Scripting Tutorial A - TManyMA - StopsThis script is for a triple moving average strategy where the user can select from different types of moving averages, price sources, lookback periods and resolutions.
Features:
- 3 Moving Averages with variable MA types, periods, price sources, resolutions and the ability to disable each individually.
- Crossovers are plotted on the chart with detailed information regarding the crossover (Ex: 50 SMA crossed over 200 SMA )
- Forecasting available for all three MAs. MA values are forecasted 5 values out and plotted as if a continuation to the MA.
- Forecast bias also applies to all forecasting. Bias means we can forecast based on an anticipated bullish, bearish or neutral direction in the market.
- To understand bias, please read the source code, or if you can't read the code just send me a message on here or Twitter. Twitter should be linked to my profile.
- Ribbons added and on by default. Optional setting to disable the ribbons. 5 ribbons between MA1 and MA2 and another 5 between MA2 and MA3.
- Ribbons are alpha-color coded based on their relation to their default MAs.
- Ribbons are only visible between MAs if the MAs being compared share the same Type, Resolution, and Source because there is no way to consolidate those three in a simple manner.
- Ribbon values are calculated based on calculated MA Periods between the MAs.
- Converted the existing study into a strategy.
- Strategy only enters long positions with a market order when MA crossovers occur.
- Strategy exits positions when crossunders occur.
- Trades 100% of the equity with one order/position by default.
- Ability to disable trading certain crosses with input checks.
- Ability to exit trades with a take profit or stop loss.
- User input to allow quick changes to the take profit or stop loss percentages.
This script is meant as an educational script with well-formatted styling, and references for specific functions.
*** PLEASE NOTE - THIS STRATEGY IS MEANT FOR LEARNING PURPOSES. DEPENDING ON IT'S CONFIGURATION IT MAY OR MAY NOT BE USEFUL FOR ACTUAL TRADING. THE STRATEGY IS NOT FINANCIAL ADVICE ***
Tìm kiếm tập lệnh với "bias"
Extended Recursive Bands - Maximum Efficiency With Extra OptionsIntroducing A New Calculation For Efficient Bands Calculation !
Here it is ! The Recursive Bands Indicator, an indicator specially created to be extremely efficient, i think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in my paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis" , the indicator framework has been widely used in my previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, i decided to add extra options, which explain the term "extended".
On The Indicator Calculation
You can skip this part if it doesn't interest you. The calculation of the indicator is based on recursion, but i want to explain the mathematical formula described in the paper.
I've seen some users trying to remake it from the calculations, however there was always something weird, and i understand, mathematical notations are always a bit weird, even myself don't always write them correctly/understand them, however this one is relatively simple to understand.
First lets explain each elements of the calculation :
α = smoothing constant, or 2/(length+1)
max/min = maximum and minimum function, max return the greatest input value while min return the lowest one, for example :
max(4,2) = 4 while min(4,2) = 2
the "||" notation mean taking the absolute value, for example : |-1| = abs(-1) = 1
The calculation after the max/min function is called the correction factor, and is the core of the indicator. The last two variables are just here to provide an initial value for upper and lower, basically when we start our calculations we will assign the value of the closing price for upper and lower.
The motivation behind using a smoothing constant in range of (0,1) was to tell the reader that the indicator is easily made adaptive, this is what i did on my adaptive trailing stop indicator by using the efficiency ratio as smoothing variable, the user can use 1/length instead of the provided calculation for alpha.
If you interested on the indicator main logic, it is actually really simple, by using upper = max(price,upper) and lower = min(price,lower) we would get the maximum/minimum price value at time t , therefore upper can only be greater or equal than its precedent value, while lower can only be lower or equal than its precedent value, in order to fix that we subtract/sum upper/lower with a value, this allow the upper band to be lower than its precedent value and lower to be greater than its precedent value, this is the role of the correction factor.
The Indicator
The indicator display one upper and one lower band, every common usages applied to bands indicators such as support/resistance, breakout, trailing stop...etc, can also be applied to this one. length control how reactive the bands are, higher values of length will make the bands cross the price less often.
In order to provide more flexibility for the user i added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range, standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator.
Classic Method
This option make the indicator use its classical calculation, this is the most efficient method of all.
Atr Method (atr)
This method use the average true range as correction factor, notice that lower values of length can still produce wide band.
Standard Deviation Method (stdev)
This method use a biased estimate of the standard deviation as correction factor.
The method produce smoother bands that converge more slowly toward the price in comparison with the classic correction factor.
Average High-Low Range Method (ahlr)
This method use the average of the high-low range as correction factor, extremely similar to the average true range.
Rising Falling Volatility (rfv) Method
A new method created for this indicator, this correction factor use the absolute prices changes when price value is greater/lower than any length past values of the price, this allow to have more boxy shaped bands, work best with greater values of length.
The bands can be in contact with this method, a possible fix in the future.
Conclusion
The recursive band indicator is one of my greatest indicators in my opinion (i would love to have yours), as you can see the idea behind it is extremely simple and allow for a super efficient band indicator, which was the original motivation behind it, in order to provide more fun for the users i also added more option for the correction factor, this allow the user to be creative and not get stuck with the original calculation.
Like the trend step indicator family we have almost ended our series on the recursive band framework, 1 more trailing stop will be added in the future, and then we'll have more "boring" stuff until i find something cool again, it shouldn't be long ;)
Thanks for reading !
Scripting Tutorial 9 - TManyMA Strategy - Long Market Order OnlyThis script is for a triple moving average strategy where the user can select from different types of moving averages, price sources, lookback periods and resolutions.
Features:
- 3 Moving Averages with variable MA types, periods, price sources, resolutions and the ability to disable each individually
- Crossovers are plotted on the chart with detailed information regarding the crossover (Ex: 50 SMA crossed over 200 SMA )
- Forecasting available for all three MAs. MA values are forecasted 5 values out and plotted as if a continuation to the MA.
- Forecast bias also applies to all forecasting. Bias means we can forecast based on an anticipated bullish, bearish or neutral direction in the market.
- To understand bias, please read the source code, or if you can't read the code just send me a message on here or Twitter. Twitter should be linked to my profile.
- Ribbons added and on by default. Optional setting to disable the ribbons. 5 ribbons between MA1 and MA2 and another 5 between MA2 and MA3.
- Ribbons are alpha-color coded based on their relation to their default MAs.
- Ribbons are only visible between MAs if the MAs being compared share the same Type, Resolution, and Source because there is no way to consolidate those three in a simple manner.
- Ribbon values are calculated based on calculated MA Periods between the MAs.
- Converted the existing study into a strategy
- Strategy only enters long positions with a market order when MA crossovers occur
- Strategy exits positions when crossunders occur
- Trades 100% of the equity with one order/position by default
- Ability to disable trading certain crosses with input checks
This script is meant as an educational script with well-formatted styling, and references for specific functions.
*** PLEASE NOTE - THIS STRATEGY IS MEANT FOR LEARNING PURPOSES. DEPENDING ON IT'S CONFIGURATION IT MAY OR MAY NOT BE USEFUL FOR ACTUAL TRADING. THE STRATEGY IS NOT FINANCIAL ADVICE ***
Scripting Tutorial 8 - Triple Many Moving Averages RibbonsThis script is for a triple moving average indicator where the user can select from different types of moving averages, price sources, lookback periods and resolutions.
Features:
- 3 Moving Averages with variable MA types, periods, price sources, resolutions and the ability to disable each individually
- Crossovers are plotted on the chart with detailed information regarding the crossover (Ex: 50 SMA crossed over 200 SMA )
- Forecasting available for all three MAs. MA values are forecasted 5 values out and plotted as if a continuation to the MA.
- Forecast bias also applies to all forecasting. Bias means we can forecast based on an anticipated bullish, bearish or neutral direction in the market.
- To understand bias, please read the source code, or if you can't read the code just send me a message on here or Twitter. Twitter should be linked to my profile.
- Ribbons added and on by default. Optional setting to disable the ribbons. 5 ribbons between MA1 and MA2 and another 5 between MA2 and MA3.
- Ribbons are alpha-color coded based on their relation to their default MAs.
- Ribbons are only visible between MAs if the MAs being compared share the same Type, Resolution, and Source because there is no way to consolidate those three in a simple manner.
- Ribbon values are calculated based on calculated MA Periods between the MAs.
This script is meant as an educational script with well-formatted styling, and references for specific functions.
Kaufman Adaptive BandsIntroduction
Bands are quite efficient in technical analysis, they can provide support and resistance levels, provide breakouts points, trailing stop loss/take profits positions and can show the current market volatility to the user. Most of the time bands are made from a central tendency estimator like a moving average plus/minus a volatility indicator. Therefore bands can be made out of pretty much everything thus allowing for any kind of flavors.
So i propose a band indicator made from a Kaufman adaptive moving average using an estimate of the standard deviation.
Construction
The Kaufman moving average is an exponential averager using the efficiency ratio as smoothing variable, length control the period of kama and in order to provide more smoothness a power parameter has been introduced, higher values of power will return smoother results.
The volatility indicator is made from a biased estimation of the standard deviation by using the square root of the mean of the square minus the square of the mean method, except that we use kama instead of a mean.
The bands are made by adding/subtracting this volatility indicator with kama.
How To Use
The ability of the indicator to adapt to the current market state is what makes him a great tool for avoiding major exposition during ranging market, therefore the indicator will have a greater motion during trending market, or more simply the bands will move during trending markets while staying "flat" during ranging ones. Therefore the indicator might be more suited to breakouts, even if some cases will return what where turning points, this is particularly true during ranging markets.
Of course the efficiency ratio is not an "unbiased" trend metric indicator, it can consider high volatility markets as trending markets. Its one of his downsides.
High values of power will create smoother bands.
When using a low power parameter use an higher mult. In general using a low power value will make the bands move more freely as well as making them closer to each others.
Conclusion
At least the indicator is really nice to the eyes when using high power values, its ability to adapt to the market is a great addition to other more classical bands indicators, i also introduced a volatility estimator based on kama, some might have used the following estimation : kama(abs(price - kama)) which would have created a slower result. A trailing stop might be made from it if i see request about such addition.
If you are curious here are some more images of the indicator performing on different markets. Thanks for reading !
5 MAs w. alerts [LucF]Is this gazillionth MA indicator worth an addition to the already crowded field of contenders? I say yes! This one shows up to 5 MAs and 6 different marker conditions that can be used to create alerts, among many other goodies.
Features
MAs can be darkened when they are falling.
MAs from another time frame can be displayed, with the option of smoothing them.
Markers can be filtered to Longs or Shorts only.
EMAs can be selected for either all or the two shortest MAs.
The background can be colored using any of the marker states except no. 3.
Markers are:
1. On crosses between any two user-defined MAs,
2. When price is above or below an MA,
3. On Quick Flips (a specific setup involving a cross, multiple MA states and increasing volume, when available),
4. When the difference between two MAs is within a % of its high/low historic values,
5. When an MA has been rising/falling for n bars,
6. When the difference between two MAs is greater than a multiple of ATR.
Some markers use similar visual cues, so distinguishing them will be a challenge if they are used concurrently.
Alerts
Alerts can be created on any combination of alerts. Only non-consecutive instances of markers 5 and 6 will trigger the alert condition. Make sure you are on the interval you want the alert to run at. Using the “Once Per Bar Close” trigger condition is usually the best option.
When an alert is created in TradingView, a snapshot of the indicator’s settings is saved with the alert, which then takes on a life of its own. That is why even though there is only one alert to choose from when you bring up the alert creation dialog box and choose “5 MAs”, that alert can be triggered from any number of conditions. You select those conditions by activating the markers you want the alert to trigger on before creating the alert. If you have selected multiple conditions, then it can be a good idea to record a reminder in the alert’s message field. When the alert triggers, you will need the indicator on the chart to figure out which one of your conditions triggered the alert, as there is currently no way to dynamically change the alert’s message field from within the script.
Background settings will not trigger alerts; only marker configurations.
Notes
MAs are just… averages. Trader lure would have them act as support and resistance levels. I’m not sure about that, and not the only one thinking along these lines. Adam Grimes has studied moving averages in quite a bit of detail. His numbers point to no evidence indicating they act as support/resistance, and to specific MA lengths not being more meaningful than others. His point of view is debated by some—not by me. Mean reversion does not entail that price stops when it reaches its MA; rather, it makes sense to me that price would often more or less oscillate around its MA, which entails the MA does not act as support/resistance. Aren’t the best mean reversion opportunities when price is furthest away from its MA? If so, it should be more profitable to identify these areas, which some of this indicator’s markers try to do.
I think MAs can be much more powerful when thought of as instruments we can use to situate price events in contexts of various resolutions, from the instantaneous to the big picture. Accordingly, I use the relative positions and slopes of MAs in both discretionary and automated trading; but never their purported ability to support/resist.
Regardless of how you use MAs, I hope you will find this indicator useful.
Biased References
The Art and Science of Technical Analysis: Market Structure, Price Action, and Trading Strategies, Adam Grimes, 2012.
Does the 200 day moving average “work”?
Moving averages: digging deeper
Linear Momentum and Performance IndicatorsThis a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index: The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index: It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index: The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index: The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedbacks are welcome
Hope you enjoy this,
CryptoStatistical
Linear Momentum and Performance Indicators (IFTA Jan 2019)This a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index : The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index : It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index : The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index : The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedback are welcome
Hope you enjoy this,
CryptoStatistical
Candlestick normalizer + MA's Crossing SignalingWell, after 25 tries I finally did it ._.
Here is the candlestick normalizer I was trying to achieve. In this way you can do a fast and not biased by price candlestick analysis, for example to catch engulfish and doji's on the go ;)
I also added a MAs crossing-over signal I optimized.
Btw, I will try to add volume signaling on this indicator. I had been thinking in 2 options:
1) Maybe as a colour/unfilled bar when volume exceed average
2) Represent the volume on the width of the candlestick.
What do you prefer? Let me know.
I hope you enjoy it!
Phi it.
FIB Band Signals with RSI FilterOriginal Author: Rashad
Added by Rashad 6-26-16
These Bollinger bands feature Fibonacci retracements to very clearly show areas of support and resistance . The basis is calculate off of the Volume Weighted Moving Average . The Bands are 3 standard deviations away from the mean. 99.73% of observations should be in this range.
Updated by Dysrupt 7-12-18
-Buy signals added on lower bands, mean and upper 3 bands
-Sell signals added to upper 3 bands
-RSI filter applied to signals
-Alerts not yet added
-Long Biased
NOTE: This is NOT a set and forget signal indicator. It is extremely versatile for all environments by adjusting the RSI filter and checking the band signals needed for the current trend and trading style.
Linear ExtrapolationBasic extrapolator for forecast a time-series, all forecasts are mades length periods ahead.
This is not a estimation of the exact price
This should only be used for forecasting direction, dont expect the price to be at the same value of its forecast.
Bias, Mean absolute error, Mean percentage error...etc look useless here, its better to use correlation as a accuracy measurement.
Correlation(Forecast ,close,period)
Rescaling for a better forecast ?
Transforming a non-stationary signal to a stationary signal can increase the forecasting accuracy, this can be done by detrending. Here is a list of somes detrending methods:
Auto-Bias : price - price
Mean-Bias : price - price moving average
Log transform : log(price/price moving average)
Correlation : correlation(price,n,period)
Ichimoku_on_steroids v 1.0 OLBased on the original Ichimoku formula, this indicator provides decent long/short entries/exit signals. It takes into account an EMA on price as well as the two leading lines (without the future projection). Works on all timeframes, on all bar style's (incl. Renko & PnF). Configurable to your taste in the settings.
Black line = EMA on close // Green line = Leading Span A // Red line = Leading Span B
Green = Long bias // Red = Short bias // Yellow = Neutral bias or close position
The cautious trader might want to wait for confirmation (red or green) before entering a position ; the riskier trader might want to enter as soon as neutral territory is reached.
As usual : use it at your own risk ;)
Comments / suggestions welcome
PS: there are more scripts in the pipeline ... :)
Anurag Balanced 0DTE Scalper SPY QQQBalanced 0DTE Scalper
1. Purpose: A 0DTE options day trading indicator for SPY/QQQ on 5-minute charts with visual CALL/PUT entry and exit signals.
2. Trend Filter: Uses 15-minute EMA crossover (9/21) + ADX to confirm trend direction before taking trades.
3. Entry Logic: Triggers on pullback to 5m EMA9 with RSI/VWAP/MACD confirmation, bullish or bearish candle required.
4. Exit System: ATR-based trailing stop, dual targets (TP1 partial, TP2 full), time stop, and auto-exit at EOD.
5. Risk Controls: Max trades/day limit, cooldown period after exits, session filter (avoids first 10 min & last 15 min).
6. Visual Feedback: Dynamic stop/target lines, entry/exit labels with P&L, background color for trend bias and cooldown.
7. Dashboard: 16-row panel showing bias, ADX, regime, RSI, VWAP, position, bars held, cooldown status, strike suggestions, and DTE recommendation.
GC/MGC VWAP Pullback + ADX Regime (Prop-Safe)GC / MGC VWAP Pullback + ADX Regime Strategy (Prop-Safe)
This strategy is designed specifically for Gold futures (GC & MGC) and prop firm trading, where capital preservation, consistency, and avoiding chop matter more than trade frequency.
The core philosophy is simple:
Only trade gold when it is expanding, aligned, and at the right location.
Strategy Concept
Gold moves in bursts, not constantly.
Most losses come from trading compression, VWAP chop, or late momentum.
This strategy filters those environments out and trades only:
Strong intraday momentum
Clear higher-timeframe direction
First pullbacks to VWAP
Clean price rejection with follow-through
It intentionally produces fewer but higher-quality trades.
Market Regime Filter (ADX)
ADX is evaluated on the 5-minute chart
This is the trade permission filter
ADX zones:
Below 18 → No trade (compression / chop)
20–35 → Optimal trading zone
35–45 → Caution (strong trend, reduced opportunity)
Above 45 → No new entries (late expansion / news risk)
ADX does not determine direction.
It only determines whether trading is allowed.
Direction Filter (Higher Timeframe)
Direction comes from the 1-Hour chart
EMA 20 above EMA 50 → Long bias only
EMA 20 below EMA 50 → Short bias only
Optional slope confirmation for additional strictness
No counter-trend trades.
Entry Logic (5-Minute Chart)
Trades are taken using a VWAP pullback continuation model.
Long Setup
ADX between 20–35
1H EMA 20 > EMA 50
Price pulls back to VWAP
Bullish rejection candle at VWAP
Entry on break of the rejection candle high
Short Setup
ADX between 20–35
1H EMA 20 < EMA 50
Price pulls back to VWAP from below
Bearish rejection candle at VWAP
Entry on break of the rejection candle low
All entries use stop orders, not market orders, to ensure follow-through.
Risk Management
Stop loss is placed beyond the rejection candle
Partial profit at 1R
Final target at 2R
No pyramiding
One clean setup is preferred over multiple trades
This structure aligns well with prop firm rules, trailing drawdowns, and consistency requirements.
What This Strategy Avoids
VWAP chop
Range-bound sessions
Overtrading
Late entries after news spikes
Counter-trend setups
If conditions are not ideal, no trade is the correct trade.
Best Use Case
Instruments: GC, MGC
Timeframe: 5-minute
Style: Intraday, prop-firm friendly
Ideal for traders who value:
Discipline
Structure
Capital protection
Futures Ultra CVD (Pure )Futures Ultra CVD (Pure)
Futures Ultra CVD (Pure) is a volume-driven Cumulative Volume Delta (CVD) indicator designed to expose real buying and selling pressure behind price movement. Unlike price-only indicators, this script analyzes how volume is distributed within each bar to determine whether aggressive buyers or sellers are in control, then tracks how that pressure evolves over time.
This version is intentionally pure and ungated: it does not rely on external symbols, market filters, session bias, or macro confirmation. All signals are derived strictly from price, volume, and delta behavior of the active chart, making it suitable for futures, equities, crypto, and FX.
Core Concept: How CVD Is Calculated
For each bar, volume is split into buying pressure and selling pressure using the bar’s price position:
Buying volume increases as price closes closer to the high
Selling volume increases as price closes closer to the low
The difference between buying and selling volume forms Delta:
Positive delta = net aggressive buying
Negative delta = net aggressive selling
This delta is then accumulated into Cumulative Volume Delta (CVD) using one of three user-selectable modes:
Total – running cumulative sum of all delta values
Periodic – rolling sum over a fixed lookback period
EMA – smoothed cumulative delta using an exponential average
This flexibility allows traders to choose between raw order-flow tracking or smoother, trend-like behavior depending on timeframe and instrument.
Visual Structure & Histogram Logic
The CVD is displayed as a column histogram, not a line, to emphasize momentum and pressure shifts.
Enhanced coloring provides additional context:
Brighter green/red bars indicate increasing momentum
Muted colors indicate stalling or weakening pressure
Optional footprint-style highlights appear when buy or sell volume overwhelms the opposite side by a user-defined imbalance factor
This allows traders to visually distinguish:
Strength vs weakness
Continuation vs exhaustion
Absorption and aggressive participation
Built-In Order Flow Signals
The script automatically detects and labels key order-flow events:
Strong Delta
Triggered when delta exceeds a user-defined threshold, highlighting unusually aggressive buying or selling.
Delta Surge
Detects sudden expansion in delta compared to the prior bar, often associated with breakout attempts or liquidation events.
Zero-Line Crosses
Marks transitions between net bullish and bearish participation as CVD crosses above or below zero.
CVD Continuation Logic (Trend Confirmation)
Beyond raw delta, the script evaluates CVD structure to identify continuation conditions:
A bullish continuation requires:
Positive and rising CVD
Strong buy delta
Confirmation from at least one of the following:
CVD above its EMA and SMA
Bullish price expansion
Sustained positive delta pressure
Bearish continuation follows the inverse logic.
These continuation signals are designed to confirm participation strength, not predict reversals.
Conflict Detection (Divergence Warning)
The indicator also flags conflict conditions, where:
Strong buying occurs while CVD remains negative
Strong selling occurs while CVD remains positive
These scenarios often precede failed breakouts, absorption zones, or short-term reversals and can be used as cautionary signals.
Alerts & Practical Use
All major events include built-in alerts:
Strong delta
Delta surge
CVD continuations
Zero-line crosses
Buy/sell imbalances
Conflict signals
Alerts can be set to trigger on bar close or intrabar in real time, depending on trader preference.
How Traders Typically Use This Indicator
Confirm breakouts with delta participation
Validate trends using CVD continuation instead of price alone
Identify absorption or exhaustion via conflicts and imbalances
Combine with price structure, VWAP, or market profile tools
This script is not a trading system by itself. It is a decision-support tool designed to reveal what price alone cannot: who is actually in control of the market.
On-Chart Symbols & What They Mean
This script uses a small number of visual symbols to communicate order-flow events clearly and consistently. All symbols are derived directly from the Cumulative Volume Delta calculations described above.
Δ+ (Green Up Arrow)
Strong Buy Delta
Indicates that buying pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market buying dominating selling volume
Often appears during breakouts, trend acceleration, or initiative buying
This symbol does not imply direction by itself; it only confirms strong buyer participation.
Δ− (Red Down Arrow)
Strong Sell Delta
Indicates that selling pressure on the current bar exceeded the Strong Delta Threshold
Represents aggressive market selling dominating buying volume
Often appears during breakdowns, liquidation events, or initiative selling
Like Δ+, this symbol measures participation strength, not trade direction.
↑ (Green Label Up)
CVD Bullish Continuation
Appears when all of the following are present:
CVD is positive and increasing
Strong buy delta is detected
At least one confirmation condition is met:
CVD is above its EMA and SMA
Price shows bullish expansion
Consecutive positive delta bars (sustained buying pressure)
This symbol highlights trend continuation supported by volume, not a reversal signal.
↓ (Red Label Down)
CVD Bearish Continuation
Appears when:
CVD is negative and decreasing
Strong sell delta is detected
At least one confirmation condition is met:
CVD is below its EMA and SMA
Price shows bearish expansion
Consecutive negative delta bars (sustained selling pressure)
This indicates bearish continuation with participation confirmation.
Cyan / Orange Histogram Bars
Footprint-Style Volume Imbalance
Cyan bars indicate buy volume exceeds sell volume by the imbalance factor
Orange bars indicate sell volume exceeds buy volume by the imbalance factor
These bars highlight areas where one side is overwhelming the other, often associated with absorption, initiative moves, or failed auctions.
Bright vs Muted Histogram Colors
CVD Momentum State
Bright colors = CVD increasing in the direction of its current bias
Muted colors = CVD losing momentum or stalling
This allows quick visual identification of strengthening vs weakening participation.
Conflict Alerts (No Symbol by Default)
Delta vs CVD Disagreement
These conditions trigger alerts (but no fixed chart icon):
Strong buying while CVD remains negative
Strong selling while CVD remains positive
Conflicts often signal absorption, trap conditions, or short-term exhaustion.
Important Usage Notes
All symbols are informational, not trade entries.
Signals are calculated from price-based volume distribution, not true bid/ask data.
Results depend on the quality of volume data provided by the exchange and TradingView.
4MA / 4MA[1] Forward Projection with 4 SD Forecast Bands4MA / 4MA Projection + 4 SD Bands + Cross Table is a forward-projection tool built around a simple moving average pair: the 4-period SMA (MA4) and its 1-bar lagged value (MA4 ). It takes a prior MA behavior pattern, projects that structure forward, and wraps the projected mean path with four Standard Deviation (SD) bands to visualize probable future price ranges.
This indicator is designed to help you anticipate:
Where the MA structure is likely to travel next
How wide the “expected” future price corridor may be
Where a future MA4 vs MA4 crossover is most likely to occur
When the real (live) crossover actually prints on the chart
What you see on the chart
1) Live moving averages (current market)
MA4 tracks the short-term mean of price.
MA4 is simply the previous bar’s MA4 value (a 1-bar lag).
Their relationship (MA4 above/below MA4 ) gives a clean, minimal read on trend alignment and directional bias.
2) Projected MA path (forward curve)
A forward “ghost” of the MA structure is drawn ahead of price. This projected curve represents the indicator’s best estimate of how the moving average structure may evolve if the market continues to rhyme with the selected historical behavior window.
3) 4 Standard Deviation bands (predictive future price ranges)
Surrounding the projected mean path are four SD envelopes. Think of these as forecast corridors:
Inner bands = tighter “expected” range
Outer bands = wider “stress / extreme” range
These bands are not a guarantee—rather, they’re a structured way to visualize “how far price can reasonably swing” around the projected mean based on observed volatility.
4) Vertical projection lines (most probable cross zone)
Within the projected region you’ll see vertical lines running through the bands. These lines mark the most probable zone where MA4 and MA4 are expected to cross in the projection.
In plain terms:
The projected MAs are two curves.
When those curves are forecasted to intersect, the script marks the intersection region with a vertical line.
This gives you a forward “timing window” for a potential MA shift.
5) Cross Table (top-right)
The table is your confirmation layer. It reports:
Current MA4 value
Current MA4 value
Whether MA4 is above or below MA4
The most recent BUY / SELL cross event
When a real, live crossover happens on the actual chart:
It registers as BUY (MA4 crosses above MA4 )
Or SELL (MA4 crosses below MA4 )
…and the table updates immediately so you can confirm the event without guessing.
How to use it
Practical workflow
Use the projected SD bands as future range context
If price is projected to sit comfortably inside inner bands, the market is behaving “normally.”
If price reaches outer bands, you’re in a higher-volatility / stretched scenario.
Use vertical lines as a “watch zone”
Vertical lines do not force a trade.
They act like a forward “heads-up”: this is the most likely window for an MA crossover to occur if the projection holds.
Use the table for confirmation
When the crossover happens for real, the table is your confirmation signal.
Combine it with structure (support/resistance, trendlines, market context) rather than trading it in isolation.
Notes and best practices
This is a projection tool: it helps visualize a structured forward hypothesis, not a certainty.
SD bands are best used as forecast corridors (risk framing, range planning, and expectation management).
The table is the execution/confirmation layer: it tells you what the MAs are doing now.
Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure.
At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior.
The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred.
🔹 Features
🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis)
HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter:
- H > Trend Start threshold suggests trend persistence and directional continuation.
- H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value.
Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias.
This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility.
🔸 Dual Channel Engine (Fast vs Slow Models)
Instead of relying on one fixed channel, HOAC computes two independent channel candidates:
Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments.
Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow.
Each model produces:
- A midline (basis)
- Outer bands (wider deviation)
- Inner bands (tighter deviation)
This structure gives you a clear core zone and an outer envelope that better represents volatility expansion.
🔸 Rolling Optimization Memory (Model Selection by Error)
HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error.
This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?”
Additionally:
If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most.
🔸 Optional Output Smoothing (User-Selectable)
The final selected channel can be smoothed using your choice of:
- SMA
- EMA
- HMA
- RMA
This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine.
🔸 Premium Visualization Layer (Inner Core + Outer Fade)
HOAC uses a layered band design:
- Inner bands define the core equilibrium zone around the midline.
- Outer bands define an extended volatility envelope for extremes.
Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity.
🔸 Adaptive Bar Tinting Strength (Regime Intensity)
Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle.
🔸 Mean-Reversion Signal Layer
Mean-reversion signals are enabled when the environment is not classified as Trending:
- Buy when price crosses back above the lower outer band
- Sell when price crosses back below the upper outer band
This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default.
🔸 Minimalist Dashboard (HUD)
A compact table displays:
- Current regime classification
- Smoothed Hurst value
- Which model is currently preferred (Fast or Slow)
- Trend flow direction (based on midline slope)
🔹 Calculations
1) Robust Hurst Exponent (R/S Analysis)
The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent.
calc_robust_hurst(int length) =>
float r = math.log(close / close )
float returns = array.new_float(length)
for i = 0 to length - 1
array.set(returns, i, r )
float mean = array.avg(returns)
float cumDev = 0.0
float maxCD = -1.0e10
float minCD = 1.0e10
float sumSqDiff = 0.0
for i = 0 to length - 1
float val = array.get(returns, i)
sumSqDiff += math.pow(val - mean, 2)
cumDev += (val - mean)
if cumDev > maxCD
maxCD := cumDev
if cumDev < minCD
minCD := cumDev
float R = maxCD - minCD
float S = math.sqrt(sumSqDiff / length)
float RS = (S == 0) ? 0.0 : (R / S)
float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5
hurst
This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure.
2) Hurst Smoothing
Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions.
float rawHurst = calc_robust_hurst(i_hurstLen)
float hVal = ta.ema(rawHurst, i_smoothHurst)
This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display.
3) Regime Classification
The smoothed Hurst reading is compared to user thresholds to label the environment.
string regime = "NEUTRAL"
if hVal > i_trendZone
regime := "TRENDING"
else if hVal < i_chopZone
regime := "MEAN REV"
Higher Hurst implies more persistence, so the indicator treats it as a trend environment.
Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation.
4) Dual Channel Models (Fast and Slow)
HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers.
Fast model (more reactive):
float fastBasis = ta.wma(close, 20)
float fastDev = ta.stdev(close, 20)
ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis))
Slow model (more stable):
float slowBasis = ta.wma(close, 50)
float slowDev = ta.stdev(close, 50)
ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis))
Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)).
5) Rolling Error Memory and Model Preference
To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals.
var float errFast = array.new_float()
var float errSlow = array.new_float()
update_error(float errArr, float error, int maxLen) =>
errArr.unshift(error)
if errArr.size() > maxLen
errArr.pop()
Each bar updates both error histories and computes which model has lower recent accumulated error.
update_error(errFast, fastM.error, i_optLookback)
update_error(errSlow, slowM.error, i_optLookback)
bool preferFast = errFast.sum() < errSlow.sum()
This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars.
6) Winner Selection Logic (Regime-Aware Hybrid)
The final model selection uses both regime and rolling error performance.
ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM)
rawMid := winner.mid
rawUp := winner.upper
rawDn := winner.lower
rawUpInner := winner.upper_inner
rawDnInner := winner.lower_inner
In Mean Reversion, the script forces the fast model to ensure responsiveness.
Otherwise, it selects the lowest-error model between fast and slow.
7) Optional Output Smoothing
After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type.
smooth(float src, string type, int len) =>
switch type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"HMA" => ta.hma(src, len)
"RMA" => ta.rma(src, len)
=> src
float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid
float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp
float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn
float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner
float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner
This preserves decision integrity since smoothing happens after model selection, not before.
8) Dynamic Visual Intensity From Hurst
Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints.
int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))
VWAP + RVOL (Merged):
📊 VWAP + RVOL (Merged)
VWAP + RVOL (Merged) is a professional intraday trading indicator that combines:
Session VWAP to define institutional direction and fair value
True Intraday Relative Volume (RVOL) to measure real-time volume strength compared to the same minute over previous days
The script is specifically designed for U.S. equities and performs best in:
Premarket momentum
Opening Range Breakout (ORB)
VWAP pullbacks
Scalping & day trading
🔍 What does this indicator provide?
1️⃣ True Intraday RVOL
Calculates minute-accurate relative volume, comparing current volume to the same minute across a user-defined number of prior days
Correctly handles sessions crossing midnight (after-hours & premarket)
Displays RVOL in a separate pane for clean, noise-free analysis
Default RVOL reference levels:
0.5 → Weak volume
1.0 → Normal volume
1.5 → Strong volume
2.0 → Unusual / institutional activity
2️⃣ Session VWAP
True session-based VWAP
Identifies institutional fair value
Acts as a primary directional filter:
Above VWAP → Bullish bias
Below VWAP → Bearish bias
✅ Practical Trading Use
Long Setup:
Price above VWAP
RVOL ≥ 1.5
Light pullback or VWAP retest
Confirmation candle with increasing volume
Avoid trades when:
Price below VWAP
RVOL < 1.0
⚙️ Settings
RVOL Lookback Days – Number of days used for RVOL comparison (default: 5)
RVOL Reference Lines – Toggle RVOL levels on/off
VWAP Source – Price source for VWAP calculation
Hide VWAP on 1D+ – Optional VWAP hiding on higher timeframes
📌 Important Notes
Designed for intraday timeframes only (≥ 1 minute and < 1 day)
Requires volume data from the data provider
Not intended for daily or higher timeframes
🎯 Who is this indicator for?
Momentum traders
Day traders & scalpers
ORB and VWAP pullback strategies
Traders seeking volume confirmation before entry
⚠️ Disclaimer
This indicator is a decision-support tool, not a trading recommendation.
Always apply proper risk management.
Participation-Weighted Orderflow Bubbles (HTF / LTF Context ToolThis indicator visualizes participation-weighted market pressure by aggregating lower-timeframe price and volume data into higher-timeframe context bubbles. It is designed to help identify directional dominance, balance, and absorption across timeframes. This is a context and bias tool, not a trade signal generator.
What the indicator shows
Each bubble represents a single chart bar, built from lower-timeframe candles.
Total Notional
Aggregated volume multiplied by price from lower-timeframe candles.
Buy / Sell Proxies
Lower-timeframe candles are classified based on where they close within their range:
– Close near the high → buy-side proxy
– Close near the low → sell-side proxy
– Middle of the range → neutral
Delta (USD and %)
Buy proxy notional minus sell proxy notional, expressed as both absolute USD delta and percentage of total notional.
Bubble colors
Green
Buy-side participation dominance.
Sell color (user configurable)
Sell-side participation dominance. The default is chosen for visibility on bearish candles and can be changed in settings.
Grey
Balanced participation. Indicates two-way trade, consolidation, or auction.
Yellow (Absorption)
High notional with limited price movement, suggesting potential absorption or distribution.
Coloring uses both relative dominance (delta percentage) and absolute dominance (minimum delta in USD), which improves behavior on higher timeframes.
Bubble size and visuals
Bubble size scales with total notional.
HD glow layers adapt automatically by timeframe.
Bubbles are drawn in front of candles for clarity.
Optional text displays delta and total notional.
Hovering over a bubble shows detailed information including total notional, buy/sell/neutral proxies, delta values, absorption status, and the number of lower-timeframe candles used.
Timeframe behavior
The indicator is designed to work across multiple timeframes. On higher timeframes, more grey bubbles are expected due to natural auction and balance behavior. Colored bubbles on higher timeframes represent sustained participation rather than short-term momentum. Visual density and performance are automatically adjusted on higher timeframes.
How to use it
Recommended workflow:
1. Higher timeframe (1H, 4H, Daily)
Use the bubbles to identify dominant buy or sell participation, balance zones, and absorption near highs or lows.
2. Lower timeframe (5m, 15m)
Take trades in alignment with the most recent higher-timeframe dominance. Be cautious or range-focused inside higher-timeframe balance zones. Use structure and price action for entries.
What this indicator is not
This indicator does not show true bid/ask data.
It does not display actual market versus limit orders.
It does not replace a DOM or exchange orderflow feed.
It should not be used as a standalone entry signal.
The indicator works within TradingView’s available data and provides a probabilistic, participation-weighted view of market pressure rather than true tape or orderflow data.
Best practices
Use a 1-minute lower timeframe for best results.
Avoid setting the lower timeframe too high relative to the chart timeframe.
Combine this tool with structure, levels, and session context.
Treat grey bubbles as information about balance, not as noise.
This tool is intended for traders who want better context and bias, not more signals.
Anurag -Precision Options Scalper [Multi-TF] -A professional-grade options day trading system built for SPY, QQQ, and SPX.
CORE FEATURES:
- Multi-timeframe analysis (15m regime → 5m setup → 1m execution)
- Market regime detection using ADX + ATR Z-Score (filters out chop)
- Confidence scoring system (0-100) — only takes high-probability setups
- Auto DTE engine recommends 0DTE vs 1DTE based on conditions
- Suggested strike prices (slightly OTM)
- Built-in position tracking with stop/target levels
- Session filtering (9:30 AM - 4:00 PM ET only)
- End-of-day forced exit warning
SIGNAL LOGIC:
CALL: 15m bullish bias + trending regime + price above VWAP/EMAs + pullback to support + bullish candle + 1m momentum confirmation
PUT: 15m bearish bias + trending regime + price below VWAP/EMAs + rejection from resistance + bearish candle + 1m momentum confirmation
RISK MANAGEMENT:
- ATR-based stops and targets
- Break-even stop movement after partial profit
- Time-based exit if momentum dies
- Max 4 trades per day (configurable)
- Gamma scalp mode for 0DTE (tighter stops/targets)
BEST ON: 5-minute chart | SPY, QQQ, SPX
STYLE: Pullback entries in trending markets
⚠️ For educational purposes. Not financial advice. Manage your own risk.
ICT Liquidity Sweep/Swing Fail Pattern V.1# ICT Liquidity Sweep/Swing Fail Pattern V.1
## Indicator Description & User Guide
---
## 📊 Indicator Overview
**Name:** ICT Liquidity Sweep/Swing Fail Pattern V.1
**Type:** Support/Resistance & Liquidity Detection
**Trading Style:** ICT Concepts (Inner Circle Trader)
**Best Timeframes:** 1M, 5M, 15M, 1H
---
## 🎯 Core Features
### 1. **Support & Resistance Lines**
- Automatically draws key swing high and swing low levels
- Based on significant pivot points in price structure
- Updates dynamically as new swings form
### 2. **"X" Mark - Liquidity Sweep**
- **Symbol:** X marker on chart
- **Meaning:** Indicates a liquidity sweep (stop hunt)
- **What it shows:** Price briefly moved beyond a key level to trigger stops, then reversed
- **Trading significance:** High-probability reversal zones after liquidity is taken
### 3. **"SFP" Label - Swing Failure Pattern**
- **Symbol:** SFP text label
- **Meaning:** Swing Failure Pattern detected
- **What it shows:** Price attempted to make a new high/low but failed and reversed sharply
- **Trading significance:** Strong reversal signal - smart money rejecting the level
---
## 📈 How to Use This Indicator
### Entry Setup Strategy:
#### **For SHORT Trades (Sell):**
1. Wait for **SFP** to appear at a swing high
2. Look for **X marker** confirming liquidity sweep above the high
3. **Entry Zone (Red Box):** Enter SHORT positions when price returns to this zone
4. **Stop Loss:** Place above the red zone (above the swept high)
5. **Take Profit (Green Box):** Target the green zone below
#### **For LONG Trades (Buy):**
1. Wait for **SFP** to appear at a swing low
2. Look for **X marker** confirming liquidity sweep below the low
3. **Entry Zone (Green Box):** Enter LONG positions when price returns to this zone
4. **Stop Loss:** Place below the green zone (below the swept low)
5. **Take Profit (Red Box):** Target the red zone above
---
## 🎨 Color Coding System
| Color | Zone Type | Usage |
|-------|-----------|-------|
| 🔴 **Red Box** | Stop Loss / Supply Zone | Place SL here for LONG trades / Entry zone for SHORT trades |
| 🟢 **Green Box** | Take Profit / Demand Zone | Target zone for LONG trades / Place SL here for SHORT trades |
| ❌ **X Mark** | Liquidity Sweep Point | Stop hunt occurred - reversal likely |
| 📝 **SFP Label** | Swing Failure Pattern | Failed breakout - strong reversal signal |
---
## 💡 Trading Examples
### Example 1: SHORT Trade (As shown in your chart)
```
1. SFP appears at swing high (Red zone around 4,000)
2. X marker confirms liquidity sweep above the high
3. Entry: SHORT when price re-enters red zone
4. Stop Loss: Above red zone (e.g., 4,002)
5. Take Profit: Green zone below (3,964-3,972)
6. Risk:Reward = 1:3+
```
### Example 2: LONG Trade
```
1. SFP appears at swing low (Green zone)
2. X marker confirms liquidity sweep below the low
3. Entry: LONG when price re-enters green zone
4. Stop Loss: Below green zone
5. Take Profit: Previous red zone above
6. Risk:Reward = 1:2 minimum
```
---
## ⚠️ Important Trading Rules
### ✅ DO:
- Wait for BOTH SFP and X marker confirmation
- Enter on price returning to the zone (not on first touch)
- Use proper position sizing (1-2% risk per trade)
- Combine with market structure analysis
- Look for confluences (orderblocks, fair value gaps)
### ❌ DON'T:
- Trade against the higher timeframe trend
- Enter without confirmation signals
- Ignore the colored zones for SL/TP placement
- Overtrade - wait for quality setups
- Move stop loss to breakeven too early
---
## 🔧 Indicator Settings (Typical)
**Adjustable Parameters:**
- Swing Length: Number of bars to identify swing points
- Show/Hide X markers
- Show/Hide SFP labels
- Zone opacity and colors
- Line thickness
---
## 📚 ICT Concepts Explained
### **Liquidity Sweep:**
Smart money intentionally pushes price beyond key levels to trigger retail stop losses, then reverses to their intended direction. The X marker identifies these moments.
### **Swing Failure Pattern (SFP):**
Price attempts to make a new high/low but lacks follow-through, indicating weak momentum and likely reversal. Similar to a "false breakout" but more specific to swing structures.
### **Supply & Demand Zones:**
- **Red zones** = Areas where selling pressure overwhelmed buyers
- **Green zones** = Areas where buying pressure overwhelmed sellers
- These zones act as magnets for price to return and react
---
## 🎓 Best Practices
1. **Confluence is Key:**
- Combine with daily/weekly bias
- Check for orderblocks nearby
- Look for imbalances (FVG)
2. **Session Timing:**
- Best during London/New York sessions
- Avoid low liquidity periods
3. **Risk Management:**
- Never risk more than 1-2% per trade
- Use proper lot sizing
- Take partial profits at key levels
4. **Timeframe Correlation:**
- Check higher timeframe for bias
- Enter on lower timeframe for precision
- Exit based on higher timeframe targets
---
## 📞 Support & Updates
**Version:** 1.0
**Compatibility:** TradingView Pine Script v5
**Updates:** Regular improvements based on ICT methodology
---
## ⚡ Quick Reference Card
| Signal | Action | SL Placement | TP Target |
|--------|--------|--------------|-----------|
| SFP + X at High | SHORT at Red Zone | Above Red | Green Zone |
| SFP + X at Low | LONG at Green Zone | Below Green | Red Zone |
**Remember:** The indicator shows you WHERE to trade, but YOU decide WHEN based on confirmation and market context.
---
*Disclaimer: This indicator is a tool for technical analysis. Always use proper risk management and never trade with money you cannot afford to lose.*
SMC Strategy Tool v1.0 - Institutional SuiteDescription: The SMC Strategy Tool v1.0 is a comprehensive technical analysis suite designed for traders following the Smart Money Concepts (SMC) methodology. It combines market structure, institutional liquidity zones, and mathematical pivots to provide a high-probability trading environment.
Key Features:
Automatic Market Structure: Real-time detection of CHoCH (Change of Character) and BOS (Break of Structure) based on price action confirmation.
Institutional Order Flow (FVG): Identifies Fair Value Gaps with a dynamic mitigation system (boxes disappear once the price fills the inefficiency).
Premium & Discount Zones: Automatically calculates the current trading range and highlights the "cheap" (Discount) and "expensive" (Premium) areas for optimal entry.
Daily Pivot Points: Seamless integration of Daily Pivots (P, R1-R3, S1-S3) for institutional confluence.
Live Analytics Dashboard: A clean, non-intrusive table monitoring Market Phase, RSI (Momentum), and ATR (Volatility).
Smart Alerts: Built-in logic for "Discount Entry" during Bullish trends and "Premium Entry" during Bearish trends.
How to Trade:
Identify the Trend: Look at the Dashboard for the current Market Phase (Bullish/Bearish).
Wait for Value: Do not chase the price. Wait for the price to return to the Discount Zone (for Longs) or Premium Zone (for Shorts).
Find Confluence: The highest probability trades occur when a Discount/Premium entry aligns with an FVG and a Daily Pivot level.
Confirmation: Check the RSI cell. If it's red/green, the move might be exhausted; wait for a neutral reading or a structural reaction.
Available Alerts:
Trend Shift (CHoCH): Get notified immediately when the market structure shifts (e.g., from Bearish to Bullish).
Trend Continuation (BOS): Signals when the current trend is confirmed by a new structural break.
Discount Zone Entry (Long Bias): Notifies you when the price enters the Discount Zone while the Market Phase is Bullish. This prevents FOMO buying at high prices.
Premium Zone Entry (Short Bias): Notifies you when the price enters the Premium Zone while the Market Phase is Bearish. This ensures you are selling at institutional "expensive" prices.
How to set up Alerts:
Click the Alerts icon in the right sidebar.
Under Condition, select: SMC Strategy Tool v1.0 - Institutional Suite.
Select "Any alert() function call" (or Qualsiasi chiamata alla funzione alert()).
Choose your preferred notification method (Popup, Email, or App notification).
The alert message will automatically include the Ticker, Timeframe, and the specific action to take!
