ICT Setup 02 [TradingFinder] Breaker Blocks + Reversal Candles🔵 Introduction
The "Breaker Block" concept, widely utilized in ICT (Inner Circle Trader) technical analysis, is a crucial tool for identifying reversal points and significant market shifts. Originating from the "Order Block" concept, Breaker Blocks help traders pinpoint support and resistance levels. These blocks are essential for understanding market trends and recognizing optimal entry and exit points.
A Breaker Block is essentially a failed Order Block that changes its role when price action breaks through it. When an Order Block fails to hold as a support or resistance level, it reverses its function, becoming a Breaker Block.
There are two primary types : Bullish Breaker Blocks and Bearish Breaker Blocks. These Breaker Blocks align with the prevailing market trend and indicate potential entry points after a liquidity sweep or a shift in market structure.
Understanding and applying the Breaker Block strategy enables traders to capitalize on the behavior of institutional investors, enhancing their trading outcomes.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The ICT Setup 02 indicator designed to automate the identification of Bullish and Bearish Breaker Blocks. This tool enables traders to easily spot these blocks on a chart and utilize them for entering or exiting trades. Below is a breakdown of how to use this indicator in both bullish and bearish setups.
🟣 Bullish Breaker Block Setup
A Bullish Breaker Block setup is identified in an uptrend, where it serves as a potential entry point. This setup occurs when a Bearish Order Block fails and the price moves above the high of that Order Block. In this scenario, the previously bearish Order Block turns into a Bullish Breaker Block, which now acts as a support level for the price.
To trade a Bullish Breaker Block, wait for the price to retest this newly formed support level. Confirmation of the uptrend can be achieved by analyzing lower time frames for further market structure shifts or other bullish indicators.
A successful retest of the Bullish Breaker Block provides a high-probability entry point for a long trade, as it signals institutional support. Traders often place their stop-loss below the low of the Breaker Block zone to minimize risk.
🟣 Bearish Breaker Block Setup
A Bearish Breaker Block setup, conversely, is used in a downtrend to identify potential sell opportunities. This setup forms when a Bullish Order Block fails, and the price moves below the low of that Order Block.
Once this Order Block is broken, it reverses its role and becomes a Bearish Breaker Block, providing resistance to the price as it pushes downward. For a Bearish Breaker Block trade, wait for the price to retest this resistance level.
A confirmation of the downtrend, such as a market structure shift on a lower time frame or additional bearish signals, strengthens the setup. The Bearish Breaker Block retest provides an opportunity to enter a short position, with a stop-loss placed just above the high of the Breaker Block zone.
🔵 Settings
Pivot Period : This setting controls the look-back period used to identify pivot points that contribute to the detection of Order Blocks. A higher period captures longer-term pivots, while a lower period focuses on more recent price action. Adjusting this parameter allows traders to fine-tune the indicator to match their trading time frame.
Breaker Block Validity Period : This setting defines how long a Breaker Block remains valid based on the number of bars elapsed since its formation. Increasing the validity period keeps Breaker Blocks active for a longer duration, which can be useful for higher time frame analysis.
Mitigation Level BB : This option lets traders choose the level of the Order Block at which the price is expected to react. Options like "Proximal," "50% OB," and "Distal" adjust the zone where a reaction may occur, offering flexibility in setting up the entry and stop-loss levels.
Breaker Block Refinement : The refinement option refines the Breaker Block zone to display a more precise range for aggressive or defensive trading approaches. The "Aggressive" mode provides a tighter range for risk-tolerant traders, while the "Defensive" mode expands the zone for those with a more conservative approach.
🔵 Conclusion
The Breaker Block indicator provides traders with a sophisticated tool for identifying key reversal zones in the market. By leveraging Breaker Blocks, traders can gain insights into institutional order flow and predict critical support and resistance levels.
Using Breaker Blocks in conjunction with other ICT concepts, like Fair Value Gaps or liquidity sweeps, enhances the reliability of trading signals. This indicator empowers traders to make informed decisions, aligning their trades with institutional moves in the market.
As with any trading strategy, it is crucial to incorporate proper risk management, using stop-losses and position sizing to minimize potential losses. The Breaker Block strategy, when applied with discipline and thorough analysis, serves as a powerful addition to any trader’s toolkit.
Cerca negli script per "stop loss"
Dynamic RSI Mean Reversion StrategyDynamic RSI Mean Reversion Strategy
Overview:
This strategy uses an RSI with ATR-Adjusted OB/OS levels in order to enhance the quality of it's mean reversion trades. It also incorporates a form of trend filtering in an effort to minimize downside and maximize upside. The backtest has fewer trades, as it uses substantial filtering to enhance trade quality. As you can see, I didn't cherry pick the results, so the results aren't the most beautiful thing you'll see in your life. I did this to ensure nobody gets misled. If you need a higher frequency of trades, consider removing the trend filter or increasing the length of the EMAs used for trend detection.
Features:
Dynamic OB/OS Levels: Uses ATR to adjust overbought and oversold thresholds dynamically, making the RSI more responsive in varying volatility conditions. This approach enhances signal strength by expanding the RSI range in high volatility and tightening it in low volatility.
Mean Reversion Focus: Designed for mean reversion but incorporates a trend-following filter to reduce countertrend trades. When the RSI is high, it often indicates an uptrend, so a trend filter prevents shorting in these cases and the same goes for downtrends and longing.
Trend Filtering: A moving average cross trend filter checks for the trend direction, with the RSI signal line color-coded to reflect trend shifts. Entries occur when the RSI crosses above or below the dynamic thresholds and is not a countertrend trade.
Stop Losses: Stop losses are set based on ATR distance from the entry price, providing volatility-adjusted protection.
Note:
If you're using this strategy on assets with a higher price, remember to increase the initial capital in the strategy settings. Otherwise, the strategy won't generate any (or many) trades and you'll end up with some inaccurate results.
Recommended Use:
Test it on different assets and timeframes. I’ve found the best results with standard RSI inputs, a relatively slow ATR, and a slower MA cross for trend filtering. Thus, the defaults are set that way. If the trend metrics are too slow, you’ll filter out too many good trades while allowing crummy ones; if too fast, most trades may be filtered out. As always, this has a lot of configurability so experiment to find the balance that works for your trading style.
Qty CalculatorThis Pine Script indicator, titled "Qty Calculator," is a customizable tool designed to assist traders in managing their trades by calculating key metrics related to risk management. It takes into account your total capital, entry price, stop-loss level, and desired risk percentage to provide a comprehensive overview of potential trade outcomes.
Key Features:
User Inputs:
Total Capital: The total amount of money available for trading.
Entry Price: The price at which the trader enters the trade.
Stop Loss: The price level at which the trade will automatically close to prevent further losses.
Risk Percentage: The percentage of the total capital that the trader is willing to risk on a single trade.
Customizable Table:
Position: The indicator allows you to choose the position of the table on the chart, with options including top-left, top-center, top-right, bottom-left, bottom-center, and bottom-right.
Size: You can adjust the number of rows and columns in the table to fit your needs.
Risk Management Calculations:
Difference Calculation: The difference between the entry price and the stop-loss level.
Risk Per Trade: Calculated as a percentage of your total capital.
Risk Levels: The indicator evaluates multiple risk levels (0.10%, 0.25%, 0.50%, 1.00%) and calculates the quantity, capital per trade, percentage of total capital, and the risk amount associated with each level.
R-Multiples Calculation:
The indicator calculates potential profit levels at 2x, 3x, 4x, and 5x the risk (R-Multiples), showing the potential gains if the trade moves in your favor by these multiples.
Table Display:
The table includes the following columns:
CapRisk%: Displays the risk percentage.
Qty: The quantity of the asset you should trade.
Cap/Trade: The capital allocated per trade.
%OfCapital: The percentage of total capital used in the trade.
Risk Amount: The monetary risk taken on each trade.
R Gains: Displays potential gains at different R-Multiples.
This indicator is particularly useful for traders who prioritize risk management and want to ensure that their trades are aligned with their capital and risk tolerance. By providing a clear and customizable table of critical metrics, it helps traders make informed decisions and better manage their trading strategies.
Monthly Day Long Strategy with VIX and Risk ManagementThis trading strategy is designed to open long positions on a specific day of the month, with the conditions for entry and exit based on the VIX index and additional risk management techniques. The strategy includes stop-loss and take-profit features to manage risk and lock in profits.
Inputs:
Entry Day of the Month (entry_day): Specifies which day of the month to consider for initiating a trade. The default value is the 27th.
Hold Duration (Days) (hold_duration_days): Defines how many days to hold the position after opening. The default value is 4 days.
VIX Threshold (vix_threshold): Sets the maximum acceptable value for the VIX index to consider an entry. If the VIX is below this threshold, it signals a potential trade. The default value is 20.0.
Stop Loss (%) (stop_loss_percentage): Determines the percentage below the entry price where the stop-loss will be triggered. The default value is 2.0%.
Take Profit (%) (take_profit_percentage): Sets the percentage above the entry price where the take-profit will be triggered. The default value is 5.0%.
Functions:
next_weekday(date): Adjusts the entry date to the next Monday if it falls on a weekend (Saturday or Sunday). This ensures trades do not occur on non-trading days.
Logic:
Entry Conditions:
Date Check: Opens a long position if the current date matches the adjusted entry date (the 27th or the next Monday if the 27th falls on a weekend).
VIX Filter: The VIX index value must be below the specified threshold (e.g., 20.0) to consider an entry.
Exit Conditions:
Time-Based Exit: Closes the position after the hold duration of 4 days.
Stop-Loss: Automatically closes the position if the price drops to a level that is a specified percentage below the entry price (e.g., 2.0%).
Take-Profit: Closes the position if the price rises to a level that is a specified percentage above the entry price (e.g., 5.0%).
Plots:
VIX Plot: Displays the VIX index on the chart for visual reference.
VIX Threshold Line: A horizontal line representing the VIX threshold value.
Summary:
The strategy aims to take advantage of specific entry days while filtering trades based on VIX levels to ensure market conditions are favorable. Risk management is enhanced through stop-loss and take-profit settings, which help in controlling potential losses and securing profits. The strategy ensures trades are only made on trading days and not on weekends, adjusting automatically to the next Monday if needed.
ChatGPT kann Fehler machen. Überprüfe wichtige Informationen.
Supertrend (Buy/Sell) With TP & SLSupertrend (Buy/Sell) with TP & SL: An Enhanced Trading Tool
This Pine Script indicator combines the popular Supertrend indicator with multiple take-profit (TP) and stop-loss (SL) levels, providing traders with a comprehensive visual aid for potential entries, exits, and risk management.
Originality
Buffer Zones for Precision: Instead of relying solely on the Supertrend line, this script incorporates buffer zones around it. This helps filter out false signals, especially in volatile markets, leading to more accurate buy/sell signals.
Flexible Stop-Loss: Offers the choice between a fixed or trailing stop-loss, allowing traders to tailor their risk management approach based on their preferences and market conditions.
Multiple Take-Profit Levels: Provides three potential take-profit levels, giving traders the flexibility to secure profits at different stages of a trend.
Heikin Ashi Candles & VWAP: Incorporates Heikin Ashi candles for smoother trend visualization and adds a VWAP line for potential support/resistance levels.
Clear Table Display: Presents key information like Stop Loss and Take Profit levels in a user-friendly table, making it easier to track trade targets.
How It Works
Supertrend Calculation: The Supertrend is calculated using ATR (Average True Range) to gauge market volatility. The script then creates buffer zones around the Supertrend line for refined signal generation.
Buy/Sell Signals:
Buy: When the close price crosses above the upper buffer zone, indicating a potential uptrend.
Sell: When the close price crosses below the lower buffer zone, suggesting a potential downtrend.
Take Profit & Stop Loss:
Take Profits: Three TP levels are calculated based on ATR and a customizable profit factor.
Stop Loss: The stop-loss can be set as either a fixed value based on ATR or as a trailing stop-loss that dynamically adjusts to lock in profits.
How To Use
Add the Indicator: Search for "Supertrend (Buy/Sell) With TP & SL" in the TradingView indicators list and add it to your chart.
Customize Inputs: Adjust parameters like ATR Period, Factor, Take Profit Factor, Stop Loss Factor, Stop Loss Type, etc., based on your trading style and preferences.
Interpret Signals: Look for buy signals when the price crosses above the upper buffer and sell signals when it crosses below the lower buffer.
Manage Risk: Use the plotted Take Profit and Stop Loss levels to manage your risk and potential rewards.
Concepts
Supertrend: A trend-following indicator that helps identify the direction of the prevailing trend.
ATR (Average True Range): A measure of market volatility.
Buffer Zones: Used to filter out false signals by creating a zone around the Supertrend line.
Trailing Stop Loss: A dynamic stop-loss that moves with the price to protect profits.
Heikin Ashi: A type of candlestick chart designed to filter out market noise and make trends easier to identify.
VWAP (Volume Weighted Average Price): An indicator that shows the average price at which a security has traded throughout the day, based on both volume and price.
Important Note: This script is for educational and informational purposes only. Backtest thoroughly and use with caution in live trading. Always manage your risk appropriately.
Sniper Entry using RSI confirmationThis is a sniper entry indicator that provides Buy and Sell signals using other Indicators to give the best possible Entries (note: Entries will not be 100 percent accurate and analysis should be done to support an entry)
Moving Average Crossovers:
The indicator uses two moving averages: a short-term SMA (Simple Moving Average) and a long-term SMA.
When the short-term SMA crosses above the long-term SMA, it generates a buy signal (indicating potential upward momentum).
When the short-term SMA crosses below the long-term SMA, it generates a sell signal (indicating potential downward momentum).
RSI Confirmation:
The indicator incorporates RSI (Relative Strength Index) to confirm the buy and sell signals generated by the moving average crossovers.
RSI is used to gauge the overbought and oversold conditions of the market.
A buy signal is confirmed if RSI is below a specified overbought level, indicating potential buying opportunity.
A sell signal is confirmed if RSI is above a specified oversold level, indicating potential selling opportunity.
Dynamic Take Profit and Stop Loss:
The indicator calculates dynamic take profit and stop loss levels based on the Average True Range (ATR).
ATR is used to gauge market volatility, and the take profit and stop loss levels are adjusted accordingly.
This feature helps traders to manage their risk effectively by setting appropriate profit targets and stop loss levels.
Combining the information provided by these, the indicator will provide an entry point with a provided take profit and stop loss. The indicator can be applied to different asset classes. Risk management must be applied when using this indicator as it is not 100% guaranteed to be profitable.
Goodluck!
BBSR Extreme Strategy [nachodog]The Bollinger Bands Stochastic RSI Extreme Strategy is a comprehensive trading approach designed for use on the TradingView platform, employing a combination of Bollinger Bands and the Stochastic RSI to identify potential entry and exit points in the market. This strategy is converted into Pine Script version 5 and is specifically tailored as a strategy rather than a mere study, allowing traders to simulate and backtest their trades within the TradingView environment.
Strategy Overview:
Bollinger Bands serve as the primary tool for volatility and price level analysis. By calculating the standard deviation of price movements around a simple moving average (SMA), this strategy identifies the upper and lower bounds of price fluctuations, helping traders spot potential reversal points.
Stochastic RSI is used to gauge the momentum by comparing the closing price's position relative to its price range over a certain period. This indicator helps in determining overbought or oversold conditions, providing insights into potential bullish or bearish momentum.
Entry Signals:
Bullish Entry: The strategy signals a long entry when the price moves from below to above the lower Bollinger Band, coupled with a Stochastic RSI indicating an exit from oversold conditions. This suggests an uptrend initiation, prompting a buy order.
Bearish Entry: Conversely, a short entry is signaled when the price drops from above to below the upper Bollinger Band while the Stochastic RSI moves from overbought territory. This condition indicates a potential downtrend, triggering a sell order.
Exit Criteria:
Stop Loss: A key feature of this strategy is the inclusion of a user-defined stop loss percentage, which helps manage risk by specifying the maximum allowable loss per trade.
Bearish Exit for Long Positions: Long positions are exited either when a bearish signal is detected or when the price crosses below the lower Bollinger Band, suggesting a reversal or weakening of the bullish trend.
Bullish Exit for Short Positions: Short positions are closed upon a bullish signal or when the price crosses above the upper Bollinger Band, indicating a potential reversal or diminishing bearish momentum.
Strategy Benefits:
The strategy provides a structured framework for entering and exiting trades, leveraging the strengths of both Bollinger Bands and Stochastic RSI.
It includes parameters for customization, such as the stop loss percentage, allowing traders to align the strategy with their risk tolerance and trading objectives.
The ability to backtest and simulate trades on TradingView enhances its utility, offering insights into the strategy's performance under historical market conditions.
Overall, the Bollinger Bands Stochastic RSI Extreme Strategy is designed for traders who seek to capitalize on trend reversals and momentum shifts, with built-in risk management features to safeguard against significant losses.
Orion:SagittaSagitta
Sagitta is an indicator the works to assist in the validation of potential long entries and to place stop-loss orders. Sagitta is not a "golden indicator" but more of a confirmation indicator of what prices might be suggesting.
The concept is that while stocks can turn in one bar, it usually takes two bars or more to signal a turn. So, using a measurement of two bars help determine the potential turning of prices.
Behind the scenes, Sagitta is nothing more than a 2 period stochastic which has had its values divided into five specific zones.
Dividing the range of the two bars in five sections, the High is equal to 100 and the Low is equal to 0.
The zones are:
20 = bearish (red) – This is when the close is the lower 20% of the two bars
40 = bearish (orange) – This is when the close is between the lower 20% and 40% of the two bars.
60 = neutral (yellow) – This is when the close is between the middle 40% - 60% of the two bars.
80 = bullish (blue) – This is when the close is between the upper 60% - 80% of the two bars.
100 = bullish (green) – This is when the close is above the upper 80% of the bar.
The general confirmation concept works as such:
When the following bar is of a higher value than the previous bar, there is potential for further upward price movement. Conversely when the following bar is lower than the previous bar, there is potential for further downward movement.
Going from a red bar to orange bar Might be an indication of a positive turn in direction of prices.
Going from a green bar to an orange bar would also be considered a negative directional turn of prices.
When the follow on bar decreases (ie, green to blue, blue to yellow, etc) placing a stop-loss would be prudent.
Maroon lines in the middle of a bar is an indication that prices are currently caught in consolidation.
Silver/Gray bars indicate that a high potential exists for a strong upward turn in prices exists.
Consolidation is calculated by determining if the close of one bar is between the high and low of another bar. This then establishes the range high and low. As long as closes continue with this range, the high and low of the range can expand. When the close is outside of the range, the consolidation is reset.
Signals in areas of consolidation (maroon center bar) should be looked upon as if the prices are going to challenge the high of the consolidation range and not necessarily break through.
The entry technique used is:
The greater of the following two calculations:
High of signal bar * 1.002 or High of signal bar + .03
The stop-loss technique used is:
The lesser of the following two calculations:
Low of signal bar * .998 or Low of signal bar - .03
IF an entry signal is generated and the price doesn’t reach the entry calculation. It is considered a failed entry and is not considered a negative or that you missed out on something. This has saved you from losing money since the prices are not ready to commit to the direction.
When placing a stop-loss, it is never suggested that you lower the value of a stop-loss. Always move your stop-losses higher in order to lock in profit in case of a negative turn.
Investments/swing trading strategy for different assetsStop worrying about catching the lowest price, it's almost impossible!: with this trend-following strategy and protection from bearish phases, you will know how to enter the market properly to obtain benefits in the long term.
Backtesting context: 1899-11-01 to 2023-02-16 of SPX by Tvc. Commissions: 0.05% for each entry, 0.05% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 5 indicators are used:
One Ema of 200 periods
Atr Stop loss indicator from Gatherio
Squeeze momentum indicator from LazyBear
Moving average convergence/divergence or Macd
Relative strength index or Rsi
Trade conditions:
There are three type of entries, one of them depends if we want to trade against a bearish trend or not.
---If we keep Against trend option deactivated, the rules for two type of entries are:---
First type of entry:
With the next rules, we will be able to entry in a pull back situation:
Squeeze momentum is under 0 line (red)
Close is above 200 Ema and close is higher than the past close
Histogram from macd is under 0 line and is higher than the past one
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
For closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Second type of entry:
With the next rules, we will not lose a possible bullish movement:
Close is above 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entry, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
---If we keep Against trend option activated, the rules are the same as the ones above, but with one more type of entry. This is more useful in weekly timeframes, but could also be used in daily time frame:---
Third type of entry:
Close is under 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entries, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Risk management
For calculating the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a buy signal at price of 4,000 usd. The stop loss price from atr stop loss is 3,900. You calculate the distance in percent between 4,000 and 3,900. In this case, that distance would be of 2.50%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(2,5%) = 1000usd. It means, you have to use 1000 usd for risking 2.5% of your account.
We will use this risk management for applying compound interest.
In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, etc.
You will find the settings for risk management at the end of the script if you want to change something. But rebember, do not change values from indicators, the idea is to not over optimize the strategy.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
If you activate break even using rsi, when rsi crosses under overbought zone break even will be activated. This can work in some assets.
---Important: In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital---
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!
Some assets and timeframes where the strategy has also worked:
BTCUSD : 4H, 1D, W
SPX (US500) : 4H, 1D, W
GOLD : 1D, W
SILVER : 1D, W
ETHUSD : 4H, 1D
DXY : 1D
AAPL : 4H, 1D, W
AMZN : 4H, 1D, W
META : 4H, 1D, W
(and others stocks)
BANKNIFTY : 4H, 1D, W
DAX : 1D, W
RUT : 1D, W
HSI : 1D, W
NI225 : 1D, W
USDCOP : 1D, W
Harmonic Pattern Detection, Prediction, and Backtesting ToolOverview:
The ultimate harmonic XABCD pattern identification, prediction, and backtesting system.
Harmonic patterns are among the most accurate of trading signals, yet they're widely underutilized because they can be difficult to spot and tedious to validate. If you've ever come across a pattern and struggled with questions like "are these retracement ratios close enough to the harmonic ratios?" or "what are the Potential Reversal levels and are they confluent with point D?", then this tool is your new best friend. Or, if you've never traded harmonic patterns before, maybe it's time to start. Put away your drawing tools and calculators, relax, and let this indicator do the heavy lifting for you.
- Identification -
An exhaustive search across multiple pivot lengths ensures that even the sneakiest harmonic patterns are identified. Each pattern is evaluated and assigned a score, making it easy to differentiate weak patterns from strong ones. Tooltips under the pattern labels show a detailed breakdown of the pattern's score and retracement ratios (see the Scoring section below for details).
- Prediction -
After a pattern is identified, paths to potential targets are drawn, and Potential Reversal Zone (PRZ) levels are plotted based on the retracement ratios of the harmonic pattern. Targets are customizable by pattern type (e.g. you can specify one set of targets for a Gartley and another for a Bat, etc).
- Backtesting -
A table shows the results of all the patterns found in the chart. Change your target, stop-loss, and % error inputs and observe how it affects your success rate.
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// Scoring
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A percentage-based score is calculated from four components:
(1) Retracement % Accuracy - this measures how closely the pattern's retracement ratios match the theoretical values (fibs) defined for a given harmonic pattern. You can change the "Allowed fib ratio error %" in Settings to be more or less inclusive.
(2) PRZ Level Confluence - Potential Reversal Zone levels are projected from retracements of the XA and BC legs. The PRZ Level Confluence component measures the closeness of the closest XA and BC retracement levels, relative to the total height of the PRZ.
(3) Point D / PRZ Confluence - this measures the closeness of point D to either of the closest two PRZ levels (identified in the PRZ Level Confluence component above), relative to the total height of the PRZ. In theory, the closer together these levels are, the higher the probability of a reversal.
(4) Leg Length Symmetry - this measures the ΔX symmetry of each leg. You can change the "Allowed leg length asymmetry %" in settings to be more or less inclusive.
So, a score of 100% would mean that (1) all leg retracements match the theoretical fib ratios exactly (to 16 decimal places), (2) the closest XA and BC PRZ levels are exactly the same, (3) point D is exactly at the confluent PRZ level, and (4) all legs are exactly the same number of bars. While this is theoretically possible, you have better odds of getting struck by lightning twice on a sunny day.
Calculation weights of all four components can be changed in Settings.
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// Targets
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A hard-coded set of targets are available to choose from, and can be applied to each pattern type individually:
(1) .618 XA = .618 retracement of leg XA, measured from point D
(2) 1.272 XA = 1.272 retracement of leg XA, measured from point D
(3) 1.618 XA = 1.618 retracement of leg XA, measured from point D
(4) .618 CD = .618 retracement of leg CD, measured from point D
(5) 1.272 CD = 1.272 retracement of leg CD, measured from point D
(6) 1.618 CD = 1.618 retracement of leg CD, measured from point D
(7) A = point A
(8) B = point B
(9) C = point C
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// Stops
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Stop-loss levels are also user-defined, in one of three ways:
(1) % beyond the furthest PRZ level (below the PRZ level for bullish patterns, and above for bearish)
(2) % beyond point D
(3) % of distance to Target 1, beyond point D. This method allows for a proper Risk:Reward approach by defining your potential losses as a percentage of the potential gains. This is the default.
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// Results Table / Backtesting Statistics
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To properly assess the effectiveness of a specific pattern type, a time limit is enforced for a completed pattern to reach the targets or the stop level. When this time limit expires, the pattern has "timed out", and is no longer considered in the Success Rate statistics. During the time limit period, if price reaches Target 1 before reaching the Stop level, the pattern is considered successful. Conversely, if price reaches the Stop level before reaching Target 1, the pattern is considered a failure. The time limit can be changed in Settings, and is defined in terms of the total pattern length (point X to point D). It is set to 1.5 by default.
Increasing the time limit value will give you more realistic Success Rate values, but will less accurately represent the success rate of the harmonic patterns (i.e. the more time that elapses after a pattern completes, the less likely it is that the price action is related to that pattern).
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// Coming soon...
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I have a handful of other features in development, including:
(1) Drawing incomplete patterns as they develop. This will allow you more time to plan entries and stops, or potentially trade reversals from point C to point D PRZ levels.
(2) Support for the Shark and Cypher patterns
(3) Alerts
Please report any bugs, runtime errors, other issues or enhancement suggestions.
I also welcome any feedback from experienced harmonic pattern traders, especially regarding your strategy for setting targets and stop-losses.
@reees
Stochastic Moving AverageHi all,
This Strategy script combines the power of EMAs along with the Stochastic Oscillator in a trend following / continuation manner, along with some cool functionalities.
I designed this script especially for trading altcoins, but it works just as good on Bitcoin itself and on some Forex pairs.
______ SIGNALS ______
The script has 4 mandatory conditions to unlock a trading signal. Find these conditions for a long trade below (works the exact other way round for shorts)
- Fast EMA must be higher than Slow EMA
- Stochastic K% line must be in oversold territory
- Stochastic K% line must cross over Stochastic D% line
- Price as to close between slow EMA and fast EMA
Once all the conditions are true, a trade will start at the opening of the next
______ SETTINGS ______
- Trade Setup:
Here you can choose to trade only longs or shorts and change your Risk:Reward.
You can also decide to adjust your volume per position according to your risk tolerance. With “% of Equity” your stop loss will always be equal to a fixed percentage of your initial capital (will “compound” overtime) and with “$ Amount” your stop loss will always be 'x' amount of the base currency (ex: USD, will not compound)
Stop Loss:
The ATR is used to create a stop loss that matches current volatility. The multiplier corresponds to how many times the ATR stop losses and take profits will be away from closing price.
- Stochastic:
Here you can find the usual K% & D% length and overbought (OB) and oversold (OS) levels.
The “Stochastic OB/OS lookback” increase the tolerance towards OB/OS territories. It allows to look 'x' bars back for a value of the Stochastic K line to be overbought or oversold when detecting an entry signal.
The “All must be OB/OS” refers to the previous “Stochastic OB/OS lookback” parameter. If this option is ticked, instead of needing only 1 OB/OS value within the lookback period to get a valid signal, now, all bars looked back must be OB/OS.
The color gradient drawn between the fast and slow EMAs is a representation of the Stochastic K% line position. With default setting colors, when fast EMA > slow EMA, gradient will become solid blue when Stochastic is oversold and when slow EMA > fast EMA, gradient will become solid blue when Stochastic is overbought
- EMAs:
Just pick your favorite ones
- Reference Market:
An additional filter to be certain to stay aligned with the current a market index trend (in our case: Bitcoin). If selected reference market (and timeframe) is trading above selected EMA, this strategy will only take long trades (vice-versa for shorts) Because, let’s face it… even if this filter isn’t bulletproof, you know for sure that when Bitcoin tanks, there won’t be many Alts going north simultaneously. Once again, this is a trend following strategy.
A few tips for increased performance: fast EMA and D% Line can be real fast… 😉
As always, my scripts evolve greatly with your ideas and suggestions, keep them coming! I will gladly incorporate more functionalities as I go.
All my script are tradable when published but remain work in progress, looking for further improvements.
Hope you like it!
Grid Like StrategyIt is possible to use progressive position sizing in order to recover from past losses, a well-known position sizing system being the "martingale", which consists of doubling your position size after a loss, this allows you to recover any previous losses in a losing streak + winning an extra. This system has seen a lot of attention from the trading community (mostly from beginners), and many strategies have been designed around the martingale, one of them being "grid trading strategies".
While such strategies often shows promising results on paper, they are often subjects to many frictions during live trading that makes them totally unusable and dangerous to the trader. The motivations behind posting such a strategy isn't to glorify such systems, but rather to present the problems behind them, many users come to me with their ideas and glorious ways to make money, sometimes they present strategies using the martingale, and it is important to present the flaws of this methodology rather than blindly saying "you shouldn't use it".
Strategy Settings
Point determines the "grid" size and should be adjusted accordingly to the scale of the symbol you are applying the strategy to. Higher value would require larger price movements in order to trigger a trade, as such higher values will generate fewer trades.
The order size determines the number of contracts/shares to purchase.
The martingale multiplier determines the factor by which the position size is multiplied after a loss, using values higher to 2 will "squarify" your balance, while a value of 1 would use a constant position sizing.
Finally, the anti-martingale parameter determines whether the strategy uses a reverse martingale or not, if set to true then the position size is multiplied after any wins.
The Grid
Grid strategies are commons and do not present huge problems until we use certain position sizing methods such as the martingale. A martingale is extremely sensitive to any kind of friction (frictional costs, slippage...etc), the grid strategy aims to provide a stable and simple environment where a martingale might possibly behave well.
The goal of a simple grid strategy is to go long once the price crossover a certain level, a take profit is set at the level above the current one and stop loss is placed at the level below the current one, in a winning scenario the price reach the take profit, the position is closed and a new one is opened with the same setup. In a losing scenario, the price reaches the stop loss level, the position is closed and a short one is opened, the take profit is set at the level below the current one, and a stop loss is set at the level above the current one. Note that all levels are equally spaced.
It follows from this strategy that wins and losses should be constant over time, as such our balance would evolve in a linear fashion. This is a great setup for a martingale, as we are theoretically assured to recover all the looses in a losing streak.
Martingale - Exponential Decays - Risk/Reward
By using a martingale we double our position size (exposure) each time we lose a trade, if we look at our balance when using a martingale we see significant drawdowns, with our balance peaking down significantly. The martingale sequence is subject to exponential growth, as such using a martingale makes our balance exposed to exponential decays, that's really bad, we could basically lose all the initially invested capital in a short amount of time, it follows from this that the theoretical success of a martingale is determined by what is the maximum losing streak you can endure
Now consider how a martingale affects our risk-reward ratio, assuming unity position sizing our martingale sequence can be described by 2^(x-1) , using this formula we would get the amount of shares/contracts we need to purchase at the x trade of a losing streak, we would need to purchase 256 contracts in order to recover from a losing streak of size 9, this is enormous when you take into account that your wins are way smaller, the risk-reward ratio is totally unfair.
Of course, some users might think that a losing streak of size 9 is pretty unlikely, if the probability of winning and losing are both equal to 0.5, then the probability of 9 consecutive losses is equal to 0.5^9 , there are approximately 0.2% of chance of having such large losing streak, note however that under a ranging market such case scenario could happen, but we will see later that the length of a losing streak is not the only problem.
Other Problems
Having a capital large enough to tank 9any number of consecutive losses is not the only thing one should focus on, as we have to take into account market prices and trading dynamics, that's where the ugly part start.
Our first problem is frictional costs, one example being the spread, but this is a common problem for any strategy, however here a martingale is extra sensitive to it, if the strategy does not account for it then we will still double our positions costs but we might not recover all the losses of a losing streak, instead we would be recovering only a proportion of it, under such scenario you would be certain to lose over time.
Another problem are gaps, market price might open under a stop-loss without triggering it, and this is a big no-no.
Equity of the strategy on AMD, in a desired scenario the equity at the second arrow should have been at a higher position than the equity at the first arrow.
In order for the strategy to be more effective, we would need to trade a market that does not close, such as the cryptocurrency market. Finally, we might be affected by slippage, altho only extreme values might drastically affect our balance.
The Anti Martingale
The strategy lets you use an anti-martingale, which double the position size after a win instead of a loss, the goal here is not to recover from a losing strike but instead to profit from a potential winning streak.
Here we are exposing your balance to exponential gross but you might also lose a trade at the end a winning streak, you will generally want to reinitialize your position size after a few wins instead of waiting for the end of a streak.
Alternative
You can use other-kind of progressions for position sizing, such as a linear one, increasing your position size by a constant number each time you lose. More gentle progressions will recover a proportion of your losses in a losing streak.
You can also simulate the effect of a martingale without doubling your position size by doubling your target profit, if for example you have a 10$ profit-target/stop-loss and lose a trade, you can use a 20$ profit target to recover from the lost trade + gain a profit of 10$. While this approach does not introduce exponential decay in your balance, you are betting on the market reaching your take profits, considering the fact that you are doubling their size you are expecting market volatility to increase drastically over time, as such this approach would not be extremely effective for high losing streak.
Conclusion
You will see a lot of auto-trading strategies that are based on a grid approach, they might even use a martingale. While the backtests will look appealing, you should think twice before using such kind of strategy, remember that frictional costs will be a huge challenge for the strategy, and that it assumes that the trader has an important initial capital. We have also seen that the risk/reward ratio is theoretically the worst you can have on a strategy, having a low reward and a high risk. This does not mean that progressive position sizing is bad, but it should not be pushed to the extreme.
It is nice to note that the martingale is originally a betting system designed for casino games, which unlike trading are not subject to frictional costs, but even casino players don't use it, so why would you?
Thx for reading
1h Liquidity Swings Strategy with 1:2 RRLuxAlgo Liquidity Swings (Simulated):
Uses ta.pivothigh and ta.pivotlow to detect 1h swing highs (resistance) and swing lows (support).
The lookback parameter (default 5) controls swing point sensitivity.
Entry Logic:
Long: Uptrend, price crosses above 1h swing low (ta.crossover(low, support1h)), and price is below recent swing high (close < resistance1h).
Short: Downtrend, price crosses below 1h swing high (ta.crossunder(high, resistance1h)), and price is above recent swing low (close > support1h).
Take Profit (1:2 Risk-Reward):
Risk:
Long: risk = entryPrice - initialStopLoss.
Short: risk = initialStopLoss - entryPrice.
Take-profit price:
Long: takeProfitPrice = entryPrice + 2 * risk.
Short: takeProfitPrice = entryPrice - 2 * risk.
Set via strategy.exit’s limit parameter.
Stop-Loss:
Initial Stop-Loss:
Long: slLong = support1h * (1 - stopLossBuffer / 100).
Short: slShort = resistance1h * (1 + stopLossBuffer / 100).
Breakout Stop-Loss:
Long: close < support1h.
Short: close > resistance1h.
Managed via strategy.exit’s stop parameter.
Visualization:
Plots:
50-period SMA (trendMA, blue solid line).
1h resistance (resistance1h, red dashed line).
1h support (support1h, green dashed line).
Marks buy signals (green triangles below bars) and sell signals (red triangles above bars) using plotshape.
Usage Instructions
Add the Script:
Open TradingView’s Pine Editor, paste the code, and click “Add to Chart”.
Set Timeframe:
Use the 1-hour (1h) chart for intraday trading.
Adjust Parameters:
lookback: Swing high/low lookback period (default 5). Smaller values increase sensitivity; larger values reduce noise.
stopLossBuffer: Initial stop-loss buffer (default 0.5%).
maLength: Trend SMA period (default 50).
Backtesting:
Use the “Strategy Tester” to evaluate performance metrics (profit, win rate, drawdown).
Optimize parameters for your target market.
Notes on Limitations
LuxAlgo Liquidity Swings:
Simulated using ta.pivothigh and ta.pivotlow. LuxAlgo may include proprietary logic (e.g., volume or visit frequency filters), which requires the indicator’s code or settings for full integration.
Action: Please provide the Pine Script code or specific LuxAlgo settings if available.
Stop-Loss Breakout:
Uses closing price breakouts to reduce false signals. For more sensitive detection (e.g., high/low-based), I can modify the code upon request.
Market Suitability:
Ideal for high-liquidity markets (e.g., BTC/USD, EUR/USD). Choppy markets may cause false breakouts.
Action: Backtest in your target market to confirm suitability.
Fees:
Take-profit/stop-loss calculations exclude fees. Adjust for trading costs in live trading.
Swing Detection:
Swing high/low detection depends on market volatility. Optimize lookback for your market.
Verification
Tested in TradingView’s Pine Editor (@version=5):
plot function works without errors.
Entries occur strictly at 1h support (long) or resistance (short) in the trend direction.
Take-profit triggers at 1:2 risk-reward.
Stop-loss triggers on initial settings or 1h support/resistance breakouts.
Backtesting performs as expected.
Next Steps
Confirm Functionality:
Run the script and verify entries, take-profit (1:2), stop-loss, and trend filtering.
If issues occur (e.g., inaccurate signals, premature stop-loss), share backtest results or details.
LuxAlgo Liquidity Swings:
Provide the Pine Script code, settings, or logic details (e.g., volume filters) for LuxAlgo Liquidity Swings, and I’ll integrate them precisely.
Dskyz (DAFE) Quantum Sentiment Flux - Beginners Dskyz (DAFE) Quantum Sentiment Flux - Beginners:
Welcome to the Dskyz (DAFE) Quantum Sentiment Flux - Beginners , a strategy and concept that’s your ultimate wingman for trading futures like MNQ, NQ, MES, and ES. This gem combines lightning-fast momentum signals, market sentiment smarts, and bulletproof risk management into a system so intuitive, even newbies can trade like pros. With clean DAFE visuals, preset modes for every vibe, and a revamped dashboard that’s basically a market GPS, this strategy makes futures trading feel like a high-octane sci-fi mission.
Built on the Dskyz (DAFE) legacy of Aurora Divergence, the Quantum Sentiment Flux is designed to empower beginners while giving seasoned traders a lean, sentiment-driven edge. It uses fast/slow EMA crossovers for entries, filters trades with VIX, SPX trends, and sector breadth, and keeps your account safe with adaptive stops and cooldowns. Tuned for more action with faster signals and a slick bottom-left dashboard, this updated version is ready to light up your charts and outsmart institutional traps. Let’s dive into why this strat’s a must-have and break down its brilliance.
Why Traders Need This Strategy
Futures markets are a wild ride—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional games that can wreck unprepared traders. Beginners often get lost in complex systems or burned by impulsive trades. The Quantum Sentiment Flux is the antidote, offering:
Dead-Simple Setup: Preset modes (Aggressive, Balanced, Conservative) auto-tune signals, risk, and sizing, so you can trade without a quant degree.
Sentiment Superpower: VIX filter, SPX trend, and sector breadth visuals keep you aligned with market health, dodging chop and riding trends.
Ironclad Safety: Tighter ATR-based stops, 2:1 take-profits, and preset cooldowns protect your capital, even in chaotic sessions.
Next-Level Visuals: Green/red entry triangles, vibrant EMAs, a sector breadth background, and a beefed-up dashboard make signals and context pop.
DAFE Swagger: The clean aesthetics, sleek dashboard—ties it to Dskyz’s elite brand, making your charts a work of art.
Traders need this because it’s a plug-and-play system that blends beginner-friendly simplicity with pro-level market awareness. Whether you’re just starting or scalping 5min MNQ, this strat’s your key to trading with confidence and style.
Strategy Components
1. Core Signal Logic (High-Speed Momentum)
The strategy’s engine is a momentum-based system using fast and slow Exponential Moving Averages (EMAs), now tuned for faster, more frequent trades.
How It Works:
Fast/Slow EMAs: Fast EMA (Aggressive: 5, Balanced: 7, Conservative: 9 bars) and slow EMA (12/14/18 bars) track short-term vs. longer-term momentum.
Crossover Signals:
Buy: Fast EMA crosses above slow EMA, and trend_dir = 1 (fast EMA > slow EMA + ATR * strength threshold).
Sell: Fast EMA crosses below slow EMA, and trend_dir = -1 (fast EMA < slow EMA - ATR * strength threshold).
Strength Filter: ma_strength = fast EMA - slow EMA must exceed an ATR-scaled threshold (Aggressive: 0.15, Balanced: 0.18, Conservative: 0.25) for robust signals.
Trend Direction: trend_dir confirms momentum, filtering out weak crossovers in choppy markets.
Evolution:
Faster EMAs (down from 7–10/21–50) catch short-term trends, perfect for active futures markets.
Lower strength thresholds (0.15–0.25 vs. 0.3–0.5) make signals more sensitive, boosting trade frequency without sacrificing quality.
Preset tuning ensures beginners get optimized settings, while pros can tweak via mode selection.
2. Market Sentiment Filters
The strategy leans hard into market sentiment with a VIX filter, SPX trend analysis, and sector breadth visuals, keeping trades aligned with the big picture.
VIX Filter:
Logic: Blocks long entries if VIX > threshold (default: 20, can_long = vix_close < vix_limit). Shorts are always allowed (can_short = true).
Impact: Prevents longs during high-fear markets (e.g., VIX spikes in crashes), while allowing shorts to capitalize on downturns.
SPX Trend Filter:
Logic: Compares S&P 500 (SPX) close to its SMA (Aggressive: 5, Balanced: 8, Conservative: 12 bars). spx_trend = 1 (UP) if close > SMA, -1 (DOWN) if < SMA, 0 (FLAT) if neutral.
Impact: Provides dashboard context, encouraging trades that align with market direction (e.g., longs in UP trend).
Sector Breadth (Visual):
Logic: Tracks 10 sector ETFs (XLK, XLF, XLE, etc.) vs. their SMAs (same lengths as SPX). Each sector scores +1 (bullish), -1 (bearish), or 0 (neutral), summed as breadth (-10 to +10).
Display: Green background if breadth > 4, red if breadth < -4, else neutral. Dashboard shows sector trends (↑/↓/-).
Impact: Faster SMA lengths make breadth more responsive, reflecting sector rotations (e.g., tech surging, energy lagging).
Why It’s Brilliant:
- VIX filter adds pro-level volatility awareness, saving beginners from panic-driven losses.
- SPX and sector breadth give a 360° view of market health, boosting signal confidence (e.g., green BG + buy signal = high-probability trade).
- Shorter SMAs make sentiment visuals react faster, perfect for 5min charts.
3. Risk Management
The risk controls are a fortress, now tighter and more dynamic to support frequent trading while keeping accounts safe.
Preset-Based Risk:
Aggressive: Fast EMAs (5/12), tight stops (1.1x ATR), 1-bar cooldown. High trade frequency, higher risk.
Balanced: EMAs (7/14), 1.2x ATR stops, 1-bar cooldown. Versatile for most traders.
Conservative: EMAs (9/18), 1.3x ATR stops, 2-bar cooldown. Safer, fewer trades.
Impact: Auto-scales risk to match style, making it foolproof for beginners.
Adaptive Stops and Take-Profits:
Logic: Stops = entry ± ATR * atr_mult (1.1–1.3x, down from 1.2–2.0x). Take-profits = entry ± ATR * take_mult (2x stop distance, 2:1 reward/risk). Longs: stop below entry, TP above; shorts: vice versa.
Impact: Tighter stops increase trade turnover while maintaining solid risk/reward, adapting to volatility.
Trade Cooldown:
Logic: Preset-driven (Aggressive/Balanced: 1 bar, Conservative: 2 bars vs. old user-input 2). Ensures bar_index - last_trade_bar >= cooldown.
Impact: Faster cooldowns (especially Aggressive/Balanced) allow more trades, balanced by VIX and strength filters.
Contract Sizing:
Logic: User sets contracts (default: 1, max: 10), no preset cap (unlike old 7/5/3 suggestion).
Impact: Flexible but risks over-leverage; beginners should stick to low contracts.
Built To Be Reliable and Consistent:
- Tighter stops and faster cooldowns make it a high-octane system without blowing up accounts.
- Preset-driven risk removes guesswork, letting newbies trade confidently.
- 2:1 TPs ensure profitable trades outweigh losses, even in volatile sessions like April 27, 2025 ES slippage.
4. Trade Entry and Exit Logic
The entry/exit rules are simple yet razor-sharp, now with VIX filtering and faster signals:
Entry Conditions:
Long Entry: buy_signal (fast EMA crosses above slow EMA, trend_dir = 1), no position (strategy.position_size = 0), cooldown passed (can_trade), and VIX < 20 (can_long). Enters with user-defined contracts.
Short Entry: sell_signal (fast EMA crosses below slow EMA, trend_dir = -1), no position, cooldown passed, can_short (always true).
Logic: Tracks last_entry_bar for visuals, last_trade_bar for cooldowns.
Exit Conditions:
Stop-Loss/Take-Profit: ATR-based stops (1.1–1.3x) and TPs (2x stop distance). Longs exit if price hits stop (below) or TP (above); shorts vice versa.
No Other Exits: Keeps it straightforward, relying on stops/TPs.
5. DAFE Visuals
The visuals are pure DAFE magic, blending clean function with informative metrics utilized by professionals, now enhanced by faster signals and a responsive breadth background:
EMA Plots:
Display: Fast EMA (blue, 2px), slow EMA (orange, 2px), using faster lengths (5–9/12–18).
Purpose: Highlights momentum shifts, with crossovers signaling entries.
Sector Breadth Background:
Display: Green (90% transparent) if breadth > 4, red (90%) if breadth < -4, else neutral.
Purpose: Faster breadth_sma_len (5–12 vs. 10–50) reflects sector shifts in real-time, reinforcing signal strength.
- Visuals are intuitive, turning complex signals into clear buy/sell cues.
- Faster breadth background reacts to market rotations (e.g., tech vs. energy), giving a pro-level edge.
6. Sector Breadth Dashboard
The new bottom-left dashboard is a game-changer, a 3x16 table (black/gray theme) that’s your market command center:
Metrics:
VIX: Current VIX (red if > 20, gray if not).
SPX: Trend as “UP” (green), “DOWN” (red), or “FLAT” (gray).
Trade Longs: “OK” (green) if VIX < 20, “BLOCK” (red) if not.
Sector Breadth: 10 sectors (Tech, Financial, etc.) with trend arrows (↑ green, ↓ red, - gray).
Placeholder Row: Empty for future metrics (e.g., ATR, breadth score).
Purpose: Consolidates regime, volatility, market trend, and sector data, making decisions a breeze.
- VIX and SPX metrics add context, helping beginners avoid bad trades (e.g., no longs if “BLOCK”).
Sector arrows show market health at a glance, like a cheat code for sentiment.
Key Features
Beginner-Ready: Preset modes and clear visuals make futures trading a breeze.
Sentiment-Driven: VIX filter, SPX trend, and sector breadth keep you in sync with the market.
High-Frequency: Faster EMAs, tighter stops, and short cooldowns boost trade volume.
Safe and Smart: Adaptive stops/TPs and cooldowns protect capital while maximizing wins.
Visual Mastery: DAFE’s clean flair, EMAs, dashboard—makes trading fun and clear.
Backtestable: Lean code and fixed qty ensure accurate historical testing.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Pick Preset: Aggressive (scalping), Balanced (versatile), or Conservative (safe). Balanced is default.
Set Contracts: Default 1, max 10. Stick low for safety.
Check Dashboard: Bottom-left shows preset, VIX, SPX, and sectors. “OK” + green breadth = strong buy.
Backtest: Run in strategy tester to compare modes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see VIX filter and stops in action.
Why It’s Brilliant
The Dskyz (DAFE) Quantum Sentiment Flux - Beginners is a masterpiece of simplicity and power. It takes pro-level tools—momentum, VIX, sector breadth—and wraps them in a system anyone can run. Faster signals and tighter stops make it a trading machine, while the VIX filter and dashboard keep you ahead of market chaos. The DAFE visuals and bottom-left command center turn your chart into a futuristic cockpit, guiding you through every trade. For beginners, it’s a safe entry to futures; for pros, it’s a scalping beast with sentiment smarts. This strat doesn’t just trade—it transforms how you see the market.
Final Notes
This is more than a strategy—it’s your launchpad to mastering futures with Dskyz (DAFE) flair. The Quantum Sentiment Flux blends accessibility, speed, and market savvy to help you outsmart the game. Load it, watch those triangles glow, and let’s make the markets your canvas!
Official Statement from Pine Script Team
(see TradingView help docs and forums):
"This warning may appear when you call functions such as ta.sma inside a request.security in a loop. There is no runtime impact. If you need to loop through a dynamic list of tickers, this cannot be avoided in the present version... Values will still be correct. Ignore this warning in such contexts."
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
RSI Failure Swing Pattern (with Alerts & Targets)RSI Failure Swing Pattern Indicator – Detailed Description
Overview
The RSI Failure Swing Pattern Indicator is a trend reversal detection tool based on the principles of failure swings in the Relative Strength Index (RSI). This indicator identifies key reversal signals by analyzing RSI swings and confirming trend shifts using predefined overbought and oversold conditions.
Failure swing patterns are one of the strongest RSI-based reversal signals, initially introduced by J. Welles Wilder. This indicator detects these patterns and provides clear buy/sell signals with labeled entry, stop-loss, and profit target levels. The tool is designed to work across all timeframes and assets.
How the Indicator Works
The RSI Failure Swing Pattern consists of two key structures:
1. Bullish Failure Swing (Buy Signal)
Occurs when RSI enters oversold territory (below 30), recovers, forms a higher low above the oversold level, and finally breaks above the intermediate swing high in RSI.
Step 1: RSI dips below 30 (oversold condition).
Step 2: RSI rebounds and forms a local peak.
Step 3: RSI retraces but does not go below the previous low (higher low confirmation).
Step 4: RSI breaks above the previous peak, confirming a bullish trend reversal.
Buy signal is triggered at the breakout above the RSI peak.
2. Bearish Failure Swing (Sell Signal)
Occurs when RSI enters overbought territory (above 70), declines, forms a lower high below the overbought level, and then breaks below the intermediate swing low in RSI.
Step 1: RSI rises above 70 (overbought condition).
Step 2: RSI declines and forms a local trough.
Step 3: RSI bounces but fails to exceed the previous high (lower high confirmation).
Step 4: RSI breaks below the previous trough, confirming a bearish trend reversal.
Sell signal is triggered at the breakdown below the RSI trough.
Features of the Indicator
Custom RSI Settings: Adjustable RSI length (default 14), overbought/oversold levels.
Buy & Sell Signals: Buy/sell signals are plotted directly on the price chart.
Entry, Stop-Loss, and Profit Targets:
Entry: Price at the breakout of the RSI failure swing pattern.
Stop-Loss: Lowest low (for buy) or highest high (for sell) of the previous two bars.
Profit Targets: Two levels calculated based on Risk-Reward ratios (1:1 and 1:2 by default, customizable).
Labeled Price Levels:
Entry Price Line (Blue): Marks the point of trade entry.
Stop-Loss Line (Red): Shows the calculated stop-loss level.
Target 1 Line (Orange): Profit target at 1:1 risk-reward ratio.
Target 2 Line (Green): Profit target at 1:2 risk-reward ratio.
Alerts for Trade Execution:
Buy/Sell signals trigger alerts for real-time notifications.
Alerts fire when price reaches stop-loss or profit targets.
Works on Any Timeframe & Asset: Suitable for stocks, forex, crypto, indices, and commodities.
Why Use This Indicator?
Highly Reliable Reversal Signals: Unlike simple RSI overbought/oversold strategies, failure swings filter out false breakouts and provide strong confirmation of trend reversals.
Risk Management Built-In: Stop-loss and take-profit levels are automatically set based on historical price action and risk-reward considerations.
Easy-to-Use Visualization: Clearly marked entry, stop-loss, and profit target levels make it beginner-friendly while still being valuable for experienced traders.
How to Trade with the Indicator
Buy Trade Example (Bullish Failure Swing)
RSI drops below 30 and recovers.
RSI forms a higher low and then breaks above the previous peak.
Entry: Buy when RSI crosses above its previous peak.
Stop-Loss: Set below the lowest low of the previous two candles.
Profit Targets:
Target 1 (1:1 Risk-Reward Ratio)
Target 2 (1:2 Risk-Reward Ratio)
Sell Trade Example (Bearish Failure Swing)
RSI rises above 70 and then declines.
RSI forms a lower high and then breaks below the previous trough.
Entry: Sell when RSI crosses below its previous trough.
Stop-Loss: Set above the highest high of the previous two candles.
Profit Targets:
Target 1 (1:1 Risk-Reward Ratio)
Target 2 (1:2 Risk-Reward Ratio)
Final Thoughts
The RSI Failure Swing Pattern Indicator is a powerful tool for traders looking to identify high-probability trend reversals. By using the RSI failure swing concept along with built-in risk management tools, this indicator provides a structured approach to trading with clear entry and exit points. Whether you’re a day trader, swing trader, or long-term investor, this indicator helps in capturing momentum shifts while minimizing risk.
Would you like any modifications or additional features? 🚀
Adaptive RSI with Real-Time Divergence [AIBitcoinTrend]👽 Adaptive RSI Trailing Stop (AIBitcoinTrend)
The Adaptive RSI Trailing Stop is an indicator that integrates Gaussian-weighted RSI calculations with real-time divergence detection and a dynamic ATR-based trailing stop. This advanced approach allows traders to monitor momentum shifts, identify divergences early, and manage risk with adaptive trailing stop levels that adjust to price action.
👽 What Makes the Adaptive RSI with Signals and Trailing Stop Unique?
Unlike traditional RSI indicators, this version applies a Gaussian-weighted smoothing algorithm, making it more responsive to price action while reducing noise. Additionally, the trailing stop feature dynamically adjusts based on volatility and trend conditions, allowing traders to:
Detects real-time divergences (bullish/bearish) with a smart pivot-based system.
Filter noise with Gaussian weighting, ensuring smoother RSI transitions.
Utilize crossover-based trailing stop activation, for systematic trade management.
👽 The Math Behind the Indicator
👾 Gaussian Weighted RSI Calculation
Traditional RSI calculations rely on simple averages of gains and losses. Instead, this indicator weights recent price changes using a Gaussian distribution, prioritizing more relevant data points while maintaining smooth transitions.
Key Features:
Exponential decay ensures recent price changes are weighted more heavily.
Reduces short-term noise while maintaining responsiveness.
👾 Real-Time Divergence Detection
The indicator detects bullish and bearish divergences using pivot points on RSI compared to price action.
👾 Dynamic ATR-Based Trailing Stop
Bullish Trailing Stop: Activates when RSI crosses above 20 and dynamically adjusts based on low - ATR multiplier.
Bearish Trailing Stop: Activates when RSI crosses below 80 and adjusts based on high + ATR multiplier
This allows traders to:
Lock in profits systematically by adjusting stop-losses dynamically.
Stay in trades longer while maintaining adaptive risk management.
👽 How It Adapts to Market Movements
✔️ Gaussian Filtering ensures smooth RSI transitions while preventing excessive lag.
✔️ Real-Time Divergence Alerts provide early trade signals based on price-RSI discrepancies.
✔️ ATR Trailing Stop dynamically expands or contracts based on market volatility.
✔️ Crossover-Based Activation enables the stop-loss system only when RSI confirms a momentum shift.
👽 How Traders Can Use This Indicator
👾 Divergence Trading
Traders can use real-time divergence detection to anticipate reversals before they happen.
Bullish Divergence Setup:
Look for RSI making a higher low, while price makes a lower low.
Enter long when RSI confirms upward momentum.
Bearish Divergence Setup:
Look for RSI making a lower high, while price makes a higher high.
Enter short when RSI confirms downward momentum.
👾 Trailing Stop Signals
Bullish Signal and Trailing Stop Activation:
When RSI crosses above 20, a trailing stop is placed using low - ATR multiplier.
If price crosses below the stop, it exits the trade and removes the stop.
Bearish Signal and Trailing Stop Activation:
When RSI crosses below 80, a trailing stop is placed using high + ATR multiplier.
If price crosses above the stop, it exits the trade and removes the stop.
This makes trend-following strategies more efficient, while ensuring proper risk management.
👽 Why It’s Useful for Traders
✔️ Dynamic and Adaptive: Adjusts to changing market conditions automatically.
✔️ Noise Reduction: Gaussian-weighted RSI reduces short-term price distortions.
✔️ Comprehensive Strategy Tool: Combines momentum detection, divergence analysis, and automated risk management into a single indicator.
✔️ Works Across Markets & Timeframes: Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
RSI Length: Defines the lookback period for RSI smoothing.
Gaussian Sigma: Controls how much weight is given to recent data points.
Enable Signal Line: Option to display an RSI-based moving average.
Divergence Lookback: Configures how far back pivot points are detected.
Crossover/crossunder values for signals: Set the crossover/crossunder values that triggers signals.
ATR Multiplier: Adjusts trailing stop sensitivity to market volatility.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Price Action Trend and Margin EquityThe Price Action Trend and Margin Equity indicator is a multifunctional market analysis tool that combines elements of money management and price pattern analysis. The indicator helps traders identify key price action patterns and determine optimal entry, exit and stop loss levels based on the current trend.
The main components of the indicator:
Money Management:
Allows the trader to set risk management parameters such as the percentage of possible loss on the position, the use of fixed leverage and the total capital.
Calculates the required leverage level to achieve a specified percentage of loss.
Price Action:
Correctly identifies various price patterns such as Pin Bar, Engulfing Bar, PPR Bar and Inside Bar.
Displays these patterns on the chart with the ability to customize candle colors and display styles.
Allows the trader to customize take profit and stop loss points to display them on the chart.
The ability to display patterns only in the direction of the trend.
Trend: (some code taken from ChartPrime)
Uses a trend cloud to visualize the current market direction.
The trend cloud is displayed on the chart and helps traders determine whether the market is in an uptrend or a downtrend.
Alert:
Allows you to set an alert that will be triggered when the pattern is formed.
Example of use:
Let's say a trader uses the indicator to trade the crypto market. He sets the money management parameters, setting the maximum loss per position to 5% and using a fixed leverage of 1:100. The indicator automatically calculates the required position size to meet these parameters ($: on the label). Or displays the leverage (X: on the label) to achieve the required risk.
The trader receives an alert when a Pin Bar is formed. The indicator displays the entry, exit, and stop loss levels based on this pattern. The trader opens a position for the recommended amount in the direction indicated by the indicator and sets the stop loss and take profit at the recommended levels.
General Settings:
Position Loss Percentage: Sets the maximum loss percentage you are willing to take on a single position.
Use Fixed Leverage: Enables or disables the use of fixed leverage.
Fixed Leverage: Sets the fixed leverage level.
Total Equity: Specifies the total equity you are using for trading. (Required for calculation when using fixed leverage)
Turn Patterns On/Off: You can turn on or off the display of various price patterns such as Pin Bar, Outside Bar (Engulfing), Inside Bar, and PPR Bar.
Pattern Colors: Sets the colors for displaying each pattern on the chart.
Candle Color: Allows you to set a neutral color for candles that do not match the price action.
Show Lines: Allows you to turn on or off the display of labels and lines.
Line Length: Sets the length of the stop, entry, and take profit lines.
Label color: One color for all labels (configured below) or the color of the labels in the color of the candle pattern.
Pin entry: Select the entry point for the pin bar: candle head, bar close, or 50% of the candle.
Coefficients for stop and take lines.
Use trend for price action: When enabled, will show price action signals only in the direction of the trend.
Display trend cloud: Enables or disables the display of the trend cloud.
Cloud calculation period: Sets the period for which the maximum and minimum values for the cloud are calculated. The longer the period, the smoother the cloud will be.
Cloud colors: Sets the colors for uptrends and downtrends, as well as the transparency of the cloud.
The logic of the indicator:
Pin Bar is a candle with a long upper or lower shadow and a short body.
Logic: If the length of one shadow is twice the body and the opposite shadow of the candle, it is considered a Pin Bar.
An Inside Bar is a candle that is completely engulfed by the previous candle.
Logic: If the high and low of the current candle are inside the previous candle, it is an Inside Bar.
An Outside Bar or Engulfing is a candle that completely engulfs the previous candle.
Logic: If the high and low of the current candle are outside the previous candle and close outside the previous candle, it is an Outside Bar.
A PPR Bar is a candle that closes above or below the previous candle.
Logic: If the current candle closes above the high of the previous candle or below its low, it is a PPR Bar.
Stop Loss Levels: Calculated based on the specified ratios. If set to 1.0, it shows the correct stop for the pattern by pushing away from the entry point.
Take Profit Levels: Calculated based on the specified ratios.
Create a Label: The label is created at the stop loss level and contains information about the potential leverage and loss.
The formula for calculating the $ value is:
=(Total Capital x (Maximum Loss Percentage on Position/100)) / (Difference between Entry Level and Stop Loss Level × Ratio that sets the stop loss level relative to the length of the candlestick shadow × Fixed Leverage Value) .
Labels contain the following information:
The percentage of price change from the recommended entry point to the stop loss level.
Required Leverage (X: ): The amount of leverage required to achieve the specified loss percentage. (Or a fixed value if selected).
Required Capital ($: ): The amount of capital required to open a position with the specified leverage and loss percentage (only displayed when using fixed leverage).
The trend cloud identifies the maximum and minimum price values for the specified period.
The cloud value is set depending on whether the current price is equal to the high or low values.
If the current closing price is equal to the high value, the cloud is set at the low value, and vice versa.
RU
Индикатор "Price Action Trend and Margin Equity" представляет собой многофункциональный инструмент для анализа рынка, объединяющий в себе элементы управления капиталом и анализа ценовых паттернов. Индикатор помогает трейдерам идентифицировать ключевые прайс экшн паттерны и определять оптимальные уровни входа, выхода и стоп-лосс на основе текущего тренда.
Основные компоненты индикатора:
Управление капиталом:
Позволяет трейдеру задавать параметры управления рисками, такие как процент возможного убытка по позиции, использование фиксированного плеча и общий капитал.
Рассчитывает необходимый уровень плеча для достижения заданного процента убытка.
Price Action:
Правильно идентифицирует различные ценовые паттерны, такие как Pin Bar, Поглащение Бар, PPR Bar и Внутренний Бар.
Отображает эти паттерны на графике с возможностью настройки цветов свечей и стилей отображения.
Позволяет трейдеру настраивать точки тейк профита и стоп лосса для отображения их на графике.
Возможность отображения паттернов только в натправлении тренда.
Trend: (часть кода взята у ChartPrime)
Использует облако тренда для визуализации текущего направления рынка.
Облако тренда отображается на графике и помогает трейдерам определить, находится ли рынок в восходящем или нисходящем тренде.
Оповещение:
Дает возможность установить оповещение которое будет срабатывать при формировании паттерна.
Пример применения:
Предположим, трейдер использует индикатор для торговли на крипто рынке. Он настраивает параметры управления капиталом, устанавливая максимальный убыток по позиции в 5% и используя фиксированное плечо 1:100. Индикатор автоматически рассчитывает необходимый объем позиции для соблюдения этих параметров ($: на лейбле). Или отображает плечо (Х: на лейбле) для достижения необходимого риска.
Трейдер получает оповещение о формировании Pin Bar. Индикатор отображает уровни входа, выхода и стоп-лосс, основанные на этом паттерне. Трейдер открывает позицию на рекомендуемую сумму в направлении, указанном индикатором, и устанавливает стоп-лосс и тейк-профит на рекомендованных уровнях.
Общие настройки:
Процент убытка по позиции: Устанавливает максимальный процент убытка, который вы готовы понести по одной позиции.
Использовать фиксированное плечо: Включает или отключает использование фиксированного плеча.
Уровень фиксированного плеча: Задает уровень фиксированного плеча.
Общий капитал: Указывает общий капитал, который вы используете для торговли. (Необходим для расчета при использовании фиксированного плеча)
Включение/отключение паттернов: Вы можете включить или отключить отображение различных ценовых паттернов, таких как Pin Bar, Outside Bar (Поглощение), Inside Bar и PPR Bar.
Цвета паттернов: Задает цвета для отображения каждого паттерна на графике.
Цвет свечей: Позволяет задать нейтральный цвет для свечей неподходящих под прйс экшн.
Показывать линии: Позволяет включить или отключить отображение лейблов и линий.
Длинна линий: Настройка длинны линий стопа, линии входа и тейк профита.
Цвет лейбла: Один цвет для всех лейблов (настраивается ниже) или цвет лейблов в цвет паттерна свечи.
Вход в пин: Выбор точки входа для пин бара: голова свечи, точка закрытия бара или 50% свечи.
Коэффиценты для стоп и тейк линий.
Использовать тренд для прайс экшна: При включении будет показывать прайс экшн сигналы только в направлении тренда.
Отображение облака тренда: Включает или отключает отображение облака тренда.
Период расчета облака: Устанавливает период, за который рассчитываются максимальные и минимальные значения для облака. Чем больше период, тем более сглаженным будет облако.
Цвета облака: Задает цвета для восходящего и нисходящего трендов, а также прозрачность облака.
Логика работы индикатора:
Pin Bar — это свеча с длинной верхней или нижней тенью и коротким телом.
Логика: Если длина одной тени вдвое больше тела и противоположной тени свечи, считается, что это Pin Bar.
Inside Bar — это свеча, полностью поглощенная предыдущей свечой.
Логика: Если максимум и минимум текущей свечи находятся внутри предыдущей свечи, это Inside Bar.
Outside Bar или Поглощение — это свеча, которая полностью поглощает предыдущую свечу.
Логика: Если максимум и минимум текущей свечи выходят за пределы предыдущей свечи и закрывается за пределами предыдущей свечи, это Outside Bar.
PPR Bar — это свеча, которая закрывается выше или ниже предыдущей свечи.
Логика: Если текущая свеча закрывается выше максимума предыдущей свечи или ниже ее минимума, это PPR Bar.
Уровни стоп-лосс: Рассчитываются на основе заданных коэффициентов. При значении 1.0 показывает правильный стоп для паттерна отталкиваясь от точки входа.
Уровки тейк-профита: Рассчитываются на основе заданных коэффициентов.
Создание метки: Метка создается на уровне стоп-лосс и содержит информацию о потенциальном плече и убытке.
Формула для вычисления значения $:
=(Общий капитал x (Максимальный процент убытка по позиции/100)) / (Разница между уровнем входа и уровнем стоп-лосс × Коэффициент, задающий уровень стоп-лосс относительно длины тени свечи × Значение фиксированного плеча).
Метки содержат следующую информацию:
Процент изменения цены от рекомендованной точки входа до уровня стоп-лосс.
Необходимое плечо (Х: ): Уровень плеча, необходимый для достижения заданного процента убытка. (Или фиксированное значение если оно выбрано).
Необходимый капитал ($: ): Сумма капитала, необходимая для открытия позиции с заданным плечом и процентом убытка (отображается только при использовании фиксированного плеча).
Облако тренда определяет максимальные и минимальные значения цены за указанный период.
Значение облака устанавливается в зависимости от того, совпадает ли текущая цена с максимальными или минимальными значениями.
Если текущая цена закрытия равна максимальному значению, облако устанавливается на уровне минимального значения, и наоборот.
ATR Trailing Stop by GideonMATR Trailing Stop Indicator
This ATR Trailing Stop Indicator is designed for traders who wish to enhance their exit strategies by leveraging volatility-based stops. It offers a systematic approach to trend management and risk control, enabling traders to capture extended trends while protecting their capital during market reversals. Works on Indian Indices as well.
Overview:
The ATR Trailing Stop indicator is a dynamic trend-following tool that adjusts stop levels based on market volatility. By incorporating the Average True Range (ATR), the indicator provides a flexible exit strategy that adapts to changing market conditions, helping traders lock in profits during trends and limit losses during reversals.
How It Works:
True Range and ATR Calculation:
The indicator first calculates the True Range (TR) for each bar, defined as the maximum of:
The difference between the high and low,
The absolute difference between the high and the previous close, and
The absolute difference between the low and the previous close.
Using the TR values, the ATR is computed over a user-defined period (default is 14 bars) with an option to use either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as the smoothing method.
Trailing Stop Determination:
Two potential stop levels are calculated:
For an uptrend, the stop is determined as:
Stop = Close – (Multiplier × ATR)
For a downtrend, the stop is:
Stop = Close + (Multiplier × ATR)
The indicator maintains a persistent trailing stop that dynamically adjusts:
In an uptrend, the trailing stop only moves upward (or remains flat) to secure gains.
In a downtrend, it only moves downward, thereby protecting the position from excessive losses.
A reversal in trend is identified when the price crosses the trailing stop level, at which point the indicator flips the trend and resets the stop level accordingly.
Rationale:
Utilizing the ATR for trailing stops ensures that the stop levels are directly influenced by market volatility. This dynamic adjustment helps accommodate the natural price fluctuations of the market, providing a more adaptive risk management tool compared to fixed stop-loss levels. The approach is particularly useful in volatile markets where traditional static stops might be triggered prematurely.
Customization:
Key parameters that can be adjusted include:
ATR Period: The number of bars used to calculate the ATR.
ATR Multiplier: The factor that determines how far the trailing stop is set from the current price.
Smoothing Method: Option to choose between SMA and EMA for ATR calculation, allowing traders to tailor the sensitivity of the indicator to their specific trading style.
CandelaCharts - Swing Failure Pattern (SFP)# SWING FAILURE PATTERN
📝 Overview
The Swing Failure Pattern (SFP) indicator is designed to identify and highlight Swing Failure Patterns on a user’s chart. This pattern typically emerges when significant market participants generate liquidity by driving price action to key levels. An SFP occurs when the price temporarily breaks above a resistance level or below a support level, only to quickly reverse and return within the previous range. These movements are often associated with stop-loss hunting or liquidity grabs, providing traders with potential opportunities to anticipate reversals or key market turning points.
A Bullish SFP occurs when the price dips below a key support level, triggering stop-loss orders, but then swiftly reverses upward, signaling a potential upward trend or reversal.
A Bearish SFP happens when the price spikes above a key resistance level, triggering stop-losses of short positions, but then quickly reverses downward, indicating a potential bearish trend or reversal.
The indicator is a powerful tool for traders, helping to identify liquidity grabs and potential reversal points in real-time. Marking bullish and bearish Swing Failure Patterns on the chart, it provides clear visual cues for spotting market traps set by major players, enabling more informed trading decisions and improved risk management.
📦 Features
Bullish/Bearish SFPs
Styling
⚙️ Settings
Length: Determines the detection length of each SFP
Bullish SFP: Displays the bullish SFPs
Bearish SFP: Displays the bearish SFPs
Label: Controls the size of the label
⚡️ Showcase
Bullish
Bearish
Both
📒 Usage
The best approach is to combine a few complementary indicators to gain a clearer market perspective. This doesn’t mean relying on the Golden Cross, RSI divergences, SFPs, and funding rates simultaneously, but rather focusing on one or two that align well in a given scenario.
The example above demonstrates the confluence of a Bearish Swing Failure Pattern (SFP) with an RSI divergence. This combination strengthens the signal, as the Bearish SFP indicates a potential reversal after a liquidity grab, while the RSI divergence confirms weakening momentum at the key level. Together, these indicators provide a more robust setup for identifying potential market reversals with greater confidence.
🚨 Alerts
This script provides alert options for all signals.
Bearish Signal
A bearish signal is triggered when a Bearish SFP is formed.
Bullish Signal
A bullish signal is triggered when a Bullish SFP is formed.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
ICT Master Suite [Trading IQ]Hello Traders!
We’re excited to introduce the ICT Master Suite by TradingIQ, a new tool designed to bring together several ICT concepts and strategies in one place.
The Purpose Behind the ICT Master Suite
There are a few challenges traders often face when using ICT-related indicators:
Many available indicators focus on one or two ICT methods, which can limit traders who apply a broader range of ICT related techniques on their charts.
There aren't many indicators for ICT strategy models, and we couldn't find ICT indicators that allow for testing the strategy models and setting alerts.
Many ICT related concepts exist in the public domain as indicators, not strategies! This makes it difficult to verify that the ICT concept has some utility in the market you're trading and if it's worth trading - it's difficult to know if it's working!
Some users might not have enough chart space to apply numerous ICT related indicators, which can be restrictive for those wanting to use multiple ICT techniques simultaneously.
The ICT Master Suite is designed to offer a comprehensive option for traders who want to apply a variety of ICT methods. By combining several ICT techniques and strategy models into one indicator, it helps users maximize their chart space while accessing multiple tools in a single slot.
Additionally, the ICT Master Suite was developed as a strategy . This means users can backtest various ICT strategy models - including deep backtesting. A primary goal of this indicator is to let traders decide for themselves what markets to trade ICT concepts in and give them the capability to figure out if the strategy models are worth trading!
What Makes the ICT Master Suite Different
There are many ICT-related indicators available on TradingView, each offering valuable insights. What the ICT Master Suite aims to do is bring together a wider selection of these techniques into one tool. This includes both key ICT methods and strategy models, allowing traders to test and activate strategies all within one indicator.
Features
The ICT Master Suite offers:
Multiple ICT strategy models, including the 2022 Strategy Model and Unicorn Model, which can be built, tested, and used for live trading.
Calculation and display of key price areas like Breaker Blocks, Rejection Blocks, Order Blocks, Fair Value Gaps, Equal Levels, and more.
The ability to set alerts based on these ICT strategies and key price areas.
A comprehensive, yet practical, all-inclusive ICT indicator for traders.
Customizable Timeframe - Calculate ICT concepts on off-chart timeframes
Unicorn Strategy Model
2022 Strategy Model
Liquidity Raid Strategy Model
OTE (Optimal Trade Entry) Strategy Model
Silver Bullet Strategy Model
Order blocks
Breaker blocks
Rejection blocks
FVG
Strong highs and lows
Displacements
Liquidity sweeps
Power of 3
ICT Macros
HTF previous bar high and low
Break of Structure indications
Market Structure Shift indications
Equal highs and lows
Swings highs and swing lows
Fibonacci TPs and SLs
Swing level TPs and SLs
Previous day high and low TPs and SLs
And much more! An ongoing project!
How To Use
Many traders will already be familiar with the ICT related concepts listed above, and will find using the ICT Master Suite quite intuitive!
Despite this, let's go over the features of the tool in-depth and how to use the tool!
The image above shows the ICT Master Suite with almost all techniques activated.
ICT 2022 Strategy Model
The ICT Master suite provides the ability to test, set alerts for, and live trade the ICT 2022 Strategy Model.
The image above shows an example of a long position being entered following a complete setup for the 2022 ICT model.
A liquidity sweep occurs prior to an upside breakout. During the upside breakout the model looks for the FVG that is nearest 50% of the setup range. A limit order is placed at this FVG for entry.
The target entry percentage for the range is customizable in the settings. For instance, you can select to enter at an FVG nearest 33% of the range, 20%, 66%, etc.
The profit target for the model generally uses the highest high of the range (100%) for longs and the lowest low of the range (100%) for shorts. Stop losses are generally set at 0% of the range.
The image above shows the short model in action!
Whether you decide to follow the 2022 model diligently or not, you can still set alerts when the entry condition is met.
ICT Unicorn Model
The image above shows an example of a long position being entered following a complete setup for the ICT Unicorn model.
A lower swing low followed by a higher swing high precedes the overlap of an FVG and breaker block formed during the sequence.
During the upside breakout the model looks for an FVG and breaker block that formed during the sequence and overlap each other. A limit order is placed at the nearest overlap point to current price.
The profit target for this example trade is set at the swing high and the stop loss at the swing low. However, both the profit target and stop loss for this model are configurable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
For Longs, the selectable stop losses are:
Swing Low
Bottom of FVG or breaker block
The image above shows the short version of the Unicorn Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
For Shorts, the selectable stop losses are:
Swing High
Top of FVG or breaker block
The image above shows the profit target and stop loss options in the settings for the Unicorn Model.
Optimal Trade Entry (OTE) Model
The image above shows an example of a long position being entered following a complete setup for the OTE model.
Price retraces either 0.62, 0.705, or 0.79 of an upside move and a trade is entered.
The profit target for this example trade is set at the -0.5 fib level. This is also adjustable in the settings.
For Longs, the selectable profit targets are:
Swing High
Fib -0.5
Fib -1
Fib -2
The image above shows the short version of the OTE Model in action!
For Shorts, the selectable profit targets are:
Swing Low
Fib -0.5
Fib -1
Fib -2
Liquidity Raid Model
The image above shows an example of a long position being entered following a complete setup for the Liquidity Raid Modell.
The user must define the session in the settings (for this example it is 13:30-16:00 NY time).
During the session, the indicator will calculate the session high and session low. Following a “raid” of either the session high or session low (after the session has completed) the script will look for an entry at a recently formed breaker block.
If the session high is raided the script will look for short entries at a bearish breaker block. If the session low is raided the script will look for long entries at a bullish breaker block.
For Longs, the profit target options are:
Swing high
User inputted Lib level
For Longs, the stop loss options are:
Swing low
User inputted Lib level
Breaker block bottom
The image above shows the short version of the Liquidity Raid Model in action!
For Shorts, the profit target options are:
Swing Low
User inputted Lib level
For Shorts, the stop loss options are:
Swing High
User inputted Lib level
Breaker block top
Silver Bullet Model
The image above shows an example of a long position being entered following a complete setup for the Silver Bullet Modell.
During the session, the indicator will determine the higher timeframe bias. If the higher timeframe bias is bullish the strategy will look to enter long at an FVG that forms during the session. If the higher timeframe bias is bearish the indicator will look to enter short at an FVG that forms during the session.
For Longs, the profit target options are:
Nearest Swing High Above Entry
Previous Day High
For Longs, the stop loss options are:
Nearest Swing Low
Previous Day Low
The image above shows the short version of the Silver Bullet Model in action!
For Shorts, the profit target options are:
Nearest Swing Low Below Entry
Previous Day Low
For Shorts, the stop loss options are:
Nearest Swing High
Previous Day High
Order blocks
The image above shows indicator identifying and labeling order blocks.
The color of the order blocks, and how many should be shown, are configurable in the settings!
Breaker Blocks
The image above shows indicator identifying and labeling order blocks.
The color of the breaker blocks, and how many should be shown, are configurable in the settings!
Rejection Blocks
The image above shows indicator identifying and labeling rejection blocks.
The color of the rejection blocks, and how many should be shown, are configurable in the settings!
Fair Value Gaps
The image above shows indicator identifying and labeling fair value gaps.
The color of the fair value gaps, and how many should be shown, are configurable in the settings!
Additionally, you can select to only show fair values gaps that form after a liquidity sweep. Doing so reduces "noisy" FVGs and focuses on identifying FVGs that form after a significant trading event.
The image above shows the feature enabled. A fair value gap that occurred after a liquidity sweep is shown.
Market Structure
The image above shows the ICT Master Suite calculating market structure shots and break of structures!
The color of MSS and BoS, and whether they should be displayed, are configurable in the settings.
Displacements
The images above show indicator identifying and labeling displacements.
The color of the displacements, and how many should be shown, are configurable in the settings!
Equal Price Points
The image above shows the indicator identifying and labeling equal highs and equal lows.
The color of the equal levels, and how many should be shown, are configurable in the settings!
Previous Custom TF High/Low
The image above shows the ICT Master Suite calculating the high and low price for a user-defined timeframe. In this case the previous day’s high and low are calculated.
To illustrate the customizable timeframe function, the image above shows the indicator calculating the previous 4 hour high and low.
Liquidity Sweeps
The image above shows the indicator identifying a liquidity sweep prior to an upside breakout.
The image above shows the indicator identifying a liquidity sweep prior to a downside breakout.
The color and aggressiveness of liquidity sweep identification are adjustable in the settings!
Power Of Three
The image above shows the indicator calculating Po3 for two user-defined higher timeframes!
Macros
The image above shows the ICT Master Suite identifying the ICT macros!
ICT Macros are only displayable on the 5 minute timeframe or less.
Strategy Performance Table
In addition to a full-fledged TradingView backtest for any of the ICT strategy models the indicator offers, a quick-and-easy strategy table exists for the indicator!
The image above shows the strategy performance table in action.
Keep in mind that, because the ICT Master Suite is a strategy script, you can perform fully automatic backtests, deep backtests, easily add commission and portfolio balance and look at pertinent metrics for the ICT strategies you are testing!
Lite Mode
Traders who want the cleanest chart possible can toggle on “Lite Mode”!
In Lite Mode, any neon or “glow” like effects are removed and key levels are marked as strict border boxes. You can also select to remove box borders if that’s what you prefer!
Settings Used For Backtest
For the displayed backtest, a starting balance of $1000 USD was used. A commission of 0.02%, slippage of 2 ticks, a verify price for limit orders of 2 ticks, and 5% of capital investment per order.
A commission of 0.02% was used due to the backtested asset being a perpetual future contract for a crypto currency. The highest commission (lowest-tier VIP) for maker orders on many exchanges is 0.02%. All entered positions take place as maker orders and so do profit target exits. Stop orders exist as stop-market orders.
A slippage of 2 ticks was used to simulate more realistic stop-market orders. A verify limit order settings of 2 ticks was also used. Even though BTCUSDT.P on Binance is liquid, we just want the backtest to be on the safe side. Additionally, the backtest traded 100+ trades over the period. The higher the sample size the better; however, this example test can serve as a starting point for traders interested in ICT concepts.
Community Assistance And Feedback
Given the complexity and idiosyncratic applications of ICT concepts amongst its proponents, the ICT Master Suite’s built-in strategies and level identification methods might not align with everyone's interpretation.
That said, the best we can do is precisely define ICT strategy rules and concepts to a repeatable process, test, and apply them! Whether or not an ICT strategy is trading precisely how you would trade it, seeing the model in action, taking trades, and with performance statistics is immensely helpful in assessing predictive utility.
If you think we missed something, you notice a bug, have an idea for strategy model improvement, please let us know! The ICT Master Suite is an ongoing project that will, ideally, be shaped by the community.
A big thank you to the @PineCoders for their Time Library!
Thank you!
CPR by NKDCentral Pivot Range (CPR) Trading Strategy:
The Central Pivot Range (CPR) is a widely-used tool in technical analysis, helping traders pinpoint potential support and resistance levels in the market. By using the CPR effectively, traders can better gauge market trends and determine favorable entry and exit points. This guide explores how the CPR works, outlines its calculation, and describes how traders can enhance their strategies using an extended 10-line version of CPR.
What Really Central Pivot Range (CPR) is?
At its core, the CPR consists of three key lines:
Pivot Point (PP) – The central line, calculated as the average of the previous day’s high, low, and closing prices.
Upper Range (R1) – Positioned above the Pivot Point, acting as a potential ceiling where price may face resistance.
Lower Range (S1) – Found below the Pivot Point, serving as a potential floor where price might find support.
Advanced traders often expand on the traditional three-line CPR by adding extra levels above and below the pivot, creating up to a 10-line system. This extended CPR allows for a more nuanced understanding of the market and helps identify more detailed trading opportunities.
Applying CPR for Trading Success
1. How CPR is Calculation
The CPR relies on the previous day's high (H), low (L), and close (C) prices to create its structure:
Pivot Point (PP) = (H + L + C) / 3
First Resistance (R1) = (2 * PP) - L
First Support (S1) = (2 * PP) - H
Additional resistance levels (R2, R3) and support levels (S2, S3) are calculated by adding or subtracting multiples of the previous day’s price range (H - L) from the Pivot Point.
2. Recognizing the Market Trend
To effectively trade using CPR, it’s essential to first determine whether the market is trending up (bullish) or down (bearish). In an upward-trending market, traders focus on buying at support levels, while in a downward market, they look to sell near resistance.
3. Finding Ideal Entry Points
Traders often look to enter trades when price approaches key levels within the CPR range. Support levels (S1, S2) offer buying opportunities, while resistance levels (R1, R2) provide selling opportunities. These points are considered potential reversal zones, where price may bounce or reverse direction.
4. Managing Risk with Stop-Loss Orders
Proper risk management is crucial in any trading strategy. A stop-loss should be set slightly beyond the support level for buy positions and above the resistance level for sell positions, ensuring that losses are contained if the market moves against the trader’s position.
5. Determining Profit Targets
Profit targets are typically set based on the distance between entry points and the next support or resistance level. Many traders apply a risk-reward ratio, aiming for larger potential profits compared to the potential losses. However, if the next resistance and support level is far then middle levels are used for targets (i.e. 50% of R1 and R2)
6. Confirmation Through Other Indicators
While CPR provides strong support and resistance levels, traders often use additional indicators to confirm potential trade setups. Indicators such as moving averages can
help validate the signals provided by the CPR.
7. Monitoring Price Action At CPR Levels
Constantly monitoring price movement near CPR levels is essential. If the price fails to break through a resistance level (R1) or holds firm at support (S1), it can offer cues on when to exit or adjust a trade. However, a strong price break past these levels often signals a continued trend.
8. Trading Breakouts with CPR
When the price breaks above resistance or below support with strong momentum, it may signal a potential breakout. Traders can capitalize on these movements by entering positions in the direction of the breakout, ideally confirmed by volume or other technical indicators.
9. Adapting to Changing Market Conditions
CPR should be used in the context of broader market influences, such as economic reports, news events, or geopolitical shifts. These factors can dramatically affect market direction and how price reacts to CPR levels, making it important to stay informed about external market conditions.
10. Practice and Backtesting for Improvements
Like any trading tool, the CPR requires practice. Traders are encouraged to backtest their strategies on historical price data to get a better sense of how CPR works in different market environments. Continuous analysis and practice help improve decision-making and strategy refinement.
The Advantages of Using a 10-Line CPR System
An extended 10-line CPR system—comprising up to five resistance and five support levels—provides more granular control and insight into market movements. This expanded view helps traders better gauge trends and identify more opportunities for entry and exit. Key benefits include:
R2, S2 Levels: These act as secondary resistance or support zones, giving traders additional opportunities to refine their trade entries and exits.
R3, S3 Levels: Provide an even wider range for identifying reversals or trend continuations in more volatile markets.
Flexibility: The broader range of levels allows traders to adapt to changing market conditions and make more precise decisions based on market momentum.
So in Essential:
The Central Pivot Range is a valuable tool for traders looking to identify critical price levels in the market. By providing a clear framework for identifying potential support and resistance zones, it helps traders make informed decisions about entering and exiting trades. However, it’s important to combine CPR with sound risk management and additional confirmation through other technical indicators for the best results.
Although no trading tool guarantees success, the CPR, when used effectively and combined with practice, can significantly enhance a trader’s ability to navigate market fluctuations.
Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
