YinYang Bar ForecastOverview:
YinYang Bar Forecast is a prediction indicator. It predicts the movement for High, Low, Open and Close for up to 13 bars into the future. We created this Indicator as we felt the TradingView community could benefit from a bar forecast as there wasn’t any currently available.
Our YinYang Bar Forecast is something we plan on continuously working on to better improve it, but at its current state it is still very useful and decently accurate. It features many calculations to derive what it thinks the future bars will hold. Let’s discuss some of the logic behind it:
Each bar has its High, Low, Open and Close calculated individually for highest accuracy. Within these calculations we first check which bar it is we are calculating and base our span back length that we are getting our data from based on the bar index we are generating. This helps us get a Moving Average for this bar index.
We take this MA and we apply our Custom Volume Filter calculation on it, which is essentially us dividing the current bars volume over the average volume in the last ‘Filtered Length’ (Setting) length. We take this decimal and multiply it on our MA and smooth it out with a VWMA.
We take the new Volume Filtered MA and apply a RSI Filter calculation on it. RSI Filter is where we take the difference between the high and low of this bar and we multiply it with an RSI calculation using our Volume Filtered MA. We take the result of that multiplication and either add or subtract it from the Volume Filtered MA based on if close > open. This makes our RSI Filtered MA.
Next, we do an EMA Strength Calculation which is where we check if close > ema(close, ‘EMA Averaged Length’) (Setting). Based on this condition we assign a multiplier that is applied to our RSI Filtered MA. We divide by how many bars we are predicting and add a bit to each predictive bar so that the further we go into the future the stronger the strength is.
Next we check RSI and RSI MA levels and apply multiplications based on its RSI levels and if it is greater than or less than the MA. Also it is affected by if the RSI is <= 30 and >= 70.
Finally we check the MFI and MFI MA levels and like RSI we apply multiplications based on its MFI levels and if it is greater than or less than the MA. It is also affected by if the MFI is <= 30 and >= 70.
Please note the way we calculate this may change in the future, this is just currently what we deemed works best for forecasting the future bars. Also note this script uses MA calculations out of scope for efficiency but there is potential for inconsistencies.
Innately it’s main use is the projection it provides. It only draws the bars for realtime bars and not historical ones, so the best way to backtest it is with TradingView’s Replay Tool.
Well, enough of the logic behind it, let's get to understanding how to use it:
Tutorial:
So unfortunately we aren’t able to plot legit bars/candles into the future so we’ve had to do a bit of a work around using lines and fills. As you can see here we have 4 Lines and 3 Zones:
Lines:
Green: Represents the High
Orange: Represents the Open
Teal: Represents the Close
Red: Represents the Low
Zones:
High Zone: This zone is from either Open or Close to the High and is ALWAYS filled with Green.
Open/Close Zone: This zone is from the Open to the Close and is filled with either Green or Red based on if it's greater than the previous bar (real or forecasted).
Low Zone: This zone is from either Open or Close to the Low and is ALWAYS filled with Red.
As you can see generally the Forecasted bars are generally within strong pivot locations and are a good estimation of what will likely go on. Please note, the WHOLE structure of the prediction can change based on the current bars movements and the way it affects the calculations.
Let's look 1 bar back from the current bar just so we can see what it used to Forecast:
As you can see it has changed quite a bit from the previous bar, but if you look close, we drew horizontal lines around where its projecting the next bar to be (our current realtime bar), if we go back to the live chart:
Its projections were pretty close for the high and low. Generally, right now at least, it does a much better job at predicting the high and low than it does the open and close, however we will do our best to fine tune that in future updates.
Remember, this indicator is not meant to base your trades on, but rather give you a Forecast towards the general direction of the next few bars. Somewhat like weather, the farther the bar (or day for weather), the harder it is to predict. For this reason we recommend you focusing on the first few bars as they are more accurate, but review the further ones as they may help show the trend and the way that pair will move.
We will conclude this tutorial here, hopefully this Predictive Indicator can be of some help and use to you. If you have any questions, comments, ideas or concerns please let us know.
Settings:
Forecast Length: How many bars should we predict into the Future? Max 13
Each Bar Length Multiplier: For each new Forecast bar, how many more bars are averaged? Min 2
VWMA Averaged Length: All Forecast bars are put into a VWMA, what length should we use?
EMA Averaged Length: All Forecast bars are put into a EMA, what length should we use?
Filtered Length: What length should we use for Filtered Volume and RSI?
EMA Strength Length: What length should we use for the EMA Strength
HAPPY TRADING!
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HILOCLOP AnalysisThe "HILOCLOP Analysis" indicator is designed to analyze price data based on different conditions and provide insights into market trends and patterns. Let's break down its features and understand its potential usefulness in trading:
Sample Length: The indicator allows the user to specify the sample length, which determines the number of bars or periods considered for the analysis. This parameter can be adjusted to capture short-term or long-term trends and patterns in the market.
Raw Up/Down Analysis: The indicator calculates the number of occurrences where the current price values (high, low, open, close) are higher or lower than their previous values. It provides separate counts for each price component. By visualizing these counts on the chart, traders can identify periods of upward or downward movement in the price data.
HICLOP Analysis: The indicator offers a color scheme option called "HICLOP," which determines the color of the plotted results. If the HICLOP analysis is enabled, the plots representing raw up/down counts will have different colors based on whether the current count is higher or lower than the previous count. This color coding helps traders quickly identify changes in price trends.
Unchecking this Box will Show the general trend.
Raw HICLOP Color Scheme
Trend Color Scheme
Analysis Up vs. Down: The indicator provides an option to analyze instances where all four price components (high, low, open, close) are higher or lower than their respective previous values. This analysis helps traders identify periods of strong upward or downward movement in the market.
Analysis High vs. Low: The indicator compares the number of occurrences where the current high is higher than the previous high and the current low is higher than the previous low. It provides insights into whether the market is experiencing higher highs or higher lows, which can help traders determine the strength of an upward or downward trend.
Analysis Open vs. Close: The indicator compares the number of occurrences where the current close is higher than the previous close and the current open is higher than the previous open. This analysis helps traders assess the relationship between opening and closing prices, providing insights into the strength of buying or selling pressure in the market.
The usefulness of the "HILOCLOP Analysis" indicator in trading depends on the specific trading strategy and the trader's preferences. Here are a few potential use cases:
Trend Identification: By analyzing the raw up/down counts and the HICLOP color scheme, traders can identify trends and changes in price momentum. Increasing raw up counts and corresponding color changes to positive values may indicate an upward trend, while increasing raw down counts and negative color changes may suggest a downward trend.
Confirmation of Breakouts: Traders often look for confirmation of breakouts from key levels or chart patterns. The "Analysis Up V Dn" feature can help identify instances where all four price components simultaneously confirm a breakout, indicating a potentially significant move in the market.
Trend Reversals: The "Analysis High V Low" and "Analysis Open V Close" features can provide insights into potential trend reversals. For example, if there are more higher highs than higher lows, it may indicate a weakening trend, potentially signaling a reversal or a correction.
Volume-based Support & Resistance Zones-V1 By Trade Mastership™ The all-new Support & Resistance Zones indicator, which has been upgraded to offer traders more powerful features and functionality. This innovative indicator identifies high-volume fractal lows or highs to create zones based on the size of the wick for that timeframe's candle. This makes it easy for traders to visualize which price levels are the most significant for either a trend continuation or a reversal when zones are broken and retested.
The original script for this indicator was created by Trade Mastership, with additional modifications by L N Behera. Credit goes to both of them for the majority of the logic behind this script. Since then, the script has been improved with several changes, including:
Changing the default S/R lines from plots to lines, and giving users the option to change between solid, dashed, or dotted lines for both S/R lines
Adding additional timeframes and more options for TF1, beyond the current TF. Now, users have four timeframes to plot S/R zones from
Giving users the option to easily change the line thickness for all S/R lines
Making it easier to change the colors of S/R lines and zones by consolidating the options under settings (rather than under style)
Adding extensions to active SR Zones to extend all the way right
Adding the option to extend or not extend the previous S/R zones up to the next S/R zone
Adding optional timeframe labels to active S/R zones, with left and right options, as well as the option to adjust how far to the right the label is set
Fixing an issue where the higher timeframe S/R zone was not properly starting from the high/low of fractal. Now, any higher timeframe S/R will begin exactly at the High/Low points. Note that this may not work perfectly on stocks, and if a fractal high/low is too many bars in the past, it will revert to a default max bars back to avoid script errors.
Adding a function to prevent S/R zones from lower timeframes displaying while on a higher timeframe. This helps clean up the chart quite a bit.
Creating arrays for each timeframe's boxes and lines so that the number of S/R zones can be controlled for each timeframe and limit memory consumption.
Adding new alert options and customized alert messages
Here's how this indicator works: it looks for fractal highs or fractal lows with volume that pierces above the volume's Moving Average. This moving average value can be modified in the settings for each timeframe. The fractal highs will be confirmed with three successive higher highs followed by two successive lower highs and vice versa for the fractal lows. The zone is created from the fractal high/low and the close of the candle for whatever timeframe you selected. The bigger the zone, the more significant that zone is.
Traders can disable any zone, change the zones to show lines only, and modify all the colors, transparencies, and thickness of lines for all the zones. To create alerts, traders can enable the types of alerts they want for each timeframe in the indicator's settings. After applying changes, right-click on one of the zones on the chart, and click "Add Alert on Vol S/R Zones." You do not need to add a title, as the correct alert messages are already built-in.
The latest update has migrated the script to Pine Script Version 5 and added a higher number of total boxes/lines to show on the chart. It has also increased the max bars count to the maximum Pine Script allows, enabling traders to utilize as many bars as possible when drawing the left side of SR zones that are very far back on the chart. Additionally, the update fixed issues where the indicator would not load on 1 minute and 3-minute charts unless higher timeframe SR zones
Candle Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed candle trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Muti-Part Green and Red Candle Trends
• A multi-part green candle trend begins upon the completion of a swing low and continues until a red candle completes the swing high, with each green candle counted as a part of the trend.
• A multi-part red candle trend begins upon the completion of a swing high and continues until a green candle completes the swing low, with each red candle counted as a part of the trend.
█ FEATURES
Inputs
Start Date
End Date
Position
Text Size
Show Sample Period
Show Plots
Table
The table is colour coded, consists of seven columns and, as many as, thirty-one rows. Blue cells denote the multi-part candle trend scenarios, green cells denote the corresponding green candle trend scenarios and red cells denote the corresponding red candle trend scenarios.
The candle trend scenarios are listed in the first column with their corresponding total counts to the right, in the second column. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third column displays the total candle trend scenarios as percentages of total 1-candle trends, or complete swing highs and swing lows. And column four displays the total candle trend scenarios as percentages of the, last, or preceding candle trend part. For example 4-candle trends as a percentage of 3-candle trends. This offers more insight into what might happen next at any given point in time.
Plots
I have added plots as a visual aid to the various candle trend scenarios listed in the table. Green up-arrows, with the number of the trend part, denote green candle trends. Red down-arrows, with the number of the trend part, denote red candle trends.
█ HOW TO USE
This indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the next candle will close higher or lower than it opened, based on the current scenario and what has happened in the past under similar circumstances. Such information can be very useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Pullback IndicatorThe Pullback Indicator is a technical analysis tool designed to identify pullbacks in the price action of a financial instrument. It is based on the concept that price tends to retrace to a previous level of support or resistance before continuing in the direction of the trend.
The indicator is plotted as a series of triangles above or below the price bars, depending on the type of pullback detected. A green triangle is displayed when a bullish pullback is detected, while a red triangle is displayed for a bearish pullback.
The Pullback Indicator uses Inside Bar Range, this number is a user-defined input that specifies the number of bars to look back for the highest high and lowest low.
The indicator classifies four types of pullbacks:
Swing Low - When the price forms a lower low and a higher low than the previous bar.
Swing High - When the price forms a higher high and a lower high than the previous bar.
High Low Sweep and close below - When the price forms a lower low and a higher low than the previous bar, but the close is below the previous high.
High Low Sweep and close above - When the price forms a higher high and a lower high than the previous bar, but the close is above the previous low.
The Pullback Indicator is best used in conjunction with other technical analysis tools to confirm the direction of the trend and to identify potential entry and exit points.
Inter-Exchanges Crypto Price Spread Clouds (Tartigradia)Display variations in min-max and median values of high, low and close across exchanges. It's a kind of realized volatility indicator, as the idea is that in times of high volatility (high emotions, fear, uncertainty), it's more likely that market inefficiencies will appear for the same asset between different market makers, ie, the price can temporarily differ a lot. This indicator will catch these instants of high differences between exchanges, even if they lasted only an instant (because we use high and low values).
Compared with my other "Inter-Exchanges Crypto Price Spread Deviation" indicator, this one overlays directly on the chart, and offers a different take based on the same premisses. Instead of summarizing volatility via standard deviation, here we display clouds of the range of values that were observed.
A big advantage of this approach is that it can also be used to determine safe stop loss levels, especially the values of percentile rank (i.e., what are the high values that were observed in at least 50% of exchanges?).
Indeed, all price levels are displayed in the indicator's status bar:
green for high values,
red for low values,
aqua for median,
purple for average,
The first two values are max and min values of high across exchanges (in green).
The next two values are max and min of low across exchanges (in red).
The next two values are median (aqua) and average (purple).
The last two values are percentile rank values for high (green) and low (red) respectively.
Another advantage is that the high (green) vs low (red) clouds can be seen as representing the buying or selling pressure respectively across exchanges, and this may in itself provide a signal to know whether one side is winning.
Link to my other complementary indicator:
Compared to other inter-exchanges spread indicators, this one offers two major features:
The symbol automatically adapts to the symbol currently selected in user's chart. Hence, switching between tickers does not require the user to modify any option, everything is dynamically updated behind the scenes.
It's easy to add more exchanges (requires some code editing because PineScript v5 does not allow dynamical request.security() calls).
Limitations/things to know:
History is limited to what the ticker itself display. Ie, even if the exchanges specified in this indicator have more data than the ticker currently displayed in the user's chart, the indicator will show only a timeperiod as long as the chart.
The indicator can manage multiple exchanges of different historical length (ie, some exchanges having more data going way earlier in the past than others), in which case they will simply be ignored from calculations when far back in the past. Hence, you should be aware that the further you go in the past, the less exchanges will have such data, and hence the less accurate the measures will be (because the deviation will be calculated from less sources than more recent bars). This is thanks to how the array.* math functions behave in case of na values, they simply skip them from calculations, contrary to math.* functions.
Band-Zigzag - TrendFollower Strategy [Trendoscope]Strategy Time!!!
Have built this on my earlier published indicator Band-Zigzag-Trend-Follower . This is just one possible implementation of strategy on Band-Based-Zigzag .
🎲 Notes
Experimental prototype. Not financial advise and strategy not guaranteed to make money despite backtest results
Not created or tested for any specific instrument or timeframe
Test and adopt with own risk
🎲 Strategy
This is trend following strategy built based on Bands and Zigzag. Traits of trend following strategies are
Lower win rate (Yes, thats right)
High risk reward (Compensates low win rate)
Higher drawdown
If market is choppy, trend following methods suffer.
The script implements few points to overcome the negatives such as lower win rate and higher drawdown by actively assessing pivots on the direction of trend along. This helps us take regular profits and exit on time during the end of trend. Most of the other concepts are defined and explained in indicator - Band-Zigzag-Trend-Follower and Band-Based-Zigzag
Defining a trend following method is simple. Basic rule of trend following is Buy High and Sell Low (Yes, you heard it right). To explain further - methodology involve finding an established trend which is flying high and join the trend with proper risk and optimal stop. Once you get into the trade, you will not exit unless there is change in the trend. Or in other words, the parameters which you used to define trend has reversed and the trend is not valid anymore.
🎯 Using bands
When price breaks out of upper bands (example, Bollinger Band , Keltener Channel, or Donchian Channel), with a pre determined length and multiplier, we can consider the trend to be bullish and similarly when price breaks down the lower band, we can consider the trend to be bearish .
🎯 Using Pivots
Simple logic using zigzag or pivot points is that when price starts making higher highs and higher lows, we can consider this as uptrend. And when price starts making lower highs and lower lows, we can consider this as downtrend. There are few supertrend implementations I have published in the past based on zigzags and pivot points .
Drawbacks of both of these methods is that there will be too many fluctuations in both cases unless we increase the reference length. And if we increase the reference length, we will have higher drawdown.
🎯 Band Based Zigzag Method
Here we use bands to define our pivot high and pivot low - this makes sure that we are identifying trend only on breakouts as pivots are only formed on breakouts
Our method also includes pivot ratio to cross over 1.0 to be able to consider it as trend. This means, we are waiting for price also to make new high high or lower low before making the decision on trend. But, this helps us ignore smaller pivot movements due to the usage of bands.
I have also implemented few tricks such as sticky bands (Bands will not contract unless there is breakout) and Adaptive Bands (Band will not expand unless price is moving in the direction of band). This makes the trend following method very robust.
To avoid fakeouts, we also use percentB of high/low in comparison with price retracement to define breakout.
🎲 Settings
Settings are fairly simpler and are explained as below. You will find most of the required information in tooltips.
Band-Zigzag Based Trend FollowerWe defined new method to derive zigzag last month - which is called Channel-Based-Zigzag . This script is an example of one of the use case of this method.
🎲 Trend Following
Defining a trend following method is simple. Basic rule of trend following is Buy High and Sell Low (Yes, you heard it right). To explain further - methodology involve finding an established trend which is flying high and join the trend with proper risk and optimal stop. Once you get into the trade, you will not exit unless there is change in the trend. Or in other words, the parameters which you used to define trend has reversed and the trend is not valid anymore.
Few examples are:
🎯 Using bands
When price breaks out of upper bands (example, Bollinger Band, Keltener Channel, or Donchian Channel), with a pre determined length and multiplier, we can consider the trend to be bullish and similarly when price breaks down the lower band, we can consider the trend to be bearish.
Here are few examples where I have used bands for identifying trend
Band-Based-Supertrend
Donchian-Channel-Trend-Filter
🎯 Using Pivots
Simple logic using zigzag or pivot points is that when price starts making higher highs and higher lows, we can consider this as uptrend. And when price starts making lower highs and lower lows, we can consider this as downtrend. There are few supertrend implementations I have published in the past based on zigzags and pivot points.
Adoptive-Supertrend-Pivots
Zigzag-Supertrend
Drawbacks of both of these methods is that there will be too many fluctuations in both cases unless we increase the reference length. And if we increase the reference length, we will have higher drawdown.
🎲 Band Based Zigzag Method
Band Based Zigzag will help overcome these issues by combining both the methods.
Here we use bands to define our pivot high and pivot low - this makes sure that we are identifying trend only on breakouts as pivots are only formed on breakouts.
Our method also includes pivot ratio to cross over 1.0 to be able to consider it as trend. This means, we are waiting for price also to make new high high or lower low before making the decision on trend. But, this helps us ignore smaller pivot movements due to the usage of bands.
I have also implemented few tricks such as sticky bands (Bands will not contract unless there is breakout) and Adaptive Bands (Band will not expand unless price is moving in the direction of band). This makes the trend following method very robust.
To avoid fakeouts, we also use percentB of high/low in comparison with price retracement to define breakout.
🎲 The indicator
The output of indicator is simple and intuitive to understand.
🎯 Trend Criteria
Uptrend when last confirmed pivot is pivot high and has higher retracement ratio than PercentB of High. Else, considered as downtrend.
Downtrend when last confirmed pivot is pivot low and has higher retracement ratio than PercentB of High. Else, considered as uptrend.
🎯 Settings
Settings allow you to select the band type and parameters used for calculating zigzag and then trend. Also has few options to hide the display.
Micro ZigzagMicro zigzag is created based on similar concepts as that of zigzag but by using lower timeframe intra-bar data. The lines join candle's high/low points but also depict how the price movement within the candle happened. That is, if the high of the candle is reached first, pivot from previous candle join the high first and then low and vice versa.
The output can also be viewed as advanced line chart.
🎲 Process
🎯 For every bar identify whether high came first or low by using lower timeframe data.
🎯 If high came before low, add high as high pivot first and then low as low pivot. If otherwise, add low as lower pivot first and then high as higher pivot.
🎯 When adding pivot, check if the last pivot is in the same direction as the new one. If yes, replace existing pivot if the new one goes beyond it. Ignore otherwise.
🎯 If the last pivot is of different direction as that one new one, then simple add the new pivot.
Fair Value Gap [LuxAlgo]Fair value gaps (FVG) highlight imbalances areas between market participants and have become popular amongst technical analysts. The following script aims to display fair value gaps alongside the percentage of filled gaps and the average duration (in bars) before gaps are filled.
Users can be alerted when an FVG is filled using the alerts built into this script.
🔶 USAGE
In practice, FVG's highlight areas of support (bullish FVG) and resistances (bearish FVG). Once a gap is filled, suggesting the end of the imbalance, we can expect the price to reverse.
This approach is more contrarian in nature, users wishing to use a more trend-following approach can use the identification of FVG as direct signals, going long with the identification of a bullish FVG, and short with a bearish FVG.
🔹 Mitigation
By default, the script highlights the areas of only unmitigated FVG's. Users can however highlight the mitigation level of mitigated FVG's, that is the lower extremity of bullish FVG's and the upper extremity of bearish FVG's.
The user can track the evolution of a mitigated FVG's using the "Dynamic" setting.
🔹 Threshold
The gap height can be used to determine the degree of imbalance between buying and selling market participants. Users can filter fair value gaps based on the gap height using the "Threshold %" setting. Using the "Auto" will make use of an automatic threshold, only keeping more volatile FVG's.
🔶 DETAILS
We use the following rules for detecting FVG's in this script:
Bullish FVG
low > high(t-2)
close(t-1) > high(t-2)
(low - high(t-2)) / high(t-2) > threshold
Upper Bullish FVG = low
Lower Bullish FVG = high(t-2)
Bearish FVG
high < low(t-2)
close(t-1) < low(t-2)
(low(t-2) - high) / high < -threshold
Upper Bearish FVG = low(t-2)
Lower Bearish FVG = high
🔶 SETTINGS
Threshold %: Threshold percentage used to filter our FVG's based on their height.
Auto Threshold: Use the cumulative mean of relative FVG heights as threshold.
Unmitigatted Levels: Extent the mitigation level of the number of unmitigated FVG's set by the user.
Mitigation Levels: Show the mitigation levels of mitigated FVG's.
Timeframe : Timeframe of the price data used to detect FVG's.
NYSE New Highs vs New LowsNYSE New Highs vs New Lows is a simple market breadth indicator that compares HIGN, the number of new highs during that day, and LOWN, the number of new lows. The new highs are on top and lows are appropriately on bottom. Without averaging, it's a little chaotic so you can smooth them out as much as you want, and the top-right label shows how much you're smoothing.
Interpretation:
Essentially, we use $SPY or $QQQ as a proxy for what's going on in the market, but because the FAANG stocks are so heavily weighted, it's not always representative. If SPY is flat/down, but there are 200 new highs today, then one of the big boys is weighing down an otherwise very bullish market. It's like looking at one of those heatmap charts, but in a single number.
Bullish Trend
- Lots of new highs
- Very few new lows
Bearish Trend
- Lots of new lows
- Very few new highs
Potential Reversal
- Too high, 250+
- Too low, 150+
Volume-based Support & Resistance ZonesThe new and improved Support & Resistance Zones indicator is here. This indicator is based on high volume at fractal lows or fractal highs with the zones based on the size of the wick for that timeframe’s candle.
This helps traders visualize which price levels are of the most significance for either reversals or continuation of the trend when zones are broken and then re-tested.
Original script is thanks to synapticex and additional modifications is thanks to Lij_MC. Credit to both of them for most of the logic behind this script.
Since then I have made many changes to this script as noted below:
Changed default S/R lines from plots to lines, and gave option to user to change between solid line, dashed line, or dotted line for both S/R lines.
Added additional time frame and gave more TF options for TF1 other than current TF. Now you will have 4 time frames to plot S/R zones from.
Gave user option to easily change line thickness for all S/R lines.
Made it easier to change colors of S/R lines and zones by consolidating the options under settings (rather than under style).
Added extensions to active SR Zones to extend all the way right.
Added option to extend or not extend the previous S/R zones up to next S/R zone.
Added optional time frame labels to active S/R zones, with left and right options as well as option to adjust how far to the right label is set.
Fixed issue where the higher time frame S/R zone was not properly starting from the high/low of fractal. Now any higher time frame S/R will begin exactly at the High/Low points. Note that this may not work perfectly on stocks and if a fractal high/low is too many bars in the past, it will revert to a default max bars back to avoid script errors.
Added to script a function that will prevent S/R zones from lower time frames displaying while on a higher time frame. This helps clean up the chart quite a bit.
Created arrays for each time frame's boxes and lines so that the number of S/R zones can be controlled for each time frame and limit memory consumption.
New alert options added and customized alert messages.
- The way this indicator works is it looks for fractal highs or fractal lows with volume that pierces above the volume's Moving Average. This moving average value can be modified in the settings for each time frame.
- The fractal highs will be confirmed with 3 successive higher highs followed by 2 successive lower highs and vice versa for the fractal lows.
- The zone is created from the fractal high/low and the close of the candle for whatever time frame you selected. The bigger the zone, the more significant that zone is.
- You can disable any zone, change the zones to show lines only, and modify all the colors, transparencies, and thickness of lines for all the zones.
- To create alerts, you first want to enable the types of alerts you want for each time frame in the indicator's settings. Then after you apply changes, right click on one of the zones on the chart, and click "Add Alert on Vol S/R Zones". You do not need to add a title as the correct alert messages are already built-in.
- More changes will be coming in the future!
I hope you find this indicator useful, if so please give it a thumbs up!
If you have any suggestions or features you would like to see, just let me know in the comment section. Thanks and enjoy!
Strat Assistant FTC OnlyStrat Assistant FTC Only
----------------------------
█ OVERVIEW
This script is intended to provide full time frame continuity information for almost all time frames (3, 5, 15, 30, 60, 4H, Day, Week, Month, Quarter)
When added, the script provides a visual indicator to the right at the current price level with indicators for the various time frames in terms of price action and candle type.
█ DETAIL
----------
Output
Time Frames: 3min, 5min, 15min, 30min, 60min, 4 Hour, Day, Week, Month Quarter
Time Frame Labels: 3, 5, 15, 30, 60, H, 4H, D, W, M, Q
Current Candle Time Frame Price Action: displayed below time frame labels. RED + Arrow Down (open > close) or GREEN + Arrow Up (open =< close)
Time Frame Compare: displayed above time frame labels. Current high/low vs prior high/low are compared. IN = Inside/Yellow (current high/low inside prior), O = Outside/Fuchsia (current high/low both greater and less than prior high/low), 2U = Up/Green (current high higher than prior, and low not lower), 2D = Down/Red (current lows lower than prior lows, and high not higher)
Will not show time frames lower than the one currently selected
Best Practices
----------
Had to decouple this from the other scripts because Trading View limits how much you can plot/show
May be a little slow at times, analyzing a lot of time periods/data be patient.
MA DerivativesMA Derivatives basicly using Ichimoku Cloud and some additional moving averages for traders.
A. ICHIMOKU
Tenkan-sen (Conversion Line): (9-period high + 9-period low)/2
On a daily chart , this line is the midpoint of the 9-day high-low range, which is almost two weeks.
Kijun-sen (Base Line): (26-period high + 26-period low)/2
On a daily chart , this line is the midpoint of the 26-day high-low range, which is almost one month.
Senkou Span A (Leading Span A): (Conversion Line + Base Line)/2
This is the midpoint between the Conversion Line and the Base Line. The Leading Span A forms one of the two Cloud boundaries. It is referred to as “Leading” because it is plotted 26 periods in the future and forms the faster Cloud boundary.
Senkou Span B (Leading Span B): (52-period high + 52-period low)/2
On the daily chart , this line is the midpoint of the 52-day high-low range, which is a little less than 3 months. The default calculation setting is 52 periods, but it can be adjusted. This value is plotted 26 periods in the future and forms the slower Cloud boundary.
Chikou Span: Represents the closing price and is plotted 26 days back.
Kumo Cloud: Kumo cloud between Senkuo Span A and Senkou Span B lines. It can be green or red. Color can be change with the trend.
You can use Ichimoku for buy&sell strategy
For Buying Strategy
- Tenkansen (Conversion Line) should crossover Kijunsen (Base line) above the highest line of cloud
- Price should be above the highest line of cloud
- Chikouspan should be above the cloud
For Selling Strategy
- Kijunsen (Base Line) should crossover Tenkansen (Conversion Line) below the lowest line of cloud
- Price should be below the lowest line of cloud
- Chikouspan should be below the cloud
B. SIMPLE MOVING AVERAGES
The indicator has some of Simple Moving Averages
It includes:
-Simple Moving Average 50
-Simple Moving Average 100
-Simple Moving Average 200
C. EXPONENTIAL MOVING AVERAGES
The indicator has some of Simple Moving Averages
It includes:
-Exponential Moving Average 9
-Exponential Moving Average 21
-Exponential Moving Average 50
D. BOLLINGER BAND
Bollinger Bands are a type of price envelope developed by John BollingerOpens in a new window. (Price envelopes define upper and lower price range levels.) Bollinger Bands are envelopes plotted at a standard deviation level above and below a simple moving average of the price. Because the distance of the bands is based on standard deviation, they adjust to volatility swings in the underlying price.
Bollinger Bands use 2 parameters, Period and Standard Deviations, StdDev. The default values are 20 for period, and 2 for standard deviations, although you may customize the combinations.
Bollinger bands help determine whether prices are high or low on a relative basis. They are used in pairs, both upper and lower bands and in conjunction with a moving average. Further, the pair of bands is not intended to be used on its own. Use the pair to confirm signals given with other indicators.
How this indicator works
When the bands tighten during a period of low volatility, it raises the likelihood of a sharp price move in either direction. This may begin a trending move. Watch out for a false move in opposite direction which reverses before the proper trend begins.
When the bands separate by an unusual large amount, volatility increases and any existing trend may be ending.
Prices have a tendency to bounce within the bands' envelope, touching one band then moving to the other band. You can use these swings to help identify potential profit targets. For example, if a price bounces off the lower band and then crosses above the moving average, the upper band then becomes the profit target.
Price can exceed or hug a band envelope for prolonged periods during strong trends. On divergence with a momentum oscillator, you may want to do additional research to determine if taking additional profits is appropriate for you.
A strong trend continuation can be expected when the price moves out of the bands. However, if prices move immediately back inside the band, then the suggested strength is negated.
Calculation
First, calculate a simple moving average. Next, calculate the standard deviation over the same number of periods as the simple moving average. For the upper band, add the standard deviation to the moving average. For the lower band, subtract the standard deviation from the moving average.
Typical values used:
Short term: 10 day moving average, bands at 1.5 standard deviations. (1.5 times the standard dev. +/- the SMA)
Medium term: 20 day moving average, bands at 2 standard deviations.
Long term: 50 day moving average, bands at 2.5 standard deviations.
E. ADJUSTABLE MOVING AVERAGES
And this script has also 2 adjustable moving average
- 1 Adjustable Simple Moving Average
- 1 Adjustable Exponential Moving Average
You can just change the length for using this tool.
Ease of Movement WatcherHere’s a handy Ease of Movement(EMV) Indicator. I tried to include detailed comments so that anyone that’s learning pine can follow along.
The Ease of Movement Indicator is a volume based oscillator that is designed to measure the ease (or movability) of price movement for a security. The EMV is a centered oscillator, meaning that values can fluctuate above and below zero.
To understand how to use and interpret the EMV Indicator, its crucial to first understand its two main calculations :
Distance Moved = ((high + low) / 2) - ((high + low ) / 2)
-This is the difference between the current period’s midpoint and the previous period’s
midpoint.
Box Ratio = (volume / 100,000) / (high - low)
-When calculating the Box Ratio, it is common to divide the volume by 100,000 for a clearer visualization of the data. However, users can choose
to modify this value with the ‘volumeDiv’ input.
The Ease of Movement Value is then pretty simple to calculate:
EMV = (Distance Moved / Box Ratio)
The indicator then plots a SMA of the previous 24 EMV Values.
Looking at the formula, we know that combining low volume with a large {high, low} range will result in a relatively small box ratio value. Thus, we know that the EMV value for that period will be higher since EMV is found by dividing the Distance Moved by the Box Ratio.
Here’s a simple guide to interpreting the EMV:
- If (EMV > 0)
then price is increasing with relative ease.
-If (EMV < 0)
then price is decreasing with relative ease.
- If high-low range is large and volume is low
then ease of movement is high.
-If high-low range is small and volume is high
then ease of movement is low.
The Chart:
-The histogram represents the Simple Moving Average of EMV Values. The default length is 24, but users can adjust this value at the inputs menu(I've
found 24 works best).
-The teal and pink dotted lines represent the standard deviation of the SMA of EMV values multiplied by 2.5.
-The histogram turns dark green when the EMV SMA is greater than the top teal dotted standard deviations line.
-The histogram turns maroon when the EMV SMA falls below the bottom pink standard deviation line.
How To Use:
Enter a long position when the most recent EMV SMA value was below the lower pink stand. dev. line and the current EMV SMA value rises above that
same pink line. That means the previous bar was maroon and the current bar is not.
If the user enables the option to show entry points, a green dot will be plotted when it is time to enter a long position.
Exit the long position when the most recent EMV SMA value was above the upper green standard deviation line and the current EMV SMA value falls
below that same line. If this is true, then the previous bar will be dark green, and the current will be light green.
If the ‘showExits’ option is enabled, then a red dot will be plotted when it is time to exit the long position.
Input Options:
- 'volumeDiv' : Integer. Used in the calculation of Box Ratio.
- 'lenSMA' : Integer. The length of the Simple Moving Average of Ease of Movement Values.
- 'showStDev' : Bool. If true, dotted green and red lines will be shown at values equal to 2.5 * standard deviation of emvSMA and -2.5 * standard deviation of
emvSMA.
- 'showEntries' and 'showExits' : Bool. If true, a green circle will be plotted at long entry points and a red circle will be plotted at long exit points.
- 'changeBgColor': Bool. If true, the background color will change to green when it is time to enter a long position and red when it is time to exit.
Alerts:
- When it is time to enter a long position, an alert with the message "EMV Tracker - Enter Long" is sent.
- When it is time to exit a long position, an alert with the message "EMV Tracker - Exit Long" is sent.
NOTE:
- I usually use this indicator to confirm signals from other indicators rather than relying on it solely.
- Most accurate signals are generated on 30 minutes with the default input values I've set in the script.
Shoot me a message if you have any ideas for modifications or questions.
~ Happy Trading ~
BAY_PIVOT S/R(4 Full Lines + ALL Labels)//@version=5
indicator("BAY_PIVOT S/R(4 Full Lines + ALL Labels)", overlay=true, max_labels_count=500, max_lines_count=500)
// ────────────────────── TOGGLES ──────────────────────
showPivot = input.bool(true, "Show Pivot (Full Line + Label)")
showTarget = input.bool(true, "Show Target (Full Line + Label)")
showLast = input.bool(true, "Show Last Close (Full Line + Label)")
showPrevClose = input.bool(true, "Show Previous Close (Full Line + Label)")
useBarchartLast = input.bool(true, "Use Barchart 'Last' (Settlement Price)")
showR1R2R3 = input.bool(true, "Show R1 • R2 • R3")
showS1S2S3 = input.bool(true, "Show S1 • S2 • S3")
showStdDev = input.bool(true, "Show ±1σ ±2σ ±3σ")
showFib4W = input.bool(true, "Show 4-Week Fibs")
showFib13W = input.bool(true, "Show 13-Week Fibs")
showMonthHL = input.bool(true, "Show 1M High / Low")
showEntry1 = input.bool(false, "Show Manual Entry 1")
showEntry2 = input.bool(false, "Show Manual Entry 2")
entry1 = input.float(0.0, "Manual Entry 1", step=0.25)
entry2 = input.float(0.0, "Manual Entry 2", step=0.25)
stdLen = input.int(20, "StdDev Length", minval=1)
fib4wBars = input.int(20, "4W Fib Lookback")
fib13wBars = input.int(65, "13W Fib Lookback")
// ────────────────────── DAILY CALCULATIONS ──────────────────────
high_y = request.security(syminfo.tickerid, "D", high , lookahead=barmerge.lookahead_on)
low_y = request.security(syminfo.tickerid, "D", low , lookahead=barmerge.lookahead_on)
close_y = request.security(syminfo.tickerid, "D", close , lookahead=barmerge.lookahead_on)
pivot = (high_y + low_y + close_y) / 3
r1 = pivot + 0.382 * (high_y - low_y)
r2 = pivot + 0.618 * (high_y - low_y)
r3 = pivot + (high_y - low_y)
s1 = pivot - 0.382 * (high_y - low_y)
s2 = pivot - 0.618 * (high_y - low_y)
s3 = pivot - (high_y - low_y)
prevClose = close_y
last = useBarchartLast ? request.security(syminfo.tickerid, "D", close , lookahead=barmerge.lookahead_off) : close
target = pivot + (pivot - prevClose)
// StdDev + Fibs + Monthly (unchanged)
basis = ta.sma(close, stdLen)
dev = ta.stdev(close, stdLen)
stdRes1 = basis + dev
stdRes2 = basis + dev*2
stdRes3 = basis + dev*3
stdSup1 = basis - dev
stdSup2 = basis - dev*2
stdSup3 = basis - dev*3
high4w = ta.highest(high, fib4wBars)
low4w = ta.lowest(low, fib4wBars)
fib382_4w = high4w - (high4w - low4w) * 0.382
fib50_4w = high4w - (high4w - low4w) * 0.500
high13w = ta.highest(high, fib13wBars)
low13w = ta.lowest(low, fib13wBars)
fib382_13w_high = high13w - (high13w - low13w) * 0.382
fib50_13w = high13w - (high13w - low13w) * 0.500
fib382_13w_low = low13w + (high13w - low13w) * 0.382
monthHigh = ta.highest(high, 30)
monthLow = ta.lowest(low, 30)
// ────────────────────── COLORS ──────────────────────
colRed = color.rgb(255,0,0)
colLime = color.rgb(0,255,0)
colYellow = color.rgb(255,255,0)
colOrange = color.rgb(255,165,0)
colWhite = color.rgb(255,255,255)
colGray = color.rgb(128,128,128)
colMagenta = color.rgb(255,0,255)
colPink = color.rgb(233,30,99)
colCyan = color.rgb(0,188,212)
colBlue = color.rgb(0,122,255)
colPurple = color.rgb(128,0,128)
colRed50 = color.new(colRed,50)
colGreen50 = color.new(colLime,50)
// ────────────────────── 4 KEY FULL LINES ──────────────────────
plot(showPivot ? pivot : na, title="PIVOT", color=colYellow, linewidth=3, style=plot.style_linebr)
plot(showTarget ? target : na, title="TARGET", color=colOrange, linewidth=2, style=plot.style_linebr)
plot(showLast ? last : na, title="LAST", color=colWhite, linewidth=2, style=plot.style_linebr)
plot(showPrevClose ? prevClose : na, title="PREV CLOSE",color=colGray, linewidth=1, style=plot.style_linebr)
// ────────────────────── LABELS FOR ALL 4 KEY LEVELS (SAME STYLE AS OTHERS) ──────────────────────
f_label(price, txt, bgColor, txtColor) =>
if barstate.islast and not na(price)
label.new(bar_index, price, txt, style=label.style_label_left, color=bgColor, textcolor=txtColor, size=size.small)
if barstate.islast
showPivot ? f_label(pivot, "PIVOT\n" + str.tostring(pivot, "#.##"), colYellow, color.black) : na
showTarget ? f_label(target, "TARGET\n" + str.tostring(target, "#.##"), colOrange, color.white) : na
showLast ? f_label(last, "LAST\n" + str.tostring(last, "#.##"), colWhite, color.black) : na
showPrevClose ? f_label(prevClose, "PREV CLOSE\n"+ str.tostring(prevClose, "#.##"), colGray, color.white) : na
// ────────────────────── OTHER LEVELS – line stops at label ──────────────────────
f_level(p, txt, tc, lc, w=1) =>
if barstate.islast and not na(p)
lbl = label.new(bar_index, p, txt, style=label.style_label_left, color=lc, textcolor=tc, size=size.small)
line.new(bar_index-400, p, label.get_x(lbl), p, extend=extend.none, color=lc, width=w)
if barstate.islast
if showR1R2R3
f_level(r1, "R1\n" + str.tostring(r1, "#.##"), color.white, colRed)
f_level(r2, "R2\n" + str.tostring(r2, "#.##"), color.white, colRed)
f_level(r3, "R3\n" + str.tostring(r3, "#.##"), color.white, colRed, 2)
if showS1S2S3
f_level(s1, "S1\n" + str.tostring(s1, "#.##"), color.black, colLime)
f_level(s2, "S2\n" + str.tostring(s2, "#.##"), color.black, colLime)
f_level(s3, "S3\n" + str.tostring(s3, "#.##"), color.black, colLime, 2)
if showStdDev
f_level(stdRes1, "+1σ\n" + str.tostring(stdRes1, "#.##"), color.white, colPink)
f_level(stdRes2, "+2σ\n" + str.tostring(stdRes2, "#.##"), color.white, colPink)
f_level(stdRes3, "+3σ\n" + str.tostring(stdRes3, "#.##"), color.white, colPink, 2)
f_level(stdSup1, "-1σ\n" + str.tostring(stdSup1, "#.##"), color.white, colCyan)
f_level(stdSup2, "-2σ\n" + str.tostring(stdSup2, "#.##"), color.white, colCyan)
f_level(stdSup3, "-3σ\n" + str.tostring(stdSup3, "#.##"), color.white, colCyan, 2)
if showFib4W
f_level(fib382_4w, "38.2% 4W\n" + str.tostring(fib382_4w, "#.##"), color.white, colMagenta)
f_level(fib50_4w, "50% 4W\n" + str.tostring(fib50_4w, "#.##"), color.white, colMagenta)
if showFib13W
f_level(fib382_13w_high, "38.2% 13W High\n" + str.tostring(fib382_13w_high, "#.##"), color.white, colMagenta)
f_level(fib50_13w, "50% 13W\n" + str.tostring(fib50_13w, "#.##"), color.white, colMagenta)
f_level(fib382_13w_low, "38.2% 13W Low\n" + str.tostring(fib382_13w_low, "#.##"), color.white, colMagenta)
if showMonthHL
f_level(monthHigh, "1M HIGH\n" + str.tostring(monthHigh, "#.##"), color.white, colRed50, 2)
f_level(monthLow, "1M LOW\n" + str.tostring(monthLow, "#.##"), color.white, colGreen50, 2)
// Manual entries
plot(showEntry1 and entry1 > 0 ? entry1 : na, "Entry 1", color=colBlue, linewidth=2, style=plot.style_linebr)
plot(showEntry2 and entry2 > 0 ? entry2 : na, "Entry 2", color=colPurple, linewidth=2, style=plot.style_linebr)
// Background
bgcolor(close > pivot ? color.new(color.blue, 95) : color.new(color.red, 95))
new_youtube_strategy//@version=5
strategy("Dow + Homma 1m Scalper (15m filter)", overlay=true, margin_long=100, margin_short=100, initial_capital=10000)
//===== INPUTS =====
maLen = input.int(50, "Trend SMA Length", minval=5)
htf_tf = input.timeframe("15", "Higher TF")
priceTolPct = input.float(0.05, "SR tolerance %", step=0.01)
wickFactor = input.float(2.0, "Hammer/ShootingStar wick factor", step=0.1)
dojiThresh = input.float(0.1, "Doji body % of range", step=0.01)
risk_RR = input.float(2.0, "Reward:Risk", step=0.1)
capitalRiskPct = input.float(1.0, "Risk % of equity per trade", step=0.1)
//===== 1m TREND (SMA) =====
sma1 = ta.sma(close, maLen)
sma1Up = sma1 > sma1
sma1Down = sma1 < sma1
uptrend1 = close > sma1 and sma1Up
downtrend1 = close < sma1 and sma1Down
//===== 15m TREND VIA request.security =====
sma15 = request.security(syminfo.tickerid, htf_tf, ta.sma(close, maLen), lookahead=barmerge.lookahead_off)
sma15Up = sma15 > sma15
sma15Down = sma15 < sma15
uptrend15 = close > sma15 and sma15Up
downtrend15 = close < sma15 and sma15Down
//===== SWING HIGHS/LOWS (LOCAL EXTREMA) =====
var int left = 3
var int right = 3
swHigh = ta.pivothigh(high, left, right)
swLow = ta.pivotlow(low, left, right)
//===== SR FLIP LEVELS =====
var float srSupport = na
var float srResistance = na
// when a swing high is broken -> new support
if not na(swHigh)
if close > swHigh
srSupport := swHigh
// when a swing low is broken -> new resistance
if not na(swLow)
if close < swLow
srResistance := swLow
//===== CANDLE METRICS =====
body = math.abs(close - open)
cRange = high - low
upperW = high - math.max(open, close)
lowerW = math.min(open, close) - low
isBull() => close > open
isBear() => close < open
bullHammer() =>
cRange > 0 and
isBull() and
lowerW >= wickFactor * body and
upperW <= body
bearShootingStar() =>
cRange > 0 and
isBear() and
upperW >= wickFactor * body and
lowerW <= body
isDoji() =>
cRange > 0 and body <= dojiThresh * cRange
bullEngulfing() =>
isBear() and isBull() and
open <= close and close >= open
bearEngulfing() =>
isBull() and isBear() and
open >= close and close <= open
//===== SR PROXIMITY =====
tol = priceTolPct * 0.01 * close
nearSupport = not na(srSupport) and math.abs(close - srSupport) <= tol
nearResistance = not na(srResistance) and math.abs(close - srResistance) <= tol
//===== SIGNAL CONDITIONS =====
bullCandle = bullHammer() or isDoji() or bullEngulfing()
bearCandle = bearShootingStar() or isDoji() or bearEngulfing()
longTrendOK = uptrend1 and uptrend15
shortTrendOK = downtrend1 and downtrend15
longSignal = longTrendOK and nearSupport and bullCandle
shortSignal = shortTrendOK and nearResistance and bearCandle
//===== POSITION SIZING (IN RISK UNITS) =====
var float lastEquity = strategy.equity
riskCapital = strategy.equity * (capitalRiskPct * 0.01)
//===== ENTRY / EXIT PRICES =====
longStop = math.min(low, nz(srSupport, low))
longRisk = close - longStop
longTP = close + risk_RR * longRisk
shortStop = math.max(high, nz(srResistance, high))
shortRisk = shortStop - close
shortTP = close - risk_RR * shortRisk
// qty in contracts (approx; assumes price * qty ≈ capital used)
longQty = longRisk > 0 ? riskCapital / longRisk : 0.0
shortQty = shortRisk > 0 ? riskCapital / shortRisk : 0.0
//===== EXECUTION =====
if longSignal and longRisk > 0 and longQty > 0
strategy.entry("Long", strategy.long, qty=longQty)
strategy.exit("Long TP/SL", from_entry="Long", stop=longStop, limit=longTP)
if shortSignal and shortRisk > 0 and shortQty > 0
strategy.entry("Short", strategy.short, qty=shortQty)
strategy.exit("Short TP/SL", from_entry="Short", stop=shortStop, limit=shortTP)
//===== PLOTS =====
plot(sma1, color=color.orange, title="SMA 1m")
plot(sma15, color=color.blue, title="HTF SMA (15m)")
plot(srSupport, "SR Support", color=color.new(color.green, 50), style=plot.style_linebr)
plot(srResistance,"SR Resistance",color=color.new(color.red, 50), style=plot.style_linebr)
// Visual debug for signals
plotshape(longSignal, title="Long Signal", style=shape.triangleup, location=location.belowbar, color=color.lime, size=size.tiny)
plotshape(shortSignal, title="Short Signal", style=shape.triangledown, location=location.abovebar, color=color.red, size=size.tiny)
Omega Correlation [OmegaTools]Omega Correlation (Ω CRR) is a cross-asset analytics tool designed to quantify both the strength of the relationship between two instruments and the tendency of one to move ahead of the other. It is intended for traders who work with indices, futures, FX, commodities, equities and ETFs, and who require something more robust than a simple linear correlation line.
The indicator operates in two distinct modes, selected via the “Show” parameter: Correlation and Anticipation. In Correlation mode, the script focuses on how tightly the current chart and the chosen second asset move together. In Anticipation mode, it shifts to a lead–lag perspective and estimates whether the second asset tends to behave as a leader or a follower relative to the symbol on the chart.
In both modes, the core inputs are the chart symbol and a user-selected second symbol. Internally, both assets are transformed into normalized log-returns: the script computes logarithmic returns, removes short-term mean and scales by realized volatility, then clips extreme values. This normalisation allows the tool to compare behaviour across assets with different price levels and volatility profiles.
In Correlation mode, the indicator computes a composite correlation score that typically ranges between –1 and +1. Values near +1 indicate strong and persistent positive co-movement, values near zero indicate an unstable or weak link, and values near –1 indicate a stable anti-correlation regime. The composite score is constructed from three components.
The first component is a normalized return co-movement measure. After transforming both instruments into normalized returns, the script evaluates how similar those returns are bar by bar. When the two assets consistently deliver returns of similar sign and magnitude, this component is high and positive. When they frequently diverge or move in opposite directions, it becomes negative. This captures short-term co-movement in a volatility-adjusted way.
The second component focuses on high–low swing alignment. Rather than looking only at closes, it examines the direction of changes in highs and lows for each bar. If both instruments are printing higher highs and higher lows together, or lower highs and lower lows together, the swing structure is considered aligned. Persistent alignment contributes positively to the correlation score, while repeated mismatches between the swing directions reduce it. This helps differentiate between superficial price noise and structural similarity in trend behaviour.
The third component is a classical Pearson correlation on closing prices, computed over a longer lookback. This serves as a stabilising backbone that summarises general co-movement over a broader window. By combining normalized return co-movement, swing alignment and standard price correlation with calibrated weights, the Correlation mode provides a richer view than a single linear measure, capturing both short-term dynamic interaction and longer-term structural linkage.
In Anticipation mode, Omega Correlation estimates whether the second asset tends to lead or lag the current chart. The output is again a continuous score around the range. Positive values suggest that the second asset is acting more as a leader, with its past moves bearing informative value for subsequent moves of the chart symbol. Negative values indicate that the second asset behaves more like a laggard or follower. Values near zero suggest that no stable lead–lag structure can be identified.
The anticipation score is built from four elements inspired by quantitative lead–lag and price discovery analysis. The first element is a residual lead correlation, conceptually similar to Granger-style logic. The script first measures how much of the chart symbol’s normalized returns can be explained by its own lagged values. It then removes that component and studies the correlation between the residuals and lagged returns of the second asset. If the second asset’s past returns consistently explain what the chart symbol does beyond its own autoregressive behaviour, this residual correlation becomes significantly positive.
The second element is an asymmetric lead–lag structure measure. It compares the strength of relationships in both directions across multiple lags: the correlation of the current symbol with lagged versions of the second asset (candidate leader) versus the correlation of lagged values of the current symbol with the present values of the second asset. If the forward direction (second asset leading the first) is systematically stronger than the backward direction, the structure is skewed toward genuine leadership of the second asset.
The third element is a relative price discovery score, constructed by building a dynamic hedge ratio between the two prices and defining a spread. The indicator looks at how changes in each asset contribute to correcting deviations in this spread over time. When the chart symbol tends to do most of the adjustment while the second asset remains relatively stable, it suggests that the second asset is taking a greater role in determining the equilibrium price and the chart symbol is adjusting to it. The difference in adjustment intensity between the two instruments is summarised into a single score.
The fourth element is a breakout follow-through causality component. The script scans for breakout events on the second asset, where its price breaks out of a recent high or low range while the chart symbol has not yet done so. It then evaluates whether the chart symbol subsequently confirms the breakout direction, remains neutral, or moves against it. Events where the second asset breaks and the first asset later follows in the same direction add positive contribution, while failed or contrarian follow-through reduce this component. The contribution is also lightly modulated by the strength of the breakout, via the underlying normalized return.
The four elements of the Anticipation mode are combined into a single leading correlation score, providing a compact and interpretable measure of whether the second asset currently behaves as an effective early signal for the symbol you trade.
To aid interpretation, Omega Correlation builds dynamic bands around the active series (correlation or anticipation). It estimates a long-term central tendency and a typical deviation around it, plotting upper and lower bands that highlight unusually high or low values relative to recent history. These bands can be used to distinguish routine fluctuations from genuinely extreme regimes.
The script also computes percentile-based levels for the correlation series and uses them to track two special price levels on the main chart: lost correlation levels and gained correlation levels. When the correlation drops below an upper percentile threshold, the current price is stored as a lost correlation level and plotted as a horizontal line. When the correlation rises above a lower percentile threshold, the current price is stored as a gained correlation level. These levels mark zones where a historically strong relationship between the two markets broke down or re-emerged, and can be used to frame divergence, convergence and spread opportunities.
An information panel summarises, in real time, whether the second asset is behaving more as a leading, lagging or independent instrument according to the anticipation score, and suggests whether the current environment is more conducive to de-alignment, re-alignment or classic spread behaviour based on the correlation regime. This makes the tool directly interpretable even for users who are not familiar with all the underlying statistical details.
Typical applications for Omega Correlation include intermarket analysis (for example, index vs index, commodity vs related equity sector, FX vs bonds), dynamic hedge sizing, regime detection for algorithmic strategies, and the identification of lead–lag structures where a macro driver or benchmark can be monitored as an early signal for the instrument actually traded. The indicator can be applied across intraday and higher timeframes, with the understanding that the strength and nature of relationships will differ across horizons.
Omega Correlation is designed as an advanced analytical framework, not as a standalone trading system. Correlation and lead–lag relationships are statistical in nature and can change abruptly, especially around macro events, regime shifts or liquidity shocks. A positive anticipation reading does not guarantee that the second asset will always move first, and a high correlation regime can break without warning. All outputs of this tool should be combined with independent analysis, sound risk management and, when appropriate, backtesting or forward testing on the user’s specific instruments and timeframes.
The intention behind Omega Correlation is to bring techniques inspired by quantitative research, such as normalized return analysis, residual correlation, asymmetric lead–lag structure, price discovery logic and breakout event studies, into an accessible TradingView indicator. It is intended for traders who want a structured, professional way to understand how markets interact and to incorporate that information into their discretionary or systematic decision-making processes.
لbsm15// This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) creativecommons.org
// © LuxAlgo
//@version=5
indicator("لbsm15", overlay = true, max_lines_count = 500, max_boxes_count = 500, max_bars_back = 3000)
//------------------------------------------------------------------------------
//Settings
//-----------------------------------------------------------------------------{
liqGrp = 'Liquidity Detection'
liqLen = input.int (7, title = 'Detection Length', minval = 3, maxval = 13, inline = 'LIQ', group = liqGrp)
liqMar = 10 / input.float (6.9, 'Margin', minval = 4, maxval = 9, step = 0.1, inline = 'LIQ', group = liqGrp)
liqBuy = input.bool (true, 'Buyside Liquidity Zones, Margin', inline = 'Buyside', group = liqGrp)
marBuy = input.float(2.3, '', minval = 1.5, maxval = 10, step = .1, inline = 'Buyside', group = liqGrp)
cLIQ_B = input.color (color.new(#4caf50, 0), '', inline = 'Buyside', group = liqGrp)
liqSel = input.bool (true, 'Sellside Liquidity Zones, Margin', inline = 'Sellside', group = liqGrp)
marSel = input.float(2.3, '', minval = 1.5, maxval = 10, step = .1, inline = 'Sellside', group = liqGrp)
cLIQ_S = input.color (color.new(#f23645, 0), '', inline = 'Sellside', group = liqGrp)
lqVoid = input.bool (false, 'Liquidity Voids, Bullish', inline = 'void', group = liqGrp)
cLQV_B = input.color (color.new(#4caf50, 0), '', inline = 'void', group = liqGrp)
cLQV_S = input.color (color.new(#f23645, 0), 'Bearish', inline = 'void', group = liqGrp)
lqText = input.bool (false, 'Label', inline = 'void', group = liqGrp)
mode = input.string('Present', title = 'Mode', options = , inline = 'MOD', group = liqGrp)
visLiq = input.int (3, ' # Visible Levels', minval = 1, maxval = 50, inline = 'MOD', group = liqGrp)
//-----------------------------------------------------------------------------}
//General Calculations
//-----------------------------------------------------------------------------{
maxSize = 50
atr = ta.atr(10)
atr200 = ta.atr(200)
per = mode == 'Present' ? last_bar_index - bar_index <= 500 : true
//-----------------------------------------------------------------------------}
//User Defined Types
//-----------------------------------------------------------------------------{
// @type used to store pivot high/low data
//
// @field d (array) The array where the trend direction is to be maintained
// @field x (array) The array where the bar index value of pivot high/low is to be maintained
// @field y (array) The array where the price value of pivot high/low is to be maintained
type ZZ
int d
int x
float y
// @type bar properties with their values
//
// @field o (float) open price of the bar
// @field h (float) high price of the bar
// @field l (float) low price of the bar
// @field c (float) close price of the bar
// @field i (int) index of the bar
type bar
float o = open
float h = high
float l = low
float c = close
int i = bar_index
// @type liquidity object definition
//
// @field bx (box) box maitaing the liquity level margin extreme levels
// @field bxz (box) box maitaing the liquity zone margin extreme levels
// @field bxt (box) box maitaing the labels
// @field brZ (bool) mainains broken zone status
// @field brL (bool) mainains broken level status
// @field ln (line) maitaing the liquity level line
// @field lne (line) maitaing the liquity extended level line
type liq
box bx
box bxz
box bxt
bool brZ
bool brL
line ln
line lne
//-----------------------------------------------------------------------------}
//Variables
//-----------------------------------------------------------------------------{
var ZZ aZZ = ZZ.new(
array.new (maxSize, 0),
array.new (maxSize, 0),
array.new (maxSize, na)
)
bar b = bar.new()
var liq b_liq_B = array.new (1, liq.new(box(na), box(na), box(na), false, false, line(na), line(na)))
var liq b_liq_S = array.new (1, liq.new(box(na), box(na), box(na), false, false, line(na), line(na)))
var b_liq_V = array.new_box()
var int dir = na, var int x1 = na, var float y1 = na, var int x2 = na, var float y2 = na
//-----------------------------------------------------------------------------}
//Functions/methods
//-----------------------------------------------------------------------------{
// @function maintains arrays
// it prepends a `value` to the arrays and removes their oldest element at last position
// @param aZZ (UDT, array, array>) The UDT obejct of arrays
// @param _d (array) The array where the trend direction is maintained
// @param _x (array) The array where the bar index value of pivot high/low is maintained
// @param _y (array) The array where the price value of pivot high/low is maintained
//
// @returns none
method in_out(ZZ aZZ, int _d, int _x, float _y) =>
aZZ.d.unshift(_d), aZZ.x.unshift(_x), aZZ.y.unshift(_y), aZZ.d.pop(), aZZ.x.pop(), aZZ.y.pop()
// @function (build-in) sets the maximum number of bars that is available for historical reference
max_bars_back(time, 1000)
//-----------------------------------------------------------------------------}
//Calculations
//-----------------------------------------------------------------------------{
x2 := b.i - 1
ph = ta.pivothigh(liqLen, 1)
pl = ta.pivotlow (liqLen, 1)
if ph
dir := aZZ.d.get(0)
x1 := aZZ.x.get(0)
y1 := aZZ.y.get(0)
y2 := nz(b.h )
if dir < 1
aZZ.in_out(1, x2, y2)
else
if dir == 1 and ph > y1
aZZ.x.set(0, x2), aZZ.y.set(0, y2)
if per
count = 0
st_P = 0.
st_B = 0
minP = 0.
maxP = 10e6
for i = 0 to maxSize - 1
if aZZ.d.get(i) == 1
if aZZ.y.get(i) > ph + (atr / liqMar)
break
else
if aZZ.y.get(i) > ph - (atr / liqMar) and aZZ.y.get(i) < ph + (atr / liqMar)
count += 1
st_B := aZZ.x.get(i)
st_P := aZZ.y.get(i)
if aZZ.y.get(i) > minP
minP := aZZ.y.get(i)
if aZZ.y.get(i) < maxP
maxP := aZZ.y.get(i)
if count > 2
getB = b_liq_B.get(0)
if st_B == getB.bx.get_left()
getB.bx.set_top(math.avg(minP, maxP) + (atr / liqMar))
getB.bx.set_rightbottom(b.i + 10, math.avg(minP, maxP) - (atr / liqMar))
else
b_liq_B.unshift(
liq.new(
box.new(st_B, math.avg(minP, maxP) + (atr / liqMar), b.i + 10, math.avg(minP, maxP) - (atr / liqMar), bgcolor=color(na), border_color=color(na)),
box.new(na, na, na, na, bgcolor = color(na), border_color = color(na)),
box.new(st_B, st_P, b.i + 10, st_P, text = 'Buyside liquidity', text_size = size.tiny, text_halign = text.align_left, text_valign = text.align_bottom, text_color = color.new(cLIQ_B, 25), bgcolor = color(na), border_color = color(na)),
false,
false,
line.new(st_B , st_P, b.i - 1, st_P, color = color.new(cLIQ_B, 0)),
line.new(b.i - 1, st_P, na , st_P, color = color.new(cLIQ_B, 0), style = line.style_dotted))
)
alert('buyside liquidity level detected/updated for ' + syminfo.ticker)
if b_liq_B.size() > visLiq
getLast = b_liq_B.pop()
getLast.bx.delete()
getLast.bxz.delete()
getLast.bxt.delete()
getLast.ln.delete()
getLast.lne.delete()
if pl
dir := aZZ.d.get (0)
x1 := aZZ.x.get (0)
y1 := aZZ.y.get (0)
y2 := nz(b.l )
if dir > -1
aZZ.in_out(-1, x2, y2)
else
if dir == -1 and pl < y1
aZZ.x.set(0, x2), aZZ.y.set(0, y2)
if per
count = 0
st_P = 0.
st_B = 0
minP = 0.
maxP = 10e6
for i = 0 to maxSize - 1
if aZZ.d.get(i) == -1
if aZZ.y.get(i) < pl - (atr / liqMar)
break
else
if aZZ.y.get(i) > pl - (atr / liqMar) and aZZ.y.get(i) < pl + (atr / liqMar)
count += 1
st_B := aZZ.x.get(i)
st_P := aZZ.y.get(i)
if aZZ.y.get(i) > minP
minP := aZZ.y.get(i)
if aZZ.y.get(i) < maxP
maxP := aZZ.y.get(i)
if count > 2
getB = b_liq_S.get(0)
if st_B == getB.bx.get_left()
getB.bx.set_top(math.avg(minP, maxP) + (atr / liqMar))
getB.bx.set_rightbottom(b.i + 10, math.avg(minP, maxP) - (atr / liqMar))
else
b_liq_S.unshift(
liq.new(
box.new(st_B, math.avg(minP, maxP) + (atr / liqMar), b.i + 10, math.avg(minP, maxP) - (atr / liqMar), bgcolor=color(na), border_color=color(na)),
box.new(na, na, na, na, bgcolor=color(na), border_color=color(na)),
box.new(st_B, st_P, b.i + 10, st_P, text = 'Sellside liquidity', text_size = size.tiny, text_halign = text.align_left, text_valign = text.align_top, text_color = color.new(cLIQ_S, 25), bgcolor=color(na), border_color=color(na)),
false,
false,
line.new(st_B , st_P, b.i - 1, st_P, color = color.new(cLIQ_S, 0)),
line.new(b.i - 1, st_P, na , st_P, color = color.new(cLIQ_S, 0), style = line.style_dotted))
)
alert('sellside liquidity level detected/updated for ' + syminfo.ticker)
if b_liq_S.size() > visLiq
getLast = b_liq_S.pop()
getLast.bx.delete()
getLast.bxz.delete()
getLast.bxt.delete()
getLast.ln.delete()
getLast.lne.delete()
for i = 0 to b_liq_B.size() - 1
x = b_liq_B.get(i)
if not x.brL
x.lne.set_x2(b.i)
if b.h > x.bx.get_top()
x.brL := true
x.brZ := true
alert('buyside liquidity level breached for ' + syminfo.ticker)
x.bxz.set_lefttop(b.i - 1, math.min(x.ln.get_y1() + marBuy * (atr), b.h))
x.bxz.set_rightbottom(b.i + 1, x.ln.get_y1())
x.bxz.set_bgcolor(color.new(cLIQ_B, liqBuy ? 73 : 100))
else if x.brZ
if b.l > x.ln.get_y1() - marBuy * (atr) and b.h < x.ln.get_y1() + marBuy * (atr)
x.bxz.set_right(b.i + 1)
x.bxz.set_top(math.max(b.h, x.bxz.get_top()))
if liqBuy
x.lne.set_x2(b.i + 1)
else
x.brZ := false
for i = 0 to b_liq_S.size() - 1
x = b_liq_S.get(i)
if not x.brL
x.lne.set_x2(b.i)
if b.l < x.bx.get_bottom()
x.brL := true
x.brZ := true
alert('sellside liquidity level breached for ' + syminfo.ticker)
x.bxz.set_lefttop(b.i - 1, x.ln.get_y1())
x.bxz.set_rightbottom(b.i + 1, math.max(x.ln.get_y1() - marSel * (atr), b.l))
x.bxz.set_bgcolor(color.new(cLIQ_S, liqSel ? 73 : 100))
else if x.brZ
if b.l > x.ln.get_y1() - marSel * (atr) and b.h < x.ln.get_y1() + marSel * (atr)
x.bxz.set_rightbottom(b.i + 1, math.min(b.l, x.bxz.get_bottom()))
if liqSel
x.lne.set_x2(b.i + 1)
else
x.brZ := false
if lqVoid and per
bull = b.l - b.h > atr200 and b.l > b.h and b.c > b.h
bear = b.l - b.h > atr200 and b.h < b.l and b.c < b.l
if bull
l = 13
if bull
st = math.abs(b.l - b.l ) / l
for i = 0 to l - 1
array.push(b_liq_V, box.new(b.i - 2, b.l + i * st, b.i, b.l + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_B, 90) ))
else
st = math.abs(b.l - b.h ) / l
for i = 0 to l - 1
if lqText and i == 0
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, text = 'Liquidity Void ', text_size = size.tiny, text_halign = text.align_right, text_valign = text.align_bottom, text_color = na, border_color = na, bgcolor = color.new(cLQV_B, 90) ))
else
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_B, 90) ))
if bear
l = 13
if bear
st = math.abs(b.h - b.h) / l
for i = 0 to l - 1
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_S, 90) ))
else
st = math.abs(b.l - b.h) / l
for i = 0 to l - 1
if lqText and i == l - 1
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, text = 'Liquidity Void ', text_size = size.tiny, text_halign = text.align_right, text_valign = text.align_top, text_color = na, border_color = na, bgcolor = color.new(cLQV_S, 90) ))
else
array.push(b_liq_V, box.new(b.i - 2, b.h + i * st, b.i, b.h + (i + 1) * st, border_color = na, bgcolor = color.new(cLQV_S, 90) ))
if b_liq_V.size() > 0
qt = b_liq_V.size()
for bn = qt - 1 to 0
if bn < b_liq_V.size()
cb = b_liq_V.get(bn)
ba = math.avg(cb.get_bottom(), cb.get_top())
if math.sign(b.c - ba) != math.sign(b.c - ba) or math.sign(b.c - ba) != math.sign(b.l - ba) or math.sign(b.c - ba) != math.sign(b.h - ba)
b_liq_V.remove(bn)
else
cb.set_right(b.i + 1)
if b.i - cb.get_left() > 21
cb.set_text_color(color.new(color.gray, 25))
//-----------------------------------------------------------------------------}
Day-Type Detector — Rejection / FNL / Outside / StopRun (Clean)Day-Type Detector — Rejection / FNL / Outside / Stop-Run (Clean Version)
This indicator identifies four high-impact candlestick day-types commonly used in professional price-action and auction-market trading: Rejection Days, Failed New Low (FNL) Days, Outside Days, and Stop-Run Days. These patterns often precede major directional moves, reversals, and absorption events, making them particularly valuable for swing traders, positional traders, and short-term discretionary traders.
The script is designed to work across all timeframes and is built around volatility-adjusted measurements using Average Daily Range (ADR) for accuracy and consistency.
What This Indicator Detects
1. Rejection Day (Bullish & Bearish)
A Rejection Day is a wide-range bar that rejects a previous extreme.
The indicator identifies rejection based on:
Range > ADR × threshold
Long lower wick (for bullish) or long upper wick (for bearish)
Close located in the strong zone of the day’s range
These conditions highlight areas where aggressive counter-orderflow entered the market.
2. Failed New Low (FNL) / Failed New High
An FNL day traps traders who attempted breakout selling or buying.
The indicator checks for:
A break beyond the previous session’s low or high
Immediate rejection back inside
Midpoint recapture conditions
ADR-normalized range requirements
These days often trigger powerful directional reversals.
3. Outside Day (Bullish & Bearish)
An Outside Day is a statistically significant expansion day that breaks both the previous high and low.
The script validates:
High > previous high and low < previous low
Range > ADR threshold
Close beyond prior session extreme to complete the rejection sequence
Outside Days often represent stop runs, shakeouts, or trend accelerations.
4. Stop-Run Day (Bullish & Bearish)
Stop-Run Days are aggressive volatility expansions and tend to be the largest ranges within short windows.
This detector identifies them using:
Range > ADR × multiplier
Close located near the extreme of the day (top for bullish, bottom for bearish)
Strong body relative to total range
Break above/below previous session extreme
These patterns indicate capitulation or forced liquidation and are often followed by continuation or sharp counter-rotation.
Key Features
✔ Historical Pattern Marking
All qualifying bars are marked on the chart using plotshape() in global scope, ensuring full historical visibility.
✔ Event Logging & Table Display
A table (top-right of the chart) displays the most recent pattern detections, including:
Timestamp
Pattern type
Bar index
This allows users to monitor and study past pattern occurrences without scanning the chart manually.
✔ ADR-Adjusted Detection
Volatility uncertainty is removed by anchoring all thresholds to ADR.
This ensures consistency across:
Different symbols
Different timeframes
Different market regimes
✔ Alerts Included
Alerts are preconfigured for:
Rejection Day Bull / Bear
FNL Bull / Bear
Outside Day Bull / Bear
Stop-Run Bull / Bear
This allows the user to receive real-time notifications when major day-type structures develop.
How to Use
Add the indicator to any timeframe chart.
Enable or disable:
Historical markers
History table
ADR diagnostics
Watch for shape markers or use alerts for real-time signals.
Use the history table to review recent occurrences.
Combine these day-types with:
Market structure levels
High/low volume nodes (LVNs)
Support/resistance zones
Trend context
These day-types are most effective when they occur near meaningful structural levels because they show where strong order-flow entered the market.
Best Practices
Use higher timeframes (1H–1D) for swing entries.
Confirm signals with market structure or volume profile.
Treat these day-types as context, not standalone signals.
Observe follow-through behavior in the next 1–3 bars after detection.
Credits
This script is based on concepts commonly seen in auction-market theory and professional price-action frameworks, such as Rejection Days, Failed New Lows, Outside Days, and Stop-Run behaviors.
All calculations and logic have been rebuilt from scratch to ensure clean, reliable, and optimized Pine Script v6 execution.
DAO - Demand Advanced Oscillator# DAO - Demand Advanced Oscillator
## 📊 Overview
DAO (Demand Advanced Oscillator) is a powerful momentum oscillator that measures buying and selling pressure by analyzing consecutive high-low relationships. It helps identify market extremes, divergences, and potential trend reversals.
**Values range from 0 to 1:**
- **Above 0.70** = Overbought (potential reversal down)
- **Below 0.30** = Oversold (potential reversal up)
- **0.30 - 0.70** = Neutral zone
---
## ✨ Key Features
✅ **Automatic Divergence Detection**
- Bullish divergences (price lower low + DAO higher low)
- Bearish divergences (price higher high + DAO lower high)
- Visual lines connecting divergence points
✅ **Multi-Timeframe Analysis**
- View higher timeframe DAO on current chart
- Perfect for trend alignment strategies
✅ **Signal Line (EMA)**
- Customizable EMA for trend confirmation
- Crossover signals for momentum shifts
✅ **Real-Time Statistics Dashboard**
- Current DAO value
- Market status (Overbought/Oversold/Neutral)
- Trend direction indicator
✅ **Complete Alert System**
- Overbought/Oversold signals
- Bullish/Bearish divergences
- Signal line crosses
- Level crosses
✅ **Fully Customizable**
- Adjustable periods and levels
- Customizable colors and zones
- Toggle features on/off
---
## 📈 Trading Signals
### 1. Divergences (Most Powerful)
**Bullish Divergence:**
- Price makes lower low
- DAO makes higher low
- Signal: Strong reversal up likely
**Bearish Divergence:**
- Price makes higher high
- DAO makes lower high
- Signal: Strong reversal down likely
### 2. Overbought/Oversold
**Overbought (>0.70):**
- Market may be overextended
- Consider taking profits or looking for shorts
- Can remain overbought in strong trends
**Oversold (<0.30):**
- Market may be oversold
- Consider buying opportunities
- Can remain oversold in strong downtrends
### 3. Signal Line Crossovers
**Bullish Cross:**
- DAO crosses above signal line
- Momentum turning positive
**Bearish Cross:**
- DAO crosses below signal line
- Momentum turning negative
### 4. Level Crosses
**Cross Above 0.30:** Exiting oversold zone (potential uptrend)
**Cross Below 0.70:** Exiting overbought zone (potential downtrend)
---
## ⚙️ Default Settings
📊 Oscillator Period: 14
Number of bars for calculation
📈 Signal Line Period: 9
EMA period for signal line
🔴 Overbought Level: 0.70
Upper threshold
🟢 Oversold Level: 0.30
Lower threshold
🎯 Divergence Detection: ON
Auto divergence identification
⏰ Multi-Timeframe: OFF
Higher TF overlay (optional)
All parameters are fully customizable!
---
## 🔔 Alerts
Six pre-configured alerts available:
1. DAO Overbought
2. DAO Oversold
3. DAO Bullish Divergence
4. DAO Bearish Divergence
5. DAO Signal Cross Up
6. DAO Signal Cross Down
**Setup:** Right-click indicator → Add Alert → Choose condition
---
## 💡 How to Use
### Best Practices:
✅ Focus on divergences (strongest signals)
✅ Combine with support/resistance levels
✅ Use multiple timeframes for confirmation
✅ Wait for price action confirmation
✅ Practice proper risk management
### Avoid:
❌ Trading on indicator alone
❌ Fighting strong trends
❌ Ignoring market context
❌ Overtrading
### Recommended Settings by Trading Style:
**Day Trading:** Period 7-10, All alerts ON
**Swing Trading:** Period 14-21, Divergence alerts
**Scalping:** Period 5-7, Signal crosses
**Position Trading:** Period 21-30, Weekly/Daily TF
---
## 🌍 Markets & Timeframes
**Works on all markets:**
- Forex (all pairs)
- Stocks (all exchanges)
- Cryptocurrencies
- Commodities
- Indices
- Futures
**Works on all timeframes:** 1m to Monthly
---
## 📊 How It Works
DAO calculates the ratio of buying pressure to total market pressure:
1. **Calculate Buying Pressure (DemandMax):**
- If current high > previous high: DemandMax = difference
- Otherwise: DemandMax = 0
2. **Calculate Selling Pressure (DemandMin):**
- If previous low > current low: DemandMin = difference
- Otherwise: DemandMin = 0
3. **Apply Smoothing:**
- Calculate SMA of DemandMax over N periods
- Calculate SMA of DemandMin over N periods
4. **Final Formula:**
```
DAO = SMA(DemandMax) / (SMA(DemandMax) + SMA(DemandMin))
```
This produces a normalized value (0-1) representing market demand strength.
---
## 🎯 Trading Strategies
### Strategy 1: Divergence Trading
- Wait for divergence label
- Confirm at support/resistance
- Enter on confirming candle
- Stop loss beyond recent swing
- Target: opposite level or 0.50
### Strategy 2: Overbought/Oversold
- Best for ranging markets
- Wait for extreme readings
- Enter on reversal from extremes
- Target: middle line (0.50)
### Strategy 3: Trend Following
- Identify trend direction first
- Use DAO to time entries in trend direction only
- Enter on pullbacks to oversold (uptrend) or overbought (downtrend)
- Trade with the trend
### Strategy 4: Multi-Timeframe
- Enable MTF feature
- Trade only when both timeframes align
- Higher TF = trend direction
- Lower TF = precise entry
---
## 📂 Category
**Primary:** Oscillators
**Secondary:** Statistics, Volatility, Momentum
---
## 🏷️ Tags
dao, oscillator, momentum, overbought-oversold, divergence, reversal, demand-indicator, price-exhaustion, statistics, volatility, forex, stocks, crypto, multi-timeframe, technical-analysis
---
## ⚠️ Disclaimer
**This indicator is for educational purposes only.** It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research, use proper risk management, and consult with financial professionals before making trading decisions. Past performance does not guarantee future results.
---
## 📄 License
Open source - Free to use for personal trading, modify as needed, and share with attribution.
---
**Version:** 1.0
**Status:** Production Ready ✅
**Pine Script:** v5
**Trademark-Free:** 100% Safe to Publish
---
*Made with 💙 for traders worldwide*
[FS] Pivot Measurements# Pivot Measurements
An advanced TradingView indicator that combines LuxAlgo's pivot point detection algorithm with automatic measurement calculations between consecutive pivots.
## Features
### Pivot Detection
- **Regular Pivots**: Detects standard pivot highs and lows using configurable pivot length
- **Missed Pivots**: Identifies missed reversal levels that occurred between regular pivots
- **Visual Indicators**:
- Regular pivot highs: Red downward triangle (▼)
- Regular pivot lows: Teal upward triangle (▲)
- Missed pivots: Ghost emoji (👻)
- **Zigzag Lines**: Connects pivots with colored lines (solid for regular, dashed for missed)
- **Ghost Levels**: Horizontal lines indicating missed pivot levels
### Measurement System
- **Automatic Measurements**: Calculates price movements between consecutive pivots
- **Visual Display**:
- Transparent colored boxes (blue for upward, red for downward movements)
- Measurement labels showing:
- Price change (absolute and percentage)
- Duration (bars, days, hours, minutes)
- Volume approximation
- **Smart Positioning**: Labels positioned outside boxes (above for upward, below for downward)
- **Color Coding**: Blue for positive movements, red for negative movements
## Parameters
### Pivot Detection
- **Pivot Length** (default: 50): Number of bars on each side to identify a pivot point
- **Regular Pivots**: Toggle and colors for regular pivot highs and lows
- **Missed Pivots**: Toggle and colors for missed pivot detection
### Measurements
- **Number of Measurements** (1-10, default: 10): Maximum number of measurements to display
- **Show Measurement Boxes**: Toggle to show/hide measurement boxes and labels
- **Box Transparency** (0-100, default: 90): Transparency level for measurement boxes
- **Border Transparency** (0-100, default: 50): Transparency level for box borders
- **Label Background Transparency** (0-100, default: 30): Transparency level for label backgrounds
- **Label Size**: Size of measurement labels (tiny, small, normal, large)
## Usage
1. Add the indicator to your chart
2. Configure the **Pivot Length** based on your timeframe:
- Lower values for shorter timeframes (e.g., 10-20 for 1-5 min)
- Higher values for longer timeframes (e.g., 50-100 for daily)
3. Adjust pivot colors and visibility as needed
4. Customize measurement display settings:
- Set the number of measurements to display
- Adjust transparency levels for boxes, borders, and labels
- Choose label size
## Technical Details
- **Pine Script Version**: v6
- **Pivot Detection**: Based on () algorithm for detecting regular and missed pivots
- **Measurement Calculation**:
- Measures between consecutive pivots (from most recent to older)
- Calculates price change, percentage change, duration, and approximate volume
- Automatically sorts pivots chronologically
- **Performance**: Optimized with helper functions to reduce code duplication
## Notes
- The indicator automatically limits the number of stored pivots to optimize performance
- Measurements are only created when there are at least 2 pivots detected
- All measurements are recalculated on each bar update
- The indicator uses `max_bars_back=5000` to ensure sufficient historical data
## License
This indicator uses LuxAlgo's pivot detection algorithm from (). Please refer to the original LuxAlgo license for pivot detection components.
LibPvotLibrary "LibPvot"
This is a library for advanced technical analysis, specializing
in two core areas: the detection of price-oscillator
divergences and the analysis of market structure. It provides
a back-end engine for signal detection and a toolkit for
indicator plotting.
Key Features:
1. **Complete Divergence Suite (Class A, B, C):** The engine detects
all three major types of divergences, providing a full spectrum of
analytical signals:
- **Regular (A):** For potential trend reversals.
- **Hidden (B):** For potential trend continuations.
- **Exaggerated (C):** For identifying weakness at double tops/bottoms.
2. **Advanced Signal Filtering:** The detection logic uses a
percentage-based price tolerance (`prcTol`). This feature
enables the practical detection of Exaggerated divergences
(which rarely occur at the exact same price) and creates a
"dead zone" to filter insignificant noise from triggering
Regular divergences.
3. **Pivot Synchronization:** A bar tolerance (`barTol`) is used
to reliably match price and oscillator pivots that do not
align perfectly on the same bar, preventing missed signals.
4. **Signal Invalidation Logic:** Features two built-in invalidation
rules:
- An optional `invalidate` parameter automatically terminates
active divergences if the price or the oscillator breaks
the level of the confirming pivot.
- The engine also discards 'half-pivots' (e.g., a price pivot)
if a corresponding oscillator pivot does not appear within
the `barTol` window.
5. **Stateful Plotting Helpers:** Provides helper functions
(`bullDivPos` and `bearDivPos`) that abstract away the
state management issues of visualizing persistent signals.
They generate gap-free, accurately anchored data series
ready to be used in `plotshape` functions, simplifying
indicator-side code.
6. **Rich Data Output:** The core detection functions (`bullDiv`, `bearDiv`)
return a comprehensive 9-field data tuple. This includes the
boolean flags for each divergence type and the precise
coordinates (price, oscillator value, bar index) of both the
starting and the confirming pivots.
7. **Market Structure & Trend Analysis:** Includes a
`marketStructure` function to automatically identify pivot
highs/lows, classify their relationship (HH, LH, LL, HL),
detect structure breaks, and determine the current trend
state (Up, Down, Neutral) based on pivot sequences.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
bullDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bullish divergences (Regular, Hidden, Exaggerated) based on pivot lows.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `low`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
below the confirming pivot low.
Returns: A tuple containing comprehensive data for a detected bullish divergence.
regBull series bool `true` if a Regular bullish divergence (Class A) is active.
hidBull series bool `true` if a Hidden bullish divergence (Class B) is active.
exgBull series bool `true` if an Exaggerated bullish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot low.
initPivotOsz series float Oscillator value of the initial pivot low.
initPivotBar series int Bar index of the initial pivot low.
lastPivotPrc series float Price value of the last (confirming) pivot low.
lastPivotOsz series float Oscillator value of the last pivot low.
lastPivotBar series int Bar index of the last pivot low.
bearDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bearish divergences (Regular, Hidden, Exaggerated) based on pivot highs.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `high`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
above the confirming pivot high.
Returns: A tuple containing comprehensive data for a detected bearish divergence.
regBear series bool `true` if a Regular bearish divergence (Class A) is active.
hidBear series bool `true` if a Hidden bearish divergence (Class B) is active.
exgBear series bool `true` if an Exaggerated bearish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot high.
initPivotOsz series float Oscillator value of the initial pivot high.
initPivotBar series int Bar index of the initial pivot high.
lastPivotPrc series float Price value of the last (confirming) pivot high.
lastPivotOsz series float Oscillator value of the last pivot high.
lastPivotBar series int Bar index of the last pivot high.
bullDivPos(regBull, hidBull, exgBull, rightLen, yPos)
Calculates the plottable data series for bullish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBull (bool) : series bool The regular bullish divergence flag from `bullDiv`.
hidBull (bool) : series bool The hidden bullish divergence flag from `bullDiv`.
exgBull (bool) : series bool The exaggerated bullish divergence flag from `bullDiv`.
rightLen (int) : series int The same `rightLen` value used in `bullDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `low`).
Returns: A tuple of three `series float` for plotting bullish divergences.
regBullPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBullPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBullPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
bearDivPos(regBear, hidBear, exgBear, rightLen, yPos)
Calculates the plottable data series for bearish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBear (bool) : series bool The regular bearish divergence flag from `bearDiv`.
hidBear (bool) : series bool The hidden bearish divergence flag from `bearDiv`.
exgBear (bool) : series bool The exaggerated bearish divergence flag from `bearDiv`.
rightLen (int) : series int The same `rightLen` value used in `bearDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `high`).
Returns: A tuple of three `series float` for plotting bearish divergences.
regBearPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBearPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBearPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
marketStructure(highSrc, lowSrc, leftLen, rightLen, srcTol)
Analyzes the market structure by identifying pivot points, classifying
their sequence (e.g., Higher Highs, Lower Lows), and determining the
prevailing trend state.
Parameters:
highSrc (float) : series float Price series for pivot high detection (e.g., `high`).
lowSrc (float) : series float Price series for pivot low detection (e.g., `low`).
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
srcTol (float) : series float Percentage tolerance to consider two pivots as 'equal' (default 0.05%).
Returns: A tuple containing detailed market structure information.
pivType series PivType The type of the most recently formed pivot (e.g., `hh`, `ll`).
lastPivHi series float The price level of the last confirmed pivot high.
lastPivLo series float The price level of the last confirmed pivot low.
lastPiv series float The price level of the last confirmed pivot (either high or low).
pivHiBroken series bool `true` if the price has broken above the last pivot high.
pivLoBroken series bool `true` if the price has broken below the last pivot low.
trendState series TrendState The current trend state (`up`, `down`, or `neutral`).
