Moon Phases + Blood MoonWhat it is
This is a simple, time-based strategy that goes long on full moons and exits on the next new moon, while visually highlighting historically known “Blood Moon” (total lunar eclipse) dates. It’s built for exploratory testing of lunar timing effects on price, not for predictive claims.
Why it’s useful / originality
Most lunar scripts only mark phases. This one (1) computes lunar phases on the chart, (2) normalizes and flags Blood Moon days from a curated list, and (3) turns the phase changes into an executable strategy with clear, reproducible entry/exit rules and a configurable start date—so traders can quickly evaluate whether a lunar timing overlay adds any edge on their market/timeframe.
How it works (concept)
Moon phase detection: Uses Julian date conversion and standard astronomical approximations to determine the most recent phase change at each bar. The script classifies phase turns as +1 = New Moon and –1 = Full Moon, tracking the latest valid time to avoid lookahead.
Blood Moon tagging: A built-in array of UTC timestamps (total lunar eclipses) is date-matched to the current session and marked as “Blood Moon” when a full moon coincides with a listed date.
Signals & trades
Plot circles above/below bars: New Moon (above), Full Moon (below), Blood Moon (below, red).
Entry: Long at Full Moon once the bar time ≥ the user’s Start date.
Exit: Close the long on the next New Moon.
How to use
Add to your chart (non-monthly timeframes only).
Optionally adjust the Start date (default: 2001-12-31 UTC) to control the backtest window.
Use the color inputs to style New Moon / Full Moon / Blood Moon markers.
Evaluate performance on liquid symbols and timeframes that provide a sufficient number of phase cycles.
Default / publish settings
Initial capital: $10,000 (suggested)
Commission: 0.05% per trade (suggested)
Slippage: 1 tick (suggested)
Position sizing: TradingView strategy defaults (no leverage logic is added).
Timeframes: Intraday/Daily/Weekly supported. Monthly is blocked by design.
Chart type: Use standard chart types only (no Heikin Ashi, Renko, Kagi, P&F, Range) for signals/backtests.
Reading the chart
New Moon: soft gray circle above bars.
Full Moon: soft yellow circle below bars.
Blood Moon (if date-matched): soft red circle below bars.
The script also ensures symbol/timeframe context is visible—keep your chart clean so the markers are easy to interpret.
Limitations & important notes
This is a time-based heuristic. It does not forecast price and does not repaint via lookahead tricks; it avoids future leakage by anchoring to the last known phase time at each bar.
No non-standard chart signals. Using non-standard charts can produce unrealistic results.
Strategy properties like commission/slippage materially affect results—please set them to realistic values.
Backtests should include a large sample (ideally >100 trades over many cycles) to make statistics meaningful.
Past performance does not guarantee future results.
Open-source reuse / credits
Uses standard, public-domain techniques for Julian date conversion and lunar-phase approximations.
Blood Moon dates are incorporated as a hard-coded list for convenience; you may extend or adjust this list as needed.
No third-party proprietary code is reused.
Changelog / versioning
v1: Initial public release on Pine v6 with phase detection, Blood-Moon tagging, and a minimal long-only phase strategy.
Pesquisar nos scripts por "the script"
Recovery Zone Hedging [Starbots]Recovery Zone Hedging Strategy — Advanced Adaptive Hedge Recovery System
This strategy introduces an innovative zone-based hedge recovery approach tailored to TradingView’s single-direction trading model. Designed for serious traders and professionals, it combines multiple technical indicators with dynamic position sizing and adaptive take-profit mechanisms to manage drawdowns and maximize recovery efficiency.
How Recovery Zones Are Calculated
The strategy defines recovery zones as a configurable percentage distance from the last executed trade price. This percentage can be adjusted to suit different market volatility environments — wider zones for volatile assets, tighter zones for stable ones. When price moves into a recovery zone against the open position, the strategy places a hedge trade in the opposite direction to help recoup losses.
Dynamic Take-Profit Calculation
Take-profit targets are not fixed. Instead, they increase dynamically based on any accumulated losses from previous hedge trades. For example, if your initial target is 2%, but you have a $5 loss from prior hedges, the next take-profit target adjusts upward to cover both the loss and your profit goal, ensuring the entire hedge sequence closes in net profit.
Originality & Value
Unlike traditional hedging or recovery scripts that rely on static stop losses and fixed trade sizing, this strategy offers:
- Dynamic Hedge Entry Zones: Uses configurable percentage-based recovery zones that adapt to price volatility, allowing precise placement of hedge trades at meaningful reversal levels.
- Multi-Indicator Signal Fusion: Integrates MACD and Directional Movement Index (DMI) signals to confirm trade entries, improving signal accuracy and reducing false triggers.
- Exponential Position Sizing: Each hedge trade’s size grows exponentially using a customizable multiplier, accelerating loss recovery while carefully balancing capital usage.
- Adaptive Take-Profit Logic: The take-profit target adjusts dynamically based on accumulated losses and profit margins, ensuring that the entire hedge sequence closes with a net gain.
- Capital Usage Monitoring: A built-in dashboard tracks real-time equity consumption, preventing over-leveraging by highlighting critical capital thresholds.
- Fail-Safe Exit Mechanism: An optional forced exit beyond the last hedge zone protects capital in extreme market scenarios.
This strategy’s layered design and adaptive mechanisms provide a unique and powerful tool for traders seeking robust recovery systems beyond standard hedge or martingale methods.
How Components Work Together
- Entry Signals: The script listens for MACD line crossovers and DMI directional crosses to open an initial trade.
- Recovery Zones: If the market moves against the initial position, the strategy calculates a recovery zone a set percentage away and places a hedge trade in the opposite direction.
- Position Scaling: Each subsequent hedge trade increases in size exponentially according to the hedge multiplier, designed to recover all previous losses plus a profit.
- Take-Profit Target: Rather than a fixed target, the TP level is dynamically calculated considering current drawdown and desired profit margin, ensuring the entire hedge sequence closes profitably.
- Cycle Management: Trades alternate direction following the recovery zones until profit is realized or a maximum hedge count is reached. If needed, a forced stop-out limits risk exposure.
Key Benefits for Professional Traders
- Enhanced Risk Management: Real-time capital usage visualization helps maintain safe exposure levels.
- Strategic Hedge Recovery: The adaptive recovery zones and exponential sizing accelerate loss recoupment more efficiently than traditional fixed-step systems.
- Multi-Indicator Confirmation: Combining MACD and DMI reduces false signals and improves hedge timing accuracy.
- Versatility: Suitable for multiple timeframes and asset classes with adjustable parameters.
- Comprehensive Visuals: On-chart recovery zones, hedge levels, dynamic take-profits, and equity usage tables enable informed decision-making.
Recommended Settings & Use Cases
- Initial Position Size: 0.1–1% of account equity
- Recovery Zone Distance: 2–5% price movement
- Hedge Multiplier: 1.5–1.85x growth per hedge step
- Max Hedge Steps: 5–10 for controlled risk exposure
Ideal for trending markets where price retracements create viable recovery opportunities. Use caution in sideways markets to avoid extended hedge sequences.
Important Notes
- TradingView’s single-direction model means hedging is simulated via alternating trades.
- Position sizes grow rapidly—proper parameter tuning is essential to avoid over-leveraging.
This script is designed primarily for professional traders seeking an advanced, automated hedge recovery framework, offering superior capital efficiency and loss management.
DSL Strategy [DailyPanda]
Overview
The DSL Strategy by DailyPanda is a trading strategy that synergistically combines the idea from indicators to create a more robust and reliable trading tool. By integrating these indicators, the strategy enhances signal accuracy and provides traders with a comprehensive view of market trends and momentum shifts. This combination allows for better entry and exit points, improved risk management, and adaptability to various market conditions.
Combining ideas from indicators adds value by:
Enhancing Signal Confirmation : The strategy requires alignment between trend and momentum before generating trade signals, reducing false entries.
Improving Accuracy : By integrating price action with momentum analysis, the strategy captures more reliable trading opportunities.
Providing Comprehensive Market Insight : The combination offers a better perspective on the market, considering both the direction (trend) and the strength (momentum) of price movements.
How the Components Work Together
1. Trend Identification with DSL Indicator
Dynamic Signal Lines : Calculates upper and lower DSL lines based on a moving average (SMA) and dynamic thresholds derived from recent highs and lows with a specified offset. These lines adapt to market conditions, providing real-time trend insights.
ATR-Based Bands : Adds bands around the DSL lines using the Average True Range (ATR) multiplied by a width factor. These bands account for market volatility and help identify potential stop-loss levels.
Trend Confirmation : The relationship between the price, DSL lines, and bands determines the current trend. For example, if the price consistently stays above the upper DSL line, it indicates a bullish trend.
2. Momentum Analysis
RSI Calculation : Computes the RSI over a specified period to measure the speed and change of price movements.
Zero-Lag EMA (ZLEMA) : Applies a ZLEMA to the RSI to minimize lag and produce a more responsive oscillator.
DSL Application on Oscillator : Implements the DSL concept on the oscillator by calculating dynamic upper and lower levels. This helps identify overbought or oversold conditions more accurately.
Signal Generation : Detects crossovers between the oscillator and its DSL lines. A crossover above the lower DSL line signals potential bullish momentum, while a crossover below the upper DSL line signals potential bearish momentum.
3. Integrated Signal Filtering
Confluence Requirement : A trade signal is generated only when both the DSL indicator and oscillator agree. For instance, a long entry requires both an uptrend confirmation from the DSL indicator and a bullish momentum signal from the oscillator.
Risk Management Integration : The strategy uses the DSL indicator's bands for setting stop-loss levels and calculates take-profit levels based on a user-defined risk-reward ratio. This ensures that every trade has a predefined risk management plan.
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Originality and Value Added to the Community
Unique Synergy : While both indicators are available individually, this strategy is original in how it combines them to enhance their strengths and mitigate their weaknesses, offering a novel approach not present in existing scripts.
Enhanced Reliability : By requiring confirmation from both trend and momentum indicators, the strategy reduces false signals and increases the likelihood of successful trades.
Versatility : The customizable parameters allow traders to adapt the strategy to different instruments, timeframes, and trading styles, making it a valuable tool for a wide range of trading scenarios.
Educational Contribution : The script demonstrates an effective method of combining indicators for improved trading performance, providing insights that other traders can learn from and apply to their own strategies.
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How to Use the Strategy
Adding the Strategy to Your Chart
Apply the DSL Strategy to your desired trading instrument and timeframe on TradingView.
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Configuring Parameters
DSL Indicator Settings :
Length (len) : Adjusts the sensitivity of the DSL lines (default is 34).
Offset : Determines the look-back period for threshold calculations (default is 30).
Bands Width (width) : Changes the distance of the ATR-based bands from the DSL lines (default is 1).
DSL-BELUGA Oscillator Settings :
Beluga Length (len_beluga) : Sets the period for the RSI calculation in the oscillator (default is 10).
DSL Lines Mode (dsl_mode) : Chooses between "Fast" (more responsive) and "Slow" (smoother) modes for the oscillator's DSL lines.
Risk Management :
Risk Reward (risk_reward) : Defines your desired risk-reward ratio for calculating take-profit levels (default is 1.5).
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Interpreting Signals
Long Entry Conditions :
Trend Confirmation : Price is above the upper DSL line and the upper DSL band (dsl_up1 > dsl_dn).
Price Behavior : The last three candles have both their opens and closes above the upper DSL line.
Momentum Signal : The DSL-BELUGA oscillator crosses above its lower DSL line (up_signal), indicating bullish momentum.
Short Entry Conditions :
Trend Confirmation : Price is below the lower DSL line and the lower DSL band (dsl_dn < dsl_up1).
Price Behavior : The last three candles have both their opens and closes below the lower DSL band.
Momentum Signal : The DSL-BELUGA oscillator crosses below its upper DSL line (dn_signal), indicating bearish momentum.
Exit Conditions :
Stop-Loss : Automatically set at the DSL indicator's band level (upper band for longs, lower band for shorts).
Take-Profit : Calculated based on the risk-reward ratio and the initial risk determined by the stop-loss distance.
Visual Aids
Signal Arrows : Upward green arrows for long entries and downward blue arrows for short entries appear on the chart when conditions are met.
Stop-Loss and Take-Profit Lines : Red and green lines display the calculated stop-loss and take-profit levels for active trades.
Background Highlighting : The chart background subtly changes color to indicate when a signal has been generated.
Backtesting and Optimization
Use TradingView's strategy tester to backtest the strategy over historical data.
Adjust parameters to optimize performance for different instruments or market conditions.
Regularly review backtesting results to ensure the strategy remains effective.
OKX: MA CrossoverEXAMPLE Scripte from my stream , how to use OKX webhooks for create strategy on Pine with real\demo trading on your OKX account. This strategy only for test the functional forward orders to OKX. The backtest not included commisions and other.
OKX MA Crossover. This strategy generate JSONs for place orders on the exchange by alerts and webhooks.
In the script 2 function to generate entry and exit orders, and input parameters that needed for setup exchange.
Use it for test this stack and to write you own strategy for trade on the OKX Exchange.
ALMA/EMA/SRSI Strategy + IndicatorBack with another great high hit rate strategy!!
Disclaimer* This strategy was sampled using source code written by @ClassicScott , as referred to in the script, there is a clear line where the source code was scripted by myself.
This Strategy consists of three key factors, the ALMA, EMA crossover, and a Stochastic Rsi
ALMA: The Alma is the step line shown, turning green and red at select times. This average value gives general oversight of the macro movement of price action. and this particular one was coded by Mr.ClassicScott.
EMA crossover: At the input screen you are given an option of the fast and slow ema's. The default is solely for the hit rate and correlation to the Alma of this strategy. The arrows you see depicted on the chart are the crossover events happening.
Stochastic Rsi: The Stochastic Rsi is a stochastic value, using data sampled from the rsi. The use of this indicator in my strategy is to prevent entries when too overbought and oversold, as well as closures and vice versa, to prevent holding bags either way.
Fixed % TP: In the input screen you are given a take profit and stop loss percentage, for good R/R the hit rate will take a notch down, but with no R/R it will be near perfect.
How to use this:
Add it to your chart to get the strategy inputs. (The strategy is really only useful on a 15min TF. However the indicator within it can be used on anything at anytime!)
Watch the yellow and aqua moving averages, these are your ema's and crossover's will trigger signals based on your integer inputs.
Find Correlation between other leading indicators, as well as crossover's down/up and a red/green alma.
DO NOT use the arrows as buy/sell signals. These are simply to show ema's are crossing under or over. Momentum indicator's paired with this can be useful to determine if it could be a buy signal or sell signal.
Cheat Code's Notes:
Almost at 1000 boosts!!! I appreciate the support from everyone and I will keep trying my best to deliver quality strategies for the people.
-Cheat Code
BYBIT:BTCUSDT
Strategy Oil Z ScoreObjective is to find forward looking indicators to find good entries into major index's.
In similar vein to my Combo Z Score script I have implemented one looking at oil and oil volatility. Interestingly the script out performs WITHOUT applying the EMA in longer timeframes but under performs in shorter timeframes, for example 2007 vs 2019. Likely due to the bullish nature of the past decade (by and large). You have some options on the underlying included Oil vs OVX (Best), MOVE vs OVX and VIX vs OVX. Oil vs OVX out performs Combo Z Script. Favours Spy over QQQ or derivations (SPXL etc).
5min Williams Fractals scalping (3commas)Another strategy I'm learning Pine Script on. It is inspired by a MoneyZG youtube strategy called "Easy 5 Minute Scalping Strategy (Simple to Follow Scalping Trading Strategy)".
Again this is a one order per trade strategy compatible with the 3commas bot (works also with the free 3commas subscription). This strategy is based on the signals from Williams Fractals, taking the signals in reverse - red triangle indicates a bottom and hence we go long. The green triangle indicates a top so we go short. By default these signals are only accepted if they occur between the two Emas. However, you can also turn this off and when a WF signal comes in, only the current price has to be between the Emas. Stop loss is set to the current Ema slow and the take profit is a multiple of the distance to the slow ema.
Like previously I have added different filters as well as the ability to view essential things like the WF signal and Emas. I hope the script will help you to be more successful and if so it would be great if you could share here your setups, or tips on what would be good to refine to make it an even a more profitable strategy. Kind of a community approach so that we help each other out :).
Instructions for the 3commas connector:
1. First, you need to prepare 3commas Long/Short bots that will only listen to custom TV signals.
2. Inputs for the 3commas bot can be found at the end of the user inputs.
3. Once you have entered the required details into the inputs, turn on 3commas comments. They should appear on the chart (looks messy).
4. Now you can add the alert where you should paste the 3commas Webhook URL: 3commas.io
5. For the alert message text insert the placeholder {{strategy.order.comment}} and delete the rest.
6. Once the alert is saved, you can turn off those 3commas comments to have a clearer chart.
7. With a new alert, the bot and trade should launch.
In the near future I would like to publish more scripts that will carry similar elements as the first two, incl. compatibility with 3commas (I don't have access to another bot system). I will choose some strategies myself, but I will also be glad for some tips on what strategy would be good to do and is still missing here on Tradingview (short youtube videos or brief strategy manuals would be great).
Thanks and keep it up
PS: My screen values starting at Long Target Profit and ending at Pullback NOT greater than: 1.5; 1.5; 0; ON; 1; 2; OFF; 17; 36; ON; 0.05; ON; Chart; 14; 46; 50; 48.5; 51; OFF; 1; ON; 4; 2.
Price Change Scalping Strategy v1.0Introduction
This strategy uses a price rate of change (ROC) momentum calculation to determine the percent change in price between a defined range of bars. The calculated ROC value is then compared to the Upper Threshold and Lower Threshold values to determine if a trade setup is to be activated. If the threshold is crossed, a trade setup will occur based on the indicator settings. Entry, Take Profit, and Stop Loss prices are calculated and displayed on the chart. Once the Entry Price is crossed, a long or short position is created (depending on the direction) and once the Take Profit price is crossed, the position is closed. If the Entry Price is not crossed within a specific number of bars, the trade setup is canceled, and it will proceed to monitor price changes for the next set up.
How is it original and useful?
This strategy is unique in that the strategy version fully supports the TradingView backtester, which will enable you to perform experiments with various settings to evaluate performance using the historical chart data. The study version implements numerous custom alerts for you to build TradingView notifications around specific price action events and stay informed with market activity in real-time. Both script versions will provide the same configuration abilities where you can define:
Define a short or long trading strategy.
Price change data source and offset settings.
Your layering placement relative to the entry price.
Your trading parameters like take profit and stop loss offsets, exchange commission rates, trading start time, and order size multiplication for each layer.
Flexible trade eligibility rules that can use other chart indicators, like RSI or EMA, to exclude the selection of entry prices for trading.
The visibility of detailed statistics from the chart history pertaining to trading sessions started and closed, session durations, win rate, price action drops and bounces, as well as layer utilization.
How does it compare to other scripts in the Public Library?
The strategy offers a very detailed, comprehensive settings to address all types of markets found on TradingView where you can implement the price change scalping strategy. The strategy version can be considered the first of its kind on TradingView to leverage the backtester to provide informative, detailed performance measurements surrounding this unique trading strategy. The study version will contain numerous custom alerts to aid in your notification preferences and stay informed on the indicator's activities:
Price Crossed Above Threshold
Price Crossed Below Threshold
Enter Long Position
Exit Long Position
Enter Short Position
Exit Short Position
Price Crossed DCA Layer 1 (Long)
Price Crossed DCA Layer 2 (Long)
Price Crossed DCA Layer 3 (Long)
Price Crossed DCA Layer 4 (Long)
Price Crossed DCA Layer 5 (Long)
Price Crossed DCA Layer 6 (Long)
Price Crossed DCA Layer 7 (Long)
Price Crossed DCA Layer 8 (Long)
Price Crossed DCA Layer 1 (Short)
Price Crossed DCA Layer 2 (Short)
Price Crossed DCA Layer 3 (Short)
Price Crossed DCA Layer 4 (Short)
Price Crossed DCA Layer 5 (Short)
Price Crossed DCA Layer 6 (Short)
Price Crossed DCA Layer 7 (Short)
Price Crossed DCA Layer 8 (Short)
Strategy Results
The default settings are designed to define a "loose" price change settings to ensure that the indicator will render chart elements when first loaded as well as to allow the backtester to gather order executions and display performance summary. The strategy version is using $10,000 initial capital, a commission rate of 0.1% for both entries and exits, and a 1 tick slippage setting. It is also using 2.74506% of the equity with a Order Size Multiplier of 1.33, using 8 total DCA layers, and a take profit of 2% with no stop loss. All other settings are defaults.
It is recommended that the indicator be "tuned" for your specific market in order to best implement the price change strategy and obtain better desirable results. You do so by scrolling through the chart's history and observing moments when prices tend to move rapidly. Measure the number or bars it typcially takes for the price to change at a specific rate. Using this information, you can adjust the Price Change Settings accordingly to configure the indicator for the chart.
Always keep in mind that past performance may not be indicative of future results. Settings that seem favorable for one market may be found to be disastrous in another. Therefore, do take the time needed to understand how the settings will behave with the given chart symbol.
Enjoy! 😊👍
How to obtain access to the script?
You have two choices:
Use the "Website" link below to obtain access to this indicator, or
Send us a private message (PM) in TradingView itself.
Quickfingers Luc's Base Breaking Strategy v2.5Introduction
The strategy attempts to implement a popular price action strategy by Luc Thomas (a.k.a. Quickfingers Luc) typically referred to as a QFL base-breaking strategy. The strategy revolves around price action movements that reveal “bases”, which are price levels of support that have a significant, rapid price surges called “bounces”. Once a base is revealed, the base price level is used as reference to implement multiple entries below the base using a layering technique of dollar-cost averaging to place multiple limit orders at various price levels below the base price. As price action breaks below the base price, the limit orders will be filled, and the take profit, breakeven and stop loss prices will be recalculated.
How is it original and useful?
This strategy is unique in that the strategy version fully supports the TradingView backtester, which will enable you to perform experiments with various settings to evaluate performance using the historical chart data. The study version implements numerous custom alerts for you to build TradingView notifications around specific price action events and stay informed with market activity in real-time. Both script versions will provide the same configuration abilities where you can define:
Base confirmation settings, including volume analysis.
Your preferred layering strategy of either Dollar-cost averaging (DCA) or grid-like layers along with precise layer placement.
Your trading parameters like take profit and stop loss offsets, exchange commission rates, trading start time, and position size multiplication for each layer.
Flexible trade eligibility rules that can use other chart indicators, like RSI or EMA, to exclude the selection of base prices for trading.
The visibility of detailed statistics from the chart history pertaining to trading sessions started and closed, session durations, win rate, price action drops and bounces, as well as layer utilization.
How does it compare to other scripts in the Public Library?
The strategy offers a very detailed, comprehensive settings to address all types of markets found on TradingView where you can implement the QFL base-breaking strategy. The strategy version can be considered the first of its kind on TradingView to leverage the backtester to provide informative, detailed performance measurements surrounding this unique trading strategy. The study version will contain numerous custom alerts to aid in your notification preferences and stay informed on the indicator's activities:
Base Created
Base Cracked
Base Respected
Any Layer Cracked
Layer 1 Cracked
Layer 2 Cracked
Layer 3 Cracked
Layer 4 Cracked
Layer 5 Cracked
Layer 6 Cracked
Layer 7 Cracked
Layer 8 Cracked
Layer 9 Cracked
Layer 1 Respected
Layer 2 Respected
Layer 3 Respected
Layer 4 Respected
Layer 5 Respected
Layer 6 Respected
Layer 7 Respected
Layer 8 Respected
Take Profit Crossed
Stop Loss Crossed
What does it do and how does it do it?
It is recommended that you start with a chart that is on an hourly timeframe with the "Scale Price Chart Only" chart setting enabled. When applied to the chart for the first time, the default settings will work to render base price levels in orange and 8 DCA layers in blue using a Fibonacci-like sequence for the deviation offset relative to the base price. As you scroll through the chart's history you should see price action crossing the DCA layers, denoted with blue triangles, and a green take-profit line will render with green triangle denoting the crossing. Lastly, when a trade session begins upon the crossing of the first layer, the indicator will continue to identify base price levels, but the color of the price lines will be gray. When the trade session concludes upon the crossing of the take profit line, the indicator will switch the most recent base price line from gray to orange to make it active and eligible for trading.
As price action develops, the indicator will use the "Base Confirmation Settings" to look back by counting the number of bars to the left and right of a pivot low point, measure the price drops and bounces, and volume amounts to validate that they are within the specified values. If so, the indicator will draw an orange triangle beneath the candle bar to denote it as the pivot low point and begin rendering the orange line as the base price. The DCA layers will be calculated and offset relative to the base price using thin blue lines.
Optionally, the breakeven price line will be drawn to help visualize the true breakeven price which takes into consideration the exchange fees being applied. Base line, take profit, stop loss and DCA layer crossings will be denoted with colorful shapes to help visually recognize the events on the chart.
The volume is validated only at the pivot low candle. It will measure the volume against the moving average to determine base confirmation. A volume factor of 1 will mean that the volume must be at least the same value as the moving average value. A volume factor of 2 means it must be twice the moving average value.
Lastly, the very last bar will render a table of statistics that summarize all the events that have taken place since the indicator began simulating trading sessions from the chart's history.
Strategy Results
The default settings are designed to define a "weak" QFL base to ensure that the indicator will render chart elements when first loaded as well as to allow the backtester to gather order executions and display performance summary. The strategy version is using $10,000 initial capital, a commission rate of 0.1% for both entries and exits, and a 1 tick slippage setting. It is also using 3.4887% of the equity with a Position Size Multiplier of 1.35, using 8 total DCA layers, and a take profit of 5% with no stop loss. All other settings are defaults.
It is recommended that the indicator be "tuned" for your specific market in order to best implement the QFL trading strategy and obtain better desirable results. You do so by using the statistics table and observe the Mean Price Drop and Bounce values to learn what the indicator is detecting when it measures from the pivot low points. Using this information, you can adjust the Base Confirmation Settings accordingly, along with any volume specifications you require, to configure the indicator for the chart.
Always keep in mind that past performance may not be indicative of future results. Settings that seem favorable for one market may be found to be disastrous in another. Therefore, do take the time needed to understand how the settings will behave with the given chart symbol.
Enjoy! 😊👍
How to obtain access to the script?
You have two choices:
Use the "Website" link below to obtain access to this indicator, or
Send us a private message (PM) in TradingView itself.
Quansium Series A BacktestThis comes with preconfigured setups or strategies. Simply choose one from our list based on the timeframe it was made for. Leverage can be changed; to keep trading safe, a maximum of 2 is allowed. In our findings, this was able to trade crypto (specifically BTC ), MES (Micro E-mini S&P 500 Index Futures ), and stocks. It is important to know that setups A, B, C, and D use variable position sizing, and dynamic stop loss/trailing stop/take profit, these parameters are provided through the alerts. The rest of the strategies were created with a simpler approach in mind, just plainly entry/exits signals.
Quansium as a framework:
Price reformat: we take the price source (Open, Close, High, Low) and remove any noise that affects the accuracy of our signals.
Time awareness: we take several time periods of the data on the chart such as start, end, and whole. We use this to add more depth to our signals.
Position size: our backtest tries to recreate as much as the real world trades as possible so our position is determined by the current equity. We also use the volatility of the market to increase or decrease our exposure or risk.
Risk awareness: stop loss, take profit, trailing stop are the risk exits we use to provide our users some peace of mind. These parameters are totally dynamic and follow the same behavior of the market.
Signals filtering: to make almost non-existent any errors and increase the quality of our trades, our indicators go through multiple phases, this avoid double entries or early exits, and help maintain a record of what has transpired and what’s currently taking place.
Indicators: whenever we can we use custom code or our own functions instead of the defaults ones provided. This gives us total control of what we’re trying to achieve. In many cases we tend to combine several indicators’ logic into one creating a more personalized take on it.
Easiness: since we started our main goal has been to provide the easiest and fastest way to alerts’ creation. It has taken us years to reach this level where now we already provide a list of preset strategies so the user doesn’t have to spend much time tinkering with scripts and more on other matters, because we know life is more than just trading.
Raw signals: we provide the option to turn off as much of our advanced features such as stop loss, take profit, trailing stop, dynamic sizing, etc, etc for a simple approach. Trade signals still go through the signals filtering method mentioned above,
Timeframe pairing: we take trading very seriously, by no way we’ll want the user to lose money (although such thing is expected because past results aren’t an indicative of futures ones), through years of experience we have found what are usually common mistakes the user makes, this feature allows us to only activate the strategy if the right timeframe is chosen.
Trend filters: through the years we have improved the arts of the trend. We like to keep things simple but yet powerful. We observe the macro and micro trend of the security. This helps confirm we are entering at the desirable timing. We also incorporate volume and volatility into decision making, we simply programmed it to trade when these are increasing and higher than the average values observed in both the short and long term. Finally we take into account the strength of the pair to make our final choice of whether to enter or wait, and if anything flashes contrary movement then we cancel the upcoming signal and stop monitoring until the next one comes along.
Full automated risk: stop loss, take profit, and trailing stops usually are set in percentages, and optimized even more using the current market behavior to become more adaptive. But always remains some sort of fixation, so the user must choose a value somewhere. This is where our framework shines the most, as previously mentioned before when we take time into our calculations, we use several periods to observe performance and get values that keep our risk exits natural and closest to the flow of the market itself.
Setups:
A: Centered oscillator with the difference of several moving averages with more sensitive settings. Momentum focused.
B: Centered oscillator using simple moving averages. Trend-Following focused.
C: Centered oscillator using smoothed data with the help of faster moving averages. Trend-Following focused.
D: Centered oscillator with the difference of several moving averages with less sensitive settings. Trend-Following focused.
E: Centered oscillator with the difference of moving averages where the standard deviation is applied first. It uses less sensitive settings. Trend-Following focused.
F: Finds the relationship between multiple readings of the price’s relative strength to better pin-point downs and ups. Trend-Following focused.
G: Centered oscillator with the difference of moving averages where the standard deviation is applied first. It uses more sensitive settings. Momentum focused.
H: Multiple centered oscillators using various moving averages. Trend-Following focused.
I: Centered oscillator using simple moving averages. Momentum focused.
Note: The framework is composed of almost 1000 lines of code as compared to each indicator that makes up the setup which is around 10. The power from Quansium doesn't come from the strategies themselves but rather the overall system that turns simple signals into complex and advanced trades.
Strategy Tester:
Initial Capital: chosen value is $20,000, as an approximate to Bitcoin’s ATH (All-Time High). In previous iterations we noticed some trades won’t go through if the capital was less than the ATH.
Order Size: 100% of equity (although the script controls this, and this is of no regards to the results).
Pyramiding: 1, system doesn’t place multiple entries in a row, only one at a time.
Commission: This simulates order execution with custom trading fees. Commissions are turned off by default because this script works in various markets and each operates differently. In order to reach results that are close to real world conditions, it is imperative the user fills this based upon their broker or exchange data.
When we started, we were focused on finding the best indicator, or creating it ourselves. After years we came to realize that the secret is not in which indicator you use but the framework behind it. All strategies have bad, good, best, worst performance periods. The key of a good system is to help keep you safe when it’s down and maximize your potential when it’s up. We hope this material at the very minimum inspires you to keep going and not lose faith, because it is not the smartest who win but those who persevere.
TTM Scalper Strategy [SystemAlpha]This is a strategy based on TTM scalper indicator. Instead of using just the normal buy and sell signal, we added an option to use trend filters, trailing stop loss and take profit targets.
The TTM scalper indicator of John Carter’s Scalper Buys and Sells was originally created by HPotter and is as a close approximation of the one described in his book Mastering the Trade.
In this study you have a choice of:
Trend Filters:
- Average Directional Index ( ADX ) – buy when price is trend is up and sell when trend is down.
- Moving Average (MA) – buy when price close above the defined moving average and sell when price close below moving average
- Parabolic SAR – buy when SAR is above price is above price and sell when SAR is below price.
- All - Use ADX , MA and SAR as filters
For MA Filter , you can use the “TF MA Type” and "TF MA Period" parameter to select Simple or Exponential Moving Average and length.
Stop Loss:
- Average True Range (ATR) – ATR % stop as trailing stop loss.
- Parabolic SAR ( SAR ) – Parabolic SAR adapted as trailing stop loss.
For ATR , you can use the “ATR Trailing Stop Multiplier” parameter to set an initial offset for trailing stop loss.
Take Profit Target:
- Average True Range (ATR) – ATR % stop as trailing stop loss.
- Standard % – Percent as target profit
For ATR , you can use the “ATR Take Profit Multiplier” parameter to set an initial offset for trailing stop loss.
Additional feature include:
- Show Bar Colors
STRATEGY ONLY:
- Set back test date range
- Set trade direction - Long, Short or Both
- Use timed exit - Select method and bars
- Method 1: Exit after specified number of bars.
- Method 2: Exit after specified number of bars, ONLY if position is currently profitable.
- Method 3: Exit after specified number of bars, ONLY if position is currently losing.
TradingView Links:
Alerts:
How to use:
1. Apply the script by browsing through Indicators --> Invite-Only scripts and select the indicator
2. Once loaded, click the gear (settings) button to select/adjust the parameters based on your preference.
3. Wait for the next BUY or SELL signal to enter the trade!
Disclaimer:
The indicator and signals generated do not constitute investment advice; are provided solely for informational purposes and therefore is not an offer to buy or sell a security; are not warranted to be correct, complete or accurate; and are subject to change without notice.
A.I.Driven TradersAI Model Trades for 20190612The entry and exit levels here are NOT derived from any specific indicator but are coming from our A.I. driven proprietary models.
This is an attempt at exploring the trading community here at TradingView and sharing our daily trading plans published at our site with the community here in the form a Pine Script - just starting and learning this platform. Please help point out any obvious errors or gotchas committed in the scripts. Thanks and have a great trading day!
**** The Trading Plan Published for today ****
>>>> Medium-Frequency Models: <<<<< For today, Wednesday 06/12, our medium-frequency models indicate using the 2895 as a pivot point - opening a long on a break above 2895, and opening a short on a break below 2895 (wait for a close on at least a five minute chart to determine the break), both sides with a 9-point trailing stop.
Note: For the trades to trigger, the breaks should occur during the regular session hours starting at 9:30am ET. By design, these models do NOT open any new positions after 3:45pm. Only one open position at any given time.
>>>>> Aggressive Intraday Models: <<<<< For today, Wednesday 06/12, our aggressive intraday models indicate going long on a break above 2892 or 2875 with an 6-point trailing stop, and going short on a break below 2887 or 2878 with an 8-point trailing stop.
Note: For the trades to trigger, the breaks should occur during regular session hours starting at 9:30am ET. Due to the intraday nature of these aggressive models, they indicate closing any open trades at 3:55pm and remaining flat into the session close. No opening of new positions after 3:45pm. Only one open position at any given time.
SimpleCrossOver_BotThis is a simple example of how you can compile your own strategy
This script contains the code for alerts and for backtesting.
In order to use the backtester, comment out the sections to be used for signals, and comment in the sections to be used on the back tester, and visa versa for using the script for alerts in order to automate your own bot.
Test Strategy 1This script takes advantage of some of the most widely used indicators but with a twist. I will only continue to improve the script with time. Currently, the best TF is the 1D for this script. Enjoy!
MP ZeroLag EMANew script based on zlema. Hopefully responds better tot ake advantage of margin trading. As usual, commands for both spot trading and margin trading are included, just need to comment or uncomment (using // ) which you prefer. They are just labels so both work in the same way (long/buy, short/sell). Also added some flair to pretty it up a bit, and yes, those divergences are in fact functional, but not really part of the script (disclosure- the divergences are taken from DonovanWall's ideas, full credit here). There is a "new stuff" section, which you CAN use, but right now it was for art and introduced way too many functions at once to be of any use, but feel free to explore as an Easter Egg :)
Autoview friendly in design :)
As usual, all proceeds go to the betterment of these scripts as well as my upcoming surgery (Carpel Tunnel Syndrome, yuck)
1Dsg49Zt2FQ9BnUHrmXQwvhL5dd3teqa7g
ltc addy- LYUpgsHSHnKeYdNaj9bu9prK4QsnJXEQtP
pinkcoin addy- 2PoeXyAk3rF9FmMC8azme2mGzMYsEiZ5eS
C320up Strategy Tester Start TimeC320up Strategy Tester Start Time
This is a little snippet you can paste into your Strategy to set the testing start date and time.
It is not a Strategy per se, though is an example with the timestamp script included.
Instructions are fairly straight forward, and are listed in the script.
If for some reason you also wanted an end date, that too is possible. Just leave a note in the comments.
Disclaimer: We searched for a similar script on TV, and could not find anything at this point in time.
You can set your preferred date and time in the input section of the settings.
Enjoy!
CCI & MFI Strategy: No EMAAlternate version of
Published for client testing:
Changes
Removed EMA filtering logic from the script.
1M XAU Cumulative Delta Volume with OB Breakouts
### Overview
This is a **session-based CVD strategy** built around the **00:00–07:00 CEST range**. It finds the high/low of that session, turns them into **adaptive ATR-based support (yellow)** and **resistance (purple)** zones, and trades only **CVD-confirmed reversals** off those levels.
---
### How it Works
* For each day, the script:
* Builds a 00:00–07:00 CEST **profile high/low**.
* Creates a **support zone** around the session low and a **resistance zone** around the session high.
* Using lower timeframe data, it reconstructs **Cumulative Volume Delta (CVD)** and a **recent delta** filter.
* It arms “pending” states when price **enters a zone from the correct side**, then confirms:
* **BUY (long):** price reclaims above support and recent CVD is strongly positive.
* **SELL (short):** price rejects below resistance and recent CVD is strongly negative.
Only these two CVD signals (`buySignal` / `sellSignal`) open trades.
---
### Strategy Logic
* **Entries**
* `buySignal` → open **long** (if flat).
* `sellSignal` → open **short** (if flat).
* No pyramiding; one position at a time.
* **Exits (only TP & SL)**
* Long: TP at `avg_price * (0.5 + TP%)`, SL at `avg_price * (1 – SL%)`.
* Short: TP at `avg_price * (0.5 – TP%)`, SL at `avg_price * (1 + SL%)`.
* No opposite-signal exits.
---
### Extras
* **Reversal markers** on yellow/purple zones and **breakout/retest markers** are plotted for context and alerts but **do not trigger entries**.
* Zone width and “thickening” are ATR-based so important touches and near-touches are easy to see.
* Only suited for **1m intraday scalping** (e.g. XAU/USD), but can be tested on other markets/timeframes.
Oracle Protocol — Arch Public (Testing Clone) Oracle Protocol — Arch Public Series (testing clone)
This model implements the Arch Public Oracle structure: a systematic accumulation-and-distribution engine built around a dynamic Accumulation Cost Base (ACB), strict profit-gate exit logic, and a capital-bounded flywheel reinvestment system.
It is designed for transparent execution, deterministic behaviour, and rule-based position management.
Core Function Set
1. Accumulation Framework (ACB-Driven)
The accumulation engine evaluates market movement against defined entry conditions, including:
Percentage-based entry-drop triggers
Optional buy-below-ACB mode
Capital-gated entries tied to available ledger balance
Fixed-dollar and min-dollar entry rules (as seen in Arch public materials)
Automated sizing through flywheel capital
Range-bounded ledger for controlled backtesting input
Each qualifying buy updates the live ACB, maintains the internal ledger, and forms the next reference point for exit evaluation.
No forecasting mechanisms are included.
2. Profit-Gate Exit System
Exits are governed by the standard Arch public approach:
A sealed ACB reference for threshold evaluation
Optional live-ACB visibility
Profit-gate triggers defined per asset class
Candle-confirmation integration (“ProfitGate + Candle” mode)
Distribution only when the smallest active threshold is met
This provides a consistent cadence with published Arch diagrams and PDFs.
3. Once-Per-Rally Governance
After a distribution, the algorithm locks until price retraces below the most recent accumulation base.
Only after re-arming can the next profit gate activate.
This prevents over-frequency selling and aligns with the public-domain Oracle behaviour.
4. Quiet-Bars & Threshold Cluster Control
A volatility-stabilisation layer prevents multiple exits from micro-fluctuations or transient spikes.
This ensures clean execution during fast markets and high volatility.
5. Flywheel Reinvestment
Distribution proceeds automatically return to the capital pool where permitted, creating a closed system of:
Entry sizing
Exit proceeds
Ledger-managed capital state
All sizing respects capital boundaries and does not breach dollar floors or overrides.
6. Automation Hooks and Integration
The script exposes:
3Commas-compatible JSON sizing
Entry/exit signalling via alertcondition()
Deterministic event reporting suitable for external automation
This allows consistent deployment across automated execution environments.
7. Visual Tooling
Optional displays include:
Live ACB line
Exit-guide markers
Capital, state, and ledger panels
Realized/unrealized outcome tracking based on internal logic only
Visual components do not influence execution rules.
Operating Notes
This model is rule-based, deterministic, and non-predictive.
It executes only according to the explicit thresholds, capital limits, and state transitions defined within the script.
No discretionary or forward-looking logic is included.
ATH대비 지정하락률에 도착 시 매수 - 장기홀딩 선물 전략(ATH Drawdown Re-Buy Long Only)본 스크립트는 과거 하락 데이터를 이용하여, 정해진 하락 %가 발생하는 경우 자기 자본의 정해진 %만큼을 진입하게 설계되어진 스트레티지입니다.
레버리지를 사용할 수 있으며 기본적으로 셋팅해둔 값이 내장되어있습니다.(자유롭게 바꿔서 쓰시면 됩니다.) 추가적으로 2번의 진입 외에도 다른 진입 기준, 진입 %를 설정하실 수 있으며 - ChatGPT에게 요청하면 수정해줄 것입니다.
실제 사용용도로는 KillSwitch 기능을 꺼주세요. 바 돋보기 기능을 켜주세요.
ATH Drawdown Re-Buy Long Only 전략 설명
1. 전략 개요
ATH Drawdown Re-Buy Long Only 전략은 자산의 역대 최고가(ATH, All-Time High)를 기준으로 한 하락폭(드로우다운)을 활용하여,
특정 구간마다 단계적으로 롱 포지션을 구축하는 자동 재매수(Long Only) 전략입니다.
본 전략은 다음과 같은 목적을 가지고 설계되었습니다.
급격한 조정 구간에서 체계적인 분할 매수 및 레버리지 활용
ATH를 기준으로 한 명확한 진입 규칙 제공
실시간으로
평단가
레버리지
청산가 추정
계좌 MDD
수익률
등을 시각적으로 제공하여 리스크와 포지션 상태를 직관적으로 확인할 수 있도록 지원
※ 본 전략은 교육·연구·백테스트 용도로 제공되며,
어떠한 형태의 투자 권유 또는 수익을 보장하지 않습니다.
2. 전략의 핵심 개념
2-1. ATH(역대 최고가) 기준 드로우다운
전략은 차트 상에서 항상 가장 높은 고가(High)를 ATH로 기록합니다.
새로운 고점이 형성될 때마다 ATH를 갱신하고, 해당 ATH를 기준으로 다음을 계산합니다.
현재 바의 저가(Low)가 ATH에서 몇 % 하락했는지
현재 바의 종가(Close)가 ATH에서 몇 % 하락했는지
그리고 사전에 설정한 두 개의 드로우다운 구간에서 매수를 수행합니다.
1차 진입 구간: ATH 대비 X% 하락 시
2차 진입 구간: ATH 대비 Y% 하락 시
각 구간은 ATH가 새로 갱신될 때마다 한 번씩만 작동하며,
새로운 ATH가 생성되면 다시 “1차 / 2차 진입 가능 상태”로 초기화됩니다.
2-2. 첫 포지션 100% / 300% 특수 규칙
이 전략의 중요한 특징은 **“첫 포지션 진입 시의 예외 규칙”**입니다.
전략이 현재 어떠한 포지션도 들고 있지 않은 상태에서
최초로 롱 포지션을 진입하는 시점(첫 포지션)에 대해:
기본적으로는 **자산의 100%**를 기준으로 포지션을 구축하지만,
만약 그 순간의 가격이 ATH 대비 설정값 이상(예: 약 –72.5% 이상 하락한 상황) 이라면
→ 자산의 300% 규모로 첫 포지션을 진입하도록 설계되어 있습니다.
이 규칙은 다음과 같이 동작합니다.
첫 진입이 1차 드로우다운 구간에서 발생하든,
첫 진입이 2차 드로우다운 구간에서 발생하든,
현재 하락폭이 설정된 기준 이상(예: –72.5% 이상) 이라면
→ “이 정도 하락이면 첫 진입부터 더 공격적으로 들어간다”는 의미로 300% 규모로 진입
그 이하의 하락폭이라면
→ 첫 진입은 100% 규모로 제한
즉, 전략은 다음 두 가지 모드로 동작합니다.
일반적인 상황의 첫 진입: 자산의 100%
심각한 드로우다운 구간에서의 첫 진입: 자산의 300%
이 특수 규칙은 깊은 하락에서는 공격적으로, 평소에는 상대적으로 보수적으로 진입하도록 설계된 것입니다.
3. 전략 동작 구조
3-1. 매수 조건
차트 상 High 기준으로 ATH를 추적합니다.
각 바마다 해당 ATH에서의 하락률을 계산합니다.
사용자가 설정한 두 개의 드로우다운 구간(예시):
1차 구간: 예를 들어 ATH – 50%
2차 구간: 예를 들어 ATH – 72.5%
각 구간에 대해 다음과 같은 조건을 확인합니다.
“이번 ATH 구간에서 아직 해당 구간 매수를 한 적이 없는 상태”이고,
현재 바의 저가(Low)가 해당 구간 가격 이하를 찍는 순간
→ 해당 바에서 매수 조건 충족으로 간주
실제 주문은:
해당 구간 가격에 맞춰 롱 포지션 진입(리밋/시장가 기반 시뮬레이션) 으로 처리됩니다.
3-2. ATH 갱신과 진입 기회 리셋
차트 상에서 새로운 고점(High)이 기존 ATH를 넘어서는 순간,
ATH가 갱신되고,
1차 / 2차 진입 여부를 나타내는 내부 플래그가 초기화됩니다.
이를 통해, 시장이 새로운 고점을 돌파해 나갈 때마다,
해당 구간에서 다시 한 번씩 1차·2차 드로우다운 진입 기회를 갖게 됩니다.
4. 포지션 사이징 및 레버리지
4-1. 계좌 자산(Equity) 기준 포지션 크기 결정
전략은 현재 계좌 자산을 다음과 같이 정의하여 사용합니다.
현재 자산 = 초기 자본 + 실현 손익 + 미실현 손익
각 진입 구간에서의 포지션 가치는 다음과 같이 결정됩니다.
1차 진입 구간:
“자산의 몇 %를 사용할지”를 설정값으로 입력
설정된 퍼센트를 계좌 자산에 곱한 뒤,
다시 전략 내 레버리지 배수(Leverage) 를 곱하여 실제 포지션 가치를 계산
2차 진입 구간:
동일한 방식으로, 독립된 퍼센트 설정값을 사용
즉, 포지션 가치는 다음과 같이 계산됩니다.
포지션 가치 = 현재 자산 × (해당 구간 설정 % / 100) × 레버리지 배수
그리고 이를 해당 구간의 진입 가격으로 나누어 실제 수량(토큰 단위) 를 산출합니다.
4-2. 첫 포지션의 예외 처리 (100% / 300%)
첫 포지션에 대해서는 위의 일반적인 퍼센트 설정 대신,
다음과 같은 고정 비율이 사용됩니다.
기본: 자산의 100% 규모로 첫 포지션 진입
단, 진입 시점의 ATH 대비 하락률이 설정값 이상(예: –72.5% 이상) 일 경우
→ 자산의 300% 규모로 첫 포지션 진입
이때 역시 다음 공식을 사용합니다.
포지션 가치 = 현재 자산 × (100% 또는 300%) × 레버리지
그리고 이를 가격으로 나누어 실제 진입 수량을 계산합니다.
이 규칙은:
첫 진입이 1차 구간이든 2차 구간이든 동일하게 적용되며,
“충분히 깊은 하락 구간에서는 첫 진입부터 더 크게,
평소에는 비교적 보수적으로” 라는 운용 철학을 반영합니다.
4-3. 실레버리지(Real Leverage)의 추적
전략은 각 바 단위로 다음을 추적합니다.
바가 시작할 때의 기존 포지션 크기
해당 바에서 새로 진입한 수량
이를 바탕으로, 진입이 발생한 시점에 다음을 계산합니다.
실제 레버리지 = (포지션 가치 / 현재 자산)
그리고 차트 상에 예를 들어:
Lev 2.53x 와 같은 형식의 레이블로 표시합니다.
이를 통해, 매수 시점마다 실제 계좌 레버리지가 어느 정도였는지를 직관적으로 확인할 수 있습니다.
5. 시각화 및 모니터링 요소
5-1. 차트 상 시각 요소
전략은 차트 위에 다음과 같은 정보를 직접 표시합니다.
ATH 라인
High 기준으로 계산된 역대 최고가를 주황색 선으로 표시
평단가(평균 진입가) 라인
현재 보유 포지션이 있을 때,
해당 포지션의 평균 진입가를 노란색 선으로 표시
추정 청산가(고정형 청산가) 라인
포지션 수량이 변화하는 시점을 감지하여,
당시의 평단가와 실제 레버리지를 이용해 근사적인 청산가를 계산
이를 빨간색 선으로 차트에 고정 표시
포지션이 없거나 레버리지가 1배 이하인 경우에는 청산가 라인을 제거
매수 마커 및 레이블
1차/2차 매수 조건이 충족될 때마다 해당 지점에 매수 마커를 표시
"Buy XX% @ 가격", "Lev XXx" 형태의 라벨로
진입 비율과 당시 레버리지를 함께 시각화
레이블의 위치는 설정에서 선택 가능:
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
5-2. 우측 상단 정보 테이블
차트 우측 상단에는 현재 계좌·포지션 상태를 요약한 정보 테이블이 표시됩니다.
대표적으로 다음 항목들이 포함됩니다.
Pos Qty (Token)
현재 보유 중인 포지션 수량(토큰 기준, 절대값 기준)
Pos Value (USDT)
현재 포지션의 시장 가치 (수량 × 현재 가격)
Leverage (Now)
현재 실레버리지 (포지션 가치 / 현재 자산)
DD from ATH (%)
현재 가격 기준, 최근 ATH에서의 하락률(%)
Avg Entry
현재 포지션의 평균 진입 가격
PnL (%)
현재 포지션 기준 미실현 손익률(%)
Max DD (Equity %)
전략 전체 기간 동안 기록된 계좌 기준 최대 손실(MDD, Max Drawdown)
Last Entry Price
가장 최근에 포지션을 추가로 진입한 직후의 평균 진입 가격
Last Entry Lev
위 “Last Entry Price” 시점에서의 실레버리지
Liq Price (Fixed)
위에서 설명한 고정형 추정 청산가
Return from Start (%)
전략 시작 시점(초기 자본) 대비 현재 계좌 자산의 총 수익률(%)
이 테이블을 통해 사용자는:
현재 계좌와 포지션의 상태
리스크 수준
누적 성과
를 직관적으로 파악할 수 있습니다.
6. 시간 필터 및 라벨 옵션
6-1. 전략 동작 기간 설정
전략은 옵션으로 특정 기간에만 전략을 동작시키는 시간 필터를 제공합니다.
“Use Date Range” 옵션을 활성화하면:
시작 시각과 종료 시각을 지정하여
해당 구간에 한해서만 매매가 발생하도록 제한
옵션을 비활성화하면:
전략은 전체 차트 구간에서 자유롭게 동작
6-2. 진입 라벨 위치 설정
사용자는 매수/레버리지 라벨의 위치를 선택할 수 있습니다.
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
이를 통해 개인 취향 및 차트 가독성에 맞추어
시각화 방식을 유연하게 조정할 수 있습니다.
7. 활용 대상 및 사용 예시
본 전략은 다음과 같은 목적에 적합합니다.
현물 또는 선물 롱 포지션 기준 장기·스윙 관점 추매 전략 백테스트
“고점 대비 하락률”을 기준으로 한 규칙 기반 운용 아이디어 검증
레버리지 사용 시
계좌 레버리지·청산가·MDD를 동시에 모니터링하고자 하는 경우
특정 자산에 대해
“새로운 고점이 형성될 때마다
일정한 규칙으로 깊은 조정 구간에서만 분할 진입하고자 할 때”
실거래에 그대로 적용하기보다는,
전략 아이디어 검증 및 리스크 프로파일 분석,
자신의 성향에 맞는 파라미터 탐색 용도로 사용하는 것을 권장합니다.
8. 한계 및 유의사항
백테스트 결과는 미래 성과를 보장하지 않습니다.
과거 데이터에 기반한 시뮬레이션일 뿐이며,
실제 시장에서는
유동성
슬리피지
수수료 체계
강제청산 규칙
등 다양한 변수가 존재합니다.
청산가는 단순화된 공식에 따른 추정치입니다.
거래소별 실제 청산 규칙, 유지 증거금, 수수료, 펀딩비 등은
본 전략의 계산과 다를 수 있으며,
청산가 추정 라인은 참고용 지표일 뿐입니다.
레버리지 및 진입 비율 설정에 따라 손실 폭이 매우 커질 수 있습니다.
특히 **“첫 포지션 300% 진입”**과 같이 매우 공격적인 설정은
시장 급락 시 계좌 손실과 청산 리스크를 크게 증가시킬 수 있으므로
신중한 검토가 필요합니다.
실거래 연동 시에는 별도의 리스크 관리가 필수입니다.
개별 손절 기준
포지션 상한선
전체 포트폴리오 내 비중 관리 등
본 전략 외부에서 추가적인 안전장치가 필요합니다.
9. 결론
ATH Drawdown Re-Buy Long Only 전략은 단순한 “저가 매수”를 넘어서,
ATH 기준으로 드로우다운을 구조적으로 활용하고,
첫 포지션에 대한 **특수 규칙(100% / 300%)**을 적용하며,
레버리지·청산가·MDD·수익률을 통합적으로 시각화함으로써,
하락 구간에서의 규칙 기반 롱 포지션 구축과
리스크 모니터링을 동시에 지원하는 전략입니다.
사용자는 본 전략을 통해:
자신의 시장 관점과 리스크 허용 범위에 맞는
드로우다운 구간
진입 비율
레버리지 설정
다양한 시나리오에 대한 백테스트와 분석
을 수행할 수 있습니다.
다시 한 번 강조하지만,
본 전략은 연구·학습·백테스트를 위한 도구이며,
실제 투자 판단과 책임은 전적으로 사용자 본인에게 있습니다.
/ENG Version.
This script is designed to use historical drawdown data and automatically enter positions when a predefined percentage drop from the all-time high occurs, using a predefined percentage of your account equity.
You can use leverage, and default parameter values are provided out of the box (you can freely change them to suit your style).
In addition to the two main entry levels, you can add more entry conditions and custom entry percentages – just ask ChatGPT to modify the script.
For actual/live usage, please turn OFF the KillSwitch function and turn ON the Bar Magnifier feature.
ATH Drawdown Re-Buy Long Only Strategy
1. Strategy Overview
The ATH Drawdown Re-Buy Long Only strategy is an automatic re-buy (Long Only) system that builds long positions step-by-step at specific drawdown levels, based on the asset’s all-time high (ATH) and its subsequent drawdown.
This strategy is designed with the following goals:
Systematic scaled buying and leverage usage during sharp correction periods
Clear, rule-based entry logic using drawdowns from ATH
Real-time visualization of:
Average entry price
Leverage
Estimated liquidation price
Account MDD (Max Drawdown)
Return / performance
This allows traders to intuitively monitor both risk and position status.
※ This strategy is provided for educational, research, and backtesting purposes only.
It does not constitute investment advice and does not guarantee any profits.
2. Core Concepts
2-1. Drawdown from ATH (All-Time High)
On the chart, the strategy always tracks the highest high as the ATH.
Whenever a new high is made, ATH is updated, and based on that ATH the following are calculated:
How many percent the current bar’s Low is below the ATH
How many percent the current bar’s Close is below the ATH
Using these, the strategy executes buys at two predefined drawdown zones:
1st entry zone: When price drops X% from ATH
2nd entry zone: When price drops Y% from ATH
Each zone is allowed to trigger only once per ATH cycle.
When a new ATH is created, the “1st / 2nd entry possible” flags are reset, and new opportunities open up for that ATH leg.
2-2. Special Rule for the First Position (100% / 300%)
A key feature of this strategy is the special rule for the very first position.
When the strategy currently holds no position and is about to open the first long position:
Under normal conditions, it builds the position using 100% of account equity.
However, if at that moment the price has dropped by at least a predefined threshold from ATH (e.g. around –72.5% or more),
→ the strategy will open the first position using 300% of account equity.
This rule works as follows:
Whether the first entry happens at the 1st drawdown zone or at the 2nd drawdown zone,
If the current drawdown from ATH is at or below the threshold (e.g. –72.5% or worse),
→ the strategy interprets this as “a sufficiently deep crash” and opens the initial position with 300% of equity.
If the drawdown is less severe than the threshold,
→ the first entry is capped at 100% of equity.
So the strategy has two modes for the first entry:
Normal market conditions: 100% of equity
Deep drawdown conditions: 300% of equity
This special rule is intended to be aggressive in extremely deep crashes while staying more conservative in normal corrections.
3. Strategy Logic & Execution
3-1. Entry Conditions
The strategy tracks the ATH using the High price.
For each bar, it calculates the drawdown from ATH.
The user defines two drawdown zones, for example:
1st zone: ATH – 50%
2nd zone: ATH – 72.5%
For each zone, the strategy checks:
If no buy has been executed yet for that zone in the current ATH leg, and
If the current bar’s Low touches or falls below that zone’s price level,
→ That bar is considered to have triggered a buy condition.
Order simulation:
The strategy simulates entering a long position at that zone’s price level
(using a limit/market-like approximation for backtesting).
3-2. ATH Reset & Entry Opportunity Reset
When a new High goes above the previous ATH:
The ATH is updated to this new high.
Internal flags that track whether the 1st and 2nd entries have been used are reset.
This means:
Each time the market makes a new ATH,
The strategy once again has a fresh opportunity to execute 1st and 2nd drawdown entries for that new ATH leg.
4. Position Sizing & Leverage
4-1. Position Size Based on Account Equity
The strategy defines current equity as:
Current Equity = Initial Capital + Realized PnL + Unrealized PnL
For each entry zone, the position value is calculated as follows:
The user inputs:
“What % of equity to use at this zone”
The strategy:
Multiplies current equity by that percentage
Then multiplies by the strategy’s leverage factor
Thus:
Position Value = Current Equity × (Zone % / 100) × Leverage
Finally, this position value is divided by the entry price to determine the actual position size in tokens.
4-2. Exception for the First Position (100% / 300%)
For the very first position (when there is no open position),
the strategy does not use the zone % parameters. Instead, it uses fixed ratios:
Default: Enter the first position with 100% of equity.
If the drawdown from ATH at that moment is greater than or equal to a predefined threshold (e.g. –72.5% or more)
→ Enter the first position with 300% of equity.
The position value is computed as:
Position Value = Current Equity × (100% or 300%) × Leverage
Then it is divided by the entry price to obtain the token quantity.
This rule:
Applies regardless of whether the first entry occurs at the 1st zone or 2nd zone.
Embeds the philosophy:
“In very deep crashes, go much larger on the first entry; otherwise, stay more conservative.”
4-3. Tracking Real Leverage
On each bar, the strategy tracks:
The existing position size at the start of the bar
The newly added size (if any) on that bar
When a new entry occurs, it calculates the real leverage at that moment:
Real Leverage = (Position Value / Current Equity)
This is then displayed on the chart as a label, for example:
Lev 2.53x
This makes it easy to see the actual leverage level at each entry point.
5. Visualization & Monitoring
5-1. On-Chart Visual Elements
The strategy plots the following directly on the chart:
ATH Line
The all-time high (based on High) is plotted as an orange line.
Average Entry Price Line
When a position is open, the average entry price of that position is plotted as a yellow line.
Estimated Liquidation Price (Fixed) Line
The strategy detects when the position size changes.
At each size change, it uses the current average entry price and real leverage to compute an approximate liquidation price.
This “fixed liquidation price” is then plotted as a red line on the chart.
If there is no position, or if leverage is 1x or lower, the liquidation line is removed.
Entry Markers & Labels
When 1st/2nd entry conditions are met, the strategy:
Marks the entry point on the chart.
Displays labels such as "Buy XX% @ Price" and "Lev XXx",
showing both entry percentage and real leverage at that time.
The label placement is configurable:
Below Bar
Above Bar
At Price
5-2. Information Table (Top-Right Panel)
In the top-right corner of the chart, the strategy displays a summary table of the current account and position status. It typically includes:
Pos Qty (Token)
Absolute size of the current position (in tokens)
Pos Value (USDT)
Market value of the current position (qty × current price)
Leverage (Now)
Current real leverage (position value / current equity)
DD from ATH (%)
Current drawdown (%) from the latest ATH, based on current price
Avg Entry
Average entry price of the current position
PnL (%)
Unrealized profit/loss (%) of the current position
Max DD (Equity %)
The maximum equity drawdown (MDD) recorded over the entire backtest period
Last Entry Price
Average entry price immediately after the most recent add-on entry
Last Entry Lev
Real leverage at the time of the most recent entry
Liq Price (Fixed)
The fixed estimated liquidation price described above
Return from Start (%)
Total return (%) of equity compared to the initial capital
Through this table, users can quickly grasp:
Current account and position status
Current risk level
Cumulative performance
6. Time Filters & Label Options
6-1. Strategy Date Range Filter
The strategy provides an option to restrict trading to a specific time range.
When “Use Date Range” is enabled:
You can specify start and end timestamps.
The strategy will only execute trades within that range.
When this option is disabled:
The strategy operates over the entire chart history.
6-2. Entry Label Placement
Users can customize where entry/leverage labels are drawn:
Below Bar (Below Bar)
Above Bar (Above Bar)
At the actual price level (At Price)
This allows you to adjust visualization according to personal preference and chart readability.
7. Use Cases & Applications
This strategy is suitable for the following purposes:
Long-term / swing-style re-buy strategies for spot or futures long positions
Testing rule-based strategies that rely on “drawdown from ATH” as a main signal
Monitoring account leverage, liquidation price, and MDD when using leverage
Handling situations where, for a given asset:
“Every time a new ATH is formed,
you want to wait for deep corrections and enter only at specific drawdown zones”
It is generally recommended to use this strategy not as a direct plug-and-play live system, but as a tool for:
Strategy idea validation
Risk profile analysis
Parameter exploration to match your personal risk tolerance and style
8. Limitations & Warnings
Backtest results do not guarantee future performance.
They are based on historical data only.
In live markets, additional factors exist:
Liquidity
Slippage
Fee structures
Exchange-specific liquidation rules
Funding fees, etc.
The liquidation price is only an approximate estimate, derived from a simplified formula.
Actual liquidation rules, maintenance margin requirements, fees, and other details differ by exchange.
The liquidation line should be treated as a reference indicator, not an exact guarantee.
Depending on the configured leverage and entry percentages, losses can be very large.
In particular, extremely aggressive settings such as “first position 300% of equity” can greatly increase the risk of large account drawdowns and liquidation during sharp market crashes.
Use such settings with extreme caution.
For live trading, additional risk management is essential:
Your own stop-loss rules
Maximum position size limits
Portfolio-level exposure controls
And other external safety mechanisms beyond this strategy
9. Conclusion
The ATH Drawdown Re-Buy Long Only strategy goes beyond simple “buy the dip” logic. It:
Systematically utilizes drawdowns from ATH as a structural signal
Applies a special first-position rule (100% / 300%)
Integrates visualization of leverage, liquidation price, MDD, and returns
All of this supports rule-based long position building in drawdown phases and comprehensive risk monitoring.
With this strategy, users can:
Explore different:
Drawdown zones
Entry percentages
Leverage levels
Run various backtests and scenario analyses
Better understand the risk/return profile that fits their own market view and risk tolerance
Once again, this strategy is intended for research, learning, and backtesting only.
All real trading decisions and their consequences are solely the responsibility of the user.
TrendPilot AI v2 — Adaptive Trend Day Trading StrategyOverview
TrendPilot AI v2 is a structured, rules-based day trading strategy that identifies and follows market momentum using a sophisticated blend of technical indicators. Optimized for 15-minute and higher timeframes on high market cap cryptocurrencies (AAVE, SOL, ETH, BCH, BTC) to minimize manipulation risks, it adapts to changing market conditions with dynamic risk management and controlled re-entry logic to maximize trend participation while minimizing noise.
Core Logic
Multiple EMA Trend Confirmation — Uses three Exponential Moving Averages (fast, medium, slow) to detect robust bullish, bearish, or neutral trends, ensuring trades align with the prevailing market direction.
ADX Momentum Filter — Employs an ADX-based filter to confirm strong trends, avoiding entries in choppy or low-momentum markets.
Smart Entry Filter — Optional ATR-based buffer (period 14, multiplier 1.5) around the fast EMA prevents entries at overextended prices, enhancing trade precision.
Flexible Exit System — Offers multiple exit options: fixed take-profit (default 1.7 offset), trend-reversal exits, or ATR-based trailing stops (period 14, multiplier 2.0), with secure modes requiring candle closes for confirmation to gain Max Profit.
Controlled Re-Entry Logic — Allows re-entries after take-profit or price-based stop-loss with configurable wait periods (default 6 bars), max attempts (default 2), and EMA touch requirements (fast, medium, or slow).
State-Aware Risk Management — Tracks trend states and recent exits to adapt entries, with daily trade limits (default 5 long/short) and loss cooldowns (default 2 stop-losses) for disciplined trading.
How to Use & Configuration
Markets & Timeframes
Works with high market cap cryptocurrencies (AAVE, SOL, ETH, BCH, BTC).
Optimized for intraday charts (15m–4h) but adaptable to higher timeframes (e.g., 1h, 4h).
Trade Direction Settings
Dual Trades — Trades both long and short, quickly re-aligning after trend reversals.
Long Only — Ignores bearish signals, ideal for bullish markets or strong uptrends.
Short Only — Ignores bullish signals, suited for bearish markets or downtrends.
Risk Management Settings
Stop Loss Types
Trend Reversal — Closes positions when an opposite trend signal is confirmed (default).
Fixed Offset — Static stop at 3.5 offset from entry price (adjustable).
ATR Based — Dynamic trailing stop using ATR (period 14, multiplier 2.0), adjusting to market volatility.
Secure SL Mode — Optional setting to trigger price-based stops only on candle closes, reducing false exits.
Maximum recommended risk per trade is 5–10% of account equity.
Trade size is configurable (default 20 units) to match individual risk appetite.
Take Profit Options
Fixed Offset — Predefined target at 1.7 offset from entry (adjustable, e.g., 2.5 for SOL).
Secure TP Mode — Exits only when a candle closes beyond the target, ensuring reliable profit capture.
Trend Reversal — Exits on opposite trend signals when fixed TP is disabled, ideal for riding longer trends.
Trade Management Controls
Smart Entry Filter — Optional ATR-based buffer (period 14, multiplier 1.5) prevents chasing overextended prices.
Max Re-Entries — Limits continuation trades per trend cycle (default 2).
Daily Trade Limits — Caps long/short trades per day (default 5 each) for disciplined trading.
Daily Loss Cooldown — Pauses trading after a set number of stop-losses (default 2) per day.
Max Bars in Trade — Closes positions after a set duration (default 1440 bars) to prevent stale trades.
Configuration Steps
Apply the strategy to your chosen symbol (e.g., AAVE/USDT, SOL/USDT) and timeframe (15m or higher).
Select Trade Direction mode (Dual, Long Only, or Short Only).
Set Stop Loss (Trend Reversal, Fixed Offset, or ATR Based) and Take Profit (fixed or trend-reversal).
Adjust Smart Entry Filter, Max Re-Entries, Daily Limits, and Loss Cooldown as needed.
Test across multiple market conditions using the performance panel (top-right, showing Total Trades, Wins, Losses, Win Rate).
Enables automated trading via webhook integration with platforms like Binance Futures.
Set up alerts for long/short entries (🟢 Long, 🔴 Short) and exits (🎯 Max TP, 🛑 Max SL, 🚨 Force Exit).
Backtesting Guidance
Use realistic commission (default 0.01%) and slippage (default 2 ticks) matching your broker and instrument.
Validate performance over long historical periods (e.g., 3–6 months) to ensure >100 trades across different market regimes.
Avoid curve-fitting by testing on multiple high market cap coins (AAVE, SOL, ETH, BCH, BTC) and avoiding over-optimization.
EMA and ATR parameters are set to balanced, industry-standard values for realistic backtesting.
Best Practices, Defaults & Disclaimer
Best Practices
Use consistent and conservative position sizing (default 20 units).
Match commission and slippage to your broker’s actual rates.
Enable secure TP/SL modes for entries and exits to reduce false signals.
Test across different symbols, timeframes, and market phases before live trading.
Keep parameters simple to avoid overfitting.
Default Settings (Recommended Starting Point)
Initial Capital: $10,000
Order Size: Fixed, 20 units
Commission: 0.01%
Slippage: 2 ticks
Take Profit Offset: 1.7 (adjustable, e.g., 2.5 for SOL)
Stop Loss Type: Trend Reversal (default), Fixed Offset (3.5), or ATR Based (period 14, multiplier 2.0)
Smart Entry Filter: ATR period 14, multiplier 1.5 (optional)
Max Re-Entries: 2 per trend cycle
Daily Trade Limits: 5 long, 5 short
Daily Loss Cooldown: 2 stop-losses
Max Bars in Trade: 1440 bars
Subscription Information
TrendPilot AI v2 is an invite-only strategy, accessible only to approved subscribers.
Benefits include full access to all features, priority support, and regular updates.
Access is limited to ensure a high-quality user experience.
Compliance Status
No functional warnings in the script.
The script uses closed candle logic, ensuring no repainting or lookahead issues.
Designed for realistic backtesting with a $10,000 account and sustainable risk (≤5–10% per trade).
Disclaimer
This strategy is intended for educational and analytical purposes only. Trading involves substantial risk, and past performance does not guarantee future results. You are solely responsible for your own trading decisions and risk management.
Developed by: TrendPilotAI Team
For questions, setup guidance, or enhancement suggestions, contact TrendPilotAI Team via TradingView.
Setup: Smooth Gaussian + Adaptive Supertrend (Manual Vol)Overview
This strategy combines two powerful trend-based tools originally developed by Algo Alpha: the Smooth Gaussian Trend (simulated) and the Adaptive Supertrend. The objective is to capture sustained bullish movements in periods of controlled volatility by filtering for high-probability entries.
Entry Logic
Long Entry Conditions:
The closing price is above the Smooth Gaussian Trend line (with length = 75), and
The volatility setting from the Adaptive Supertrend is manually defined as either 2 or 3
Exit Condition:
The closing price falls below the Smooth Gaussian Trend line
This script uses a simulated version of the Gaussian Trend line via double-smoothed SMA, as the original Algo Alpha indicator is protected and cannot be accessed directly in code.
Features
Plots entry and exit signals directly on the chart
Manual toggle to enable or disable the volatility filter
Lightweight design to allow flexible backtesting even without access to proprietary indicators
Important Note
This strategy does not connect to the actual Adaptive Supertrend from Algo Alpha. Users must manually input the volatility level based on what they observe on the chart when the original indicator is also applied. The Smooth Gaussian Trend is approximated and may differ slightly from the original.
Suggested Use
Recommended timeframes: 1H, 4H, or Daily
Best used alongside the original indicators displayed on the chart
Consider incorporating additional structure, momentum, or volume filters to enhance performance
If you have suggestions or would like to contribute improvements, feel free to reach out or fork the script.
AccumulationPro Money Flow StrategyAccumulationPro Money Flow Strategy identifies stock trading opportunities by analyzing money flow and potential long-only opportunities following periods of increased money inflow. It employs proprietary responsive indicators and oscillators to gauge the strength and momentum of the inflow relative to previous periods, detecting money inflow, buying/selling pressure, and potential continuation/reversals, while using trailing stop exits to maximize gains while minimizing losses, with careful consideration of risk management and position sizing.
Setup Instructions:
1. Configuring the Strategy Properties:
Click the "Settings" icon (the gear symbol) next to the strategy name.
Navigate to the "Properties" tab within the Settings window.
Initial Capital: This value sets the starting equity for the strategy backtesting. Keep in mind that you will need to specify your current account size in the "Inputs" settings for position sizing.
Base Currency: Leave this setting at its "Default" value.
Order Size: This setting, which determines the capital used for each trade during backtesting, is automatically calculated and updated by the script. You should leave it set to "1 Contract" and the script will calculate the appropriate number of contracts based on your risk per trade, account size, and stop-loss placement.
Pyramiding: Set this setting at 1 order to prevent the strategy from adding to existing positions.
Commission: Enter your broker's commission fee per trade as a percentage, some brokers might offer commission free trading. Verify Price for limit orders: Keep this value as 0 ticks.
Slippage: This value depends on the instrument you are trading, If you are trading liquid stocks on a 1D chart slippage might be neglected. You can Keep this value as 1 ticks if you want to be conservative.
Margin for long positions/short positions: Set both of these to 100% since this strategy does not employ leverage or margin trading.
Recalculate:
Select the "After order is filled" option.
Select the "On every tick" option.
Fill Orders: Keep “Using bar magnifier” unselected.
Select "On bar close". Select "Using standard OHLC"
2. Configuring the Strategy Inputs:
Click the "Inputs" tab in the Settings window.
From/Thru (Date Range): To effectively backtest the strategy, define a substantial period that includes various bullish and bearish cycles. This ensures the testing window captures a range of market conditions and provides an adequate number of trades. It is usually favorable to use a minimum of 8 years for backtesting. Ensure the "Show Date Range" box is checked.
Account Size: This is your actual current Account Size used in the position sizing table calculations.
Risk on Capital %: This setting allows you to specify the percentage of your capital you are willing to risk on each trade. A common value is 0.5%.
3. Configuring Strategy Style:
Select the "Style" tab.
Select the checkbox for “Stop Loss” and “Stop Loss Final” to display the black/red Average True Range Stop Loss step-lines
Make sure the checkboxes for "Upper Channel", "Middle Line", and "Lower Channel" are selected.
Select the "Plots Background" checkboxes for "Color 0" and "Color 1" so that the potential entry and exit zones become color-coded.
Having the checkbox for "Tables" selected allows you to see position sizing and other useful information within the chart.
Have the checkboxes for "Trades on chart" and "Signal Labels" selected for viewing entry and exit point labels and positions.
Uncheck* the "Quantity" checkbox.
Precision: select “Default”.
Check “Labels on price scale”
Check “Values in status line”
Strategy Application Guidelines:
Entry Conditions:
The strategy identifies long entry opportunities based on substantial money inflow, as detected by our proprietary indicators and oscillators. This assessment considers the strength and momentum of the inflow relative to previous periods, in conjunction with strong price momentum (indicated by our modified, less-lagging MACD) and/or a potential price reversal (indicated by our modified, less-noisy Stochastic). Additional confirmation criteria related to price action are also incorporated. Potential entry and exit zones are visually represented by bands on the chart.
A blue upward-pointing arrow, accompanied by the label 'Long' and green band fills, signifies a long entry opportunity. Conversely, a magenta downward-pointing arrow, labeled 'Close entry(s) order Long' with yellow band fills, indicates a potential exit.
Take Profit:
The strategy employs trailing stops, rather than fixed take-profit levels, to maximize gains while minimizing losses. Trailing stops adjust the stop-loss level as the stock price moves in a favorable direction. The strategy utilizes two types of trailing stop mechanisms: one based on the Average True Range (ATR), and another based on price action, which attempts to identify shifts in price momentum.
Stop Loss:
The strategy uses an Average True Range (ATR)-based stop-loss, represented by two lines on the chart. The black line indicates the primary ATR-based stop-loss level, set upon trade entry. The red line represents a secondary ATR stop-loss buffer, used in the position sizing calculation to account for potential slippage or price gaps.
To potentially reduce the risk of stop-hunting, discretionary traders might consider using a market sell order within the final 30 to 60 minutes of the main session, instead of automated stop-loss orders.
Order Types:
Market Orders are intended for use with this strategy, specifically when the candle and signal on the chart stabilize within the final 30 to 60 minutes of the main trading session.
Position Sizing:
A key aspect of this strategy is that its position size is calculated and displayed in a table on the chart. The position size is calculated based on stop-loss placement, including the stop-loss buffer, and the capital at risk per trade which is commonly set around 0.5% Risk on Capital per Trade.
Backtesting:
The backtesting results presented below the chart are for informational purposes only and are not intended to predict future performance. Instead, they serve as a tool for identifying instruments with which the strategy has historically performed well.
It's important to note that the backtester utilizes a tiny portion of the capital for each trade while our strategy relies on a diversified portfolio of multiple stocks or instruments being traded at once.
Important Considerations:
Volume data is crucial; the strategy will not load or function correctly without it. Ensure that your charts include volume data, preferably from a centralized exchange.
Our system is designed for trading a portfolio. Therefore, if you intend to use our system, you should employ appropriate position sizing, without leverage or margin, and seek out a variety of long opportunities, rather than opening a single trade with an excessively large position size.
If you are trading without automated signals, always allow the chart to stabilize. Refrain from taking action until the final 1 hour to 30 minutes before the end of the main trading session to minimize the risk of acting on false signals.
To align with the strategy's design, it's generally preferable to enter a trade during the same session that the signal appears, rather than waiting for a later session.
Disclaimer:
Trading in financial markets involves a substantial degree of risk. You should be aware of the potential for significant financial losses. It is imperative that you trade responsibly and avoid overtrading, as this can amplify losses. Remember that market conditions can change rapidly, and past performance is not indicative of future results. You could lose some or all of your initial investment. It is strongly recommended that you fully understand the risks involved in trading and seek independent financial advice from a qualified professional before using this strategy.
