Non-Sinusoidal Multi-Layered Moving Average OscillatorThis indicator utilizes multiple moving averages (MAs) of different lengths their difference and its rate of change to provide a comprehensive view of both short-term and long-term market trends. The output signal is characterized by its non-sinusoidal nature, offering distinct advantages in trend analysis and market forecasting.
Combining the difference between two moving averages with the ROC allows to assess not only the direction and strength of the trend but also the momentum behind it. Transforming these signal in to non-sinusoidal output enhances its utility.
The indicator allows traders to select any one or more of seven moving average options. Larger timeframes (e.g., MA89/MA144) provide a broader identification of the overall trend, helping to understand the general market direction. Smaller timeframes (e.g., MA5/MA8) are more sensitive to price changes and can indicate better entry and exit points, aiding in the identification of retracements and pullbacks. By combining multiple timeframes, traders can get a comprehensive view of the market, enabling more precise and informed trading decisions.
Key Features:
Multiple Moving Averages:
The indicator calculates several exponential moving averages (EMAs) based on different lengths: MA5, MA8, MA13, MA21, MA34, MA55, MA89, and MA144.
These MAs are further smoothed using a secondary exponential moving average, with the smoothing length customizable by the user.
Percentage Differences:
The indicator computes the percentage differences between successive MAs (e.g., (MA5 - MA8) / MA8 * 100). These differences highlight the relative movement of prices over different periods, providing insights into market momentum and trend strength.
Short-term MA differences (e.g., MA5/MA8) are more sensitive to recent price changes, making them useful for detecting quick market movements.
Long-term MA differences (e.g., MA89/MA144) smooth out short-term fluctuations, helping to identify major trends.
Rate of Change (ROC):
The indicator applies the Rate of Change (ROC) to the percentage differences of the MAs. ROC measures the speed at which the percentage differences are changing over time, providing an additional layer of trend analysis.
ROC helps in understanding the acceleration or deceleration of market trends, indicating the strength and potential reversals.
Transformations:
The percentage differences undergo a series of mathematical transformations (either inverse hyperbolic sine transformation or inverse fisher transformation) to refine the signal and enhance its interpretability. These transformations include adjustments to stabilize the values and highlight significant movements.
checkbox allows users to select which mathematical transformations to use.
Non-Sinusoidal Nature:
The output signal of this indicator is non-sinusoidal, characterized by abrupt changes and distinct patterns rather than smooth, wave-like oscillations.
The non-sinusoidal signal provides clearer demarcations of trend changes and is more responsive to sudden market shifts.
This nature reduces the lag typically associated with sinusoidal indicators, allowing for more timely and accurate trading decisions.
Customizable Options:
Users can select which MA pairs to include in the analysis using checkboxes. This flexibility allows the indicator to adapt to different trading strategies, whether focused on short-term movements or long-term trends.
Visual Representation:
The indicator plots the transformed values on a separate panel, making it easy for traders to visualize the trends and potential entry or exit points.
Usage Scenarios:
Short-Term Trading: By focusing on shorter MAs (e.g., MA5/MA8), traders can capture quick market movements and identify short-term trends.
Long-Term Analysis: Utilizing longer MAs (e.g., MA89/MA144) helps in identifying major market trends.
Combination of MAs: The ability to mix different MA lengths provides a balanced view, helping traders make decisions based on both immediate price actions and overall market direction.
Practical Benefits:
Early Signal Detection: The sensitivity of short-term MAs provides early signals for potential trend changes, assisting traders in timely decision-making.
Trend Confirmation: Long-term MAs offer stable trend confirmation, reducing the likelihood of false signals in volatile markets.
Noise Reduction: The mathematical transformations and ROC applied to the percentage differences help in filtering out market noise, focusing on meaningful price movements.
Improved Responsiveness: The non-sinusoidal nature of the signal allows the indicator to react more quickly to market changes, providing more accurate and timely trading signals.
Clearer Trend Demarcations: Non-sinusoidal signals make it easier to identify distinct phases of market trends, aiding in better interpretation and decision-making.
Osciladores centrados
CCI and MACD Auto Trading Strategy with Risk/RewardOverview:
This strategy combines the Commodity Channel Index (CCI) and the Moving Average Convergence Divergence (MACD) indicators to automate trading decisions. It dynamically sets stop-loss and take-profit levels based on recent lows and highs, ensuring a risk/reward ratio of 1:1.5. This script aims to leverage trend and momentum signals while maintaining effective risk management.
Originality and Usefulness:
This script is not just a simple mashup of CCI and MACD indicators; it incorporates dynamic risk management by setting stop-loss and take-profit levels based on recent price action. This approach helps traders to:
・Identify potential trend reversals using the combination of CCI and MACD signals.
・Manage trades effectively by setting realistic stop-loss and take-profit levels based on recent market data.
・Maintain a balanced risk/reward ratio, which is essential for sustainable trading.
Indicators Used:
・CCI (Commodity Channel Index):
・Measures the deviation of the price from its average over a specified period, typically ranging from -100 to +100.
・Helps identify overbought and oversold conditions.
・MACD (Moving Average Convergence Divergence):
・Utilizes the difference between short-term and long-term moving averages to indicate trend strength and direction.
・Provides momentum signals that can be used for timing entries and exits.
How It Works:
Entry Conditions:
Long Entry:
・The MACD histogram is above zero.
・The CCI crosses above the -100 line.
Short Entry:
・The MACD histogram is below zero.
・The CCI crosses below the +100 line.
Exit Conditions:
Long Positions:
・The stop-loss is set at the recent low.
・The take-profit is set at 1.5 times the distance between the entry price and the stop-loss.
Short Positions:
・The stop-loss is set at the recent high.
・The take-profit is set at 1.5 times the distance between the entry price and the stop-loss.
Risk Management:
・The script dynamically adjusts stop-loss and take-profit levels based on recent market data, ensuring that the risk/reward ratio is maintained at 1:1.5.
・This approach helps in managing the risk effectively while aiming for consistent profits.
Strategy Properties:
・Account Size: Configured for a realistic account size suitable for the average trader.
・Commission and Slippage: Includes settings for realistic commission and slippage to reflect real market conditions.
・Risk per Trade: Designed to risk no more than 5-10% of equity per trade, aligning with sustainable trading practices.
・Backtesting Results: Configured to generate a sufficient sample size (ideally more than 100 trades) for reliable backtesting results.
Revised Backtesting Settings
Ensure that your backtesting settings are realistic:
・Account Size: Set a realistic initial capital suitable for the average trader.
・Commission and Slippage: Include realistic commission fees and slippage.
・Risk Management: Ensure that each trade risks no more than 5-10% of the account equity.
・Sufficient Sample Size: Choose a dataset that will generate more than 100 trades to provide a robust sample size.
Glitch IndexGlitch Index is an oscillator from an unknown origin that is discovered in 2013 as a lua indicator taken from MetaStock days and we are not really sure how far back the original idea goes.
How it Works?
As I found this indicator and looking at it's code in different platform I can see it comes back from a basic idea of getting a price value, calculating it's smoothed average with a set multiplier and getting the difference then presenting it on a simplified scale. It appears to be another interpretation of figuring out price acceleration and velocity. The main logic is calculated as below:
price = priceSet(priceType)
_ma = getAverageName(price, MaMethod, MaPeriod)
rocma = ((_ma - _ma ) * 0.1) + 1
maMul = _ma * rocma
diff = price - maMul
gli_ind = (diff / price) * -10
How to Use?
Glitch Index can be used based on different implementations and along with your already existing trading system as a confirmation. Yoıu can use it as a Long signal when the histogram crosses inner levels or you can use it as an overbough and oversold signals when the histogram crosses above outter levels and gets back in the range between outter and inner levels.
You can customise the settings and set your prefered inner and outter levels in indicator settings along with gradient or static based coloring and modify the code as you see fit. The coloring code is set below:
gli_col = gli_ind > outterLevel ? color.green : gli_ind < -outterLevel ? color.red : gli_ind > innerLevel ? color.rgb(106, 185, 109, 57) : gli_ind < -innerLevel ? color.rgb(233, 111, 111, 40) : color.new(color.yellow, 60)
gradcol = color.from_gradient(gli_ind, -outterLevel, outterLevel, color.red, color.green)
colorSelect = colorType == "Gradient" ? gradcol : gli_col
KNN OscillatorOverview
The KNN Oscillator is an advanced technical analysis tool designed to help traders identify potential trend reversals and market momentum. Using the K-Nearest Neighbors (KNN) algorithm, this oscillator normalizes KNN values to create a dynamic and responsive indicator. The oscillator line changes color to reflect the market sentiment, providing clear visual cues for trading decisions.
Key Features
Dynamic Color Oscillator: The line changes color based on the oscillator value – green for positive, red for negative, and grey for neutral.
Advanced KNN Algorithm: Utilizes the K-Nearest Neighbors algorithm for precise trend detection.
Normalized Values: Ensures the oscillator values are normalized to align with the stock price range, making it applicable to various assets.
Easy Integration: Can be easily added to any TradingView chart for enhanced analysis.
How It Works
The KNN Oscillator leverages the K-Nearest Neighbors algorithm to calculate the average distance of the nearest neighbors over a specified period. These values are then normalized to match the stock price range, ensuring they are comparable across different assets. The oscillator value is derived by taking the difference between the normalized KNN values and the source price. The line's color changes dynamically to provide an immediate visual indication of the market's state:
Green: Positive values indicate upward momentum.
Red: Negative values indicate downward momentum.
Grey: Neutral values indicate a stable or consolidating market.
Usage Instructions
Trend Reversal Detection: Use the color changes to identify potential trend reversals. A shift from red to green suggests a bullish reversal, while a shift from green to red indicates a bearish reversal.
Momentum Analysis: The oscillator's value and color help gauge market momentum. Strong positive values (green) indicate strong upward momentum, while strong negative values (red) indicate strong downward momentum.
Market Sentiment: The dynamic color changes provide an easy-to-understand visual representation of market sentiment, helping traders make informed decisions quickly.
Confirmation Tool: Use the KNN Oscillator in conjunction with other technical indicators to confirm signals and improve the accuracy of your trades.
Scalability: Applicable to various timeframes and asset classes, making it a versatile tool for all types of traders.
Chande Momentum Oscillator (CMO) Buy Sell Strategy [TradeDots]The "Chande Momentum Oscillator (CMO) Buy Sell Strategy" leverages the CMO indicator to identify short-term buy and sell opportunities.
HOW DOES IT WORK
The standard CMO indicator measures the difference between recent gains and losses, divided by the total price movement over the same period. However, this version of the CMO has some limitations.
The primary disadvantage of the original CMO is its responsiveness to short-term volatility, making the signals less smooth and more erratic, especially in fluctuating markets. This instability can lead to misleading buy or sell signals.
To address this, we integrated the concept from the Moving Average Convergence Divergence (MACD) indicator. By applying a 9-period exponential moving average (EMA) to the CMO line, we obtained a smoothed signal line. This line acts as a filter, identifying confirmed overbought or oversold states, thereby reducing the number of false signals.
Similar to the MACD histogram, we generate columns representing the difference between the CMO and its signal line, reflecting market momentum. We use this momentum indicator as a criterion for entry and exit points. Trades are executed when there's a convergence of CMO and signal lines during an oversold state, and they are closed when the CMO line diverges from the signal line, indicating increased selling pressure.
APPLICATION
Since the 9-period EMA smooths the CMO line, it's less susceptible to extreme price fluctuations. However, this smoothing also makes it more challenging to breach the original +50 and -50 benchmarks.
To increase trading opportunities, we've tightened the boundary ranges. Users can customize the target benchmark lines in the settings to adjust for the volatility of the underlying asset.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Signal Cool Down Period: 5
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
MACD Highlight Zones for PrimetimeUse the MACD Highlight Zones to easily spot changes in market momentum and make more informed trading decisions.
The MACD Highlight Zones script visually enhances your chart by highlighting different zones based on the MACD's relationship to the zero line and its signal line. This script helps traders quickly identify the market's momentum and potential reversal points.
Features:
🟢 Green Background: Indicates the MACD line is above 0, signaling bullish momentum.
🟡 Yellow Background: Indicates the MACD line crosses the signal line, suggesting a potential momentum shift.
🔴 Red Background: Indicates the MACD line is below 0, signaling bearish momentum.
LBR-S310ROC @shrilssOriginally made by Linda Raschke, The S310ROC Indicator combines the Rate of Change (ROC) indicator with the 3-10 Oscillator (Modified MACD) and plots to capture rapid price movements and gauge market momentum.
- Rate of Change (ROC): This component of the indicator measures the percentage change in price over a specified short interval, which can be set by the user (default is 2 days). It is calculated by subtracting the closing price from 'X' days ago from the current close.
- 3-10 Oscillator (MACD; 3,10,16): This is a specialized version of the Moving Average Convergence Divergence (MACD) but uses simple moving averages instead of exponential. Using a fast moving average of 3 days and a slow moving average of 10 days with a smoothing period of 16.
- ROC Dots: A great feature based on the oscillator's readings. Dots are displayed directly on the oscillator or the price chart to provide visual momentum cues:
- Aqua Dots: Appear when all lines (ROC, MACD, Slowline) are sloping downwards, indicating bearish momentum and potentially signaling a sell opportunity.
- White Dots: Appear when all lines are sloping upwards, suggesting bullish momentum and possibly a buy signal.
Linear Regression Oscillator [ChartPrime]Linear Regression Oscillator Indicator
Overview:
The Linear Regression Oscillator is a custom TradingView indicator designed to provide insights into potential mean reversion and trend conditions. By calculating a linear regression on the closing prices over a user-defined period, this oscillator helps identify overbought and oversold levels and highlights trend changes. The indicator also offers visual cues and color-coded price bars to aid in quick decision-making.
Key Features:
◆ Customizable Look-Back Period:
Input: Length
Default: 20
Description: Determines the period over which the linear regression is calculated. A longer period smooths the oscillator but may lag, while a shorter period is more responsive but may be noisier.
◆ Overbought and Oversold Thresholds:
Inputs: Upper Threshold and Lower Threshold
Default: 1.5 and -1.5 respectively
Description: Define the upper and lower bounds for identifying overbought and oversold conditions. Values outside these thresholds suggest potential reversals.
◆ Candlestick Color Plotting:
Input: Plot Bar Color
Default: false
Description: Option to color the price bars based on the oscillator's value, providing a visual representation of market conditions. Bars turn cyan for positive oscillator values and blue for negative.
◆ Mean Reversion and Trend Signals:
Visual markers and labels indicate when the oscillator suggests mean reversion or trend changes, aiding in identifying key market turning points.
◆ Invalidation Levels:
Tracks the highest and lowest prices over a recent period to set levels where the current trend signal would be considered invalidated.
◆ Gradient Color Coding:
Utilizes gradient color coding to enhance the visualization of oscillator values, making it easier to interpret overbought and oversold conditions.
◆ Usage Notes:
Setting the Look-Back Period:
Adjust the "Length" input based on the timeframe and the type of trading you are conducting. Shorter periods are more suited for intraday trading, while longer periods can be used for swing trading.
Interpreting Thresholds:
Use the upper and lower threshold inputs to fine-tune the sensitivity of the overbought and oversold signals. Higher absolute values reduce the number of signals but increase their reliability.
Candlestick Coloring:
Enabling the "Plot Bar Color" option can help quickly identify the current state of the oscillator in relation to the zero line. This visual aid can be particularly useful in fast-moving markets.
Mean Reversion and Trend Signals:
Pay attention to the symbols and labels on the chart indicating mean reversion and trend changes. These signals are designed to highlight potential entry and exit points.
Invalidation Levels:
Use the plotted invalidation levels as stop-loss or signal invalidation points. If the price moves beyond these levels, the current trend signal is likely invalid.
This indicator helps traders identify overbought and oversold conditions, potential mean reversions, and trend changes based on the linear regression of the closing prices over a specified look-back period.
Multi Timeframe Moving Average Convergence Divergence {DCAquant}Overview
The MTF MACD indicator provides a unique view of MACD (Moving Average Convergence Divergence) and Signal Line dynamics across various timeframes. It calculates the MACD and Signal Line for each selected timeframe and aggregates them for analysis.
Key Features
MACD Calculation
Utilizes standard MACD calculations based on user-defined parameters like fast length, slow length, and signal smoothing.
Determines the difference between the MACD and Signal Line to identify convergence or divergence.
Multiple Timeframe Analysis
Allows users to select up to six different timeframes for analysis, ranging from minutes to days, providing a holistic view of market trends.
Calculates MACD and Signal Line for each timeframe independently.
Aggregated Analysis
Combines MACD and Signal Line values from multiple timeframes to derive a consolidated view.
Optionally applies moving average smoothing to aggregated MACD and Signal Line values for better clarity.
Position Identification
Determines the trading position (Long, Short, or Neutral) based on the relationship between MACD and Signal Line.
Considers the proximity of MACD and Signal Line to identify potential trading opportunities.
Visual Representation
Plots MACD and Signal Line on the price chart for visual analysis.
Utilizes color-coded backgrounds to indicate trading conditions (Long, Short, or Neutral) for quick interpretation.
Dynamic Table Display
Displays trading position alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table.
Offers flexibility in table placement and size for user preference.
How to Use
Parameter Configuration
Adjust parameters like fast length, slow length, and signal smoothing to fine-tune MACD calculations.
Select desired timeframes for analysis based on trading preferences and market conditions.
Interpretation
Monitor the relationship between MACD and Signal Line on the price chart.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable insights.
Decision Making
Consider entering Long positions when MACD is above the Signal Line and vice versa for Short positions.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management
Combine MTF MACD analysis with risk management strategies to optimize trade entries and exits.
Set stop-loss and take-profit levels based on individual risk tolerance and market conditions.
Conclusion
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator offers a robust framework for traders to analyze market trends across multiple timeframes efficiently. By combining MACD insights from various time horizons and presenting them in a clear and actionable format, it empowers traders to make informed decisions and enhance their trading strategies.
Disclaimer
The Multi Timeframe Moving Average Convergence Divergence (MTF MACD) indicator provided here is intended for educational and informational purposes only. Trading in financial markets involves risk, and past performance is not indicative of future results. The use of this indicator does not guarantee profits or prevent losses.
Please be aware that trading decisions should be made based on your own analysis, risk tolerance, and financial situation. It is essential to conduct thorough research and seek advice from qualified financial professionals before engaging in any trading activity.
The MTF MACD indicator is a tool designed to assist traders in analyzing market trends and identifying potential trading opportunities. However, it is not a substitute for sound judgment and prudent risk management.
By using this indicator, you acknowledge that you are solely responsible for your trading decisions, and you agree to indemnify and hold harmless the developer and distributor of this indicator from any losses, damages, or liabilities arising from its use.
Trading in financial markets carries inherent risks, and you should only trade with capital that you can afford to lose. Exercise caution and discretion when implementing trading strategies, and consider seeking independent financial advice if necessary.
Median Momentum with Buy/Sell Signals and Bar ColorMomentum Calculation:
Momentum is calculated as the difference between the current close price and the close price momentum_length periods ago: momentum = close - close .
Highest and Lowest Momentum:
The highest and lowest momentum values over the specified length are calculated.
Median Momentum:
The median momentum is calculated as the average of the highest and lowest momentum values.
Color Setting:
medianColor is set based on whether the momentum is above, below, or equal to the median momentum.
barColor is set similarly for bar coloring.
Plotting:
The script plots the median momentum and the actual momentum values.
Buy and sell signals are generated when momentum crosses over or under the median momentum.
The script also plots the buy and sell signals with arrows on the chart.
Velocity And Acceleration with Strategy: Traders Magazine◙ OVERVIEW
Hi, Ivestors and Traders... This Indicator, the focus is Scott Cong's article in the Stocks & Commodities September issue, “VAcc: A Momentum Indicator Based On Velocity And Acceleration”. I have also added a trading strategy for you to benefit from this indicator. First of all, let's look at what the indicator offers us and what its logic is. First, let's focus on the logic of the strategy.
◙ CONCEPTS
Here is a new indicator based on some simple physics concepts that is easy to use, responsive and precise. Learn how to calculate and use it.
The field of physics gives us some important principles that are highly applicable to analyzing the markets. In this indicator, I will present a momentum indicator. Scott Cong developed based on the concepts of velocity and acceleration this indicator. Of the many characteristics of price that traders and analysts often study, rate and rate of change are useful ones. In other words, it’s helpful to know: How fast is price moving, and is it speeding up or slowing down? How is price changing from one period to the next? The indicator I’m introducing here is calculated using the current bar (C) and every bar of a lookback period from the current bar. He named the indicator the VAcc since it’s based on the average of velocity line (av) and acceleration line (Acc) over the lookback period. For longer periods, the VAcc behaves the same way as the MACD, only it’s simpler, more responsive, and more precise. Interestingly, for shorter periods, VAcc exhibits characteristics of an oscillator, such as the stochastics oscillator.
◙ CALCULATION
The calculation of VAcc involves the following steps:
1. Relatively weighted average where the nearer price has the largest influence.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. The Velocity Average is smoothed with an exponential moving average. Now it get:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Similarly, accelerations for each bar within the lookback period and scale factor are calculated as:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEGY
In fact, Scott probably preferred to use it in periods 9 and 26 because it was similar to Macd and used the ratio of 0.5. However, I preferred to use the 8 and 21 periods to provide signals closer to the stochastic oscillator in the short term and used the 0.382 ratio. The logic of the strategy is this
Long Strategy → acc(Acceleration Line) > 0.1 and av(Velocity Average Line) > 0.1(Long Factor)
Short strategy → acc(Acceleration Line) < -0.1 and av(Velocity Average Line) < -0.1(Long Factor)
Here, you can change the Short Factor and Long Factor as you wish and produce more meaningful results that are closer to your own strategy.
I hope you benefits...
◙ GENEL BAKIŞ
Merhaba Yatırımcılar ve Yatırımcılar... Bu Gösterge, Scott Cong'un Stocks & Emtia Eylül sayısındaki “VAcc: Hız ve İvmeye Dayalı Bir Momentum Göstergesi” başlıklı makalesine odaklanmaktadır. Bu göstergeden faydalanabilmeniz için bir ticaret stratejisi de ekledim. Öncelikle göstergenin bize neler sunduğuna ve mantığının ne olduğuna bakalım. Öncelikle stratejinin mantığına odaklanalım.
◙ KAVRAMLAR
İşte kullanımı kolay, duyarlı ve kesin bazı basit fizik kavramlarına dayanan yeni bir gösterge. Nasıl hesaplanacağını ve kullanılacağını öğrenin.
Fizik alanı bize piyasaları analiz etmede son derece uygulanabilir bazı önemli ilkeler verir. Bu göstergede bir momentum göstergesi sunacağım. Scott Cong bu göstergeyi hız ve ivme kavramlarına dayanarak geliştirdi. Yatırımcıların ve analistlerin sıklıkla incelediği fiyatın pek çok özelliği arasında değişim oranı ve oranı yararlı olanlardır. Başka bir deyişle şunu bilmek faydalı olacaktır: Fiyat ne kadar hızlı hareket ediyor ve hızlanıyor mu, yavaşlıyor mu? Fiyatlar bir dönemden diğerine nasıl değişiyor? Burada tanıtacağım gösterge, mevcut çubuk (C) ve mevcut çubuktan bir yeniden inceleme döneminin her çubuğu kullanılarak hesaplanır. Göstergeye, yeniden inceleme dönemi boyunca hız çizgisinin (av) ve ivme çizgisinin (Acc) ortalamasına dayandığı için VAcc adını verdi. Daha uzun süreler boyunca VACc, MACD ile aynı şekilde davranır, yalnızca daha basit, daha duyarlı ve daha hassastır. İlginç bir şekilde, daha kısa süreler için VAcc, stokastik osilatör gibi bir osilatörün özelliklerini sergiliyor.
◙ HESAPLAMA
VAcc'nin hesaplanması aşağıdaki adımları içerir:
1. Yakın zamandaki fiyatın en büyük etkiye sahip olduğu göreceli ağırlıklı ortalamayı hesaplatıyoruz.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. Hız Ortalamasına üstel hareketli ortalamayla düzleştirme uygulanır. Şimdi bu şekilde aşağıdaki kod ile bunu şöyle elde ediyoruz:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Benzer şekilde, yeniden inceleme süresi ve ölçek faktörü içindeki her bir çubuk için fiyattaki ivmelenler yada momentum şu şekilde hesaplanır:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEJİ
Aslında Scott muhtemelen Macd'e benzediği ve 0,5 oranını kullandığı için 9. ve 26. periyotlarda kullanmayı tercih etmişti. Ancak kısa vadede stokastik osilatöre daha yakın sinyaller sağlamak için 8 ve 21 periyotlarını kullanmayı tercih ettim ve 0,382 oranını kullandım. Stratejinin mantığı şu
Uzun Strateji → acc(İvme Çizgisi) > 0,1 ve av(Hız Ortalama Çizgisi) > 0,1(Uzun Faktör)
Kısa strateji → acc(İvme Çizgisi) < -0,1 ve av(Hız Ortalama Çizgisi) < -0,1(Uzun Faktör)
Burada Kısa Faktör ve Uzun Faktör' ü dilediğiniz gibi değiştirip, kendi stratejinize daha yakın, daha anlamlı sonuçlar üretebilirsiniz.
umarım faydasını görürsün...
ADX-DI - Made EasyThis indicator is a visually improved version of ADX. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the ADX direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation and divergences.
Please note that the divergences on ADX are just experimental and are based on calculations, so there is no guarantee the direction will change.
MMI (Multi.Index.Indicator)Multi-Index Momentum Indicator (MMI)
The Multi-Index Momentum Indicator (MMI) is a custom TradingView Pine Script indicator designed to calculate and display the momentum difference between the base and quote indexes of various currency pairs. This indicator helps traders identify the relative strength or weakness of a currency pair by comparing the momentum of its base and quote indexes.
Features:
Currency Pair Detection: The indicator automatically detects the currency pair of the current chart and selects the appropriate base and quote indexes for that pair.
Index Data Retrieval: It fetches the closing prices of the base and quote indexes for the specified timeframe.
Momentum Calculation:
The indicator calculates the 14-period momentum for both the base and quote indexes and then computes the momentum difference.
Visual Representation: The momentum difference is plotted on the chart as a colored line. If the momentum difference is positive, the line is green; if negative, the line is red.
Data Availability Check:
The script checks if the index data is available. If any index data is missing, the script displays a red label on the chart indicating which index data is missing.
Zero Line: A horizontal line at the zero level is plotted for reference.
Supported Currency Pairs and Their Indexes:
USDJPY: Base Index - DXY, Quote Index - JPYX
EURUSD: Base Index - EXY, Quote Index - DXY
GBPUSD: Base Index - BXY, Quote Index - DXY
AUDUSD: Base Index - AXY, Quote Index - DXY
USDCHF: Base Index - DXY, Quote Index - SXY
USDCAD: Base Index - DXY, Quote Index - CXY
GBPJPY: Base Index - BXY, Quote Index - JPYX
CME Gap Oscillator [CryptoSea]Introducing the CME Gap Oscillator , a pioneering tool designed to illuminate the significance of market gaps through the lens of the Chicago Mercantile Exchange (CME). By leveraging gap sizes in relation to the Average True Range (ATR), this indicator offers a unique perspective on market dynamics, particularly around the critical weekly close periods.
Key Features
Gap Measurement : At its core, the CME Oscillator quantifies the size of weekend gaps in the context of the market's volatility, using the ATR to standardize this measurement.
Dynamic Levels : Incorporating a dynamic extreme level calculation, the tool adapts to current market conditions, providing real-time insights into significant gap sizes and their implications.
Band Analysis : Through the introduction of upper and lower bands, based on standard deviations, traders can visually assess the oscillator's position relative to typical market ranges.
Enhanced Insights : A built-in table tracks the frequency of the oscillator's breaches beyond these bands within the latest CME week, offering a snapshot of recent market extremities.
Settings & Customisation
ATR-Based Measurement : Choose to measure gap sizes directly or in terms of ATR for a volatility-adjusted view.
Band Period Adjustability : Tailor the oscillator's sensitivity by modifying the band calculation period.
Dynamic Level Multipliers : Adjust the multiplier for dynamic levels to suit your analysis needs.
Visual Preferences : Customise the oscillator, bands, and table visuals, including color schemes and line styles.
In the example below, it demonstrates that the CME will want to return to the 0 value, this would be considered a reset or gap fill.
Application & Strategy
Deploy the CME Oscillator to enhance your market analysis
Market Sentiment : Gauge weekend market sentiment shifts through gap analysis, refining your strategy for the week ahead.
Volatility Insights : Use the oscillator's ATR-based measurements to understand the volatility context of gaps, aiding in risk management.
Trend Identification : Identify potential trend continuations or reversals based on the frequency and magnitude of gaps exceeding dynamic levels.
The CME Oscillator stands out as a strategic tool for traders focusing on gap analysis and volatility assessment. By offering a detailed breakdown of market gaps in relation to volatility, it empowers users with actionable insights, enabling more informed trading decisions across a range of markets and timeframes.
Price Ratio Indicator [ChartPrime]The Price Ratio Indicator is a versatile tool designed to analyze the relationship between the price of an asset and its moving average. It helps traders identify overbought and oversold conditions in the market, as well as potential trend reversals.
◈ User Inputs:
MA Length: Specifies the length of the moving average used in the calculation.
MA Type Fast: Allows users to choose from various types of moving averages such as Exponential Moving Average (EMA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Relative Moving Average (RMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Zero-Lag Exponential Moving Average (ZLEMA), and Hull Moving Average (HMA).
Upper Level and Lower Level: Define the threshold levels for identifying overbought and oversold conditions.
Signal Line Length: Determines the length of the signal line used for smoothing the indicator's values.
◈ Indicator Calculation:
The indicator calculates the ratio between the price of the asset and the selected moving average, subtracts 1 from the ratio, and then smooths the result using the chosen signal line length.
// 𝙄𝙉𝘿𝙄𝘾𝘼𝙏𝙊𝙍 𝘾𝘼𝙇𝘾𝙐𝙇𝘼𝙏𝙄𝙊𝙉𝙎
//@ Moving Average's Function
ma(src, ma_period, ma_type) =>
ma =
ma_type == 'EMA' ? ta.ema(src, ma_period) :
ma_type == 'SMA' ? ta.sma(src, ma_period) :
ma_type == 'WMA' ? ta.wma(src, ma_period) :
ma_type == 'VWMA' ? ta.vwma(src, ma_period) :
ma_type == 'RMA' ? ta.rma(src, ma_period) :
ma_type == 'DEMA' ? ta.ema(ta.ema(src, ma_period), ma_period) :
ma_type == 'TEMA' ? ta.ema(ta.ema(ta.ema(src, ma_period), ma_period), ma_period) :
ma_type == 'ZLEMA' ? ta.ema(src + src - src , ma_period) :
ma_type == 'HMA' ? ta.hma(src, ma_period)
: na
ma
//@ Smooth of Source
src = math.sum(source, 5)/5
//@ Ratio Price / MA's
p_ratio = src / ma(src, ma_period, ma_type) - 1
◈ Visualization:
The main plot displays the price ratio, with color gradients indicating the strength and direction of the ratio.
The bar color changes dynamically based on the ratio, providing a visual representation of market conditions.
Invisible Horizontal lines indicate the upper and lower threshold levels for overbought and oversold conditions.
A signal line, smoothed using the specified length, helps identify trends and potential reversal points.
High and low value regions are filled with color gradients, enhancing visualization of extreme price movements.
MA type HMA gives faster changes of the indicator (Each MA has its own specifics):
MA type TEMA:
◈ Additional Features:
A symbol displayed at the bottom right corner of the chart provides a quick visual reference to the current state of the indicator, with color intensity indicating the strength of the ratio.
Overall, the Price Ratio Indicator offers traders valuable insights into price dynamics and helps them make informed trading decisions based on the relationship between price and moving averages. Adjusting the input parameters allows for customization according to individual trading preferences and market conditions.
WaveTrend Oscillator PlusThe WaveTrend based on “Enhanced WaveTrend” of EliCobra. The WaveTrend Oscillator is a popular technical analysis tool used to identify overbought and oversold conditions in the market and generate trading signals. This indicator introduces additional features for improved analysis and comparison across assets.
WaveTrend:
The original WaveTrend indicator calculates two lines based on exponential moving averages and their relationship to the asset's price. The first line measures the distance between the asset's price and its EMA, while the second line smooths the first line over a specific period. The result is divided by 0.015 multiplied by the smoothed difference ('d' for reference). The indicator aims to identify overbought and oversold conditions by analyzing the relationship between the two lines.
In the original formula, the rudimentary estimation factor 0.015 times 'd' fails to accomodate for approximately a quarter of the data, preventing the indicator from reaching the traditional stationary levels of +-100. This limitation renders the indicator quantitatively biased, as it relies on the user's subjective adjustment of the levels. The enhanced version replaces this factor with the standard deviation of the asset's price, resulting in improved estimation accuracy and provides a more dynamic and robust outcome, we thereafter multiply the result by 100 to achieve a more traditional oscillation.
Enhancements and Features:
Dynamic Estimation: The original indicator uses an arbitrary estimation factor, while the enhanced version replaces it with the standard deviation of the asset's price. This modification provides a more dynamic and accurate estimation, adapting to the specific price characteristics of each asset.
Stationary Support and Resistance Levels: The enhanced version provides stationary key support and resistance levels that range from -150 to 150. These levels are determined based on the analysis of the indicator's data and encompass more than 95% of the indicator's values. These levels offer important reference points for traders to identify potential price reversals or significant price movements.
Comparison Across Assets: The enhanced version allows for better comparison and analysis across different assets. By incorporating the standard deviation of the asset's price, the indicator provides a more consistent and comparable interpretation of the market conditions across multiple assets.
Z-Score Analysis:
The Z-Score is a statistical measurement that quantifies how far a particular data point deviates from the mean in terms of standard deviations. In the enhanced version, the calculation involves determining the basis (mean) and deviation (standard deviation) of the asset's price to calculate its Z-Score, thereafter applying a smoothing technique to generate the final WaveTrend value.
Utility:
The offers traders and investors valuable insights into overbought and oversold conditions in the market. By analyzing the indicator's values and referencing the stationary support and resistance levels, traders can identify potential trend reversals, evaluate market strength, and make better informed analysis.
The following indicators were added:
⎆⎆ Squeeze Momentum Indicator
⎆⎆ Elliott Wave Oscillator
⎆⎆ Expert Trend Locator
Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
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فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
Kalman Volume Filter [ChartPrime]The "Kalman Volume Filter" , aims to provide insights into market volume dynamics by filtering out noise and identifying potential overbought or oversold conditions. Let's break down its components and functionality:
Settings:
Users can adjust various parameters to customize the indicator according to their preferences:
Volume Length: Defines the length of the volume period used in calculations.
Stabilization Coefficient (k): Determines the level of noise reduction in the signals.
Signal Line Length: Sets the length of the signal line used for identifying trends.
Overbought & Oversold Zone Level: Specifies the threshold levels for identifying overbought and oversold conditions.
Source: Allows users to select the price source for volume calculations.
Volume Zone Oscillator (VZO):
Calculates a volume-based oscillator indicating the direction and intensity of volume movements.
Utilizes a volume direction measurement over a specified period to compute the oscillator value.
Normalizes the oscillator value to improve comparability across different securities or timeframes.
// VOLUME ZONE OSCILLATOR
VZO(get_src, length) =>
Volume_Direction = get_src > get_src ? volume : -volume
VZO_volume = ta.hma(Volume_Direction, length)
Total_volume = ta.hma(volume, length)
VZO = VZO_volume / (Total_volume)
VZO := (VZO - 0) / ta.stdev(VZO, 200)
VZO
Kalman Filter:
Applies a Kalman filter to smooth out the VZO values and reduce noise.
Utilizes a stabilization coefficient (k) to control the degree of smoothing.
Generates a filtered output representing the underlying volume trend.
// KALMAN FILTER
series float M_n = 0.0 // - the resulting value of the current calculation
series float A_n = VZO // - the initial value of the current measurement
series float M_n_1 = nz(M_n ) // - the resulting value of the previous calculation
float k = input.float(0.06) // - stabilization coefficient
// Kalman Filter Formula
kalm(k)=>
k * A_n + (1 - k) * M_n_1
Volume Visualization:
Displays the volume histogram, with color intensity indicating the strength of volume movements.
Adjusts bar colors based on volume bursts to highlight significant changes in volume.
Overbought and Oversold Zones:
Marks overbought and oversold levels on the chart to assist in identifying potential reversal points.
Plotting:
Plots the Kalman Volume Filter line and a signal line for visual analysis.
Utilizes different colors and fills to distinguish between rising and falling trends.
Highlights specific events such as local buy or sell signals, as well as overbought or oversold conditions.
This indicator provides traders with a comprehensive view of volume dynamics, trend direction, and potential market turning points, aiding in informed decision-making during trading activities.
VWAP DivergenceThe "VWAP Divergence" indicator leverages the VWAP Rolling indicator available in TradingView's library to analyze price and volume dynamics. This custom indicator calculates a rolling VWAP (Volume Weighted Average Price) and compares it with a Simple Moving Average (SMA) over a specified historical period.
Advantages:
1. Accurate VWAP Calculation: The VWAP Rolling indicator computes a VWAP that dynamically adjusts based on recent price and volume data. VWAP is a vital metric used by traders to understand the average price at which a security has traded, factoring in volume.
2. SMA Comparison: By contrasting the rolling VWAP from the VWAP Rolling indicator with an SMA of the same length, the indicator highlights potential divergences. This comparison can reveal shifts in market sentiment.
3. Divergence Identification: The primary purpose of this indicator is to detect divergences between the rolling VWAP from VWAP Rolling and the SMA. Divergence occurs when the rolling VWAP significantly differs from the SMA, indicating potential changes in market dynamics.
Interpretation:
1. Positive Oscillator Values: A positive oscillator (difference between rolling VWAP and SMA) suggests that the rolling VWAP, derived from the VWAP Rolling indicator, is above the SMA. This could indicate strong buying interest or accumulation.
2. Negative Oscillator Values: Conversely, a negative oscillator value indicates that the rolling VWAP is below the SMA. This might signal selling pressure or distribution.
3. Divergence Signals: Significant divergences between the rolling VWAP (from VWAP Rolling) and SMA can indicate shifts in market sentiment. For instance, a rising rolling VWAP diverging upwards from the SMA might suggest increasing bullish sentiment.
4. Confirmation with Price Movements: Traders often use these divergences alongside price action to confirm potential trend reversals or continuations.
Implementation:
1. Length Parameter: Adjust the Length input to modify the lookback period for computing both the rolling VWAP from VWAP Rolling and the SMA. A longer period provides a broader view of market sentiment, while a shorter period is more sensitive to recent price movements.
2. Visualization: The indicator plots the VWAP SMA Oscillator, which visually represents the difference (oscillator) between the rolling VWAP (from VWAP Rolling) and SMA over time.
3. Zero Line: The zero line (gray line) serves as a reference point. Oscillator values crossing above or below this line can be interpreted as bullish or bearish signals, respectively.
4. Contextual Analysis: Interpret signals from this indicator in conjunction with broader market conditions and other technical indicators to make informed trading decisions.
This indicator, utilizing the VWAP Rolling component, is valuable for traders seeking insights into the relationship between volume-weighted price levels and traditional moving averages, aiding in the identification of potential trading opportunities based on market dynamics.
MACD 4C with DivergenceMACD 4C Indicator with Divergence
This indicator, named MACD 4C, enhances the traditional MACD (Moving Average Convergence Divergence) by providing a visually intuitive representation with four distinct colors for the histogram bars. It offers a clear interpretation of market momentum and potential trend reversals.
Key Features:
Customizable Parameters: Users can adjust the fast and slow moving average periods along with the signal smoothing parameter to tailor the indicator to their preferred trading style and market conditions.
Four-color Histogram: The histogram bars are color-coded for easy interpretation. Lime and green bars indicate increasing bullish momentum, while maroon and red bars signify increasing bearish momentum.
Bullish and Bearish Divergence Detection: The indicator identifies bullish and bearish divergences between the MACD histogram and price action. Bullish divergence occurs when the price makes a lower low while the MACD histogram forms a higher low, indicating potential bullish reversal. Conversely, bearish divergence occurs when the price makes a higher high while the MACD histogram forms a lower high, suggesting a potential bearish reversal.
How to Use:
Trend Confirmation: Monitor the color of the histogram bars. A series of green (or lime) bars suggests a strengthening bullish trend, while a series of red (or maroon) bars indicates a strengthening bearish trend.
Divergence Identification: Watch for divergences between the MACD histogram and price action. Bullish divergence may signal a potential bullish reversal, while bearish divergence may indicate a potential bearish reversal. These signals can be used in conjunction with other technical analysis tools to confirm trade entries and exits.
The MACD 4C indicator was developed by user vkno422 You can find the original author and their work on their TradingView profile: www.tradingview.com
RSI and MACD Composite ScoreComponents of the Indicator
RSI Settings:
The RSI is set with a length parameter, which can be adjusted by the user but defaults to 14. This measures the speed and change of price movements.
MACD Settings:
The MACD is composed of two lines: the MACD line and the signal line, which are calculated from exponential moving averages (EMAs) of different lengths (fast and slow). The default settings are 9 for the fast length, 26 for the slow length, and 3 for the signal length.
The MACD histogram, which is the difference between the MACD line and the signal line, is also calculated.
Normalization and Combination
RSI Normalization : The RSI values are normalized around 0 by subtracting 50 from the RSI and then dividing by 50. This scaling adjusts the RSI to fluctuate around 0, where positive values indicate strength and negative values indicate weakness relative to the median RSI value of 50.
MACD Normalization : The MACD histogram is normalized by dividing it by the highest absolute value of the histogram over the slow length period. This adjustment scales the MACD histogram to fall between -1 and 1, making it comparable in magnitude to the normalized RSI.
Composite Score Calculation
The composite score is simply the sum of the normalized RSI and the normalized MACD histogram. This results in a combined score that reflects both momentum (from RSI) and trend (from MACD), providing a multifaceted view of market dynamics.
Visualization
The composite score is plotted as an oscillator, with a horizontal zero line that helps identify when the score shifts from positive to negative or vice versa.
The background color changes based on the trend: green if the composite score is above zero (bullish trend) and red if below zero (bearish trend).
KC-MACD Entry Master @shrilssThe KC-MACD Entry Master is designed to enhance trading strategies by utilizing Keltner Channels and MACD for dynamic market analysis. This indicator excels in visually identifying market conditions with a sophisticated bar coloring system and an informative MACD Traffic Light feature.
Key Features:
- Dynamic Bar Coloring: The core feature of this indicator is its ability to adjust the color of bars based on their positioning relative to the Keltner Channels and the EMA (Exponential Moving Average). It colors bars lime or red when the closing price is within the Keltner Channels but above or below the EMA, respectively. Additionally, it uses a fuchsia color to indicate breakouts when the price extends beyond the Keltner Channels. This visual aid helps traders quickly identify potential buying or selling opportunities based on market volatility and price action.
- MACD Traffic Light: Positioned at the bottom of the chart, this unique feature displays the histogram color of the MACD, set by default to a 3/10/16 configuration—known as the 3-10 Oscillator. This Traffic Light gives traders an at-a-glance view of the underlying momentum and trend shifts, further aiding in decision-making processes.
- MACD-Based Entry Signals: By calculating the fast and slow moving averages specified by the user, the script determines MACD values and their crossover with a smoothed signal line. Entry points are then highlighted with shapes (e.g., "Buy" or "Sell") plotted on the chart when conditions are met, including alignment with the bar colors for enhanced accuracy.
Dynamic Price Oscillator (Zeiierman)█ Overview
The Dynamic Price Oscillator (DPO) by Zeiierman is designed to gauge the momentum and volatility of asset prices in trading markets. By integrating elements of traditional oscillators with volatility adjustments and Bollinger Bands, the DPO offers a unique approach to understanding market dynamics. This indicator is particularly useful for identifying overbought and oversold conditions, capturing price trends, and detecting potential reversal points.
█ How It Works
The DPO operates by calculating the difference between the current closing price and a moving average of the closing price, adjusted for volatility using the True Range method. This difference is then smoothed over a user-defined period to create the oscillator. Additionally, Bollinger Bands are applied to the oscillator itself, providing visual cues for volatility and potential breakout signals.
█ How to Use
⚪ Trend Confirmation
The DPO can serve as a confirmation tool for existing trends. Traders might look for the oscillator to maintain above or below its mean line to confirm bullish or bearish trends, respectively. A consistent direction in the oscillator's movement alongside price trend can provide additional confidence in the strength and sustainability of the trend.
⚪ Overbought/Oversold Conditions
With the application of Bollinger Bands directly on the oscillator, the DPO can highlight overbought or oversold conditions in a unique manner. When the oscillator moves outside the Bollinger Bands, it signifies an extreme condition.
⚪ Volatility Breakouts
The width of the Bollinger Bands on the oscillator reflects market volatility. Sudden expansions in the bands can indicate a breakout from a consolidation phase, which traders can use to enter trades in the direction of the breakout. Conversely, a contraction suggests a quieter market, which might be a signal for traders to wait or to look for range-bound strategies.
⚪ Momentum Trading
Momentum traders can use the DPO to spot moments when the market momentum is picking up. A sharp move of the oscillator towards either direction, especially when crossing the Bollinger Bands, can indicate the start of a strong price movement.
⚪ Mean Reversion
The DPO is also useful for mean reversion strategies, especially considering its volatility adjustment feature. When the oscillator touches or breaches the Bollinger Bands, it indicates a deviation from the normal price range. Traders might look for opportunities to enter trades anticipating a reversion to the mean.
⚪ Divergence Trading
Divergences between the oscillator and price action can be a powerful signal for reversals. For instance, if the price makes a new high but the oscillator fails to make a corresponding high, it may indicate weakening momentum and a potential reversal. Traders can use these divergence signals to initiate counter-trend moves.
█ Settings
Length: Determines the lookback period for the oscillator and Bollinger Bands calculation. Increasing this value smooths the oscillator and widens the Bollinger Bands, leading to fewer, more significant signals. Decreasing this value makes the oscillator more sensitive to recent price changes, offering more frequent signals but with increased noise.
Smoothing Factor: Adjusts the degree of smoothing applied to the oscillator's calculation. A higher smoothing factor reduces noise, offering clearer trend identification at the cost of signal timeliness. Conversely, a lower smoothing factor increases the oscillator's responsiveness to price movements, which may be useful for short-term trading but at the risk of false signals.
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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!
