapping : Color gradients encode momentum strength and polarity. Green-yellow transitions highlight increasing upward dominance, while red-yellow transitions indicate weakening downward force.
Pressure-Zone Anchoring (±50) : The system defines statistically significant pressure zones at ±50. Moves beyond these levels reflect dominant directional control, and rejections inside the zone signal potential exhaustion.
Signal Generation : Momentum events are evaluated through velocity and acceleration. Standard signals appear as triangle markers indicating validated momentum flips. Strong signals appear as triangles with diamonds when acceleration confirms a high-conviction transition.
A cooldown rule spaces signals apart to reduce clutter and emphasize structurally meaningful events.
Interpretation
The Reduced-Lag CMO reframes momentum as a dynamic equilibrium between directional force and structural pressure:
Positive Momentum Phases : Curves above zero with green-yellow gradients indicate sustained upward pressure. Shallow retracements or midline tests denote controlled pullbacks.
Negative Momentum Phases : Curves below zero with red-yellow gradients show downward dominance. Rejections from –50 highlight potential exhaustion and reversal readiness.
Pressure-Zone Dynamics (±50) : Crosses beyond ±50 confirm dominant directional force. Meanwhile, rejections and rotations inside the zone signal structural fatigue.
Velocity & Acceleration Analysis : Rising momentum with decelerating velocity suggests fading force; acceleration alignment amplifies signal strength and forms the basis of strong signals.
Signal Architecture
The Reduced-Lag CMO produces a single event type with two intensities: a validated momentum inflection.
Standard Signals - Triangles:
Triggered by momentum flips confirmed by velocity.
Represent moderate-intensity directional changes.
Appear at zero-line crosses or ±50 rejections with aligned velocity.
Strong Signals Triangles + Diamonds:
Triggered when acceleration confirms the directional change.
Represent high-intensity, high-conviction shifts.
Rare by design; indicate robust momentum inflections.
Cooldown mechanics prevent repeated signals in short succession, emphasizing structural reliability over noise.
Strategy Integration
Trend Confirmation : Align zero-line flips with higher-timeframe directional bias.
Reversal Detection : Strong signals from ±50 zones highlight potential inflection points.
Volatility Assessment : Gradient transitions reveal strengthening or weakening momentum.
Pullback Timing : Multi-layer curvature identifies controlled retracements vs trend exhaustion.
Confluence Mapping : Pair with structure-based indicators to filter signals in context.
Technical Implementation Details
Core Engine : Classical CMO with Ehlers reduced-lag extension
Lag Reduction : Dual EMA filtering
Smoothing : Optional SMA/EMA/WMA post-filter
Multi-Layer Curve : Shadow, midline, main
Signal System : Two-tier momentum-acceleration framework
Pressure Zones : ±50 statistically validated thresholds
Cooldown Logic : Bar-indexed suppression
Gradient Mapping : Encodes magnitude and direction
Alerts : Standard and strong signals
Optimal Application Parameters
Timeframes:
1 - 5 min : Intraday momentum tracking
15 - 60 min : Trend rotations & volatility transitions
4H - Daily : Macro momentum exhaustion & re-accumulation mapping
Suggested Ranges:
CMO Length : 7 - 12
Reduced-Lag Length : 5 - 15
Smoothing : 10 - 20
Cooldown Bars : 5 - 15
Performance Characteristics
High Effectiveness:
Markets with directional pulses & clean pressure transitions
Trending phases with measurable pullbacks
Instruments with stable volatility cycles
Reduced Edge:
Choppy consolidations
Ultra-low volatility environments
Disclaimer
The Reduced-Lag Chande Momentum Oscillator is a professional-grade analytical tool. It is not predictive and carries no guaranteed profitability. Effectiveness depends on asset class, volatility regime, parameter selection, and disciplined execution. Any suggested application timeframes or recommended ranges are guidance only - they are not universally optimal and will not deliver consistent accuracy on every asset or market condition. BOSWaves recommends using it in conjunction with structure, liquidity, and momentum context.
Gaussian Kernel Smoothing MomentumOverview:
The Gaussian Kernel Smoothing Momentum indicator analyzes and quantifies market momentum by applying statistical techniques to price and returns data. This indicator uses Gaussian kernel smoothing to filter noise and provide a more accurate representation of momentum. Additionally, it includes a option to evaluate the absolute score of the momentum to determine if the beginning of a "trend" is likely or if you can expect a "trend" to come to an end.
Kernels and Their Role In Time Series Analysis:
In statistical analysis, a kernel is a weighting function used to estimate the properties of a dataset. Kernels are particularly useful in non-parametric methods, where they serve to smooth data or estimate probability density functions without assuming a specific underlying distribution. The Gaussian kernel, one of the most commonly used, is characterized by its smooth, bell-shaped curve which provides a natural way to give more weight to data points closer to the target value and less weight to those further away.
Uses of Kernels in Time Series Analysis
Kernels play a significant role in time series analysis, especially in the context of smoothing and filtering. With kernel functions, you can reduce noise and extract the underlying systematic component or signal from the data. This process is essential for identifying long-term patterns in the data, which is often obscured by short-term fluctuations and random noise.
Kernel Smoothing
Kernel smoothing is a technique that applies a kernel function to a set of data points to create a smooth curve, effectively reducing the impact of random variations. In time series analysis, kernel smoothing helps to filter out short-term noise while retaining significant trends and "patterns". The Gaussian kernel, with its emphasis on nearby points, is particularly effective for this purpose, as it smooths the data in a way that highlights the underlying structure without overfitting to random fluctuations.
Additionally, kernels are used in non-parametric volatility estimation, option pricing models, and for detecting anomalies in financial data. Their flexibility and ability to handle complex, non-linear relationships make them well-suited for the often noisy data encountered in financial markets.
Momentum Component
The momentum component of the indicator is designed to quantify the directional movement of asset prices by applying the Gaussian kernel smoothing to the expected return of the price data. The data then has the variance stabilized and normalizes the distribution of price changes to be able to more efficiently analyze the momentum.
The Gaussian kernel smoothing function serves to filter out high-frequency noise, isolating the underlying systematic component of the momentum. This is achieved by weighting the data points based on their proximity to the current observation, with closer data points exerting a stronger influence. The resulting smoothed momentum provides a clearer of the directional bias in the market, devoid of short-term volatility.
Absolute Move Component
The absolute move component is a extension of the momentum analysis, focusing on the magnitude rather than the direction of the price movements. This component captures the absolute score of the smoothed momentum series, providing a measure of strength or intensity of the price movement, independent from its direction. The absolute move component also incorporates a Kalman filter to further smooth and refine the signal. The Kalman filter dynamically adjusts based on the observed variance in the data, to reduce the impact of outliers.
What to make of this indicator
The smoothed momentum line helps determine whether the market is experiencing upward and downward momentum. If the momentum line is above zero and rising, this suggest a positive expected returns. Conversely, if the momentum line is below zero and falling, it indicates negative expected returns.
You should also pay attention to changes in the slope of the momentum line and the moving average of the smoothed momentum(weighted with an optimal sampling size algorithm). A flattening or reversal of the slope may signal a potential shift in market direction. For example, if the momentum line and moving average transitions from rising to falling, it means that the expected return is going from positive to negative so you can see the "trend" as weakening or forming a trend of negative expected returns.
The absolute move component is designed to measure the intensity or strength of the current market movement. A low absolute move value, especially when they are negative or at the lower end of their band, indicates that the momentum and expected return is close to zero, which suggest that the market is experiencing minimal directional movement, which can be a sign of consolidation. High absolute values signal that the market is undergoing a significant price movement. When the absolute move is high and/or rising, it indicates that the movement of the momentum is strong, regardless of whether it is bullish or bearish.
If the absolute move reaches unusually high levels, it could indicate that the market is experiencing an exceptional price move, which might be unsustainable. Traders can anticipate potential reversals or profit taking targets. However, you should avoid trying to trade reversals as exceptionally high values in a time series do not guarantee an immediate reversal. This high values often occur during periods of strong trends or significant events, which can continue longer than expected, and you cant time when it will return to its mean. The mean-reverting nature of some statistical models can suggest a return to the mean, but this assumption can be misleading in financial markets, where trends can persist despite overextending conditions.
Squeeze Momentum TD - A Revisited Version of the TTM SqueezeDescription:
The "Squeeze Momentum TD" is our unique take on the highly acclaimed TTM Squeeze indicator, renowned in the trading community for its efficiency in pinpointing market momentum. This script is a tribute and an extension to the foundational work laid by several pivotal figures in the trading industry:
• John Carter, for his creation of the TTM Squeeze and TTM Squeeze Pro, which revolutionized the way traders interpret volatility and momentum.
• Lazybear, whose original interpretation of the TTM Squeeze, known as the "Squeeze Momentum Indicator", provided an invaluable foundation for further development.
• Makit0, who evolved Lazybear's script to incorporate enhancements from the TTM Squeeze Pro, resulting in the "Squeeze PRO Arrows".
Our script, "Squeeze Momentum TD", represents a custom version developed after reviewing all variations of the TTM Squeeze indicator. This iteration focuses on a distinct visualization approach, featuring an overlay band on the chart for an user-friendly experience. We've distilled the essence of the TTM Squeeze and its advanced version, the TTM Squeeze Pro, into a form that emphasizes intuitive usability while retaining comprehensive analytical depth.
Features:
-Customizable Bollinger Bands and Keltner Channels: These core components of the TTM Squeeze.
-Dynamic Squeeze Conditions: Ranging from No Squeeze to High Compression.
-Momentum Oscillator: A linear regression-based momentum calculation, offering clear insights into market trends.
-User-Defined Color Schemes: Personalize your experience with adjustable colors for bands and plot shapes.
-Advanced Alert System: Alerts for key market shifts like Bull Watch Out, Bear Watch Out, and Momentum shifts.
-Adaptive Band Widths: Modify the band widths to suit your preference.
How to use it?
• Transition from Light Green to Dark Green: Indicates a potential end to the bullish momentum. This 'Bull Watch Out' signal suggests that traders should be cautious about continuing bullish trends.
• Transition from Light Red to Dark Red: Signals that the bearish momentum might be fading, triggering a 'Bear Watch Out' alert. It's a hint for traders to be wary of ongoing bearish trends.
• Shift from Dark Green to Light Green: This change suggests an increase in bullish momentum. It's an indicator for traders to consider bullish positions.
• Change from Dark Red to Light Red: Implies that bearish momentum is picking up. Traders might want to explore bearish strategies under this condition.
• Rapid Change from Light Red to Light Green: This swift shift indicates a quick transition from bearish to bullish sentiment. It's a strong signal for traders to consider switching to bullish positions.
• Quick Shift from Light Green to Light Red: Demonstrates a speedy change from bullish to bearish momentum. It suggests that traders might want to adjust their strategies to align with the emerging bearish trend.
Acknowledgements:
Special thanks to Beardy_Fred for the significant contributions to the development of this script. This work stands as a testament to the collaborative spirit of the trading community, continuously evolving to meet the demands of diverse trading strategies.
Disclaimer:
This script is provided for educational and informational purposes only. Users should conduct their own due diligence before making any trading decisions.
Matrix Momentum Expansion [IkkeOmar]The indicator consists of several features:
Candlestick chart: The indicator plots a candlestick chart based on the input parameters of the user. The candlesticks are colored blue or orange depending on whether the closing price is above or below the upper and lower bands.
Support and Resistance levels: The indicator also plots support and resistance levels based on the CCI (Commodity Channel Index) of the asset's price. These levels are dynamic and change based on the user's input parameters.
Momentum: The indicator calculates the momentum of the market based on the smoothed and standard deviation of the asset's price. It uses this momentum to calculate upper and lower bands that are plotted on the chart.
Warning signals: The indicator can also be used to identify potential warning signals. When the closing price of the asset moves above the upper band, it could indicate that the market is overbought and a potential reversal could occur. Conversely, when the closing price moves below the lower band, it could indicate that the market is oversold and a potential reversal could occur.
Contractions and expansions in the bands can provide important information to traders about potential price movements.
When the bands contract, it indicates that the market is experiencing low volatility and the price is likely to move sideways. During these periods, traders may look for other signals, such as support and resistance levels or price patterns, to determine potential entry and exit points.
On the other hand, when the bands expand, it indicates that the market is experiencing high volatility and the price is likely to move in a particular direction. Traders can use this information to identify potential trend reversals or continuation patterns. When the upper and lower bands move further apart, it indicates that the trend is becoming stronger, while when they move closer together, it indicates that the trend may be weakening.
When the price moves outside of the bands, it can also provide important information to traders. If the price moves above the upper band, it could indicate that the market is overbought and a potential reversal could occur. Conversely, if the price moves below the lower band, it could indicate that the market is oversold and a potential reversal could occur.
Very important note!
When you see contractions, please understand that it's a wonderful opportunity to pivot into position to catch a good trade because we will see an expansion after!
GKD-C Smoother Momentum MACD w/ dual DSL [Loxx]Giga Kaleidoscope GKD-C Smoother Momentum MACD w/ dual DSL is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Smoother Momentum MACD w/ dual DSL
What is Smoother Momentum?
Smoother Momentum is a technical indicator used to evaluate the momentum of financial assets over a specific period. It is a popular tool among traders and analysts as it helps filter out noise from the price data and provides a clearer understanding of the underlying trend. The code snippet provided is a function, smmom(), that calculates the Smoother Momentum using a combination of Exponential Moving Averages (EMAs). In the following, we will delve into the concept of Smoother Momentum, its formulation, and the rationale behind the calculations.
Smoother Momentum Formula:
The Smoother Momentum calculation involves three EMAs with different smoothing factors. The function smmom() takes two input parameters: src, which represents the source data (such as price), and per, which represents the period for smoothing.
smmom(float src, float per)=>
float alphareg = 2.0 / (1.0 + per)
float alphadbl = 2.0 / (1.0 + math.sqrt(per))
float ema = src
float ema21 = src
float ema22 = src
if bar_index > 0
ema := nz(ema ) + alphareg * (src - nz(ema ))
ema21 := nz(ema21 ) + alphadbl * (src - nz(ema21 ))
ema22 := nz(ema22 ) + alphadbl * (ema21 - nz(ema22 ))
float out = (ema22 - ema)
out
The smoothing factors for the three EMAs are as follows:
alphareg = 2.0 / (1.0 + per)
alphadbl = 2.0 / (1.0 + sqrt(per))
These factors determine the degree of smoothing applied to the input data. The alphareg factor provides regular smoothing, while the alphadbl factor introduces a double smoothing effect.
The three EMAs are calculated as follows:
ema = src
ema21 = src
ema22 = src
For each bar index greater than zero, the EMAs are updated using the following formulas:
ema := nz(ema ) + alphareg * (src - nz(ema ))
ema21 := nz(ema21 ) + alphadbl * (src - nz(ema21 ))
ema22 := nz(ema22 ) + alphadbl * (ema21 - nz(ema22 ))
The Smoother Momentum (out) is then calculated as the difference between ema22 and ema:
out = (ema22 - ema)
Rationale Behind Smoother Momentum:
The Smoother Momentum indicator is designed to provide a refined view of an asset's momentum by employing multiple levels of smoothing. By incorporating the regular EMA (ema) and the double smoothed EMAs (ema21 and ema22), the indicator minimizes the impact of price fluctuations, resulting in a smoother momentum line.
The use of different smoothing factors allows the indicator to capture both short-term and long-term price movements, making it a valuable tool for various trading strategies. The Smoother Momentum provides traders with a better understanding of the underlying trend and helps them identify potential entry and exit points.
Smoother Momentum is a powerful technical indicator that offers valuable insights into an asset's momentum by leveraging a combination of Exponential Moving Averages with different smoothing factors. The smmom() function is an efficient implementation of the Smoother Momentum indicator, providing traders and analysts with a clear and concise view of the asset's underlying trend. By incorporating this indicator into their trading strategies, market participants can make more informed decisions and improve their overall performance.
What is the Moving Average Convergence Divergence (MACD)?
The Moving Average Convergence Divergence (MACD) is a widely-used technical indicator that measures the relationship between two Exponential Moving Averages (EMAs) of an asset's price. Developed by Gerald Appel in the 1970s, the MACD is employed by traders and analysts to identify trend reversals, bullish or bearish momentum, and potential entry or exit points in the market. This following will provide an in-depth understanding of the MACD, its formulation, and the rationale behind its calculations.
MACD Formula:
The MACD is derived from two Exponential Moving Averages of different periods, usually 12 and 26. The MACD line is calculated as the difference between the short-term (12-period) EMA and the long-term (26-period) EMA. Alongside the MACD line, a signal line, typically a 9-period EMA of the MACD line, is calculated. The interaction between the MACD line and the signal line forms the basis for generating trading signals.
Here are the formulas for calculating the MACD components:
1. Short-term EMA (12-period): EMA_short = EMA(price, 12)
2. Long-term EMA (26-period): EMA_long = EMA(price, 26)
3. MACD Line: MACD = EMA_short - EMA_long
4. Signal Line (9-period EMA of MACD): Signal = EMA(MACD, 9)
5. Additionally, the MACD Histogram represents the difference between the MACD line and the signal line, visualizing the degree of separation between the two lines.
MACD Histogram: Histogram = MACD - Signal
Rationale Behind MACD:
The MACD indicator is based on the principle that moving averages can provide insights into an asset's trend and momentum. By calculating the difference between two EMAs of different periods, the MACD line oscillates around the zero line, capturing the underlying trend and momentum of the asset. When the short-term EMA is above the long-term EMA, the MACD line is positive, indicating bullish momentum. Conversely, when the short-term EMA is below the long-term EMA, the MACD line is negative, signifying bearish momentum.
The signal line, a 9-period EMA of the MACD line, serves as a smoothing factor and a trigger for trading signals. When the MACD line crosses above the signal line, it generates a bullish signal, suggesting a potential buying opportunity. On the other hand, when the MACD line crosses below the signal line, it produces a bearish signal, indicating a possible selling opportunity.
The MACD Histogram visualizes the divergence between the MACD line and the signal line, helping traders assess the strength of the trend and the momentum. A widening histogram signifies an increasing divergence between the two lines, indicating stronger momentum, while a narrowing histogram denotes decreasing divergence, suggesting weakening momentum.
The Moving Average Convergence Divergence (MACD) is a powerful and versatile technical indicator that offers valuable insights into an asset's trend and momentum. By examining the interactions between the MACD line, the signal line, and the MACD Histogram, traders can identify potential trend reversals, bullish or bearish momentum, and entry or exit points in the market. The MACD's effectiveness in various market conditions and its compatibility with different trading strategies make it an indispensable tool for market participants seeking to make well-informed decisions and enhance their overall performance.
What is a Discontinued Signal Line (DSL)?
Many indicators employ signal lines to more easily identify trends or desired states of the indicator. The concept of a signal line is straightforward: by comparing a value to its smoothed, slightly lagging state, one can determine the current momentum or state.
The Discontinued Signal Line builds on this fundamental idea by extending it: rather than having a single signal line, multiple lines are used based on the indicator's current value.
The "signal" line is calculated as follows:
When a specific level is crossed in the desired direction, the EMA of that value is calculated for the intended signal line.
When that level is crossed in the opposite direction, the previous "signal" line value is "inherited," becoming a sort of level.
This approach combines signal lines and levels, aiming to integrate the advantages of both methods.
In essence, DSL enhances the signal line concept by inheriting the previous signal line's value and converting it into a level.
You can select between anchored and unanchored DSL, as well as utilize zero-line crosses without DSL.
What is the Smoother Momentum MACD w/ dual DSL?
This indicator uses the Smoother Momentum algorithm to calculate a MACD. Signals are created by middle crosses, signal crosses, or DSL crosses.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Smoother Momentum MACD w/ dual DSL as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
Trend and Momentum DashboardI created this indicator to tell me when it's time to trade (going long) and when it's time to wait (or going short).
You can enter up to 13 ticker (default is S&P500 and key market segments).
For each ticker, fibonacci levels are calculated and represented either in 5 color or 3 color mode as single lines.
(Thanks to eykpunter for the fibonacci level implementation. I'm using his code and modified it slightly).
Color coding (5 color mode) explanation:
blue = in uptrend area
light blue = in prudent buyers area
gray = in center area
light red = in prudent sellers area
red = in downtrend area
The topline is a combination of all ticker and shows if the market is either bullish or bearish (threshold adjustable in settings)
The bullish/bearish trend can also be used as background color. Alternatively the last bar in the selected time period is been highlighted.
How to use it:
The indicator works on all timeframes. Use the color coding explanation above to see the status of each asset.
a) You can evaluate "long" term trend using day or week timeframe. e.g. I'm usually trading only long and stay out of the market when it is not bullish (top line & background = blue). I'm also using it to know which segments/assets are currently "hot".
b) You can evaluate short term momentum (using 1h or lower timeframe) and see in which direction the market/assets are moving. e.g. I use this when the exchanges open to see how the day is going to move.
I've attached 3 examples in the screenshot - first is the default, in the second one I'm using different asset classes and the third one is for crypto.
Limitations:
There are security request limits as well as string limitations for the security calls in pine script, so I went to the maximum what is currently possible.
(No financial advise, for testing purposes only)
WaveRider Momentum OscillatorWaveRider Momentum Oscillator
The WaveRider Momentum Oscillator applies principles inspired by fluid dynamics to model price momentum as a flowing system, rather than relying on traditional static calculations. By interpreting market movement through the lens of velocity, viscosity, and turbulence—core concepts in fluid mechanics—this indicator offers a more adaptive and nuanced view of momentum that adjusts dynamically to changing market conditions.
Conceptual Foundation
Velocity: Just as fluid velocity measures the speed of flow at a point, WaveRider calculates momentum velocity by measuring the rate of price change over a specified period, smoothed to reduce noise.
Viscosity: In fluid dynamics, viscosity represents internal friction that resists flow. Here, viscosity is modeled based on volatility, modulating momentum signals to account for the “thickness” or noise level of the market. High volatility increases viscosity’s damping effect, reducing false signals during turbulent price action.
Turbulence: Turbulence characterizes sudden, chaotic changes in fluid flow. WaveRider detects rapid acceleration bursts in momentum analogous to turbulence, highlighting moments when momentum is shifting sharply and potentially signaling strong upcoming price moves.
Technical Features and Interpretation
Adaptive Momentum Calculation: Momentum is scaled by volatility-adjusted viscosity, making the oscillator less prone to whipsaws and more responsive during stable trends.
Turbulence Burst Detection: The oscillator incorporates a turbulence factor, identifying abrupt momentum accelerations that traditional oscillators often miss. This feature provides early warning signals of potential breakout or reversal points.
HSV Gradient Color Mapping: The oscillator visualizes acceleration using a continuous hue gradient—ranging from red (deceleration) through yellow (neutral) to green (acceleration). This continuous color transition provides intuitive, real-time insight into momentum dynamics beyond mere numeric values.
Pivot Point Identification: WaveRider automatically marks momentum pivots, signaling local maxima and minima in momentum flow. These points serve as critical confirmation markers for potential entry and exit decisions.
How to Interpret WaveRider
Colors:
Green hues indicate positive acceleration — momentum is increasing, favoring bullish positions.
Yellow hues represent neutral momentum — the market is consolidating or pausing.
Red hues signal negative acceleration — momentum is weakening, suggesting caution or bearish bias.
Oscillator Direction:
An upward sloping oscillator line reflects strengthening momentum.
A downward slope indicates weakening momentum or a potential reversal.
Pivot Labels:
▲ (Pivot Low): Denotes local momentum troughs; potential points to consider initiating long positions.
▼ (Pivot High): Marks local momentum peaks; useful for identifying possible short entries or profit-taking zones.
Summary
By grounding momentum analysis in fluid dynamics, WaveRider transcends the limitations of traditional oscillators. It accounts for the market’s inherent volatility and captures real-time acceleration changes, enabling traders to detect meaningful momentum shifts with greater accuracy and clarity.
WaveRider is designed for traders seeking a scientifically informed tool that adapts fluidly with market conditions—offering deeper insight into momentum flow and better timing for entries and exits.
Adaptive Sharp Momentum█ Introduction
The Adaptive Sharp Momentum Study has the following all-in-one features:
• A noise-free, trend-following indicator.
• Automatically detects implied tops and bottoms within fast price cycles.
• It identifies price consolidations and periods of indecision; often challenging to spot.
• Includes a unique feature for detecting directional price squeezes.
• An integrated volatility measure helps avoid false signals and clarifies trend direction.
• Lastly, it alerts traders when a volume climax is likely reached during a move.
This study primarily focuses on capturing momentum while concurrently alerting traders to shifting market dynamics, thereby aiding in the decision to either extend a position’s duration or optimize exit timing. The set of analytical tools, deployed alongside the trend-following indicator, are integrated to reflect the concepts outlined above. Furthermore, this framework utilizes distinctive methods for trend identification, consolidation recognition, directional squeeze assessment, and volume climax analysis—approaches that are not currently documented in publicly available resources.
█ Explanation of Core Components
1. Trend Following Consolidated Adaptive Moving Average:
At the core of the study is the Jurik Adaptive Average Curve, a fast-response adaptive moving average refined with an adaptive Relative Strength Index (RSX) function, known as Jurik RSX. This curve displays three trend modes—bullish, bearish, and indecisive—each customizable in color.
Users can adjust parameters such as the Phase and Consolidation Period:
• Phase: Influences the timing of trend signals, accommodating various trading styles. A lower phase value can produce leading signals, while a higher value may result in lagging signals.
• Consolidation Period: Helps filter out false signals. Optimize this period based on the time frame and instrument.
• Momentum Slope Threshold: As mentioned earlier, the Jurik moving average values are consolidated against the Dynamic Jurik RSX. Crossing the slope threshold of the Jurik RSX will trigger consolidation.
The main curve in the middle represents the overall trend. The issue with moving averages is that they work well in trends but when market is in consolidation, many false signals can be generated. The consolidation period acts as a second fast signal curve that helps eliminate the false signals generated through the standard adaptive moving average. This is basically done by measuring the momentum of the move itself through the Jurik RSX. There are other tools in this study that should also help the trader avoid false signals which will be fully described below.
2. Implied Tops and Bottoms
The study also detects Implied Tops and Bottoms during market cycles using the Composite Momentum and Projections. It offers three detection modes:
• Strong Signals: Indicate significant potential reversal points.
• Medium Signals: Typically displayed near the end of a trend, suggesting traders should prepare to exit.
• Rolling Signals: Alert traders to set tight stop losses to secure profits, as the market may be approaching a turning point.
By default, the colors of Rolling Signals and Medium Signals are the same for simplicity.
Note the following:
• The fast and slow period have the most effect on implied tops and bottoms detection.
• Adjusting the main period will also have an overall effect.
The above chart shows rolling tops, rolling bottoms, strong tops, and strong bottoms. A rolling top of bottom indicate an increase in momentum in that direction and thus a tight stoploss would be recommended, while a strong top/bottom indicates that an exit is warranted.
3. Consolidation and Volatility
If enabled, '+' will appear above the ceiling and floor plots if consolidation is detected. Consolidation is detected by using lookback function that determine if price is below a threshold or not. If below, then consolidation would be confirmed. This is accomplished by adjusting the ' Price Consolidation Threshold ' period
The above chart demonstrates detection of consolidation on a 1-minute chart. Also, note the ceiling and floor plot, it expands when volatility is high.
Consolidation detection helps weed out long and short signals indicated by the main curve.
4. Directional Squeeze
Another unique feature of this indicator is the detection of directional price squeeze. Directional squeeze is defined as a price push in the direction indicated by momentum whether upward or downward. This is different from the common squeeze indicators found on the web since this one is detecting a directional push.
The Directional Squeeze feature, indicated by up and down triangles above the main curve, highlights strong trends in the market's current direction:
• Trend Continuation: Allows traders to stay in profitable trades longer during strong trending markets.
• Multiple Modes: Offers single-bar (short-term) and longer-term squeezes. Single-bar squeezes can signal potential market reversals, while longer-term squeezes are useful in sustained trends.
Be mindful that under certain conditions, the directional squeeze could be directionless(sideways) if consolidation is outlined by the indicator. This is another useful feature the trader could utilize. The chart above mostly demonstrates directional squeeze but directionless can also be observed.
5. Volume Volatility and Volume Climax Detection
An essential feature of the Adaptive Sharp Momentum Study is its ability to measure Volume Volatility and detect Volume Climax moments:
• Volume Volatility Measure: Integrated into the study to help avoid false signals by assessing the strength of market moves. It provides better clarity on trend direction by indicating when the market is experiencing significant volume changes.
• Volume Climax Alerts: The study alerts traders when a volume climax is likely reached during a move, which is helpful for identifying potential reversal points or the culmination of a trend. Brighter confirmation signal dots indicate these climaxes, helping traders make timely entry/exit decisions.
• Adjustable Parameters: Traders can set the Volume Volatility Threshold and adjust the Volume Lookback Period to tailor the sensitivity of volume climax detection according to their trading strategy.
5. The indicator contains other useful features:
• Cycles: Helps determine when to enter long or short trades based on upward or downward market cycles. It also aids in recognizing retracement levels during a trend, allowing traders to capitalize on brief counter-trend movements. Those cycles can be observed as the up and down gray lines on the chart.
• Real-Time Table: The table is another visual aid that summarizes the status of each feature in real-time.
█ How to Use this Study Effectively
The main curve in the middle is your final decision point. Prior to entering a trade look for the following:
• Is the market in consolidation? If yes, then you'd be advised not to enter the trade until the study clearly shows no consolidation
• Is the ceil or floor plots showing a strong top or bottom, or even a volume climax in the direction to intend to enter? If yes, then either ensure you enter at a tight stop or don't enter
• Is there an indication of a directional squeeze with no consolidation or volume climax? Then this would be an ideal place to enter. Be mindful though that entering directional squeeze too late is not recommended.
• Once you are in the trade, look at consolidation, implied tops and bottoms, and volume climax to determine exit point. You will quickly realize if you entered a trade prematurely.
• Utilize the directional squeeze and the prevalent trend to help you stay in the trade longer.
• Adjust your stop losses depending on whether you are seeing a rolling implied top/bottom or a strong top/bottom.
• Also, at volume climaxes, be ready to exit. The approach with volume climax detection should be the same as the implied tops/bottoms.
Below is a chart demonstrating trading on a 1-minute chart. The study could be used for any time frame:
** Important Note **
This study relies on volume readings. Incorrect evaluation will be concluded without proper volume data.
█ How the Adaptive Sharp Momentum Works?
---Main Curve - Jurik Moving Average and RSX---
The Jurik Moving Average (JMA) and the Jurik RSX with Fisher transform (Relative Strength Index Extended) are technical tools designed to enhance data processing efficiency. The JMA uses an adaptive smoothing algorithm to dynamically adjust to market conditions, reducing lag while maintaining high responsiveness to price changes. the JMA incorporates a mechanism that determines smoothness based on input volatility. The RSX, on the other hand, tracks relative strength without introducing the overshoots and noise commonly seen in other momentum indicators. It achieves this by applying a yet another JMA smoothing function that ensures stability and consistency, making it a better candidate for identifying shifts.
This is a unique approach, but can simply be equated to two moving averages crossing over, except in this case, the RSX is crossing over with the JMA.
The process of determining market trends and consolidation for the main curve revolves around evaluating multiple conditions and rankings of indicators such as Jurik RSX, Fisher Transform, and Volume-based metrics (Adaptive On Balance Volume and Price Volatility). Here's how consolidation and trends are identified:
1. Trend Override Logic: The core logic evaluates whether specific conditions override the default trend determined by the JMA.
• Bearish Overrides: A trend is classified as bearish if specific conditions involving negative slopes of the RSX, bearish Fisher Transform readings, and other auxiliary rankings (AOBV trend rank or volatility ranks) are met.
• Bullish Overrides: Similarly, bullish trends are determined by the presence of positive RSX slopes, bullish Fisher readings, and supporting AOBV and volatility ranks.
• Neutral Overrides: If neither bullish nor bearish overrides dominate, and conflicting conditions are detected (e.g., a bearish Fisher with a bullish OBV), the trend can be overridden to neutral.
2. Dynamic Slope and Rank Analysis: RSX and Jurik Slopes: The slopes of the RSX and Jurik indicators play an important role. Increasing slopes suggest bullish momentum, while decreasing slopes imply bearish momentum.
3. Narrow Spread Analysis: Consolidation zones are identified by examining conditions like narrow spreads in price action and mixed indicator signals (e.g., a positive RSX slope alongside a neutral or bearish AOBV).
• When consolidation is detected, the system looks for confirming signals (AOBV or Fisher alignment) to determine whether the next move is likely to be bullish or bearish.
4.Fallback Logic:
If no explicit conditions are met for bullish, bearish, or neutral trends, the system defaults to comparing the current and previous values of the Jurik Moving Average. If the JMA is rising, the trend is set to bullish; otherwise, it defaults to bearish.
The process of consolidating The RSX with JMA, attempts to confirm the trend suggested by the Jurik moving average. As shown above, several factors play into this, but it is mostly motivated by the RSX and its slope
-- Detecting Tops and Bottoms --
• Composite Momentum
The Composite Momentum indicator analyzes the market's directional strength to identify implied tops and bottoms, especially at extreme values. It evaluates momentum by categorizing it into ranges that reflect moderate or strong trends for both bullish and bearish conditions. When momentum exceeds a positive threshold, it indicates a strong top, whereas values below a negative threshold then it's a strong bottom.
• Laguerre Dynamic Projection Bands
The Laguerre Dynamic Projection Bands focuses on price positioning within calculated dynamic boundaries. By applying linear regression, it projects upper and lower price bands, which serve as potential resistance and support levels. The oscillator value ranges from 0 to 100, representing the relative position of the current price. A value above 70 indicates the price is near a projected top, while a value below 30 suggests proximity to a projected bottom. Through custom Laguerre smoothing, the setup ensures that its signals remain stable and actionable.
• How They Work Together
The Composite Momentum and Projection Oscillator complement each other in detecting market tops and bottoms. The Projection Oscillator provides an early indication when price nears a critical level, while the Composite Momentum confirms whether the momentum supports the formation of a significant top or bottom.
-- Consolidation Detection, Volatility, and Volume Climax Detection --
• Summary of Consolidation Detection:
Consolidation is identified through a combination of statistical and smoothing applied to price data. The approach calculates deviations around the main plot using squared price inputs, smoothed averages, and adaptive multipliers. These deviations form dynamic upper and lower boundaries that adapt to changing market conditions. The system further evaluates these boundaries against historical bars to calculate a volume percentage, which indicates how often recent price action remains within these bands. A low percentage suggests consolidation, characterized by reduced volatility and price movement confined within a tighter range.
The bands around the main plot are derived from the calculated maximum deviations, creating adaptive ceilings and floors that expand or contract based on market dynamics. The Ceiling and Floor plots represent the outermost boundaries, while additional retracement plots are drawn based on the Composite Momentum wave rank. For example, during an uptrend, the retrace levels adjust upward in fractional steps relative to the deviation, signaling possible resistance levels. In downtrends, similar logic applies in reverse to determine support levels. These bands visually represent the volatility envelope and help contextualize price movements relative to expected ranges. Whenever, low volatility is detected, a visual "+" indicator is added to the plot to highlight that the market is likely in consolidation mode.
• How the Adaptive OBV Applies the Same Logic:
The Adaptive On-Balance Volume (OBV) uses a similar mechanism to detect volume climaxes by analyzing deviations in volume data. Instead of price, the OBV logic applies the squared input and smoothing methods to volume flows. By comparing these deviations to historical norms, the system identifies periods of high or low volatility in volume, which often coincide with potential breakouts or consolidation zones.
• How They Work Together
The consolidation detection process and the adaptive bands work in tandem to provide traders with a clear visualization of market conditions. When consolidation is detected, the dynamic bands narrow and a "+" sign is visualized, signaling reduced volatility and potential breakout opportunities. Similarly, volume-based analysis through the adaptive OBV helps confirm whether a breakout is accompanied by significant volume, adding confidence to trade decisions. Together, they enable anticipation of market shifts.
-- Directional Squeeze --
A directional price squeeze refers to a market condition where price compresses in a particular direction. This provides traders with an opportunity to stay in trades longer by aligning with the prevailing directional bias. This unique concept generates dynamic limits based on lookback period. Their convergence upward or downward is typically a strong indication of a price push toward the respective direction.
In this approach, the system looks at the highest and lowest values of a smoothed momentum reading over a recent period and measures the distance between them. Instead of relying on a static “overbought” or “oversold” line, it calculates new boundaries as a fraction of that distance, scaling the thresholds to match the price behavior. When these dynamically adjusted limits converge, it suggests a “directional squeeze”—meaning price is moving within a more compressed or focused range. Because these boundaries adapt to the market’s own highs and lows, they provide a more responsive indication of when price may be shifting into or out of a strong directional move.
• Determining the Directional Squeeze
Directional squeeze is identified using dynamic limits derived from two key factors:
Schaff Trend Cycle (STC) for single-bar squeezes. and the Slow RSI (SRSI) for multi-bar or longer-term squeezes. Both are utilizing a custom alpha factor for adaptability and conformance with the JMA and Dynamic RSX studies.
• Directional Trend Confirmation:
If the SRSI or STC approaches the limits, additional conditions such as Fisher RSX (momentum signals) and AOBV (volume signals) and the trend already established by the JMA are aligned. If so, then a squeezed in that trend directional is established.
█ Why These Components All Work Together?
The Adaptive Sharp Momentum Study integrates multiple components to provide a framework for analyzing market dynamics. Each feature addresses specific challenges in trading:
• Core Trend Identification:
The Jurik Adaptive Moving Average (JMA) and Jurik RSX ensure better trend detection by reducing noise and dynamically confirming momentum, thus minimizing lag and false signals.
• Implied Tops and Bottoms:
The combination of Composite Momentum and Laguerre Dynamic Projection Bands highlights critical turning points. This dual-layered approach identifies potential reversals and key support/resistance levels with improved clarity.
• Consolidation and Volatility:
Adaptive ceilings, floors, and consolidation detection filter out indecisive market phases. This helps avoid unreliable signals and provides a better perspective on potential breakouts or continuations.
• Directional Squeeze:
The Directional Squeeze feature identifies directional bias in price compression. Its dynamic thresholds adapt to market conditions, aiding in the assessment of strong directional moves.
• Volume Climax:
Volume volatility and climax detection highlight key moments of market activity, aiding in the evaluation of trend strength and potential turning points.
• Integrated Framework:
The integration of these components creates a system where each element complements the others.
This study offers a methodical approach to analyzing trends, momentum, and volatility while filtering noise. It is a tool designed to assist traders in navigating complex market conditions.
█ Disclaimer
This script is provided for educational and informational purposes only and should not be considered financial advice. Trading financial instruments carries a high level of risk and may not be suitable for all investors. Before using this script, please consult with a qualified financial advisor to ensure it aligns with your individual circumstances. The author does not guarantee the accuracy or completeness of the script and is not responsible for any losses or damages that may occur from its use. Use this script at your own risk.
Uptrick: Momentum Channel Indicator
### 🌟 **Uptrick: Momentum Channel Indicator (MC_Ind)** 🌟
The **"Uptrick: Momentum Channel Indicator"** is a powerful tool designed to help traders gauge market momentum and identify potential overbought or oversold conditions. Whether you're a day trader, swing trader, or long-term investor, this indicator can be your compass 🧭 in the complex world of trading.
### 🎯 **Purpose of the Indicator**
The primary goal of the **Momentum Channel Indicator** is to measure the deviation of price from its moving average (the mid-point) and to smooth this deviation to identify momentum shifts. By plotting overbought and oversold levels, the indicator helps traders spot potential reversal points where the market might change direction, offering valuable entry or exit signals.
### 🔧 **Inputs & Parameters**
Let's break down the input parameters that you can adjust to tailor the indicator to your trading style:
1. **`length1` (Channel Length) 📏**: This is the period over which the moving average (mid-point) and price deviation are calculated. The default value is 14, meaning the last 14 bars are considered for calculations.
2. **`length2` (Smoothing Length) 🧘**: This parameter controls the smoothing of the channel index, with a default value of 28. The higher the value, the smoother the momentum line, reducing noise and making trends more visible.
3. **`overbought1` & `overbought2` (Overbought Levels) 🔴**: These levels, set at 70 and 65 by default, represent the threshold above which the market is considered overbought, potentially signaling a selling opportunity.
4. **`oversold1` & `oversold2` (Oversold Levels) 🟢**: Similarly, these levels, set at -70 and -65, mark the threshold below which the market is considered oversold, indicating a potential buying opportunity.
### 🛠️ **How the Indicator Works**
Now, let's dive into the mechanics of the Momentum Channel Indicator:
1. **Mid-Point Calculation 🏁**: The mid-point is calculated using a simple moving average (SMA) of the closing prices over the `length1` period. This mid-point acts as a reference line from which deviations are measured.
2. **Price Deviation 📊**: The price deviation is the absolute difference between the closing price and the mid-point, smoothed over the same period (`length1`). This represents the typical price movement away from the mid-point.
3. **Channel Index 📉**: The channel index is calculated by dividing the price deviation by a fraction (0.01) of the mid-point, providing a normalized measure of how far the price has deviated from the average.
4. **Smoothing of the Channel Index 🌊**: The smoothed index (`mci1`) is calculated by applying a smoothing filter (SMA) over the channel index using the `length2` parameter. This helps reduce noise and highlight the true momentum of the market.
5. **Momentum Lines 📈**:
- **`mci1`**: The main momentum line, representing the smoothed channel index.
- **`mci2`**: A secondary momentum line, which is a further smoothed version of `mci1` using a 6-period SMA.
6. **Signal Lines 🚦**:
- **Overbought & Oversold Levels**: Horizontal lines plotted at `overbought1`, `overbought2`, `oversold1`, and `oversold2` levels serve as visual cues for overbought and oversold conditions.
- **Zero Line**: A central reference line at 0, indicating neutral momentum.
### 📈 **How to Use the Indicator**
#### 1. **Day Traders ⚡**
For day traders, the Momentum Channel Indicator can be a quick signal generator for short-term trades. Here's how you can use it:
- **Identify Entry Points 🎯**: Look for a **bullish crossover** when `mci1` crosses above `mci2` from below the `oversold1` level. This signals a potential upward reversal.
- **Spot Exit Points 🏁**: Watch for a **bearish crossunder** when `mci1` crosses below `mci2` from above the `overbought1` level. This could indicate a downward reversal.
- **Scalping 🔄**: In a fast-moving market, use the indicator to scalp by entering and exiting trades at these crossover points, with a tight stop-loss strategy.
#### 2. **Swing Traders 🎢**
Swing traders benefit from using the Momentum Channel Indicator to identify potential reversal points over a longer period:
- **Trend Confirmation 📊**: Use the smoothing effect of `mci2` to confirm trends. If `mci2` remains consistently above 0, it indicates a strong bullish trend, and vice versa.
- **Overbought/Oversold Reversals 🚀**: Enter trades when the price approaches the overbought or oversold levels (`overbought1`, `oversold1`). Combine this with other indicators, such as RSI, for more reliable signals.
- **Hold Positions 🧗**: Let the momentum lines guide your hold strategy. If the momentum lines stay aligned (both `mci1` and `mci2` are moving in the same direction), consider holding the position until a crossover or reversal signal appears.
#### 3. **Long-Term Investors 🏦**
For long-term investors, the Momentum Channel Indicator helps in fine-tuning entry and exit points based on broader market momentum:
- **Divergence Analysis 📐**: Look for divergence between the price and the momentum lines. If the price makes new highs but the momentum lines do not, it could signal a weakening trend and a potential reversal.
- **Strategic Entry/Exit 🏹**: Use the `overbought2` and `oversold2` levels to strategically enter or exit positions. These secondary levels provide an early warning before the market reaches extreme conditions.
- **Risk Management 🛡️**: The indicator can also be used as part of a risk management strategy by identifying when to reduce exposure in overbought markets or increase exposure in oversold markets.
### 🖼️ **Visualization & Interpretation**
The Momentum Channel Indicator is visually intuitive, with each component providing key insights:
1. **Momentum Lines (MCI1 & MCI2) 📈**:
- **Blue Line (`mci1`)**: Represents the main momentum line, providing immediate insights into market direction.
- **Orange Line (`mci2`)**: A secondary momentum line, further smoothed to confirm trends.
2. **Overbought/Oversold Levels 🔴🟢**:
- **Solid & Dashed Lines**: These lines highlight overbought and oversold regions, guiding traders on when to consider entering or exiting trades.
3. **MCI Difference (Purple Area) 🌌**:
- **Shaded Area**: The difference between `mci1` and `mci2`, shaded in purple, helps visualize the strength of the momentum. The larger the shaded area, the stronger the momentum.
### 🚀 **Advanced Tips & Tricks**
For those looking to maximize the potential of the Momentum Channel Indicator, here are some advanced strategies:
1. **Combine with Volume Indicators 📊**: Use volume indicators like OBV (On-Balance Volume) or Volume Oscillator to confirm momentum signals. For instance, a bullish crossover combined with increasing volume can reinforce a buy signal.
2. **Multiple Timeframe Analysis 🕒**: Apply the Momentum Channel Indicator across multiple timeframes (e.g., daily and weekly) to get a more comprehensive view of the market. This can help in aligning short-term trades with long-term trends.
3. **Adjusting Parameters 🔄**: Depending on market conditions, tweak the `length1` and `length2` parameters. In a highly volatile market, shorter lengths might provide quicker signals, whereas in a stable market, longer lengths could smooth out noise.
4. **Divergence & Convergence 📐**: Watch for divergence between price and momentum lines as a leading indicator of potential reversals. Convergence (when the price and momentum move in sync) can confirm the strength of the trend.
### **Conclusion**
The **Uptrick: Momentum Channel Indicator** is a versatile tool that can be customized for various trading styles and market conditions. Whether you're trading in fast-paced environments or analyzing long-term trends, this indicator offers a clear and intuitive way to gauge market momentum, identify potential reversals, and make informed trading decisions.
By understanding and applying the principles outlined above, you can harness the full power of this indicator, transforming your trading strategy from good to great! 🌟
Machine Learning Momentum Index (MLMI) [Zeiierman]█ Overview
The Machine Learning Momentum Index (MLMI) represents the next step in oscillator trading. By blending traditional momentum analysis with machine learning, MLMI delivers a potent and dynamic tool that aligns with the complexities of modern financial landscapes. Offering traders an adaptive way to understand and act on market momentum and trends, this oscillator provides real-time insights into market momentum and prevailing trends.
█ How It Works:
Momentum Analysis: MLMI employs a dual-layer analysis, utilizing quick and slow weighted moving averages (WMA) of the Relative Strength Index (RSI) to gauge the market's momentum and direction.
Machine Learning Integration: Through the k-Nearest Neighbors (k-NN) algorithm, MLMI intelligently examines historical data to make more accurate momentum predictions, adapting to the intricate patterns of the market.
MLMI's precise calculation involves:
Weighted Moving Averages: Calculations of quick (5-period) and slow (20-period) WMAs of the RSI to track short-term and long-term momentum.
k-Nearest Neighbors Algorithm: Distances between current parameters and previous data are measured, and the nearest neighbors are used for predictive modeling.
Trend Analysis: Recognition of prevailing trends through the relationship between quick and slow-moving averages.
█ How to use
The Machine Learning Momentum Index (MLMI) can be utilized in much the same way as traditional trend and momentum oscillators, providing key insights into market direction and strength. What sets MLMI apart is its integration of artificial intelligence, allowing it to adapt dynamically to market changes and offer a more nuanced and responsive analysis.
Identifying Trend Direction and Strength: The MLMI serves as a tool to recognize market trends, signaling whether the momentum is upward or downward. It also provides insights into the intensity of the momentum, helping traders understand both the direction and strength of prevailing market trends.
Identifying Consolidation Areas: When the MLMI Prediction line and the WMA of the MLMI Prediction line become flat/oscillate around the mid-level, it's a strong sign that the market is in a consolidation phase. This insight from the MLMI allows traders to recognize periods of market indecision.
Recognizing Overbought or Oversold Conditions: By identifying levels where the market may be overbought or oversold, MLMI offers insights into potential price corrections or reversals.
█ Settings
Prediction Data (k)
This parameter controls the number of neighbors to consider while making a prediction using the k-Nearest Neighbors (k-NN) algorithm. By modifying the value of k, you can change how sensitive the prediction is to local fluctuations in the data.
A smaller value of k will make the prediction more sensitive to local variations and can lead to a more erratic prediction line.
A larger value of k will consider more neighbors, thus making the prediction more stable but potentially less responsive to sudden changes.
Trend length
This parameter controls the length of the trend used in computing the momentum. This length refers to the number of periods over which the momentum is calculated, affecting how quickly the indicator reacts to changes in the underlying price movements.
A shorter trend length (smaller momentumWindow) will make the indicator more responsive to short-term price changes, potentially generating more signals but at the risk of more false alarms.
A longer trend length (larger momentumWindow) will make the indicator smoother and less responsive to short-term noise, but it may lag in reacting to significant price changes.
Please note that the Machine Learning Momentum Index (MLMI) might not be effective on higher timeframes, such as daily or above. This limitation arises because there may not be enough data at these timeframes to provide accurate momentum and trend analysis. To overcome this challenge and make the most of what MLMI has to offer, it's recommended to use the indicator on lower timeframes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Filtered Momentum Indicator (FMI)The Filtered Momentum Indicator (FMI) is a tool created to assist traders in identifying changes in momentum and gaining insights into potential shifts in price trends. By combining the concepts of momentum and Bollinger Bands, the FMI offers a unique perspective on momentum values and their relationship to price movements, helping traders make informed trading decisions. The FMI is calculated using two main components:
-- Momentum Calculation : Momentum measures the strength and velocity of price changes. It is calculated by comparing the current price to the price 14 (default) periods ago and expressing it as a percentage.
-- Bollinger Bands Calculation : Bollinger Bands are based on the momentum values and provide a range within which the momentum is expected to fluctuate. The upper and lower bands are determined using a specified period (default of 20) and deviations (default of 2.0).
The FMI consists of two lines : F+ (Filtered Plus) and F- (Filtered Minus). These lines help gauge the strength of bullish and bearish momentum:
-- F+ represents the difference between the upper Bollinger Band and the momentum values. It indicates the strength of bullish momentum. F+ is colored aqua.
-- F- represents the difference between the momentum values and the lower Bollinger Band. It indicates the strength of bearish momentum. F- is colored yellow.
When analyzing the FMI, pay attention to the relationship between F+ and F-:
-- If F- is greater than F+ , it suggests potential bullish momentum, indicating that prices may have room to rise.
-- If F+ is greater than F- , it suggests potential bearish momentum, indicating that prices may have room to decline.
Coloration of the FMI enhances its interpretability - when F- is greater than F+, the indicator color is set to lime (green), signaling potential bullish momentum; when F+ is greater than F-, the indicator color is set to fuchsia (purple), signaling potential bearish momentum.
The FMI can be applied in various ways for trading strategies:
-- Identifying Potential Reversals : Watch for crossovers between the F- and F+ lines, as they may indicate a potential shift in momentum and offer opportunities to enter or exit trades.
-- Confirmation Tool : Combine the FMI with other technical indicators or price patterns to validate potential trend reversals or continuations. By aligning signals from different indicators, you can strengthen your trading decisions.
-- Trade Timing : Consider taking trades in the direction of the dominant FMI color. When the indicator shows strong bullish momentum (F- > F+), consider going long. Conversely, when it shows strong bearish momentum (F+ > F-), consider going short.
It is essential to be aware of the limitations of the FMI:
-- False Signals : The FMI, like any indicator, may generate false signals, especially during low volatility or choppy market conditions. Always use the FMI in conjunction with other analysis techniques for confirmation.
-- Lagging Nature : The FMI relies on historical price data, causing it to lag behind sudden market moves. Keep in mind that the FMI provides insights based on past momentum and may not capture immediate changes in market conditions.
By combining momentum and Bollinger Bands, this indicator provides a unique perspective for making informed trading decisions. Utilize the FMI in conjunction with other analysis techniques, considering its limitations, to enhance your trading strategy and improve decision-making.
TRIX with Momentum----------- ENGLISH --------------
This indicator is called "TRIX with Momentum" and is used to analyze the momentum of an asset's price and predict potential trend reversals. The logic of operation is based on the combination of two indicators: the Triple Exponential Moving Average (TRIX) and the momentum oscillator.
The TRIX is calculated using three exponential moving averages (EMA) of the asset's closing price, with a user-defined length (set to 14 by default). The TRIX is then normalized and centered around 0 to facilitate analysis of its relationship with the momentum oscillator.
The momentum oscillator is calculated using the EMA of the normalized TRIX with a user-defined length (set to 14 by default).
The indicator plots the normalized TRIX and the momentum oscillator on a chart, using different colors to indicate whether the TRIX is above or below 0. Additionally, the color of the y-axis label changes based on the position of the oscillator, while the color of the x-axis label remains gray.
The indicator uses a weighted average between the normalized TRIX and the momentum oscillator to create a colored background of the chart, which changes based on the weighted average. If the weighted average is positive, the chart's background is green, otherwise it is red. Finally, a horizontal line is drawn at point 0 to facilitate visual analysis of the chart.
------------ ITALIANO -------------
Questo indicatore è chiamato "TRIX with Momentum" ed è utilizzato per analizzare il momentum del prezzo di un asset e prevedere eventuali inversioni di trend. La logica di funzionamento è basata sulla combinazione di due indicatori: il TRIX (Indicatori di media mobile Tripla Esponenziale) e l'oscillatore momentum.
L'indicatore consente all'utente di impostare la lunghezza del TRIX e dell'oscillatore momentum come input personalizzato. Il TRIX viene calcolato utilizzando tre medie mobili esponenziali (EMA) della chiusura dei prezzi dell'asset, mentre l'oscillatore momentum viene calcolato utilizzando l'EMA del TRIX normalizzato.
Il TRIX normalizzato viene centrato intorno allo 0 per facilitare l'analisi della sua relazione con l'oscillatore momentum. L'indicatore plotta il TRIX normalizzato e l'oscillatore momentum su un grafico, utilizzando diversi colori per indicare se il TRIX è sopra o sotto lo 0.
L'indicatore utilizza una media pesata tra il TRIX normalizzato e l'oscillatore momentum per creare uno sfondo colorato del grafico, che cambia in base alla media pesata. L'utente può impostare il peso da dare al TRIX e all'oscillatore momentum come input personalizzato, e il peso dell'oscillatore momentum verrà automaticamente impostato come complementare al peso del TRIX.
Se la media pesata è positiva, lo sfondo del grafico è verde, altrimenti è rosso. Viene tracciata anche una linea orizzontale al punto 0 per facilitare l'analisi visiva del grafico.
Infine, il colore dell'etichetta dell'asse y cambia in base alla posizione dell'oscillatore, mentre il colore dell'etichetta dell'asse x rimane sempre grigio.
Indicator: Intrady Momentum IndexThe Intraday Momentum Index (IMI), developed by Tushar Chande, is a cross-breed between RSI and candlestick analysis. IMI determines the candle type that dominated the recent price action, using that to pinpoint the extremes in intraday momentum.
As the market tries to bottom after a sell off, there are gradually more candles with green bodies, even though prices remain in a narrow range. IMI can be used to detect this shift, because its values will increase towards 70. Similarly, as the market begins to top, there will be more red candles, causing IMI to decline towards 20. When the market is in trading range, IMI values will be in the neutral range of 40 to 60.
Usually intraday momentum leads interday momentum. QStick can show interday momentum, it complements IMI. You will find it in my published indicators.
I have added volatility bands based OB/OS, in addition to static OB/OS levels. You can also turn on IMI Ehlers smoothing. BTW, all parameters are configurable, so do check out the options page.
List of my other indicators:
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- Google doc: docs.google.com
CSI Cycle Swing Momentum Indicator ProAdaptive Ultra-Smooth Momentum (Cycle-Swing Indicator – CSI)
The Cycle-Swing Indicator (CSI) is an advanced, adaptive momentum oscillator designed to extract clean, reliable signals from market data by focusing on the swing of the dominant market cycle rather than raw momentum. By identifying and aligning with the current dominant cycle, the CSI produces a momentum curve that is exceptionally smooth, responsive, and context-aware.
Key Advantages
The CSI offers several improvements over traditional momentum-based indicators:
Ultra-smooth signal line without sacrificing responsiveness
Zero-lag behavior, enabling timely entries and exits
Pronounced turning-point precision, enhancing signal clarity
Adaptive to real market cycles, automatically adjusting to changing conditions
Reliable deviation and divergence detection, even in noisy environments
Why Standard Indicators Fall Short
Conventional oscillators often struggle in real-world market conditions:
Excessive noise leads to frequent false signals.
Added smoothing reduces noise but introduces significant lag, delaying actionable insights.
Fixed-length parameters make indicators highly sensitive to user settings—you never truly know the "right" length.
The CSI solves all these challenges through its adaptive cyclic algorithm, which automatically aligns itself with the market’s dominant cycle—no manual tuning required.
Practical Example
In the example chart, the CSI highlights clear turning points and deviations with far less noise than the standard momentum indicator, demonstrating its superior clarity and responsiveness.
How to Use
The CSI is fully adaptive and requires no parameters. Simply apply it to any symbol and timeframe—the indicator automatically detects the dominant cycle and produces an ultra-smooth, cycle-aligned momentum curve.
Included features:
Adaptive upper and lower bands identifying extreme conditions
Automatic divergence detection (toggle on/off)
Works on any timeframe and any asset
Adaptive length - no input parameter required
How to Read the Indicator
The CSI functions similarly to a traditional momentum oscillator but with enhanced adaptive context:
Look for divergences between price and the CSI signal line — powerful early warnings of weakening trends or impending shifts.
Note on Divergence Signals:
The divergence markers displayed on the chart are generated using embedded pivot-based detection. Because pivots must be confirmed by price action, divergence signals can only be plotted after a pivot forms. For real-time monitoring on the latest bar, users should watch for early-forming divergences as they develop, since confirmed pivot-based divergences will always appear with a slight delay. Script parameters are available for precise adjustment of pivot detection behaviour.
Info: Legacy vs. Pro Version
This is the actively maintained and continuously enhanced edition of my free, open-source indicator “Cycle Swing Momentum”. The Pro Version will remain fully up to date with the latest Pine Script standards and will receive ongoing refinements and feature improvements, all while preserving the core logic and intent of the original tool. The legacy version will continue to be available for code review and educational purposes, but it will no longer receive updates. The legacy open-source version is always available in the public TV indicator repository.
Adaptive Momentum Oscillator [BackQuant]Adaptive Momentum Oscillator
Please take time to read the following.
Conceptual Foundation and Innovation
The Adaptive Momentum Oscillator brings a new approach to momentum trading by introducing percentile-based adaptive thresholding. Unlike traditional momentum oscillators that rely on static overbought and oversold levels, this indicator adjusts dynamically to changing market conditions, providing more relevant signals in real-time. By combining percentile-based thresholds with a smoothed momentum oscillator, this tool allows traders to detect trend shifts with a higher degree of accuracy.
Technical Composition and Calculation
The core of this oscillator uses a lookback period to calculate the highest and lowest values of a smoothed price source (using a non-robust moving average). These values are then used to compute the oscillator, which normalizes the current price between the lookback high and low. The true innovation lies in its adaptive thresholds, which adjust based on percentiles of past oscillator values over a user-defined lookback period.
Lookback Period: The indicator checks the highest and lowest smoothed price over a set period, which becomes the basis for calculating momentum.
Percentile-Based Thresholds: The upper and lower thresholds are dynamically set at user-defined percentiles of historical momentum values, allowing the oscillator to adapt to the volatility and strength of the market.
Smoothing Length: Users can adjust the smoothing of the source input to fine-tune the sensitivity of the oscillator.
Features and User Inputs offer a host of customizable settings to suit different market conditions and trading strategies:
Adaptive Thresholding: Traders can set the lookback period and define the percentile levels for the upper (long) and lower (short) thresholds. This provides the ability to dynamically adjust to changing market conditions and avoid static thresholds that may become irrelevant over time.
Signal Line Customization: Users can configure the signal line width, colors for long, short, and neutral conditions, and choose whether to display adaptive threshold lines on the chart.
Candle Coloring: An optional feature allows traders to color the price bars based on the oscillator's trend signal, adding a visual confirmation layer for trend shifts.
Practical Applications
This oscillator is particularly effective in markets where the strength and direction of momentum are essential for identifying potential trend reversals or confirming ongoing trends. Traders can leverage the Adaptive Momentum Oscillator to:
Capture Adaptive Trends: The percentile-based thresholds adjust dynamically, ensuring that traders catch significant trends while filtering out market noise.
Avoid False Signals: By adapting to historical momentum levels, the oscillator reduces the risk of false breakouts or breakdowns, allowing for more reliable entries and exits.
Optimize Entries and Exits: With dynamically adjusting thresholds, the oscillator helps traders time their positions more effectively, minimizing the risk of getting caught in choppy or uncertain markets.
Advantages and Strategic Value
It offers a clear advantage over traditional static oscillators by continuously adjusting its sensitivity to market conditions. The adaptive percentile thresholds ensure that the indicator remains relevant, regardless of changes in volatility or market direction. This feature, combined with a customizable UI, makes the Adaptive Momentum Oscillator a powerful tool for traders looking to refine their momentum-based strategies with dynamic thresholds.
Summary and Usage Tips
The Adaptive Momentum Oscillator is a versatile tool for both trend-following and contrarian traders. Its dynamic nature allows for better alignment with current market conditions, while its user-friendly inputs offer extensive customization options. Traders are encouraged to experiment with the percentile-based threshold settings to find the optimal balance between signal sensitivity and noise reduction, particularly in fast-moving or volatile markets.
This indicator is best used in combination with other trend-confirmation tools, offering a dynamic layer to your trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Squeeze Momentum DeluxeThe Squeeze Momentum Deluxe is a comprehensive trading toolkit built with features of momentum, volatility, and price action. This script offers a suite for both mean reversion and trend-following analysis. Developed based on the original TTM Squeeze implementation by @LazyBear, this indicator introduces several innovative components to enhance your trading insights.
🔲 Components and Features
Momentum Oscillator - as rooted in the TTM Squeeze, quantifies the relationship between price and its extremes over a defined period. By normalizing the calculation, the values become comparable throughout time and across securities, allowing for a nuanced assessment of Bullish and Bearish momentum. Furthermore, by presenting it as a ribbon with a signal line we gain additional information about the direction of price swings.
Squeeze Bars - The original squeeze concept is based on the relationship between the Bollinger Bands and Keltner Channel , once the BB resides inside the KC a squeeze occurs. By understanding their fundamentals a new form of calculation can be inferred.
method bb(float src, simple int len, simple float mult) => method kc(float src, simple int len, simple float mult) =>
float basis = ta.sma (src, len) float basis = ta.sma (src, len)
float dev = ta.stdev(src, len) float rng = ta.atr ( len)
float upper = basis + dev * mult float upper = basis + rng * mult
float lower = basis - dev * mult float lower = basis - rng * mult
Both BB and KC are constructed upon a moving average with the addition of Standard Deviation and Average True Range respectively. Therefore, the calculation can be transformed to when the Stdev is lower than the ATR a squeeze occurs.
method sqz(float src, simple int len) =>
float dev = ta.stdev(src, len)
float atr = ta.atr ( len)
dev < atr ? true : false
This indicator uses three different thresholds for the ATR to gain three levels of price "Squeeze" for further analysis.
Directional Flux- This component measures the overall direction of price volatility, offering insights into trend sentiment. Presented as waves in the background, it includes an OverFlux feature to signal extreme market bias in a particular direction which can signal either exhaustion or vital continuation. Additionally, the user can choose if to base the calculation on Heikin-Ashi Candles to bias the tool toward trend assessment.
Confluence Gauges - Placed at the top and bottom of the indicator, these gauges measure confluence in the relationship between the Momentum Oscillator and Directional Flux. They provide traders with an easily interpretable visual aid for detecting market sentiment. Reversal doritos displayed alongside them contribute to mean reversion analysis.
Divergences (Real-Time) - Equipped with a custom algorithm, the indicator detects real-time divergences between price and the oscillator. This dynamic feature enhances your ability to spot potential trend reversals as they occur.
🔲 Settings
Directional Flux Length - Adjusts the period of which the background volatility waves operate on.
Trend Bias - Bases the calculation of the Flux to HA candles to bias its behavior toward the trend of price action.
Squeeze Momentum Length - Calibrates the length of the main oscillator ribbon as well as the period for the squeeze algorithm.
Signal - Controls the width of the ribbon. Lower values result in faster responsiveness at the cost of premature positives.
Divergence Sensitivity - Adjusts a threshold to limit the amount of divergences detected based on strength. Higher values result in less detections, stronger structure.
🔲 Alerts
Sell Signal
Buy Signal
Bullish Momentum
Bearish Momentum
Bullish Flux
Bearish Flux
Bullish Swing
Bearish Swing
Strong Bull Gauge
Strong Bear Gauge
Weak Bull Gauge
Weak Bear Gauge
High Squeeze
Normal Squeeze
Low Squeeze
Bullish Divergence
Bearish Divergence
As well as the option to trigger 'any alert' call.
The Squeeze Momentum Deluxe is a comprehensive tool that goes beyond traditional momentum indicators, offering a rich set of features to elevate your trading strategy. I recommend using toolkit alongside other indicators to have a wide variety of confluence to therefore gain higher probabilistic and better informed decisions.
Histogram Momentum Shaded CandlesDescription:
The Histogram Momentum Shaded Candles indicator (HMSC) is a powerful technical analysis tool that combines the concepts of the MACD (Moving Average Convergence Divergence) indicator and shaded candlestick visualization. It provides insights into momentum and trend strength by representing the MACD histogram as shaded candles on the chart.
How it Works:
The HMSC indicator calculates the MACD (Moving Average Convergence Divergence) using user-defined parameters such as the fast length, slow length, source, signal smoothing, and moving average types. It then calculates the MACD histogram by subtracting the signal line from the MACD line. The indicator transforms the histogram values into transparency levels for the shaded candles, representing bullish and bearish momentum.
Usage:
To effectively utilize the Histogram Momentum Shaded Candles indicator, follow these steps:
1. Apply the HMSC indicator to your chart by adding it from the available indicators.
2. Customize the MACD settings such as the fast length, slow length, source, signal smoothing, and moving average types according to your trading preferences.
3. Observe the shaded candles plotted on the chart:
- Bullish shaded candles (green by default) indicate positive momentum and potential buying pressure.
- Bearish shaded candles (red by default) indicate negative momentum and potential selling pressure.
4. Assess the intensity of the shaded candles:
5. Shading intensity is determined by the magnitude of the MACD histogram, with higher values resulting in more opaque candles.
6. The shading intensity reflects the strength of momentum and can help identify significant shifts in price action.
7. Combine the analysis of shaded candles with traditional candlestick patterns, trend lines, support and resistance levels, and other technical indicators to validate potential trade setups.
8. Implement appropriate risk management strategies, including setting stop-loss orders and position sizing, to manage your trades effectively and protect your capital.
