Logic Flow Signals & Backtest [bercutiatia]To understand the advanced logic of the tool, it is essential that you carefully read each topic and check the visual examples in this presentation.
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Who is the Logic Flow Signals & Backtest tool recommended for?
Ideal for traders looking to increase the reliability and level of their operations. Recommended for those who want to create rigorous confluences, validate strategies with backtesting, and transform emotional management into systematic and measurable processes.
How can the Logic Flow Signals & Backtest tool help me?
High-confidence signals! You combine TradingView indicators and create a single robust signal, eliminating the frustration of having to spend hours in front of the chart and still clicking at the wrong time. This ensures that your entry is validated by logic, not emotional impulse.
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Logic Flow Signals & Backtest is a versatile and powerful tool designed to test and validate your trading ideas with indicators from the TradingView community.
Extreme flexibility: Allows you to combine indicators available on TradingView (EMAs, RSI, MACD, SMC, etc.) to create custom entry and exit logics.
Sequential Logic: Goes far beyond simple crossovers. You can define rules where signal A must occur before signal B — and, if desired, before signal C or D — to validate an entry. Add time, order, and context filters, creating truly intelligent sequential logic that generates a single final alert only when all conditions align.
With Stages (Stage 1, Stage 2, etc.), your entries follow the exact sequence you define. And the best part: you no longer need to spend hours in front of the chart waiting for confluences. Simply set up your stages once, create an alert in TradingView, and the system will automatically notify you when the ideal combination of signals occurs.
Sequence Invalidation: Offers the option to define conditions that, if they occur, immediately cancel an ongoing entry sequence, helping to avoid entries in unfavorable scenarios.
Explaining the first image example (chart below):
LONG INDICATOR 1 (Stage 1): The market confirms a change in character (CHoCH Bullish). The system enters an alert state awaiting the confluence of the next indicators.
LONG INDICATOR 2 and 3 (Stage 2): Entry is only released when the SMA17 crosses above the SMA72 (indicator 2), but with one condition: The SMA72 must be ABOVE the SMA305 (indicator 3); Without this alignment of indicator 3, the signal of indicator 2 does not occur.
LONG INDICATOR 4 (Invalidation Rule): If at any point in the sequence the SMA72 crosses below the SMA305, the setup is immediately canceled and no entry signal is generated. The sequence restarts with indicator 1.
EXIT LONG (Hybrid Exit TP + SIGNAL): The trade seeks a TP target of 1000 ticks, but has a technical "Trailing Stop": if the trend reverses (Exit Long Indicator 1 = SMA72 crosses below the SMA305) before the target, the position is closed to protect capital.
SHORT INDICATOR 1 (Stage 1): Identification of weakness in the market with a Bearish CHoCH.
SHORT INDICATOR 2 and 3 (Stage 2): Entry is only released when the SMA17 crosses below the SMA72 (indicator 2), but with a strict condition: The SMA72 must be BELOW the SMA305 (indicator 3); Without this STATE of indicator 3, the signal from indicator 2 does not occur.
SHORT INDICATOR 4 (Invalidation Rule): If at any point in the sequence the SMA72 crosses above the SMA305, the setup is immediately canceled and no entry signal is generated. The sequence starts again with indicator 1.
EXIT SHORT (Hybrid Exit TP + SIGNAL): The trade seeks a target of 1000 ticks, but has a technical "Trailing Stop": if the downtrend reverses (Exit Short Indicator 1 = SMA72 crosses above the SMA305) before the target, the position is closed to protect capital.
In this strategy, we use the external indicators: Multiple MTF MA and Smart Money Concepts (Advanced)
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Stage Duration: In STAGE DURATION , you control the maximum time (in candles) allowed for each transition between stages to occur. If the time limit expires before the next stage is reached, the sequence is reset. Keep it at 0 to disable the time limit.
The "Stage Duration" function is available in four separate blocks on the settings panel:
- LONG - STAGE DURATION: Controls the time limit (in candles) between Long entry stages (for example from Stage 1 to Stage 2).
- LONG EXIT - STAGE DURATION: Controls the time limit between Long exit stages.
- SHORT - STAGE DURATION: Controls the time limit between Short entry stages.
- SHORT EXIT - STAGE DURATION: Controls the time limit between Short exit stages.
Explaining the second image example (chart below):
Stage 1 (INDICATOR 1): New Fair Value Gap (FVG) Bullish Confirmed.
- Meaning: The move starts with a bullish FVG (Fair Value Gap), indicating a confirmed imbalance where buyers were much more aggressive than sellers.
Stage 2 (INDICATOR 2): EMA10 crossing above the EMA50.
- Meaning: Immediately after the FVG trigger, the fast moving average (10 periods) crosses the intermediate moving average (50 periods). This confirms that the initial FVG impulse was not an isolated event but the beginning of a short-term trend.
Stage 3: In this final stage, we require two simultaneous confirmations to validate the entry:
- INDICATOR 3: The EMA10 crosses above the EMA100, indicating that the movement has enough strength to break through larger barriers.
- INDICATOR 4: The RSI must be above its own moving average (SMA14). This ensures the asset is gaining momentum at the exact moment the averages are broken, avoiding entries in "tired" markets.
Stage Duration: The most important feature of this setup is the restricted time window.
- Rule: From Stage 1 to 2, and from Stage 2 to 3, the maximum interval to accept confluences is only 3 candles.
- Why this is vital? If the market took 20 candles to align these conditions, it would indicate weakness or indecision. By demanding that everything happens within a maximum of 3 candles per step, the setup filters only the moves where buying pressure is urgent and aggressive, increasing the probability of an explosive move in favor of the trade.
Asymmetric Risk Management: To complement a high-probability and high-pressure setup, we use aggressive risk management:
- Stop Loss (Technical/Short): 200 Ticks. If the buying pressure fails quickly, we exit early with a small loss.
- Take Profit (Long Target): 1000 Ticks. We aim to ride the impulse "leg" that the setup identified.
- Risk/Reward: 5:1. This means a single winning trade covers five losing trades, making the strategy mathematically viable in the long term.
In this strategy, we use the external indicators: Multiple MTF MA , Smart Money Concepts (Advanced) and Relative Strength Index (RSI) .
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Multiple Operating Modes
It is not limited to sequences. It can operate by confluence (where all signals must be valid at the same time), by single trigger (only one signal is required), or by "OR" logic (any one of the defined signals).
- If you use only Stage 1 in more than one indicator session, the entry will only occur if all enabled conditions are true simultaneously.
- Any condition defined as OR can trigger the entry by itself.
- If only one condition block is enabled, the single indicator will function as a simple signal.
Multiple and Simultaneous Exits
It allows for the configuration of exits by both indicators and TP/SL targets. The strategy will close the trade as soon as any of these conditions are met first (indicator signal, profit target, or loss limit
Integrated Risk Management
It includes Stop Loss and Take Profit exits by percentage and ticks, which are easy to configure and essential for risk management. The strategy calculates the exact TP and SL prices based on your entry price and monitors the market on every tick.
Explaining the Third Image Example (Chart Below)
The move was validated by a 4-step logical sequence (Stage 1) and managed by a hybrid exit system.
Short Indicator 1, 2, and 3: The price (Close) crossed below the SMA200, SMA72, and SMA17 averages simultaneously.
- What this means: When a single candle has the strength to break below the short-term (17), mid-term (72), and long-term (200) averages, it indicates a high probability for the price to seek lower levels.
To reinforce Indicators 1 through 3, we added an extra layer of confirmation.
Short Indicator 4: The Positive Volume Index (PVI) needed to be below its own long-term average (EMA300).
- Why this is important: PVI below the average confirms that selling volume is dominant, validating that the break of the averages was not just noise.
Triple Exit Management (Maximum Security)
The great advantage of this tool is the ability to manage risk dynamically. In this trade, we configured three simultaneous exit conditions, where the first one to be met closes the position:
1. Financial Target (TP): A fixed Take Profit of 15%.
2. Exit Short Indicator 1 (Technical Exit 1): If the average (SMA72) crosses above the average (SMA200), the trade is closed.
3. Exit Short Indicator 2 (Technical Exit 2): If the PVI crosses above the EMA300, indicating an entry of buying strength, the trade is closed.
"OR" Logic: The tool monitors these conditions in real-time. Whichever occurs first triggers the exit, ensuring you lock in profit (TP) or protect your capital at the first sign from the indicators.
In this strategy, we use the external indicators: Multiple MTF MA and Positive Volume Index .
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Reversal Mode (Stop and Reverse)
The Reversal Mode (Stop and Reverse) allows a new signal in the opposite direction (e.g., a SELL signal) to automatically close an existing position (e.g., BUY) and open a new one (sell). This "stop and reverse" function can be enabled or disabled in the settings, giving you full control over whether the strategy should only exit (awaiting a new signal) or immediately reverse the position.
Explaining the Fourth Image Example (Chart Below)
In this example, we demonstrate a setup focused on capturing every market "flip," keeping the trader positioned 100% of the time ("Always-in"), a technique widely used in automation.
- Long Entry: Occurs immediately upon confirming a bullish change of character (New CHoCH Bullish).
- Short Entry: Occurs immediately upon confirming a bearish change of character (New CHoCH Bearish).
- Exit (The Differentiator): We are not using fixed TP or SL here. The exit is triggered by Automatic Reversal.
The Power of "Exit by Opposite Signal"
Notice the labels on the chart: "Close Short" followed immediately by a "Long." This happens because the Allow Reversal function is enabled in the tool's settings.
When the market generates a buy signal, the tool understands that the sell thesis has been invalidated. It simultaneously sends an order to close the Short position and open a new Long position.
When to use this exit rule?
- Capturing Long Trends / Directional Movements: Ideal for volatile assets where you want to ride the trend until the market structure effectively changes.
- Operational Simplification: Eliminates the need to guess profit targets and acts as a loss limiter when the price moves against your position. The market dictates when to enter and when to exit.
Hybrid Flexibility:
The strongest point of Logic Flow is that you don't have to choose just one method. Reversal can be used in two ways:
1. Individually (as in the image): Reversal is the only form of exit. You stay in the move until the opposite signal.
2. Combined (Hybrid): You can enable Reversal and configure a safety Stop Loss + technical Take Profit (Exit Long/Short Indicator).
- Example: If the price hits your TP/SL first, you exit. If the market turns before the TP, the Reversal takes you out of the trade and generates a new trend alert.
In this strategy, we use the external indicators: Smart Money Concepts .
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Backtesting: Far beyond creating logic and generating signals, Logic Flow Signals stands out due to its Integrated Backtest.
Backtesting serves as a reality check for the trader. It takes the strategy out of the realm of "imagination" and puts it to the test against historical data.
Here are the 4 main practical uses:
1. Verifying Feasibility (Proof of Concept): The most obvious use is to answer: "Does this idea make money?". Many strategies look visually perfect on the chart, but when you run the backtest, you discover that brokerage fees or frequent "stops" consume all the profit.
2. Knowing the "Worst-Case Scenario" (Drawdown): Maximum Drawdown: It shows you what the largest accumulated drop the strategy has ever experienced was. By identifying a Drawdown that exceeds the desired risk tolerance, the backtest allows for parameter optimization in search of a more efficient balance between risk and return.
3. Fine-Tuning (Optimization): It allows you to make changes such as: Increasing the profit target, changing the stop, removing an indicator, changing the chart timeframe, among other actions. You can test various variations instantly to find the most efficient configuration.
4. Expectation Management and Discipline: Backtesting does not eliminate fear nor guarantee that the future will repeat the past, but it serves as a reference map.
The Real Role: Aligning expectation with reality.
In the image below, you can check out how a backtest result is generated:
To understand the backtest results shown above, check the chart and the detailed operational logic below:
This operational example seeks to identify altcoins that are demonstrating an explosive decorrelation relative to Bitcoin. The logic is: we want to buy only the assets that are outperforming the market leader, precisely at the moment when speculative money (Open Interest) heavily enters the market.
For the buy signal (Long) to be triggered, three conditions must be simultaneously true (Stage 1):
Long Indicator 1 (Altcoin Strength): The asset's RSI must be above the 70 level (Overbought), indicating extremely strong bullish momentum.
Long Indicator 2 (Bitcoin Weakness): Bitcoin's RSI must be below the 50 level. This confirms that the Altcoin's rally is genuine and independent.
Long Indicator 3 (Money Flow): The Open Interest (open contracts) must be above the Extreme level of the OI DELTA indicator. This validates that new money is aggressively entering the asset to sustain the rally.
Risk Management: In this example, we configured an aggressive target to capture the altcoin volatility:
- Take Profit: 100%
- Stop Loss: 20%
- Risk/Reward: 5:1
In this strategy, we use the external indicators: RSI Crypto Strength (Asset vs BTC) and Open Interest Delta .
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Configuring an Indicator Block
Each block (BUY INDICATOR 1, BUY INDICATOR 2, ...) allows you to define a complete condition.
- Enable (Activate): Simply turns this indicator block on or off.
- Source A: The first value you want to analyze.
example: The Closing Price (Close), Opening Price (Open), or another TradingView indicator.
- Condition: How 'Source A' will be compared.
example: Crossover/Crossunder, Greater Than, Less Than, Cross Up.
- Comparison Type: The option that defines whether you will compare 'Source A' with a fixed number or with another indicator.
- Fixed Value: Used if you selected "Fixed Value".
example: For an RSI greater than 70 condition, Source A would be the RSI, the Condition would be Greater Than, and the Fixed Value would be 70.
- Source B: Used if you selected "Source B".
example: For a condition where the EMA10 crosses above the EMA200, Source A would be the EMA10, the Condition would be 'Cross Up', and Source B would be the EMA200.
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Configurable Alert Signals
Configurable Alert Signals: The tool allows for the creation of fully customized alerts for different types of events, such as entries, signal-based exits, take profit, and stop loss. These alerts can be used for both strategy automation and manual, real-time notifications.
The message field is highly flexible: it accepts dynamic placeholders, JSON structure, UUID identifiers, or any custom text, allowing integration with other external tools and systems via webhook.
Configuring Your Messages:
- LONG/SHORT - ALERTS: Defines the message for new entries.
- LONG/SHORT INDICATOR EXIT - ALERTS: Defines the message for signal-based exits (e.g., moving average cross).
- REVERSAL - ALERTS: Defines the message for when a position is closed by an opposite signal (stop-and-reverse).
- LONG/SHORT TP/SL EXIT - ALERTS: Defines the message for exits triggered by take profit (TP) or stop loss (SL), via percentage or ticks.
A Single Alert to Control Everything
You don't need to create separate alerts for "Buy," "Sell," or "Exits." On a single screen, you can create strategies by defining entries, signal-based exits, profit targets, or stop limits.
Alert Times (Operating Window)
In the Alert Times section, you can define a specific time (and time zone) for the strategy to generate entry or exit signals.
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To create your alert, simply follow these steps:
- Condition: Select the script name: "Logic Flow Signals & Backtest".
- Message: Insert only the placeholder: {{strategy.order.alert_message}}
Once this single alert is active, it will "listen" to all orders executed by the strategy.
This means you can have your Long-Term, Short-Term, Signal-Based Exits, and TP/SL strategies active simultaneously. When any of these events are plotted on the chart, the script will send the customized message (which you wrote in the fields) to your single alert.
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Advanced period filters: Allow you to test the strategy in specific date ranges, over the last X days, or over the last X bars, facilitating performance analysis in different market environments.
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Status Panel: Displays a clear summary of all active rules and settings directly on the chart, facilitating the visualization and confirmation of the running logic.
Additionally, it has a settings box where you can activate or deactivate the panel, choose its position (such as at the bottom or side), and adjust its size.
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The Thumbnail strategy uses the following external indicators: Multiple MTF MA and Breakout Finder .
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Final Considerations:
The Logic Flow Signals & Backtest tool is a versatile and powerful system, designed to test and apply trading ideas based on multiple indicators from TradingView.
Its differential is being a customization environment: the script does not have integrated graphical indicators, as the objective is precisely to allow the user to combine and integrate multiple existing indicators in the TradingView community to build unique entry and exit logics.
It offers flexibility and precision, but the true value emerges when the trader integrates the tool into a consistent trading plan, with efficient risk management (Stop Loss and Take Profit), leverage control, and a professional mindset.
Important: Risk of Repainting (Unstable Data): Avoid indicators that 'repaint' (those that change their values in past bars after the closing of new candles). The backtest will be invalidated, and the actual performance of the strategy will fail.
Legal Warning and Didactic Purpose:
It is fundamental to understand that all visual examples, charts, and texts contained in this description do not constitute financial advice, buy or sell recommendations, nor a promise of easy or guaranteed gains.
This is an advanced support tool, not an automatic profit system. Use the integrated backtesting to evaluate the historical behavior of strategies before real execution and understand how different market conditions impact your results. The sole purpose of this material is to demonstrate the logical and execution capacity of the script, serving as a didactic guide for you to test and validate your own ideas.
Conclusion and Risk Warning:
Success in financial markets comes not only from a set of charting indicators, but from the trader's understanding, practice, and discipline. Our objective is to provide a robust, customizable, and intuitive solution, created to enhance your technical analysis and broaden your strategic vision, without replacing critical thinking and conscious decision-making.
Finally, remember: past results do not guarantee future performance. The real differentiator lies in continuous learning, testing, and evolution.
Backtest
PA Builder [PrimeAutomation]1. PA Builder – Overview
PA Builder is not a fixed strategy; it’s a framework for building strategies. Instead of giving traders one rigid system, it provides a toolbox where entries, exits, filters, risk parameters, and automation rules can all be defined and combined. The core philosophy is confluence: the idea that a trade should only be taken when multiple independent signals agree. The Builder is built around this principle. Every module; trend, reactors, bands, reversals, volume, structure, divergences, externals can be treated as one layer of confidence. The stronger the alignment across layers, the higher the quality of the setup in theory.
In practice, this means PA Builder encourages traders to think in terms of “confluence,” not single indicators. Trend and positioning define whether you should even be looking for longs or shorts. Timing tools such as bands, reversals and candlestick structures determine when inside that broader bias you want to engage. Confirmation tools like volume and flow tell you whether capital is actually supporting the move. Filter systems then ensure that even if everything looks good locally, you still respect higher-timeframe or opposing warnings. The Builder’s philosophy is simple: enter less often, but only when conditions are genuinely in your favour.
2. Core Entry Signal Components
The entry logic in PA Builder is built on a set of signal engines that can be combined in many ways. Trend Signals form a natural foundation. They use low-lag low-pass filters, borrowed from audio signal processing, to extract directional bias from price without the classic delay of classical moving averages. The sensitivity parameter controls how reactive this engine is: lower values favour cleaner trends and fewer whipsaws, while higher values are better suited to short-term intraday trading where speed matters more than smoothness. Many traders start by requiring that Trend Signals show “all bullish” or “all bearish” before allowing any entries in that direction.
Trend signals firing short positions
On top of this directional backbone, the Dynamic Reactor behaves as an adaptive baseline. It accelerates in volatile phases and slows down during consolidation, effectively acting as a moving reference point for both trend and price position. A typical use of this module is to insist that, for long trades, the price sits above a bullish reactor; for shorts, below a bearish one. At the higher-timeframe level, the Quantum Reactor provides a VWAP-style reference that can be anchored to larger candles than the chart you are trading. A common configuration is to trade on a 15-minute chart while requiring that price is above the 4-hour Quantum Reactor for longs or below it for shorts. The “fast” and “slow” options determine how quickly this reference adapts to new information.
Timing is then refined with tools like Quantum Bands, reversals and candle structure analysis. Quantum Bands identify extremes within the current environment. In an uptrend, a tag of the lower band can be treated as a pullback rather than a breakdown; in a downtrend, the upper band acts like a shorting zone. Many traders combine “trend up and above higher-timeframe reactor” with “price temporarily below lower band” to construct a mean-reversion entry inside a larger uptrend. Reversal detection modules examine recent bars to find turning points, with shorter lookbacks capturing fast flips and longer lookbacks tracking deeper structural changes. Candle structure logic goes beyond classical candlestick names and instead focuses on whether price action confirms follow-through or reversion behaviour, with options like “2X” modes that wait for two successive confirmations before acting.
Before and after filtering using reactor applied.
Additional confirmation layers come from Volume Matrix, Money Flow, OSC True7 and divergence detection. Volume and flow tools answer whether actual capital is participating in the move or whether price is drifting on thin activity. OSC True7 categorises the state of the trend into intuitive buckets, strong, healthy, neutral, or exhausted, making it easier to avoid chasing extremes. Divergences between price and momentum can be used either as entry triggers in contrarian systems or as hard filters that block trades when warning signs are present. Finally, two external indicator inputs make it possible to integrate RSI, MACD, custom indicators or even other strategies into the Builder, either as simple thresholds or as comparative logic between two external sources (for example, requiring a fast EMA to be above a slow EMA before allowing longs).
3. Exit System & Trade Management
The exit systems in PA Builder are designed to be as vital as the entry logic. It assumes exits are not an afterthought, but half of the edge. Instead of forcing a single take profit point, the system uses a three-tier structure where you can assign different portions of the position to different targets. A common pattern is to scale out a small portion early (for example at one ATR), another portion at an intermediate level, and keep the largest slice for a deeper move. This creates a natural balance: you book something early to reduce emotional stress, while leaving room to participate in the full potential of a trend.
Targets can be defined using ATR multiples or risk-to-reward ratios that are directly tied to the initial stop distance. Using ATR keeps exits proportional to current volatility. A two ATR target in a quiet environment is very different in absolute price distance from the same multiple in a high-volatility environment, yet conceptually it represents the same “size” move. Risk-to-reward exits build on this by ensuring that if you risk one unit (1R), the reward targets are set at predefined multiples of that risk. This enforces positive expectancy at the structural level: the strategy cannot generate entries with inherently negative payoffs.
Once price begins to move in your favour, trailing logic takes over if you choose to enable it. Trailing can begin immediately from entry or only after a target has been hit. Many users prefer to let TP1 and TP2 behave as fixed profit points and then apply a trailing stop or trailing take profit to the final remainder. That way, routine winners are banked mechanically, while occasional explosive moves can be ridden for as long as the market allows. The breakeven module supports this behaviour by automatically moving stops to entry (or slightly through entry into profit) after a specified condition such as TP1 being hit. This transforms the risk profile mid trade: once breakeven has been secured, remaining size can be managed with much less psychological pressure.
The system also recognises the cost of time. Kill Switch functionality exits trades that have been open too long under mediocre conditions, typically when they are in modest profit but not progressing. This protects you from capital being tied up while better opportunities appear elsewhere. Underlying all of this are several trailing stop mechanisms: percentage-based, tick-based for very short-term strategies, TP linked trailing that activates only once a certain profit threshold has been achieved, and ATR based trailing that automatically scales the trail distance with volatility. Each method serves a slightly different profile of strategy, but all share the same aim: preserve gains and limit downside in a structured way rather than rely on discretionary judgement after the fact.
4. Filters and Risk Management
The filter systems in PA Builder formalise the idea that good trading is often about knowing when not to act. “Do Not Trade” conditions can be configured so that even a perfectly aligned bullish entry stack is overridden if certain bearish evidence is present. These can include higher timeframe reversal structures, powerful opposing divergences, or conflicting signals in key modules. By assigning conditions specifically to “Do Not Long” and “Do Not Short” rather than only to entries, you create asymmetry: buying requires bullish evidence and an absence of strong bearish warnings; selling requires the mirror.
Volatility filters extend this logic to the regime level. Some strategies are inherently suited to low volatility, range bound environments where fading extremes is profitable; others require expansion and energy to function properly. By binding trading permission to volatility ranges, you ensure that a mean-reversion system does not blindly attempt to fade a breakout, and that a momentum system does not spin its wheels in a dead, sideways market. You can even reference volatility from a higher timeframe than the one you trade, so that a five-minute strategy is still aware of the broader one-hour volatility regime it sits inside.
Applied DO NOT TRADE - removes poor signal
Risk management and position sizing are configured so each trade is expressed in units of risk rather than arbitrary size. Leverage, in this framework, is simply a scaling factor for capital efficiency; the actual risk per trade is still controlled by the distance between entry and stop and the percentage of equity you choose to expose. Reinvestment options then decide what proportion of accumulated profit is fed back into position sizing. A more aggressive reinvestment setting accelerates compounding but increases the amplitude of drawdowns; a more conservative one smooths the equity curve at the cost of slower growth. The Base Trade Value parameter ties all of this together by deciding how much nominal capital or how many contracts are committed per trade in light of your maximum allowed simultaneous positions and your intended use of leverage.
External exit conditions provide further flexibility. For example, you might design a system whose entries rely purely on PA Builder’s internal modules, but whose exits use RSI readings, moving average crosses, or a proprietary external indicator. The separation of entry and exit logic allows you to bolt on different behaviours at the tail end of trades while keeping your core signal engine intact. In all cases, the objective is the same: express risk in a controlled, repeatable way that can survive long stretches of unfavourable market conditions.
5. PDT, Cooldowns and Visual Modes
For traders subject to Pattern Day Trading rules, PA Builder includes a day-trade tracking system that counts business days correctly and respects the three-trades-in-five-days limit. This goes beyond simple compliance; it forces discipline. When intraday trading is heavily constrained, you are naturally pushed toward swing-oriented strategies with fewer, more selective entries. The tool visually marks your PDT status so you never inadvertently cross the line and trigger a lockout.
Cooldown systems address another reality: psychological vulnerability after streaks. Following several consecutive wins, many traders unconsciously loosen their standards, take marginal signals, oversize positions, or overtrade. A win-streak cooldown deliberately pauses trading after a configured number of wins, giving you time to reset. The same applies to losing streaks. After a run of losses, the strongest temptation is often to “make it back now,” which is exactly when discipline is weakest. A loss-streak cooldown enforces a break in activity during this high-risk emotional state, helping to prevent cascading damage driven by revenge trading.
Visualisation comes in two main modes. Classic mode emphasises precision: it draws explicit entry lines, stop levels, target levels and fill zones, making it easy to audit risk/reward on each trade, verify that the exit logic behaves as intended, and review historical trades in detail. Modern mode emphasises market feel: instead of focusing on exact levels, it colours candles and backgrounds to reflect momentum, profit state and dynamics.
This helps you see at a glance whether a strategy is operating in a smooth trending environment or a choppy, fragmented one, and whether current trades are broadly working or struggling. Many users develop and debug in Classic mode and then monitor live performance in Modern mode, so both representations become part of the workflow.
6. Strategy Design Workflow, Examples and Cautions
Designing with PA Builder is inherently iterative. You begin with a simple theory and a minimal configuration, perhaps just a trend filter and a basic stop/target structure, and run a backtest. You then examine where the system fails. If you see many losses occurring in counter-trend conditions, you add an additional directional filter or restrict entries with a higher-timeframe reactor condition. If you observe many small whipsaw losses, you might require candle structure confirmation or volume confirmation before allowing an entry. Each change is made one at a time and evaluated. This process gradually builds a layered system where every component has a clear purpose: some reduce drawdown, some increase win rate, some cut out only the worst trades, and others help capture more of the best ones.
A conservative swing strategy might need an agreement between short-term trend signals, a higher-timeframe Quantum position, and a bullish Dynamic Reactor state, while checking that volume supports the move and that no significant bearish reversals or divergences are present on higher timeframes. It might accept relatively few trades, but each trade would be tightly controlled, scaled out over several ATR-based targets and protected with breakeven and trailing logic. On the opposite end, an aggressive scalping configuration would relax some filters, favour faster sensitivities, use short lookback reversals, and tighten stops and targets dramatically, relying on high frequency and careful volatility filtering to maintain edge.
Throughout all of this, overfitting remains the main danger. The more parameters you tune and the more coincidental rules you add to make the backtest equity curve smoother, the more likely it is that you are capturing noise rather than a real, repeatable edge. Signs of overfitting include heavily optimised numeric values with no intuitive justification, large differences between in-sample and out-of-sample results, or strategies that work spectacularly in very specific regimes and collapse elsewhere. To mitigate this, keep strategies as simple as possible, test across different market regimes (bull, bear, range), and accept that robust systems usually look less “perfect” on the historical chart.
Bridging the gap from backtest to live trading is another critical step. Before risking capital, it is wise to paper trade the configuration for a number of trades to confirm that signal frequency, behaviour and execution align with expectations. When going live, starting with minimal size and gradually scaling up based on real-world performance helps manage both financial and psychological risk. If live results diverge significantly from backtest expectations due to slippage, fees, or changing market conditions, you can adjust, reduce size, or temporarily pause rather than commit fully to a failing configuration.
Ultimately, PA Builder is designed to be a tool for building structured, rules-driven trading systems. It gives you the tools to express your ideas, test them, refine them, and run them under controlled risk. It does not remove uncertainty or guarantee results, but it does provide a clear, transparent way to translate trading concepts into executable, testable logic, and to evolve those systems as markets change and your understanding deepens.
Breakdown Sniper [Riz]Breakdown Sniper is a complete structural-based price-action system designed to identify and validate three major setups
1. Failed Breakdowns (FBD)
2. Breakouts / Breakdowns (BO)
3. Back-Tests (BT)
The script analyzes swing structure, undercuts, reclaim behavior, channel bias, support/resistance levels, and a multi-layer confluence engine to highlight high-quality long/short signals.
It also includes trade management, target projections, trailing logic, risk models, and an optional dashboard for clarity.
Core Concepts Behind the System
1. Pivot Structure & New Low/High Logic
Breakdown Sniper continuously detects pivot highs and lows using user-defined left/right bars.
These pivots are used to determine
⦁ Recent structural lows/highs
⦁ Undercuts (for failed breakdowns)
⦁ Structural breaks (for FBO/BO setups)
This provides the foundation for all three setup types.
2. Failed Breakdown (FBD) Detection
The primary logic of the script is to detect failed breakdowns, which follow this sequence:
1. Identify an initial pivot low
2. Price undercuts that low
3. Price reclaims the level by a specified number of points
4. Optional: new higher low print confirming strength
5. Once confirmed, the script calculates:
⦁ Entry trigger price
⦁ Stop placement (multiple options: below undercut, below initial low, ATR-based, fixed)
⦁ Three profit targets based on risk multiples
The reverse logic is applied for failed breakouts (FBO).
3. Breakouts & Breakdowns (BO)
The system also captures momentum breakouts/breakdowns defined by:
⦁ Price breaking major support/resistance
⦁ Bar-level strength (close vs range)
⦁ ATR-based expansion
⦁ Holding above/below breakout level for a user-defined number of bars
If confirmed, the script projects T1/T2/T3 targets and stop placement automatically.
4. Back-test Setups (BT)
After a confirmed breakout/breakdown, the script monitors for a return to the breakout level, within a percentage tolerance.
If a clean retest occurs:
⦁ A BT Long or BT Short setup is generated
⦁ Risk and target calculations are performed automatically
This allows identifying continuation setups after strong breaks.
Channel & Levels System (Support/Resistance Engine)
The script builds a hybrid S/R and environment model using:
⦁ Regression channel OR
⦁ Donchian, Keltner, Bollinger channels (user-selectable)
The channel provides:
⦁ Upper/Lower boundaries
⦁ Midline
⦁ Trend bias based on slope
Additionally, a multi-touch support/resistance detector clusters pivot-based levels and scores them by:
⦁ Touch count
⦁ Recency
⦁ Age
⦁ Whether they classify as major levels
This explains where reversals and breakouts are most likely.
Confluence Engine
Every Long/Short signal receives a 0–100 score derived from:
⦁ Market structure: HH/HL or LL/LH
⦁ Trend filter (EMA-based)
⦁ Volatility conditions (ATR range requirements)
⦁ Session bias (Asian / London / New York / Overlap)
⦁ Volume expansion
⦁ Higher-timeframe trend (optional)
⦁ Location inside channel
⦁ Distance to nearest S/R
⦁ Setup-type priority (FBD/BO/BT)
Users can require a minimum score before a signal becomes valid.
Trade Management Logic
Once a trade triggers, the indicator handles:
⦁ Entry execution confirmation
⦁ Stop loss tracking
⦁ Three independent profit targets
⦁ Optional scale-ins
⦁ ATR-based trailing stop
⦁ Risk calculations
⦁ Real-time PnL monitoring
The script does not execute live trades — it only visualizes management levels for analysis.
Visual Components
Breakdown Sniper plots:
⦁ Channels & fills
⦁ Auto-detected S/R levels
⦁ Pivot highs/lows
⦁ Buy/Sell markers
⦁ Entry/Stop/Targets
⦁ Trade dashboard (optional)
⦁ Equity curve (optional)
Everything is toggle-based for clean charting.
How To Use the Indicator
Recommended Use-Case
⦁ Futures (ES/NQ/CL/RTY)
⦁ Indices
⦁ Crypto
⦁ FX
Works well on:
⦁ 5m / 15m / 1H
Signals do not repaint because pivots and reclaim sequences require bar completion.
Basic Usage Steps
1. Enable the setups you want to trade: FBD, BO, BT
2. Optionally turn on filters:
⦁ Trend filter
⦁ Volatility filter
⦁ Market structure filter
⦁ MTF trend filter
3. Wait for a valid long/short signal with sufficient confluence
4. Follow the plotted entry level, stop, and targets
5. Use the dashboard to monitor performance of each setup type
Important Notes
This is a structural/price-action tool, not a prediction model
No guarantee of profitability is provided
The indicator is educational and analytical
Always use independent confirmation and risk management
Disclaimer
This script is for education and analysis. It does not provide financial advice. Markets involve risk. Past behavior of any pattern or study does not imply future results. You are responsible for your own decisions.
Golden BOS Strategy - ChecklistA clean, mechanical on-chart checklist designed for multi-timeframe traders using the Golden BOS / Institutional Retracement Framework.
This tool helps you stay disciplined by tracking each requirement of the strategy in real time:
Included Criteria
4H Bias: Bullish or bearish macro structure
1H Structure: Push/pull phase + golden zone retracement
5M Entry Model:
Break of Structure (BOS)
5M golden zone retracement
POI validation (OB/FVG/Breaker)
Final micro BOS or rejection confirmation
Risk Filters:
Session validity (London / NY)
Red news avoidance
Stop-loss placement check
Liquidity-based target confirmation
Purpose
This overlay ensures every trade meets strict criteria before execution, removing emotion and improvisation. Ideal for backtesting, forward testing, and staying consistent during live market conditions.
Golden BOS Strategy — Description
The Golden BOS Strategy is a structured, multi-timeframe trading system designed to capture high-probability continuation moves during London and New York sessions. The strategy combines institutional concepts with Fibonacci-based retracements to identify discounted entry zones aligned with higher-timeframe direction.
Using the 4H timeframe, traders establish the daily macro bias and identify the dominant trend. The 1H chart is then used to confirm the current phase of market structure, distinguishing between impulsive “push” moves and corrective “pullback” phases. A Fibonacci retracement is applied to the most recent 1H impulse leg to define a high-value discount or premium zone where entries become valid.
Execution takes place on the 5-minute chart. Once price reaches the 1H golden zone (61.8–78.6%), a Break of Structure (BOS) is required to confirm a shift in short-term momentum. A second Fibonacci retracement is then drawn on the 5M impulse leg that caused the BOS, and price must retrace back into the 5M golden zone. Traders refine their entry using a confluence point of interest (POI) such as a Fair Value Gap (FVG), Order Block, Breaker Block, or Inverse FVG, ideally accompanied by a final micro BOS or rejection candle.
Risk management is strict and rule-driven. Stop loss is placed beyond the extreme wick of the POI, while take-profit targets are set at logical liquidity pools in the direction of the higher-timeframe trend. The strategy avoids red-folder news and only allows trades during active sessions to ensure optimal volatility and reliability.
The Golden BOS Strategy is designed to impose discipline, reduce discretionary errors, and give traders a repeatable, mechanical framework for navigating trending markets with precision.
Adaptive Trend SelectorThe Adaptive Trend Selector is a comprehensive trend-following tool designed to automatically identify the optimal moving average crossover strategy. It features adjustable parameters and an integrated backtester that delivers institutional-grade insights into the recommended strategy. The model continuously adapts to new data in real time by evaluating multiple moving average combinations, determining the best performing lengths, and presenting the backtest results in a clear, color-coded table that benchmarks performance against the buy-and-hold strategy.
At its core, the model systematically backtests a wide range of moving average combinations to identify the configuration that maximizes the selected optimization metric. Users can choose to optimize for absolute returns or risk-adjusted returns using the Sharpe, Sortino, or Calmar ratios. Alternatively, users can enable manual optimization to test custom fast and slow moving average lengths and view the corresponding backtest results. The label displays the Compounded Annual Growth Rate (CAGR) of the strategy, with the buy-and-hold CAGR in parentheses for comparison. The table presents the backtest results based on the fast and slow lengths displayed at the top:
Sharpe = CAGR per unit of standard deviation.
Sortino = CAGR per unit of downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Return sensitivity relative to buy-and-hold.
Alpha (α) = Excess annualized risk-adjusted returns.
Win Rate = Ratio of profitable trades to total trades.
Profit Factor = Total gross profit per unit of losses.
Expectancy = Average expected return per trade.
Trades/Year = Average number of trades per year.
This indicator is designed with flexibility in mind, enabling users to specify the start date of the backtesting period and the preferred moving average strategy. Supported strategies include the Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), and Volume-Weighted Moving Average (VWMA). To minimize overfitting, users can define constraints such as a minimum and maximum number of trades per year, as well as an optional optimization margin that prioritizes longer, more robust combinations by requiring shorter-length strategies to exceed this threshold. The table follows an intuitive color logic that enables quick performance comparison against buy-and-hold (B&H):
Sharpe = Green indicates better than B&H, while red indicates worse.
Sortino = Green indicates better than B&H, while red indicates worse.
Calmar = Green indicates better than B&H, while red indicates worse.
Max DD = Green indicates better than B&H, while red indicates worse.
Beta (β) = Green indicates better than B&H, while red indicates worse.
Alpha (α) = Green indicates above 0%, while red indicates below 0%.
Win Rate = Green indicates above 50%, while red indicates below 50%.
Profit Factor = Green indicates above 2, while red indicates below 1.
Expectancy = Green indicates above 0%, while red indicates below 0%.
In summary, the Adaptive Trend Selector is a powerful tool designed to help investors make data-driven decisions when selecting moving average crossover strategies. By optimizing for risk-adjusted returns, investors can confidently identify the best lengths using institutional-grade metrics. While results are based on the selected historical period, users should be mindful of potential overfitting, as past results may not persist under future market conditions. Since the model recalibrates to incorporate new data, the recommended lengths may evolve over time.
My setup [Pro] (fadi)My Setup is a powerful TradingView indicator that visualizes your trading strategy, helping you find high-probability setups with precision and discipline. It combines Higher Timeframe (HTF) context with Lower Timeframe (LTF) entries on a single chart, streamlining your trading process.
What It Does
Tracks your chosen timeframe and its paired higher timeframe for custom trade setups, so you don’t have to stay glued to the screen.
Plots clear Entry, Stop Loss, and Take Profit levels when your conditions align.
Customizes to your strategy with HTF triggers (e.g., sweeps, liquidity grabs) and LTF entries (e.g., Order Blocks, FVGs, Breakers).
Ensures discipline by only showing setups that meet all your rules, eliminating emotional trading and FOMO.
Backtest your edge by visualizing past setups to refine entries, stops, and confluences.
How It Works
Set Your HTF Trigger: Choose a market event like a sweep of a high/low, pivot point, or liquidity grab on the paired higher timeframe (e.g., 1H for a 5m chart).
Define Your LTF Entry: Select your entry model from a range of institutional concepts, such as Order Block, Fair Value Gap (FVG), Inverted FVG (iFVG), Breaker Block, Unicorn Model, and more, on the chart’s timeframe.
Add Confluence Filters: Stack conditions like requiring an FVG + Breaker for higher-probability setups.
See It on Your Chart: When a setup forms, it’s instantly plotted with Entry, Stop Loss, and Take Profit levels based on your Risk-to-Reward ratio.
Key Features
Multi-Timeframe Sync: Pair your chart’s timeframe (e.g., 5m) with a higher timeframe (e.g., 1H) for seamless analysis.
Institutional Tools: Supports a comprehensive suite of ICT concepts, including Order Blocks, FVGs, iFVGs, Breakers, Unicorn Model, and additional entry models.
Custom Risk Management: Set your Stop Loss and Take Profit levels with fixed R:R or measured moves using large range of entry and stop levels.
Session Filtering: Limit setups to specific trading sessions (e.g., London, New York) with timezone support.
Visual Clarity: Displays HTF candles and key levels on your chart for context, with customizable colors and styles.
Alerts: Get notified the moment a valid setup appears, even on live candles.
Who It’s For
Traders who want to systematize their ICT-based strategy on a single chart.
Those seeking to trade with discipline and avoid impulsive decisions.
Anyone looking to backtest and optimize their setups with clear, visual feedback.
Busy traders who need a tool to track their chart while they focus on life.
Why Choose My Setup ?
Save Time: Let the indicator track your chart and its paired timeframe.
Trade Confidently: Only take A+ setups that match your exact rules.
Learn and Improve: Analyze historical setups to refine your strategy.
Disclaimer of Warranties and Limitation of Liability for [My Setup ]
Please read this disclaimer carefully before using the [My Setup ] indicator (hereafter referred to as "the Software").
1. No Financial Advice
The Software is provided for educational and informational purposes only. The data, calculations, and signals generated by the Software are not, and should not be interpreted as, financial advice, investment advice, trading advice, or a recommendation or solicitation to buy, sell, or hold any security or financial instrument.
2. Assumption of Risk You acknowledge that trading and investing are inherently risky activities that carry a high potential for significant financial loss. All actions you take in the market, including but not limited to trade execution and risk management, are your sole responsibility. You agree to use the Software at your own sole risk. The creator shall not be held responsible or liable for any financial losses or damages you may incur as a result of using the Software.
3. No Warranty; "AS IS" Provision
The Software is provided "AS IS" and "AS AVAILABLE", without any warranties of any kind, either express or implied. The creator disclaims all warranties, including, but not limited to, implied warranties of merchantability, fitness for a particular purpose, accuracy, timeliness, completeness, and non-infringement.
The creator does not warrant that the Software will be error-free, uninterrupted, secure, or free of bugs, viruses, or other harmful components. You acknowledge that software is never wholly free from defects, and you are responsible for implementing your own procedures for data accuracy and security.
4. Limitation of Liability
TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW, IN NO EVENT SHALL THE CREATOR, FADI ZEIDAN, BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT, OR OTHERWISE, ARISING FROM, OUT OF, OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
This limitation of liability applies to any and all damages, including but not limited to:
Direct, indirect, incidental, special, consequential, or exemplary damages.
Loss of profits, revenue, data, or use.
Financial losses resulting from trading decisions made based on the Software.
Damages arising from software defects, interruptions, or inaccuracies.
5. Indemnification
You agree to indemnify, defend, and hold harmless the creator, Fadi Zeidan, from and against any and all claims, liabilities, damages, losses, or expenses, including reasonable attorneys' fees and costs, arising out of or in any way connected with your access to or use of the Software.
6. Acknowledgment and Agreement
By accessing, installing, or using the [My Setup ] indicator, you acknowledge that you have read, understood, and agree to be bound by the terms of this disclaimer. If you do not agree with these terms, you must not use the Software.
Portfolio Strategy TesterThe Portfolio Strategy Tester is an institutional-grade backtesting framework that evaluates the performance of trend-following strategies on multi-asset portfolios. It enables users to construct custom portfolios of up to 30 assets and apply moving average crossover strategies across individual holdings. The model features a clear, color-coded table that provides a side-by-side comparison between the buy-and-hold portfolio and the portfolio using the risk management strategy, offering a comprehensive assessment of both approaches relative to the benchmark.
Portfolios are constructed by entering each ticker symbol in the menu, assigning its respective weight, and reviewing the total sum of individual weights displayed at the top left of the table. For strategy selection, users can choose between Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), Moving Average Convergence Divergence (MACD), and Volume-Weighted Moving Average (VWMA). Moving average lengths are defined in the menu and apply only to strategy-enabled assets.
To accurately replicate real-world portfolio conditions, users can choose between daily, weekly, monthly, or quarterly rebalancing frequencies and decide whether cash is held or redistributed. Daily rebalancing maintains constant portfolio weights, while longer intervals allow natural drift. When cash positions are not allowed, capital from bearish assets is automatically redistributed proportionally among bullish assets, ensuring the portfolio remains fully invested at all times. The table displays a comprehensive set of widely used institutional-grade performance metrics:
CAGR = Compounded annual growth rate of returns.
Volatility = Annualized standard deviation of returns.
Sharpe = CAGR per unit of annualized standard deviation.
Sortino = CAGR per unit of annualized downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Sensitivity of returns relative to benchmark returns.
Alpha (α) = Excess annualized risk-adjusted returns relative to benchmark.
Upside = Ratio of average return to benchmark return on up days.
Downside = Ratio of average return to benchmark return on down days.
Tracking = Annualized standard deviation of returns versus benchmark.
Turnover = Average sum of absolute changes in weights per year.
Cumulative returns are displayed on each label as the total percentage gain from the selected start date, with green indicating positive returns and red indicating negative returns. In the table, baseline metrics serve as the benchmark reference and are always gray. For portfolio metrics, green indicates outperformance relative to the baseline, while red indicates underperformance relative to the baseline. For strategy metrics, green indicates outperformance relative to both the baseline and the portfolio, red indicates underperformance relative to both, and gray indicates underperformance relative to either the baseline or portfolio. Metrics such as Volatility, Tracking Error, and Turnover ratio are always displayed in gray as they serve as descriptive measures.
In summary, the Portfolio Strategy Tester is a comprehensive backtesting tool designed to help investors evaluate different trend-following strategies on custom portfolios. It enables real-world simulation of both active and passive investment approaches and provides a full set of standard institutional-grade performance metrics to support data-driven comparisons. While results are based on historical performance, the model serves as a powerful portfolio management and research framework for developing, validating, and refining systematic investment strategies.
Force of Strategy (FoS, Multi TF/TA, Backtest, Alerts)Introducing the FoS Trading System
A comprehensive and innovative solution designed for both novice and experienced traders to enhance their intraday trading.
The basic idea of creating this script is to stay profitable in any market
Key Features:
There are over 25 no-repaint strategies for generating buy and sell signals to choose from
10 symbols for simultaneous trading
Webhook alerts in TTA format (tradingview to anywhere) pre-configured to send messages for trading cross-margin futures on major Crypto Exchanges: Binance, Bitget, BingX, Bybit, GateIO and OKX
A unique automated "Strategy switcher" feature for backtesting and live trading—not just a specific strategy, but the logic behind choosing a trading one or another strategy based on backtesting data obtained in real time
Advanced risk management options and backtest result metrics
Higher Timeframe filters (Technical Rating, ADX, Volatility) and ability for check backtest results with 9 main higher timeframes
Buy and sell signals are generated using TradingView Technical Ratings, indicators with adaptive length algorithms and various classic indicators with standard settings to avoid overfitting
Next, I will describe in detail what this script does and what settings it operates with:
"All Strategies" off
- In the global settings block, as shown in the main chart screenshot, you select how long the script will perform backtests in days, with a limitation on the number of bars for calculations. This limitation is necessary to maintain an acceptable calculation speed. You also choose which two higher timeframes we will use for signal and filters when confirming the opening of trades
- With "All Strategies" off - as in the example on the main chart screenshot, trading is carried out by strategy #1 on 10 selected tickers simultaneously. By default, I selected the 9 top-capitalized cryptocurrencies on the Bitget exchange and the chart symbol. You can change that choice of 9 non chart opened instruments and # strategy for each them
- The first row in the table 1 shows some of the main choosen script settings, in attached example: initial capital 20$, leverage 50L, 20 backtest days, 3$ is invest in one deal, 60m - is chart timeframe, next 60m is higher timeframe 1 and last 90m is higher timeframe 2. In first column you see shortened to 5 characters ticker names
- The exchange name in the second row determines the alert messages format
I've attached another example of trading with setting "All strategies" off in the image below. In this example, trading 10 standard symbols on an hourly timeframe, 2 coins from 10: 1000SATS and DOGE have generated a profit of over $65 over the past 20 days using strategy #4
Can you browse a wide range of trading instruments and select the 10 best strategies and settings for future trading? Of course, trading is what this script is do!
The parameters in the table 1 mean the following:
TR - count of closed trading deals
WR - Winning Rate, PF - Profit Factor
MDD - Max Draw Down for all calculated time from initial capital
R$ - trading profit result in usd
The parameters in the table 2 is just more metrics for chart symbol:
PT - result in usd Per one Trade
PW - result Per Win, PL - result Per Lose
ROI - Rate of Investments
SR - Sharpe Ratio, MR - CalMAR ration
Tx - Commision Fee in Usd
R$ - trading profit result in usd again
Table 2 separate trade results of backtesting for longs and shorts. In first column you see how many USD were invested in one trade, taking into account possible position splitting (will be discussed in more detail in the risk management section)
Settings:
"All Strategies" on, "Check Last" off
When "All Strategies" is active, trading changed from 10 symbols and one strategy to all strategies and one chart symbol. If option "Check Last" is inactive you will see backtest results for each of strategy in backtest setting days. This is useful, for example, if you want to see backtest results under different settings over a long period of time for calibrating risk management or entry rules
"All Strategies" on, "Check Last" on
- If "All Strategies" and "Check Last" is active trading will occur on the chart symbol only for those strategies that meet the criteria of the settings block for the enabled "All Strategies" option. For example your criteria is: for last 5 trades for all strategies, open next trade only on strategy which reached ROI 25% and WinRate 50%. When strategy with this setting criteria receive Buy or Sell Signal this trade will be opened, and when trade will be close "check last" will repeat. This feature i called "Strategy switcher"
-In Table 1 if strategy meet criteria you will see "Ok" label, if strategy meet criteria and have maximum from other reached ROI they labeled "Best". Chart strategy labeled "Chart", Chart and Ok labels in one time is "Chart+", "Chart" and "Best" is labeled "Best+"
- The color in the first column of table 1 indicates that the strategy is currently in an open position: green means an open long position, red means an open short position.
In picture bellow you will see good example for trading with check results for last 10 trades, and make desicion for trading when criteries 0.25 ROI and WinRate 50% reached for Top 2 by ROI strategies from all list of them. This example of trading logic in last 20 days (include periods when strategy don't arise 10 trades) give a profit $30+. At the bottom of the screen, you can see Labels with the numbers of the strategies that opened the trades. In this example, trades were primarily opened using strategy number 2, and the second most effective strategy after the 20-day backtest was strategy number 9
Who can promise you'll make a profit of $30 in the next 20 days with a drawdown of no more than $8 from the initial $20 with invest in one trade just 2.7$? No one. But this script guarantees that in the future it will repeat the same logic of switching trading strategies that brought profit over the last 20 days
Risk management options
- When a buy or sell trade is opened, you'll see three lines on the chart: a red stop-loss line (SL), a green take-profit line (TP), and a blue line representing the entry price. The trade will be closed if the high price or low price reaches the line TP or SL (no wait for bar close) and alert will be triggered once per bar when script recalculates
- Several options are available to control the behavior of SL/TP lines, such as stop-loss by percentage, ATR, or Highest High (HH) and Lowest Low (LL). Take Profit can be in percent, ATR or in Risk Reward ratio. There some Trailing Stop with start trail trigger options, like ATR, percent or HH / LL
- Additionally, in risk managment settings a function has been implemented for adding a position when the breakeven level expressed in the current ROI is reached for opened trade (splitting position). The position is added within the bar.
- Webhook alerts in TTA format with message contained next info : Buy / Sell or adding Quantity, Leverage, SL price, TP price and close trade
Keep in mind if the stop-loss changed when adding a position, the stop-loss will not be able to be higher than the current bar's low price, regardless of your settings, as backtest trades do not use intra-bar data, in this situation SL will be correct at next bar (but alert message don't be sended twice). And please note that this script does not have an option to simultaneously open trades in different directions. Only 1 trade can be opened for 1 trading instrument at a time
Backtest Engine
Backtest is a very important part of this script. Here describe how its calculate:
- Profit or Loss is USD: close trade price * open trade quantity - open trade price * open trade quantity - open trade quantity * (open trade price + close trade price)/2 * commision fee
Possible slippage or alert sending delay needed to be include in commission % which you will set in risk managment settings block, default settings is 0.15% (0,06% for open, 0,06% for close and 0,03% for possible slippage or additional fees)
- Maximum Draw Down: Drawdown = (peak - current equity) / peak * 100 ;
Drawdown > maxDrawdown ? maxDrawdown = Drawdown
- ROI: profit result in USD / sum of all positions margin
- CalMAR Ratio: ROI / (-MaxDrawDown)
- Sharpe Ratio: ROI / standard deviation for (Sum of all Profits and Loses) / (Sum of all Position Margins)
This description was added because in metrics i don't use parameters like "The risk-free rate of return". Keep in mind how exactly this script calculate profit and perfomance when adjusting key criteria in the strategy switching parameters block of script settings
Strategies itself
For trading, you can enable or disable various Higher Timeframes Filters (ADX, volatility, technical rating).
With filters enabled, trades will only open when the setting parameters are reached
- Strategy number 1, 2 and 3: is Higher Timeframe TradingView Technical Ratings itself, 1 is summary total rating, 2 is oscillators and 3 is moving averages. When TR filter cross filter levels trade will be open at chart bar close. By Default on chart you see Summary Technical Rating oscillator, but here the options for change it to Oscillator TR or Moving Average TR
- Strategy number 4, 5 and 6: is Chart TimeFrame TR. Trades will open when its values (Summary, Oscillators and Moving Averages) reached setting buy sell level
- Strategy number 7, 8 and 9: is Alternative buy sell logic for Chart TimeFrame TR, trades will open when counting rising or falling values will be reached
- Strategies with number from 10 to 18: is chosen by user adaptive moving averages and oscillators indicators. There in settings you will see many different adaptive length algorithms for trading and different types of moving averages and oscillators. In tooltips in settings you will find very more information, and in settings you will see list of all indicators and algorithms (more than 30 variations). All adaptive strategies have their options in settings for calibrating and plotting
- Strategies with number from 19: its can't be chosen or calibarted, this is needed for avoid overfitting, i try to found mostly time worked strategies and use its with standard settings. In future it's possible to changing current or adding additional strategies. At the time of publication this script uses: Dynamic Swing HH LL (19), Composite indicator (20), %R Exhausting with different signals (21,22,23), Pivot Point SuperTrend (24), Ichimoku Cloud (25), TSI (26), Fib Level RSI (27). I don't plot classic strategies in this script
Let me explain, the value of this script is not in the strategies it includes, but in how exactly it collects the results of their work, how it filters the opening of trades, what risk management it applies and what strategy switching logic it performs. The system itself that you are now reading about represents the main value of this script
Finally if you get access for this script
- You will see many other not described options and possibilities like Kelly position or list of settings for adaptive strategies, also i added many usefull tooltips in script settings
Happy trading, and stay tuned for updates!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorized for this script, and the information published with them. This script is strictly for individual use. No one know future and Investments are always made at your own risk. I am not responsible for any losses you may incur. Please before investment make sure that chosen logic is enaugh profitable on virtual demo account.
The Best Strategy Template[LuciTech]Hello Traders,
This is a powerful and flexible strategy template designed to help you create, backtest, and deploy your own custom trading strategies. This template is not a ready-to-use strategy but a framework that simplifies the development process by providing a wide range of pre-built features and functionalities.
What It Does
The LuciTech Strategy Template provides a robust foundation for building your own automated trading strategies. It includes a comprehensive set of features that are essential for any serious trading strategy, allowing you to focus on your unique trading logic without having to code everything from scratch.
Key Features
The LuciTech Strategy Template integrates several powerful features to enhance your strategy development:
•
Advanced Risk Management: This includes robust controls for defining your Risk Percentage per Trade, setting a precise Risk-to-Reward Ratio, and implementing an intelligent Breakeven Stop-Loss mechanism that automatically adjusts your stop to the entry price once a specified profit threshold is reached. These elements are crucial for capital preservation and consistent profitability.
•
Flexible Stop-Loss Options: The template offers adaptable stop-loss calculation methods, allowing you to choose between ATR-Based Stop-Loss, which dynamically adjusts to market volatility, and Candle-Based Stop-Loss, which uses structural price points from previous candles. This flexibility ensures the stop-loss strategy aligns with diverse trading styles.
•
Time-Based Filtering: Optimize your strategy's performance by restricting trading activity to specific hours of the day. This feature allows you to avoid unfavorable market conditions or focus on periods of higher liquidity and volatility relevant to your strategy.
•
Customizable Webhook Alerts: Stay informed with advanced notification capabilities. The template supports sending detailed webhook alerts in various JSON formats (Standard, Telegram, Concise Telegram) to external platforms, facilitating real-time monitoring and potential integration with automated trading systems.
•
Comprehensive Visual Customization: Enhance your analytical clarity with extensive visual options. You can customize the colors of entry, stop-loss, and take-profit lines, and effectively visualize market inefficiencies by displaying and customizing Fair Value Gap (FVG) boxes directly on your chart.
How It Does It
The LuciTech Strategy Template is meticulously crafted using Pine Script, TradingView's powerful and expressive programming language. The underlying architecture is designed for clarity and modularity, allowing for straightforward integration of your unique trading signals. At its core, the template operates by taking user-defined entry and exit conditions and then applying a sophisticated layer of risk management, position sizing, and trade execution logic.
For instance, when a longCondition or shortCondition is met, the template dynamically calculates the appropriate position size. This calculation is based on your specified risk_percent of equity and the stop_distance (the distance between your entry price and the calculated stop-loss level). This ensures that each trade adheres to your predefined risk parameters, a critical component of disciplined trading.
The flexibility in stop-loss calculation is achieved through a switch statement that evaluates the sl_type input. Whether you choose an ATR-based stop, which adapts to market volatility, or a candle-based stop, which uses structural price points, the template seamlessly integrates these methods. The ATR calculation itself is further refined by allowing various smoothing methods (RMA, SMA, EMA, WMA), providing granular control over how volatility is measured.
Time-based filtering is implemented by comparing the current bar's time with user-defined start_hour, start_minute, end_hour, and end_minute inputs. This allows the strategy to activate or deactivate trading during specific market sessions or periods of the day, a valuable tool for optimizing performance and avoiding unfavorable conditions.
Furthermore, the template incorporates advanced webhook alert functionality. When a trade is executed, a customizable JSON message is formatted based on your webhook_format selection (Standard, Telegram, or Concise Telegram) and sent via alert function. This enables seamless integration with external services for real-time notifications or even automated trade execution through third-party platforms.
Visual feedback is paramount for understanding strategy behavior. The template utilizes plot and fill functions to clearly display entry prices, stop-loss levels, and take-profit targets directly on the chart. Customizable colors for these elements, along with dedicated options for Fair Value Gap (FVG) boxes, enhance the visual analysis during backtesting and live trading, making it easier to interpret the strategy's actions.
How It's Original
The LuciTech Strategy Template distinguishes itself in the crowded landscape of TradingView scripts through its unique combination of integrated, advanced risk management features, highly flexible stop-loss methodologies, and sophisticated alerting capabilities, all within a user-friendly and modular framework. While many templates offer basic entry/exit signal integration, LuciTech goes several steps further by providing a robust, ready-to-use infrastructure for managing the entire trade lifecycle once a signal is generated.
Unlike templates that might require users to piece together various risk management components or code complex stop-loss logic from scratch, LuciTech offers these critical functionalities out-of-the-box. The inclusion of dynamic position sizing based on a user-defined risk percentage, a configurable risk-to-reward ratio, and an intelligent breakeven mechanism significantly elevates its utility. This comprehensive approach to capital preservation and profit targeting is a cornerstone of professional trading and is often overlooked or simplified in generic templates.
Furthermore, the template's provision for multiple stop-loss calculation types—ATR-based for volatility adaptation, and candle-based for structural support/resistance—demonstrates a deep understanding of diverse trading strategies. The underlying code for these calculations is already implemented, saving developers considerable time and effort. The subtle yet powerful inclusion of FVG (Fair Value Gap) related inputs also hints at advanced price action concepts, offering a sophisticated layer of analysis and execution that is not commonly found in general-purpose templates.
The advanced webhook alerting system, with its support for various JSON formats tailored for platforms like Telegram, showcases an originality in catering to the needs of modern, automated trading setups. This moves beyond simple TradingView pop-up alerts, enabling seamless integration with external systems for real-time trade monitoring and execution. This level of external connectivity and customizable data output is a significant differentiator.
In essence, the LuciTech Strategy Template is original not just in its individual features, but in how these features are cohesively integrated to form a powerful, opinionated, yet highly adaptable system. It empowers traders to focus their creative energy on developing their core entry/exit signals, confident that the underlying framework will handle the complexities of risk management, trade execution, and external communication with precision and flexibility. It's a comprehensive solution designed to accelerate the development of robust and professional trading strategies.
How to Modify the Logic to Apply Your Strategy
The LuciTech Strategy Template is designed with modularity in mind, making it exceptionally straightforward to integrate your unique trading strategy logic. The template provides a clear separation between the core strategy management (risk, position sizing, exits) and the entry signal generation. This allows you to easily plug in your own buy and sell conditions without altering the robust underlying framework.
Here’s a step-by-step guide on how to adapt the template to your specific trading strategy:
1.
Locate the Strategy Logic Section:
Open the Pine Script editor in TradingView and navigate to the section clearly marked with the comment //Strategy Logic Example:. This is where the template’s placeholder entry conditions (a simple moving average crossover) are defined.
2.
Define Your Custom Entry Conditions:
Within this section, you will find variables such as longCondition and shortCondition. These are boolean variables that determine when a long or short trade should be initiated. Replace the existing example logic with your own custom buy and sell conditions. Your conditions can be based on any combination of indicators, price action patterns, candlestick formations, or other market analysis techniques. For example, if your strategy involves a combination of RSI and MACD, you would define longCondition as (rsi > 50 and macd_line > signal_line) and shortCondition as (rsi < 50 and macd_line < signal_line).
3.
Leverage the Template’s Built-in Features:
Once your longCondition and shortCondition are defined, the rest of the template automatically takes over. The integrated risk management module will calculate the appropriate position size based on your Risk % input and the chosen Stop Loss Type. The Risk:Reward ratio will determine your take-profit levels, and the Breakeven at R feature will manage your stop-loss dynamically. The time filter (Use Time Filter) will ensure your trades only occur within your specified hours, and the webhook alerts will notify you of trade executions.
Replay time-fix last candleReplay indicator to avoid showing the fully closed last candle on higher timeframes.
This indicator displays the last candle up to the current point of the replay instead of the full candle.
For example, if you are on a 4H chart at the 1:00 candle and the replay is at 2:00, it will show the last candle from 1:00 → 2:00 only.
Important: To see the correct candles, go to your chart settings and untick the checkboxes for: "Body", "Borders", "Wick", and "Last price line".
Autoback Grid Lab [trade_lexx]Autoback Grid Lab: Your personal laboratory for optimizing grid strategies.
Introduction
First of all, it is important to understand that Autoback Grid Lab is a powerful professional tool for backtesting and optimization, created specifically for traders using both grid strategies and regular take profit with stop loss.
The main purpose of this script is to save you weeks and months of manual testing and parameter selection. Instead of manually testing one combination of settings after another, Autoback Grid Lab automatically tests thousands of unique strategies on historical data, providing you with a comprehensive report on the most profitable and, more importantly, sustainable ones.
If you want to find mathematically sound, most effective settings for your grid strategy on a specific asset and timeframe, then this tool was created for you.
Key Features
My tool has functionality that transforms the process of finding the perfect strategy from a routine into an exciting exploration.
🧪 Mass testing of thousands of combinations
The script is able to systematically generate and run a huge number of unique combinations of parameters through the built-in simulator. You set the ranges, and the indicator does all the work, testing all possible options for the following grid settings:
* Number of safety orders (SO Count)
* Grid step (SO Step)
* Step Multiplier (SO Multiplier) for building nonlinear grids
* Martingale for controlling the volume of subsequent orders
* Take Profit (%)
* Stop Loss (%), with the possibility of calculating both from the entry point and from the dynamic breakeven line
* The volume of the base order (Volume BO) as a percentage of the deposit
🏆 Unique `FinalScore` rating system
Sorting strategies by net profit alone is a direct path to self—deception and choosing strategies that are "tailored" to history and will inevitably fail in real trading. To solve this problem, we have developed FinalScore, a comprehensive assessment of the sustainability and quality of the strategy.
How does it work?
FinalScore analyzes each combination not one by one, but by nine key performance metrics at once, including Net Profit, Drawdown, Profit Factor, WinRate, Sharpe coefficients, Sortino, Squid and Omega. Each of these indicators is normalized, that is, reduced to a single scale. Then, to test the strategy for strength, the system performs 30 iterations, each time assigning random weights to these 9 metrics. A strategy gets a high FinalScore only if it shows consistently high results under different evaluation criteria. This proves her reliability and reduces the likelihood that her success was an accident.
📈 Realistic backtesting engine
The test results are meaningless if they do not take into account the actual trading conditions. Our simulator simulates real trading as accurately as possible, taking into account:
* Leverage: Calculation of the required margin to open and hold positions.
* Commission: A percentage commission is charged each time an order is opened and closed.
* Slippage: The order execution price is adjusted by a set percentage to simulate real market conditions.
* Liquidation model: This is one of the most important functions. The script continuously monitors the equity of the account (capital + unrealized P&L). If equity falls below the level of the supporting margin (calculated from the current value of the position), the simulator forcibly closes the position, as it would happen on a real exchange. This eliminates unrealistic scenarios where the strategy survives after a huge drawdown.
🔌 Integration with external signals
The indicator operates in two modes:
1. `No Signal': Standard mode. The trading cycle starts immediately as soon as the previous one has been closed. Ideal for testing the "pure" mechanics of the grid.
2. `External Signal`: In this mode, a new trading cycle will start only when a signal is received from an external source. You can connect any other indicator (such as the RSI, MACD, or your own strategy) to the script and use it as a trigger to log in. This allows you to combine the power of a grid strategy with your own entry points.
📊 Interactive and informative results panel
Upon completion of the calculations, a detailed table with the TOP N best strategies appears on the screen, sorted according to your chosen criterion. For each strategy in the rating, you will see not only the key metrics (Profit, Drawdown, duration of transactions), but also all the parameters that led to this result. You can immediately take these settings and apply them in your trading.
Application Options: How To Solve Your Problems
Autoback Grid Lab is a flexible tool that can be adapted to solve various tasks, from complete grid optimization to fine—tuning existing strategies. Here are some key scenarios for its use:
1. Complete Optimization Of The Grid Strategy
This is the basic and most powerful mode of use. You can find the most efficient grid configuration for any asset from scratch.
* How to use: Set wide ranges for all key grid parameters ('SO Count`, SO Step, SO Multiplier, Martingale, TP, etc.).
* In the `No Signal` mode: You will find the most stable grid configuration that works as an independent, constantly active strategy, regardless of which-or entrance indicators.
* In the `External Signal` mode: You can connect your favorite indicator for input (for example, RSI, MACD or a complex author's script) and find the optimal grid parameters that best complement your input signals. This allows you to turn a simple signaling strategy into a full-fledged grid system.
2. Selecting the Optimal Take Profit and Stop Loss for Your Strategy
Do you already have an entry strategy, but you are not sure where it is best to put Take Profit and Stop Loss? Autoback Grid Lab can solve this problem as well.
* How to use:
1. Disable optimization of all grid parameters (uncheck SO Count, SO Step, Martingale, etc.). Set the Min value for SO Count to 0.
2. Set the ranges for iteration only for 'Take Profit` and `Stop Loss'.
3. Turn on the External Signal mode and connect your indicator with input signals.
* Result: The script will run your historical entry signals with hundreds of different TP and SL combinations and show you which stop order levels bring maximum profit with minimal risk specifically for your entry points.
3. Building a Secure Network with Risk Management
Many traders are afraid of grid strategies because of the risk of large drawdowns. With the help of the optimizer, you can purposefully find the parameters for such a grid, which includes mandatory risk management through Stop Loss.
* How to use: Enable and set the range for Stop Loss, along with other grid parameters. Don't forget to test both types of SL calculations (`From entry point` and `From breakeven line`) to determine which one works more efficiently.
* Result: You will find balanced strategies in which the grid parameters (number of orders, martingale) and the Stop Loss level are selected in such a way as to maximize profits without going beyond the acceptable risk level for you.
How To Use The Indicator (Step-By-Step Guide)
Working with the Autoback Grid Lab is a sequential process consisting of four main steps: from initial setup to analysis of the finished results. Follow this guide to get the most out of the tool.
Step 1: Initial Setup
1. Add the indicator to the chart of your chosen asset and timeframe.
2. Open the script settings. The first thing you should pay attention to is the ⚙️ Optimization Settings ⚙️ group.
3. Set the `Bars Count'. This parameter determines how much historical data will be used for testing.
* Important: The more bars you specify, the more statistically reliable the backtest results will be. We recommend using the maximum available value (25,000) to test strategies at different market phases.
* Consider: The indicator performs all calculations on the last historical bar. After applying the TradingView settings, it will take some time to load all the specified bars. The results table will appear only after the data is fully loaded. Don't worry if it doesn't appear instantly. And if an error occurs, simply switch the number of combinations to 990 and back to 1000 until the table appears.
Step 2: Optimization Configuration
At this stage, you define the "universe" of parameters that our algorithm will explore.
1. Set the search ranges (🛠 Optimization Parameters 🛠 group).
For each grid parameter that you want to optimize (for example, SO Count or `Take Profit'), you must specify three values:
* Min: The minimum value of the range.
* Max: The maximum value of the range.
* Step: The step with which the values from Min to Max will be traversed.
*Example:* If you set Min=5, Max=10, and Step=1 for SO Count, the script will test strategies with 5, 6, 7, 8, 9, and 10 safety orders.
* Tip for users: To get the first results quickly, start with a larger step (for example, TP from 0.5% to 2.5% in 0.5 increments instead of 0.1). After you identify the most promising areas, you can perform a deeper analysis by expanding the ranges around these values.
2. Set Up Money Management (Group `💰 Money Management Settings 💰`).
Fill in these fields with the values that best match your actual trading conditions. This is critically important for obtaining reliable results.
* Capital: Your initial deposit.
* Leverage: Leverage.
* Commission (%): Your trading commission as a percentage.
* Slippage (%): Expected slippage.
* Liquidation Level (%): The level of the supporting margin (MMR in %). For example, for Binance Futures, this value is usually between 0.4% and 2.5%, depending on the asset and position size. Specify this value for your exchange.
3. Select the Sorting Criterion and the Direction (Group `⚙️ Optimization Settings ⚙️').
* `Sort by': Specify the main criteria by which the best strategies will be selected and sorted. I strongly recommend using finalScore to find the most balanced and sustainable strategies.
* `Direction': Choose which trades to test: Long, Short or Both.
Step 3: Start Testing and Work with "Parts"
The total number of unique combinations generated based on your ranges can reach tens of millions. TradingView has technical limitations on the number of calculations that the script can perform at a time. To get around this, I implemented a "Parts" system.
1. What are `Part` and `Combinations in Part'?
* `Combinations in Part': This is the number of backtests that the script performs in one run (1000 by default).
* `Part`: This is the number of the "portion" of combinations that you want to test.
2. How does it work in practice?
* After you have everything set up, leave Part:1 and wait for the results table to appear. You will see the TOP N best strategies from the first thousand tested.
* Analyze them. Then, to check the next thousand combinations, just change the Part to 2 in the settings and click OK. The script will run a test for the next batch.
* Repeat this process by increasing the Part number (`3`, 4, 5...), until you reach the last available part.
* Where can I see the total number of parts? In the information row below the results table, you will find Total parts. This will help you figure out how many more tests are left to run.
Step 4: Analyze the Results in the Table
The results table is your main decision—making tool. It displays the best strategies found, sorted by the criteria you have chosen.
1. Study the performance metrics:
* Rating: Position in the rating.
* Profit %: Net profit as a percentage of the initial capital.
* Drawdown%: The maximum drawdown of the deposit for the entire test period.
* Max Length: The maximum duration of one transaction in days, hours and minutes.
* Trades: The total number of completed trades.
2. Examine the winning parameters:
* To the right of the performance metrics are columns showing the exact settings that led to this result ('SO Count`, SO Step, TP (%), etc.).
3. How to choose the best strategy?
* Don't chase after the maximum profit! The strategy with the highest profit often has the highest drawdown, which makes it extremely risky.
* Seek a balance. The ideal strategy is a compromise between high profitability, low drawdown (Drawdown) and the maximum length of trades acceptable to you (Max Length).
* finalScore was created to find this balance. Trust him — he often highlights not the most profitable, but the most stable and reliable options.
Detailed Description Of The Settings
This section serves as a complete reference for each parameter available in the script settings. The parameters are grouped in the same way as in the indicator interface for your convenience.
Group: ⚙️ Optimization Settings ⚙️
The main parameters governing the testing process are collected here.
* `Enable Optimizer': The main switch. Activates or deactivates all backtesting functionality.
* `Direction': Determines which way trades will be opened during the simulation.
* Long: Shopping only.
* Short: Sales only.
* Both: Testing in both directions. Important: This mode only works in conjunction with an External Signal, as the script needs an external signal to determine the direction for each specific transaction.
* `Signal Mode`: Controls the conditions for starting a new trading cycle (opening a base order).
* No Signal: A new cycle starts immediately after the previous one is completed. This mode is used to test "pure" grid mechanics without reference to market conditions.
* External Signal: A new cycle begins only when a signal is received from an external indicator connected via the Signal field.
* `Signal': A field for connecting an external signal source (works only in the `External Signal` mode). You can select any other indicator on the chart.
* For Long** trades, the signal is considered received if the value of the external indicator ** is greater than 0.
* For Short** trades, the signal is considered received if the value of the external indicator ** is less than 0.
* `Bars Count': Sets the depth of the history in the bars for the backtest. The maximum value (25000) provides the most reliable results.
* `Sort by`: A key criterion for selecting and ranking the best strategies in the final table.
* FinalScore: Recommended mode. A comprehensive assessment that takes into account 9 metrics to find the most balanced and sustainable strategies.
* Profit: Sort by net profit.
* Drawdown: Sort by minimum drawdown.
* Max Length: Sort by the minimum length of the longest transaction.
* `Combinations Count': Indicates how many of the best strategies (from 1 to 50) will be displayed in the results table.
* `Close last trade`: If this option is enabled, any active trade will be forcibly closed at the closing price of the last historical bar. For grid strategies, it is recommended to always enable this option in order to get the correct calculation of the final profit and eliminate grid strategies that have been stuck for a long time.
Group: 💰 Money Management Settings 💰
The parameters in this group determine the financial conditions of the simulation. Specify values that are as close as possible to your actual values in order to get reliable results.
* `Capital': The initial deposit amount for the simulation.
* `Leverage`: The leverage used to calculate the margin.
* `Slippage` (%): Simulates the difference between the expected and actual order execution price. The specified percentage will be applied to each transaction.
* `Commission` (%): The trading commission of your exchange as a percentage. It is charged at the execution of each order (both at opening and closing).
* `Liquidation Level' (%): Maintenance Margin Ratio. This is a critical parameter for a realistic test. Liquidation in the simulator occurs if the Equity of the account (Capital + Unrealized P&L) falls below the level of the supporting margin.
Group: 🛠 Optimization Parameters 🛠
This is the "heart" of the optimizer, where you set ranges for iterating through the grid parameters.
* `Part`: The portion number of the combinations to be tested. Start with 1, and then increment (`2`, 3, ...) sequentially to check all generated strategies.
* `Combinations in Part': The number of backtests performed at a time (in one "Part"). Increasing the value may speed up the process, but it may cause the script to error due to platform limitations. If an error occurs, it is recommended to switch to the step below and back.
Three fields are available for each of the following parameters (`SO Count`, SO Step, SO Multiplier, etc.):
* `Min`: Minimum value for testing.
* `Max': The maximum value for testing.
* `Step`: The step with which the values in the range from Min to Max will be iterated over.
There is also a checkbox for each parameter. If it is enabled, the parameter will be optimized in the specified range. If disabled, only one value specified in the Min field will be used for all tests.
* 'Stop Loss': In addition to the standard settings Min, Max, Step, it has an additional parameter:
* `Type`: Defines how the stop loss price is calculated.
* From entry point: The SL level is calculated once from the entry price (base order price).
* From breakeven line: The SL level is dynamically recalculated from the average position price after each new safety order is executed.
Group: ⚡️Filters⚡️
Filters allow you to filter out those results from the final table that do not meet your minimum requirements.
For each filter (`Max Profit`, Min Drawdown, `Min Trade Length`), you can:
1. Turn it on or off using the checkbox.
2. Select the comparison condition: Greater (More) or Less (Less).
3. Set a threshold value.
*Example:* If you set Less and 20 for the Min Drawdown filter, only those strategies with a maximum drawdown of less than 20% will be included in the final table.
Group: 🎨 Visual Settings 🎨
Here you can customize the appearance of the results table.
* `Position': Selects the position of the table on the screen (for example, Bottom Left — bottom left).
* `Font Size': The size of the text in the table.
* `Header Background / Data Background`: Background colors for the header and data cells.
* `Header Font Color / Data Font Color`: Text colors for the header and data cells.
Important Notes and Limitations
So that you can use the Autoback Grid Lab as efficiently and consciously as possible, please familiarize yourself with the following key features of its work.
1. It is a Tool for Analysis, not for Signals
It is extremely important to understand that this script does not generate trading signals in real time. Its sole purpose is to conduct in—depth research (**backtesting**) on historical data.
* The results you see in the table are a report on how a particular strategy would have worked in the past.
* The script does not provide alerts and does not draw entry/exit points on the chart for the current market situation.
* Your task is to take the best sets of parameters found during optimization and use them in your real trading, for example, when setting up a trading bot or in a manual trading system.
2. Features Of Calculations (This is not a "Repainting")
You will notice that the results table appears and is updated only once — when all historical bars on the chart are loaded. It does not change in real time with each tick of the price.
This is correct and intentional behavior.:
* To test thousands, and sometimes millions of combinations, the script needs to perform a huge amount of calculations. In the Pine Script™ environment, it is technically possible to do this only once, at the very last bar in history.
* The script does not show false historical signals, which then disappear or change. It provides a static report on the results of the simulation, which remains unchanged for a specific historical period.
3. Past Results do not Guarantee Future Results.
This is the golden rule of trading, and it fully applies to the results of backtesting. Successful strategy performance in the past is not a guarantee that it will be as profitable in the future. Market conditions, volatility and trends are constantly changing.
My tool, especially when sorting by finalScore, is aimed at finding statistically stable and reliable strategies to increase the likelihood of their success in the future. However, it is a tool for managing probabilities, not a crystal ball for predicting the future. Always use proper risk management.
4. Dependence on the Quality and Depth of the Story
The reliability of the results directly depends on the quantity and quality of the historical data on which the test was conducted.
* Always strive to use the maximum number of bars available (`Bars Count: 25,000`) so that your strategy is tested on different market cycles (rise, fall, flat).
* The results obtained on data for one month may differ dramatically from the results obtained on data for two years. The longer the testing period, the higher the confidence in the parameters found.
Conclusion
The Autoback Grid Lab is your personal research laboratory, designed to replace intuitive guesses and endless manual selection of settings with a systematic, data—driven approach. Experiment with different assets, timeframes, and settings ranges to find the unique combinations that best suit your trading style.
Multi Channel GRID & DCA LTF [trade_lexx]Multi Channel GRID & DCA LTF
Usage Guide
Part 1: The concept and general possibilities of the "Multi Channel GRID & DCA LTF" strategy
Introduction
Welcome to the guide to "Multi Channel GRID & DCA LTF", a powerful and versatile automated trading strategy for the TradingView platform. This tool was developed for traders who are looking for flexibility, control and a high degree of adaptability to various market conditions.
The strategy is based on a hybrid approach that combines two popular and time-tested techniques.:
1. GRID (grid trading): The classic method of averaging a position is by placing a grid of limit orders.
2. DCA (Dollar Cost averaging): Smart position averaging based on signals from external indicators.
However, "Multi Channel GRID & DCA LTF" goes far beyond the simple combination of these two techniques. The strategy includes a number of unique and innovative features, such as cascading MultiGRID grids for dealing with extreme volatility, Channel Mode range trading mode for profiting from sideways movement, and Low Time Frame analysis (LTF) to achieve surgical accuracy in backtesting. Deep customization options for risk management, capital, take profits, and stop losses allow you to configure a strategy for almost any trading style, asset, and timeframe.
The basic idea: How does it work?
Let's take a detailed look at each of the key concepts embedded in the logic of the strategy.
1. GRID — Automatic placement of buy and sell orders at certain price intervals.
This is a fundamental mode of operation. Its main goal is to systematically improve the average entry price for a position if the market is going against you.
* The principle of operation: After opening the base (first) order (`BO`), the strategy automatically places a series of pending limit orders (here they are called "safety orders" or "SO") at certain price intervals. For a long position, orders are placed below the entry price, and for a short position, orders are placed higher.
* Target: When the price moves against an open position, it consistently hits and executes safety orders. Each such execution adds additional volume to the position at a more favorable price, thereby shifting the overall average entry price (`position_avg_price') closer to the current market price. This means that a much smaller corrective movement will be required to gain ground.
* Flexibility: You have full control over the geometry of the grid: the number of safety orders, the percentage distance between them (`SO Step`), and you can even set a coefficient that will increase this step for each subsequent order (`SO Multiplier`), creating an expanding grid.
2. DCA (Signal Averaging) — Smart Averaging
This mode adds an additional layer of analysis to the averaging process. Instead of just buying/selling at the set price levels, the strategy waits for a confirmation signal.
* Working principle: You can connect any external indicator (for example, RSI, CCI, or even your own complex signal system) to the strategy, which outputs numerical values. As standard, 1 is used for a long signal, and -1 is used for a short signal. The strategy will place the next averaging order only at the moment when it receives the appropriate signal.
* Goal: To average a position not just during a fall (or a rise for a short), but at the moments that your main trading system considers the most favorable for this. This allows you to avoid "catching falling knives" and enter only if there are good reasons.
3. Hybrid Mode (GRID+DCA) is the best of the previous two modes
This mode is designed for maximum filtering and control. It requires two conditions to be fulfilled simultaneously.
* Working principle: The safety order will be executed only if the price has reached the calculated grid level and a confirmation signal has been received from your external indicator. If a confirmation signal is received from an external indicator, the next calculated grid level activates the limit order.
* Goal: To create the most reliable averaging system that protects against premature entries and requires double confirmation (both by price and indicator) before increasing the position size.
4. MultiGRID — Adaptation to extreme volatility
This is one of the most powerful and unique features of a strategy designed to survive and make a profit in the face of strong, protracted trends or "black swans".
* The problem it solves: The usual grid of orders has a limited depth. If the price goes beyond the last safety order, the strategy loses the opportunity to average and becomes vulnerable.
* The principle of operation: The MultiGRID function allows you to create "cascades" — several grids following one another. When all the orders of the first grid are executed, the strategy does not stop. Instead, she can activate the second, third (and so on) a grid of orders. The new grid can be activated by one of two triggers:
1. Offset: The new grid is activated when the price passes another set percentage deviation from the last executed order.
2. Signal: The new grid is activated when a signal is received from an external indicator.
* Goal: To significantly expand the working range of the strategy. This allows it to adapt to strong market movements that would "break" the usual grid, and continue to effectively average a position at a much greater depth of decline or growth.
5. Channel Mode — Trading in the range
This feature turns a standard averaging strategy into a machine for "farming" profits within a price channel that is formed during a sideways market movement.
* The problem it solves: In the standard grid strategy, after partially closing a take profit position, the volume of this part "leaves" the trade until the deal is fully closed. You are missing the opportunity to reuse this capital.
* Operating principle: When Channel Mode is enabled, the following happens. Suppose the price went against you, executed several safety orders, and then turned around and reached one of the partial take profits. At this point, the strategy is:
1. Fixes the profit, as it should be.
2. Instantly places a new limit order to buy (or sell for a short) at exactly the same price level where the last triggered safety order was executed. The volume of this order is equal to the volume of the part that was just closed for take profit.
3. If the price goes down again and executes this "repeat" order, the strategy immediately sets a corresponding take profit for it at the level where the previous profit was taken.
* Goal: To create a continuous buy-sell cycle within the local range (channel). The lower limit of the channel is the price of the last averaging, and the upper limit is the price of a partial take profit. This allows you to repeatedly profit from sideways price fluctuations, without waiting for the full closure of the main, large transaction.
6. LTF (Lower Timeframe Analysis) — Surgical precision of backtesting
This feature is critically important for obtaining reliable results during historical testing (backtesting) of grid strategies.
* The problem it solves: The standard testing mechanism in TradingView has a serious limitation. Working, for example, on a 4-hour chart, he sees only 4 candle points: Open, High, Low and Close. He does not know in what order the price moved within these 4 hours. He could have touched High first and then Low, or vice versa. For grid strategies, this is fatal — the engine can show that a take profit has been executed, although in reality the price first went down, collected the entire grid of orders and only then turned around.
* How it works: When you turn on the LTF mode, the strategy for each candle on your main chart (for example, 4H) requests and analyzes all candles from the lower timeframe you specified (for example, 1-minute). Then it virtually trades the entire price path for these minute candles, executing orders, take profits and stop losses in the sequence in which they would occur in reality. It works in the single take profit mode of the Grid strategy.
* Goal: To provide the most realistic and reliable backtest that reflects the real dynamics of the market. This allows you to avoid false expectations and accurately assess the potential performance of the strategy.
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Part 2: Detailed description of the strategy settings
This section is your main guide to all the switches and options available in the strategy. Understanding each setting is the key to unlocking the full potential of this powerful tool.
1. 🛡️ Risk Management 🛡️
This group contains fundamental parameters that determine the basic logic of risk management and the geometry of grid orders.
* Strategy type: Determines the direction of transactions.
* Long: The strategy will only open long positions (buy).
* Short: The strategy will only open short positions (sell).
* Both: The strategy will work both ways, opening long or short depending on the incoming signal.
* SO Count: Sets the maximum number of Safety (averaging) Orders (SO) that the strategy will place within the same grid. If you have MultiGRID enabled, this number applies to each individual grid.
* SO Step (%): This is the base percentage deviation from the entry price at which the first safety order will be placed. For example, at a value of 0.5, the first SO in a long trade will be placed 0.5% lower than the opening price of the base order.
* SO Multiplier: A coefficient that exponentially increases the step for each subsequent safety order. This allows you to create an expanding grid where averaging orders are placed further and further apart, which is effective with strong and accelerating price movements.
* *The step formula for the nth order*: Step(N) = (SO Step) * (SO Multiplier ^(N-1)).
* If the value is 1, all steps will be the same.
* With a value of 1.6, the step of the second SO will be 1.6 times larger than the first, the step of the third will be 1.6 times larger than the second, and so on.
* 1️⃣ TP/SL: These are simplified settings for quick configuration. They allow you to turn on/off the main take profit and stop loss and set basic percentage values for them. More detailed settings for these parameters can be found in the relevant sections below.
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2. 💰 Money Management 💰
Everything related to position size, leverage, and capital is configured here.
* Volume BO (Base Order): Determines the size of the trade's opening order.
* Volume BO: A fixed amount in the quote currency (for example, in USDT).
* USDT (check mark): Manages the information in the comments to the orders. If enabled, the volume of orders in USDT will be displayed in the comments. This is convenient for visual analysis and for sending the amount of USDT by the placeholder {{strategy.order.comment}} via webhooks when connecting the strategy to the exchange or trading terminals.
* or % of deposit: The amount calculated as a percentage of the available capital of the strategy. The check mark to the right of this field enables this mode. Important: using a percentage activates the effect of compounding (compound interest), as the amount of each new transaction will be automatically recalculated based on the current capital (initial capital + profit/loss). If enabled, the percentage of orders will be displayed in the comments. This is convenient for visual analysis and for sending percentages on the placeholder {{strategy.order.comment}} via webhooks when connecting the strategy to the stock exchange, trading terminals, or creating Copy trading.
* Martingale: The coefficient applied to the volume of orders. It increases the size of each subsequent insurance order compared to the base one.
* Volume formula for the nth SO: Volume SO (N) = (Volume BO) * (Martingale^N).
* With a value of 1.2, the volume of the first SO will be 1.2 times greater than the base, the second — 1.44 times (`1.2 * 1.2`) and so on.
* Leverage: Specify the size of your leverage. This parameter is used exclusively for calculating and displaying the approximate liquidation price. It does not affect the size of positions, but it helps to visually assess the risks.
* Liquidation: Enables or disables the calculation and display of the liquidation line on the chart.
* Margin type: Allows you to select a method for calculating the liquidation price, simulating the logic of exchanges:
* Isolated: The liquidation price is calculated based on the size and leverage of the current open position only.
* Cross: The calculation simulates using the entire available balance to maintain a position. In the strategy, the liquidation price is calculated as the level at which the loss on the current transaction is equal to the current capital.
* Commission (%): Specify the percentage of your exchange's commission per transaction. The correct value of this parameter is crucial for obtaining realistic backtest results.
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3. 🕸️ Grid Management 🕸️
This group is responsible for the logic of safety orders and advanced mechanics such as Channel Mode and MultiGRID.
* SO Type: Defines the logic of placing averaging orders.
* GRID: Classic grid. All safety orders are placed in advance as limit orders.
* DCA: Signal averaging. The strategy is waiting for a signal from an external indicator to place a market averaging order.
* GRID+DCA: Hybrid. The strategy waits for a signal, and if it arrives, places a limit order at the appropriate price level of the grid or executes a market order if the signal has arrived below the limit order level.
* Signal for SO: A data source (indicator) that will be used for signals in DCA and GRID+DCA modes.
* ↔️ Channel Mode: When this option is enabled, the strategy tries to trade in a sideways range. After partially closing a take profit position, it immediately places a limit order for re-entry at the price of the last triggered safety order. This creates a buy-sell cycle within the local channel.
* Best Price Only: This filter adds an additional condition for averaging in DCA and MultiGRID modes (when it operates on a signal). The next averaging order or a new grid will be activated only if the current price is more favorable (lower for long, higher for short) than the price of the previous entry.
* 🧩 MultiGRID ⮕ Enables cascading grid mode.
* Grid Count: The total number of grids that can be activated sequentially.
* Offset: Percentage deviation from the price of the last order of the previous grid. When this margin is reached, the following grid of orders is activated (this mode does not require a signal).
* Or signal: Allows you to use the signal from an external indicator as a trigger to activate the next grid. The checkmark on the right turns on this mode.
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4. 🎯 Entry and Stop 🎯
This group of settings allows you to fine-tune the conditions for starting a new trade and all aspects related to protective stop orders, including the complex mechanics of trailing and managing SL after partial take profits.
* 🎯 Signal: A data source (indicator) that will be used to determine when to enter a trade. The strategy expects a value of 1 for the start of a long trade and -1 for a short trade.
* Min Bars: Sets the minimum number of candles that must pass from the moment of opening the previous trade to the moment of opening the next one. A value of 0 disables this filter. This is a useful tool to prevent overly frequent entries in a "noisy" market.
* Non-stop: If this option is enabled, the strategy ignores the Entry Signal and opens a new trade immediately after closing the previous one (taking into account the Min Bars filter, if it is set). This turns the strategy into a constantly working mechanism that is always on the market.
* 🛑 SL Type: Defines the base price from which the stop loss percentage will be calculated. The stop loss in the first section must be enabled for this block of settings to work.
* From the entry point: SL is always calculated from the opening price of the very first base order. It remains static throughout the entire transaction unless it is moved by other functions.
* From breakeven line: SL is dynamically recalculated and shifted each time a safety order is executed. It always follows the average price of the position, being at a given percentage distance from it.
* From last executed SO: SL is recalculated from the price of the last executed order, whether it is a base or a safety order.
* From last SO: SL is calculated from the price of the most recent possible safety order in the grid. This is usually the most remote and conservative type of SL.
* Trailing SL Type: Defines the algorithm by which the stop loss will move after its activation.
* Standard: Classic trailing. After activation, SL will follow the price at a fixed distance.
* ATR: SL will follow the price at a distance equal to the value of the ATR indicator multiplied by the specified multiplier.
* External Source: SL will follow any selected line of the third-party indicator.
* Period and Multiplier: Common parameters for all types of trailing.
* Source: The source of the line for the trailing SL of the third-party indicator.
* Trailing SL after entry: The mode of activation of the trailing SL after entering the transaction
* SL management after TP (sections 1️⃣, 2️⃣, 3️⃣): These three blocks allow you to create a complex stop loss management logic as profits are recorded.
For each take profit level (TP1, TP2, TP3), you can configure:
* SL BE / SL TP1 / SL TP2: When the corresponding TP is reached, the stop loss will be moved to the breakeven point (for TP1), to the TP1 price level (for TP2) or to the TP2 price level (for TP3).
* Trailing SL: When the corresponding TP is reached, the trailing stop loss is activated according to the settings above.
* By ↔️ Signal: A very powerful option. If it is enabled, the above action (SL transfer or trailing activation) will occur when the opposite trading signal is received from an external indicator. This allows you to protect profits or reduce losses if the market turns sharply, even before reaching the target.
* SL Delay ⮕ Allows you to delay the activation of the stop loss.
* Number of Bars: The Stop loss will be physically placed on the market only after the specified number of candles has passed since entering the trade. This can help to avoid "taking out" the stop with a random short movement (squiz) immediately after opening a position.
* SL Block: Unique defensive mechanics for trading both ways (`Strategy Type: Both`).
* Number of SL: If the strategy receives the specified number of stop losses in a row in one direction (for example, 2 stops long), it temporarily blocks the opportunity to open new trades in that direction.
* Lock Reset mode:
* By direction: The lock is lifted if a profitable trade is closed in the allowed direction or if a stop loss is triggered in the opposite direction.
* First profit: The lock is lifted after closing any profitable transaction, regardless of its direction.
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5. ✅ Take Profit ✅
This group of settings provides comprehensive control over profit taking, from a simple take profit to a complex system of partial closures and trailing.
* ✅ TP Type: Defines the base price for calculating the percentage deviation of the take profit.
* From entry point: TP is calculated from the base order price.
* From breakeven line: TP dynamically follows the average position price.
* From last executed SO: TP is calculated from the price of the last executed order.
* Filters for closing on signal
* Only ➕: If TP is triggered by a signal, the deal will be closed only if it is in the black relative to the average price.
* Or >TP: If TP is triggered by a signal, the trade will be closed only if the closing price is better than (or equal to) the estimated price of this TP.
* TP type of trailing: Yes, take profit has a trailing too! It works differently than the SL trailing.
* Standard / ATR: After the price touches the "virtual" TP level, the trailing is activated. He does not place a stop order, but begins to move away from the price, dynamically moving the limit order to close further and further in the profitable direction, allowing him to collect the maximum from the impulse movement.
* External Source: TP will follow any selected line of the third-party indicator.
* Period and Multiplier: Parameters for calculating the trailing margin TP.
* Source: The source of the line for the trailing TP of the third-party indicator.
* TP level settings (sections 1️⃣, 2️⃣, 3️⃣, 4️⃣): The strategy supports up to four independent take profit levels, which allows for a flexible system of partial commits.
For each level, you can set:
* TP: Enable the level and set its percentage deviation from the base price.
* Size: What percentage of the current position will be closed when this level is reached. For the last active TP, this parameter is ignored, and 100% of the remaining position is closed.
* Trailing TP: Enable the above-described trailing mechanism for this particular level.
* Signal: Enable closing based on the signal from the external indicator for this level.
* Or take: If both the closing on the signal and the limit order are enabled, then whatever comes first will work.
* After SO: Activate this TP level only after the specified number of safety orders has been executed. This allows you to set closer targets for riskier (deeply averaged) positions.
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6. 🔬 GRID and MultiGrid Analysis on Lower TFs (LTF) 🔬
This group activates one of the most important functions for accurate testing of grid strategies.
* Enable LTF Calculation ⮕ The main switch of the analysis mode on the lower timeframes.
* Timeframe selection: A drop-down list where you can select a timeframe for detailed analysis. For example, if your main schedule is 1 hour, you can select 1 minute here. The strategy will emulate the trading of minute candles within each hour candle.
❗️Important: As mentioned in the first part, the use of this mode is critically necessary to obtain realistic backtest results, especially for strategies with a dense grid of orders. Without it, the results may be overly optimistic and not reflect the real dynamics of the market. It should be remembered that TradingView imposes a limit on the number of intra-bars (minor TF bars) that can be requested. This is usually about 100,000 bars.
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7. 🕘 Backtest Date Range 🕘
This group allows you to focus testing on a specific historical period.
* Limit Date Range: Enables date filtering.
* Start time: The date and time when the strategy will start analyzing and opening deals.
* End time: The date and time after which the strategy will stop opening new deals and complete testing.
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8. 🎨 Visualization 🎨
All the options responsible for the appearance and information content of the chart are collected here.
* Show PnL labels: Enables/disables the display of text labels with the result (profit/loss) after closing each trade.
* Statistics Table: Enables/disables the main dashboard with detailed statistics on the results of the backtest.
* Strategy Settings Table: Enables/disables an additional panel that summarizes all the key parameters of the current configuration.
* Monthly Profit Table: Enables/disables a table with a breakdown of percentage returns by month and year.
* Table settings: For each of the three tables, you can individually adjust the Text size and Table Position on the screen to position them as conveniently as possible.
* Decimal places: Defines how many decimal places will be displayed in numeric values in tables and on labels.
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9. ✉️ Webhook Settings ✉️
This group is intended for traders who want to automate trading on strategy signals using third-party services and exchanges (for example, 3Commas, WunderTrading, Cryptorobotics, Cryptohopper, Bitsgap, Binance, ByBit, OKX, Pionex, Bitget or proprietary solutions).
For each key event in the strategy, there is a separate switch and a text field:
* Webhook for Open: Enable and set a message for the webhook that will be sent when the base order is opened.
* Webhook for Averaging: A message sent when executing any insurance order.
* Webhook for Take Profit: A message sent when closing on take profit (including partial ones).
* Webhook for Stop-Loss: A message sent when a stop loss is closed.
You can insert a JSON code or any other message format that your service requires for automation into the text fields. The strategy supports special placeholders (for example, `{{strategy.order.alert_message}}`), which allow you to dynamically insert the necessary data into the message, such as the amount of USDT or the percentage of the deposit for entry, averaging and take profit orders.
Backtest - Strategy Builder [AlgoAlpha]🟠 OVERVIEW
This script by AlgoAlpha is a modular Strategy Builder designed to let traders test custom trade entry and exit logic on TradingView without writing their own Pine code. It acts as a framework where users can connect multiple external signals, chain them in sequences, and run backtests with built-in leverage, margin, and risk controls. Its main strength is flexibility—you can define up to five sequential steps for entry and exit conditions on both long and short sides, with logic connectors (AND/OR) controlling how conditions combine. This lets you test complex multi-step confirmation workflows in a controlled, visual backtesting environment.
🟠 CONCEPTS
The system works by linking external signals —these can be values from other indicators, and/or custom sources—to conditional checks like “greater than,” “less than,” or “crossover.” You can stack these checks into steps , where all conditions in a step must pass before the sequence moves to the next. This creates a chain of logic that must be completed before a trade triggers. On execution, the strategy sizes positions according to your chosen leverage mode ( Cross or Isolated ) and allocation method ( Percent of equity or absolute USD value]). Liquidation prices are simulated for both modes, allowing realistic margin behaviour in testing. The script also tracks performance metrics like Sharpe, Sortino, profit factor, drawdown, and win rate in real time.
🟠 FEATURES
Up to 5 sequential steps for both long and short entries, each with multiple conditions linked by AND/OR logic.
Two leverage modes ( Cross and Isolated ) with independent long/short leverage multipliers.
Separate multi-step exit triggers for longs and shorts, with optional TP/SL levels or opposite-side triggers for flipping positions.
Position sizing by equity percent or fixed USD amount, applied before leverage.
Realistic liquidation price simulation for margin testing.
Built-in trade gating and validation—prevents trades if configuration rules aren’t met (e.g., no exit defined for an active side).
Full performance dashboard table showing live strategy status, warnings, and metrics.
Configurable bar coloring based on position side and TP/SL level drawing on chart.
Integration with TradingView's strategy backtester, allowing users to view more detailed metrics and test the strategy over custom time horizons.
🟠 USAGE
Add the strategy to your chart. In the settings, under Master Settings , enable longs/shorts, select leverage mode, set leverage multipliers, and define position sizing. Then, configure your Long Trigger and Short Trigger groups: turn on conditions, pick which external signal they reference, choose the comparison type, and assign them to a sequence step. For exits, use the corresponding Exit Long Trigger and Exit Short Trigger groups, with the option to link exits to opposite-side entries for auto-flips. You can also enable TP and/or SL exits with custom sources for the TP/SL levels. Once set, the strategy will simulate trades, show performance stats in the on-chart table, and highlight any configuration issues before execution. This makes it suitable for testing both simple single-signal systems and complex, multi-filtered strategies under realistic leverage and margin constraints.
🟠 EXAMPLE
The backtester on its own does not contain any indicator calculation; it requires input from external indicators to function. In this example, we'll be using AlgoAlpha's Smart Signals Assistant indicator to demonstrate how to build a strategy using this script.
We first define the conditions beforehand:
Entry :
Longs – SSA Bullish signal (strong OR weak)
Shorts – SSA Bearish signal (strong OR weak)
Exit
Longs/Shorts: (TP/SL hit OR opposing signal fires)
Other Parameters (⚠️Example only, tune this based on proper risk management and settings)
Long Leverage: default (3x)
Short Leverage: default (3x)
Position Size: default (10% of equity)
Steps
Load up the required indicators (in this example, the Smart Signals Assistant).
Ensure the required plots are being output by the indicator properly (signals and TP/SL levels are being plotted).
Open the Strategy Builder settings and scroll down to "CONDITION SETUP"; input the signals from the external indicator.
Configure the exit conditions, add in the TP/SL levels from the external indicator, and add an additional exit condition → {{Opposite Direction}} Entry Trigger.
After configuring the entry and exit conditions, the strategy should now be running. You can view information on the strategy in TradingView's backtesting report and also in the Strategy Builder's information table (default top right corner).
It is important to note that the strategy provided above is just an example, and the complexity of possible strategies stretches beyond what was shown in this short demonstration. Always incorporate proper risk management and ensure thorough testing before trading with live capital.
Script pago
Backtest [OptAlgo]This backtest script is designed to convert ideas or indicators into backtest results. The script creates buy/sell signals by comparing price sources against fixed values or other imported plots using many comparison methods. It has many features including multiple exit systems: TP/SL, custom plot-based stops and more. It supports full trading automation through webhook alerts with live signal processing.
🔢 Signal Creation System
→ Values Group : Compare price sources against fixed numerical values
→ Plots Group : Compare two different price sources/indicators against each other
→ Flexible Comparisons : 15+ comparison methods (equal, crossover, rising...)
→ Signal Types : Long, Short, Close All, Block signals, and combination signals
→ Merge Rules : Minimum condition requirements for signal activation
🔀 Advanced Signal Logic
→ Counter Signals : Choose between reversing positions or closing them
→ Signal Inversion : Flip all buy/sell signals with one toggle
→ External Signal Import : Import coded signals (1=Long, -1=Short, 0=Close)
→ Day Blocker : Enable/disable trading on specific weekdays
→ Session Control : Limit trading to specific market sessions
⚙️ Strategy Settings
→ Position Sides : All Ways, Long Only, or Short Only modes
→ Signal Control : Individual enable/disable for long and short signals
→ Counter Signal Mode : Reverse Open Position vs Close Open Position
→ Signal Reversal : Global signal inversion capability
🔰 Risk Management (Limiter Settings)
→ Leverage Control : Leverage with liquidation warnings
→ Drawdown Limit : Auto-halt strategy at specified drawdown percentage
→ Tradable Ratio : Use portion of available balance (0.01-1.0)
→ Contract Limit : Cap maximum contract size regardless of balance
🎯 TP/SL System
→ Fixed TP/SL : Set percentage-based take profit and stop loss
→ Custom Plot Stops : Use any indicator/plot as dynamic stop loss
→ ATR-Based Exits : Volatility-adjusted TP/SL using Average True Range
→ Realistic Protection : Prevents unrealistic TP/SL prices in live trading
→ Stop Modes : Instant (Sudden) vs Candle Close execution
→ ATR Stop Loss : Override fixed SL with volatility-based calculations
→ ATR Take Profit : Dynamic TP based on market volatility
→ Trailing Options : Safe, Normal, or Aggressive trailing methods
→ Calculation Modes : Normal, Volume-weighted, or Limited (with max %) options
→ Volume Integration : ATR levels adjust based on volume influx
🤖 Automation & Alerts
→ Webhook Integration : Send JSON alerts for automated execution
→ Live Signals : Real-time signal processing (every tick vs bar close)
→ Strategy Key : Unique identifier for automated systems
→ Early Entry : Send alerts X seconds before candle close
→ Fast Execution : Prevent signal lag in automated trading
🐞 Development Tools
→ Alert Plotting : Visualize signals directly on chart (disable for live alerts)
→ Professional Mode : Remove UI controls for faster calculation
→ Debug : Metrics are plotted in data window.
📊 Key Advantages
→ Multi-Condition Logic : Combine multiple indicators with flexible rules
→ Risk-First Design : Built-in drawdown and leverage protection
→ Automation Ready : Full webhook and alert system integration
⚠️ Important Warnings
→ High leverage combined with high SL may adjust to liquidation price
→ Use consistent leverage across all strategies on same trading isolated margin pair
→ Live signals require "Calculate on every tick" enabled in settings
→ Disable alert plotting when creating actual alerts to prevent latency
Combo 2/20 EMA & Bandpass Filter by TamarokDescription:
This strategy combines a 2/20 exponential moving average (EMA) crossover with a custom bandpass filter to generate buy and sell signals.
Use the Fast EMA and Slow EMA inputs to adjust trend sensitivity, and the Bandpass Filter Length, Delta, and Zones to fine-tune momentum turns.
Signals occur when both EMA and BPF agree in direction, with optional reversal and time filters.
How to use:
1. Add the script to your chart in TradingView.
2. Adjust the EMA and BP Filter parameters to match your asset’s volatility.
3. Enable ‘Reverse Signals’ to trade counter-trend, or use the time filter to limit sessions.
4. Set alerts on Long Alert and Short Alert for automated notifications.
Inspiration:
Based on HPotter’s original combo strategy (Stocks & Commodities Mar 2010).
Updated to Pine Script v6 with streamlined code and alerts.
WARNING:
For purpose educate only
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
Cyber Strategy V1Сyber Strategy V1 – Indicator Testing & Strategy Execution Framework
✅ Overview
Cyber Strategy V1 is a closed-source strategy framework engineered to turn any of yours external indicator into a systematic, rule-based trading system. Designed for rigorous testing and live deployment, it combines multi-signal inputs, confirmations and automated execution paths to help traders and developers validate signal quality and manage risk with precision.
✅ Core Functionality
Multi-Source Independent Signal Inputs
Reversal Logic
Take Profit: up to 5 staggered TP levels, specified as percentage
Stop Loss: configurable via fixed percentage or dynamic SL that trails a reverse signals.
✅ Statistical Drawdown Analysis
For all profitable trades, tracks the maximum intratrade drawdown.
Computes percentile levels of profitable trades that hits minimum drawdowns to inform:
Entry buffer zones (e.g. avoid entering during transient noise)
Partial entry scaling prices.
✅ Signal Confirmation
Optional confirmation delays: hold entry until other signal section send a confirmation from another indicator.
✅ Automated Execution Integrations
Cornix Text Alerts: Generates pre-formatted alerts compatible with Cornix for semi-automated or bot trading.
Webhook Support: Emits JSON payloads on order-fill events to any endpoint, enabling full automation through third-party services or custom order-routing systems.
Important Notes
⚠️ THIS STRATEGY DOES NOT INCLUDE INDICATORS. Examples shown on screenshots use third-party tools. NO PROPRIETARY INDICATORS INCLUDED: Cyber Strategy V1 relies entirely on external signal inputs.
⚠️ All backtesting parameters are customizable; thorough backtesting under realistic slippage, fees and spread assumptions is essential before live deployment.
Uptrick: Asset Rotation SystemOverview
The Uptrick: Asset Rotation System is a high-level performance-based crypto rotation tool. It evaluates the normalized strength of selected assets and dynamically simulates capital rotation into the strongest asset while optionally sidestepping into cash when performance drops. Built to deliver an intelligent, low-noise view of where capital should move, this system is ideal for traders focused on strength-driven allocation without relying on standard technical indicators.
Purpose
The purpose of this tool is to identify outperforming assets based strictly on relative price behavior and automatically simulate how a portfolio would evolve if it consistently moved into the strongest performer. By doing so, it gives users a realistic and dynamic model for capital optimization, making it especially suitable during trending markets and major crypto cycles. Additionally, it includes an optional safety fallback mechanism into cash to preserve capital during risk-off conditions.
Originality
This system stands out due to its strict use of normalized performance as the only basis for decision-making. No RSI, no MACD, no trend oscillators. It does not rely on any traditional indicator logic. The rotation logic depends purely on how each asset is performing over a user-defined lookback period. There is a single optional moving average filter, but this is used internally for refinement, not for entry or exit logic. The system’s intelligence lies in its minimalism and precision — using normalized asset scores to continuously rotate capital with clarity and consistency.
Inputs
General
Normalization Length: Defines how many bars are used to calculate each asset’s normalized score. This score is used to compare asset performance.
Visuals: Selects between Equity Curve (show strategy growth over time) or Asset Performance (compare asset strength visually).
Detect after bar close: Ensures changes only happen after a candle closes (for safety), or allows bar-by-bar updates for quicker reactions.
Moving Average
Used internally for optional signal filtering.
MA Type: Lets you choose which moving average type to use (EMA, SMA, WMA, RMA, SMMA, TEMA, DEMA, LSMA, EWMA, SWMA).
MA Length: Sets how many bars the moving average should calculate over.
Use MA Filter: Turns the filter on or off. It doesn’t affect the signal directly — just adds a layer of control.
Backtest
Used to simulate equity tracking from a chosen starting point. All calculations begin from the selected start date. Prior data is ignored for equity tracking, allowing users to isolate specific market cycles or testing periods.
Starting Day / Month / Year: The exact day the strategy starts tracking equity.
Initial Capital $: The amount of simulated starting capital used for performance calculation.
Rotation Assets
Each asset has 3 controls:
Enable: Include or exclude this asset from the rotation engine.
Symbol: The ticker for the asset (e.g., BINANCE:BTCUSDT).
Color: The color for visualization (labels, plots, tables).
Assets supported by default:
BTC, ETH, SOL, XRP, BNB, NEAR, PEPE, ADA, BRETT, SUI
Cash Rotation
Normalization Threshold USDC: If all assets fall below this threshold, the system rotates into cash.
Symbol & Color: Sets the cash color for plots and tables.
Customization
Dynamic Label Colors: Makes labels change color to match the current asset.
Enable Asset Label: Plots asset name labels on the chart.
Asset Table Position: Choose where the key asset usage table appears.
Performance Table Position: Choose where the backtest performance table appears.
Enable Realism: Enables slippage and fee simulation for realistic equity tracking. Adjusted profit is shown in the performance table.
Equity Styling
Show Equity Curve (STYLING): Toggles an extra-thick visual equity curve.
Background Color: Adds a soft background color that matches the current asset.
Features
Dual Visualization Modes
The script offers two powerful modes for real-time visual insights:
Equity Curve Mode: Simulates the growth of a portfolio over time using dynamic asset rotation. It visually tracks capital as it moves between outperforming assets, showing compounded returns and the current allocation through both line plots and background color.
Asset Performance Mode: Displays the normalized performance of all selected assets over the chosen lookback period. This mode is ideal for comparing relative strength and seeing how different coins perform in real-time against one another, regardless of price level.
Multi-Asset Rotation Logic
You can choose up to 10 unique assets, each fully customizable by symbol and color. This allows full flexibility for different strategies — whether you're rotating across majors like BTC, ETH, and SOL, or including meme tokens and stablecoins. You decide the rotation universe. If none of the selected assets meet the strength threshold, the system automatically moves to cash as a protective fallback.
Key Asset Selection Table
This on-screen table displays how frequently each enabled asset was selected as the top performer. It updates in real time and can help traders understand which assets the system has historically favored.
Asset Name: Shortened for readability
Color Box: Visual color representing the asset
% Used: How often the asset was selected (as a percentage of strategy runtime)
This table gives clear insight into historical rotation behavior and asset dominance over time.
Performance Comparison Table
This second table shows a full backtest vs. chart comparison, broken down into key performance metrics:
Backtest Start Date
Chart Asset Return (%) – The performance of the asset you’re currently viewing
System Return (%) – The equity growth of the rotation strategy
Outperformed By – Shows how many times the system beat the chart (e.g., 2.1x)
Slippage – Estimated total slippage costs over the strategy
Fees – Estimated trading fees based on rotation activity
Total Switches – Number of times the system changed assets
Adjusted Profit (%) – Final net return after subtracting fees and slippage
Equity Curve Styling
To enhance visual clarity and aesthetics, the equity curve includes styling options:
Custom Thickness Curve: A second stylized line plots a shadow or highlight of the main equity curve for stronger visual feedback
Dynamic Background Coloring: The chart background changes color to match the currently held asset, giving instant visual context
Realism Mode
By enabling Realism, the system calculates estimated:
Trading Fees (default 0.1%)
Slippage (default 0.05%)
These costs are subtracted from the equity curve in real time, and shown in the table to produce an Adjusted Return metric — giving users a more honest and execution-aware picture of system performance.
Adaptive Labeling System
Each time the asset changes, an on-chart label updates to show:
Current Asset
Live Equity Value
These labels dynamically adjust in color and visibility depending on the asset being held and your styling preferences.
Full Customization
From visual position settings to table placements and custom asset color coding, the entire system is fully modular. You can move tables around the screen, toggle background visuals, and control whether labels are colored dynamically or uniformly.
Key Concepts
Normalized values represent how much an asset has changed relative to its past price over a fixed period, allowing performance comparisons across different assets. Outperforming refers to the asset with the highest normalized value at a given time. Cash fallback means the system moves into a stable asset like USDC when no strong performers are available. The equity curve is a running total of simulated capital over time. Slippage is the small price difference between expected and actual trade execution due to market movement.
Use Case Flexibility
You don’t need to use all 10 assets. The system works just as effectively with only 1 asset — such as rotating between CASH and SOL — for a simple, minimal strategy. This is ideal for more focused portfolios or thematic rotation systems.
How to Use the Indicator
To use the Uptrick: Asset Rotation System, start by selecting which assets to include and entering their symbols (e.g., BINANCE:BTCUSDT). Choose between Equity Curve mode to see simulated portfolio growth, or Asset Performance mode to compare asset strength. Set your lookback period, backtest start date, and optionally enable the moving average filter or realism settings for slippage and fees. The system will then automatically rotate into the strongest asset, or into cash if no asset meets the strength threshold. Use alerts to be notified when a rotation occurs.
Asset Switch Alerts
The script includes built-in alert conditions for when the system rotates into a new asset. You can enable these to be notified when the system reallocates to a different coin or to cash. Each alert message is labeled by target asset and can be used for automation or monitoring purposes.
Conclusion
The Uptrick: Asset Rotation System is a next-generation rotation engine designed to cut through noise and overcomplication. It gives users direct insight into capital strength, without relying on generic indicators. Whether used to track a broad basket or focus on just two assets, it is built for accuracy, adaptability, and transparency — all in real-time.
Disclaimer
This script is for research and educational purposes only. It is not intended as financial advice. Past performance is not a guarantee of future results. Always consult with a financial professional and evaluate risks before trading or investing.
ETF Builder & Backtest System [TradeDots]Create, analyze, and monitor your own custom “ETF-like” portfolio directly on TradingView. This script merges up to 10 different assets with user-defined weightings into a single composite chart, allowing you to see how your personalized portfolio would have performed historically. It is an original tool designed to help traders and investors quickly gauge risk and return profiles without leaving the TradingView platform.
📝 HOW IT WORKS
1. Custom Portfolio Construction
Multiple Assets : Combine up to 10 different stocks, ETFs, cryptocurrencies, or other symbols.
User-Defined Weights : Allocate each asset a percentage weight (e.g., 15% in AAPL, 10% in MSFT, etc.).
Single Composite Value : The script calculates a weighted “ETF-style” price, effectively simulating a merged portfolio curve on your chart.
2. Performance Tracking & Return Analysis
Automatic History Capture : The indicator records each asset’s starting price when it first appears in your chosen date range.
Rolling Updates : As time progresses, all asset prices are continually evaluated and the portfolio value is updated in real time.
Buy & Hold Returns : See how each asset—and the overall portfolio—performed from the “start” date to the most recent bar.
Annualized Return : Automatically calculates CAGR (Compound Annual Growth Rate) to help visualize performance over varying timescales.
3. Table & Visual Output
Performance Table : A comprehensive table displays individual asset returns, annualized returns, and portfolio totals.
Normalized Chart Plot : The composite ETF value is scaled to 100 at the start date, making it easy to compare relative growth or decline.
Optional Time Filter : You can define a specific date range (Start/End Dates) to focus on a particular period or to limit historical data.
⚙️ KEY FEATURES
1. Flexible Asset Selection
Choose any symbols from multiple asset classes. The script will only run calculations when data is available—no need to worry about missing quotes.
2. Dynamic Table Reporting
Start Price for each asset
Percentage Weight in the portfolio
Total Return (%) and Annualized Return (%)
3. Simple Backtesting Logic
This script takes a straightforward Buy & Hold perspective. Once the start date is reached, the portfolio remains static until the end date, so you can quickly assess hypothetical growth.
4. Plot Customization
Toggle the main “ETF” plot on/off.
Alter the visual style for tables and text.
Adjust the time filter to limit or extend your performance measurement window.
🚀 HOW TO USE IT
1. Add the Script
Search for “ETF Builder & Backtest System ” in the Indicators & Strategies tab or manually add it to your chart after saving it in your Pine Editor.
2. Configure Inputs
Enable Time Filter : Choose whether to restrict the analysis to a particular date range.
Start & End Date : Define the period you want to measure performance over (e.g., from 2019-12-31 to 2025-01-01).
Assets & Weights : Enter each symbol and specify a percentage weight (up to 10 assets).
Display Options : Pick where you want the Table to appear and choose background/text colors.
3. Interpret the Table & Plots
Asset Rows : Each asset’s ticker, weighting, start price, and performance metrics.
ETF Total Row : Summarizes total weighting, composite starting value, and overall returns.
Normalized Plot : Tracks growth/decline of the combined portfolio, starting at 100 on the chart.
4. Refine Your Strategy
Compare how different weights or a new mix of assets would have performed over the same period.
Assess if certain assets contribute disproportionately to your returns or volatility.
Use the results to guide allocations in your real trading or paper trading accounts.
❗️LIMITATIONS
1. Buy & Hold Only
This script does not handle rebalancing or partial divestments. Once the portfolio starts, weights remain fixed throughout the chosen timeframe.
2. No Reinvestment Tracking
Dividends or other distributions are not factored into performance.
3. Data Availability
If historical data for a particular asset is unavailable on TradingView, related results may display as “N/A.”
4. Market Regimes & Volatility
Past performance does not guarantee similar future behavior. Markets can change rapidly, which may render historical backtests less predictive over time.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The “ETF Builder & Backtest System ” is provided for informational and educational purposes only. It does not constitute financial advice.
Always conduct your own research.
Use proper risk management and position sizing.
Past performance does not guarantee future results.
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Use this indicator as part of a broader trading or investment approach—consider fundamental and technical factors, overall market context, and personal risk tolerance. No trading tool can assure profits; exercise caution and responsibility in all financial decisions.
Backtesting Stats (Altrady)Track and analyze your backtesting results directly on your chart.
This indicator simplifies manual backtesting by summarizing your trades in a clear, structured table. Enter your R-values (one per line) in the text area, and instantly see:
✅ Trade list – All entries displayed with color-coded wins/losses.
✅ Key stats – Total trades, win rate, and RR sum in the top row.
✅ Quick insights – Spot trends, refine your strategy, and track performance without spreadsheets.
How to Use
1️⃣ Open settings and enter R-values, one per line (e.g., 2.5, -1, 3.2) along with short comments (bad entry, counter trend, etc)
2️⃣ View the table in the top-right corner of your chart.
3️⃣ Analyze your results, adjust your strategy, and improve consistency.
Perfect for manual backtesters who want a fast, no-spreadsheet solution. 🚀
*Auto Backtest & Optimize EngineFull-featured Engine for Automatic Backtesting and parameter optimization. Allows you to test millions of different combinations of stop-loss and take profit parameters, including on any connected indicators.
⭕️ Key Futures
Quickly identify the optimal parameters for your strategy.
Automatically generate and test thousands of parameter combinations.
A simple Genetic Algorithm for result selection.
Saves time on manual testing of multiple parameters.
Detailed analysis, sorting, filtering and statistics of results.
Detailed control panel with many tooltips.
Display of key metrics: Profit, Win Rate, etc..
Comprehensive Strategy Score calculation.
In-depth analysis of the performance of different types of stop-losses.
Possibility to use to calculate the best Stop-Take parameters for your position.
Ability to test your own functions and signals.
Customizable visualization of results.
Flexible Stop-Loss Settings:
• Auto ━ Allows you to test all types of Stop Losses at once(listed below).
• S.VOLATY ━ Static stop based on volatility (Fixed, ATR, STDEV).
• Trailing ━ Classic trailing stop following the price.
• Fast Trail ━ Accelerated trailing stop that reacts faster to price movements.
• Volatility ━ Dynamic stop based on volatility indicators.
• Chandelier ━ Stop based on price extremes.
• Activator ━ Dynamic stop based on SAR.
• MA ━ Stop based on moving averages (9 different types).
• SAR ━ Parabolic SAR (Stop and Reverse).
Advanced Take-Profit Options:
• R:R: Risk/Reward ━ sets TP based on SL size.
• T.VOLATY ━ Calculation based on volatility indicators (Fixed, ATR, STDEV).
Testing Modes:
• Stops ━ Cyclical stop-loss testing
• Pivot Point Example ━ Example of using pivot points
• External Example ━ Built-in example how test functions with different parameters
• External Signal ━ Using external signals
⭕️ Usage
━ First Steps:
When opening, select any point on the chart. It will not affect anything until you turn on Manual Start mode (more on this below).
The chart will immediately show the best results of the default Auto mode. You can switch Part's to try to find even better results in the table.
Now you can display any result from the table on the chart by entering its ID in the settings.
Repeat steps 3-4 until you determine which type of Stop Loss you like best. Then set it in the settings instead of Auto mode.
* Example: I flipped through 14 parts before I liked the first result and entered its ID so I could visually evaluate it on the chart.
Then select the stop loss type, choose it in place of Auto mode and repeat steps 3-4 or immediately follow the recommendations of the algorithm.
Now the Genetic Algorithm at the bottom right will prompt you to enter the Parameters you need to search for and select even better results.
Parameters must be entered All at once before they are updated. Enter recommendations strictly in fields with the same names.
Repeat steps 5-6 until there are approximately 10 Part's left or as you like. And after that, easily pour through the remaining Parts and select the best parameters.
━ Example of the finished result.
━ Example of use with Takes
You can also test at the same time along with Take Profit. In this example, I simply enabled Risk/Reward mode and immediately specified in the TP field Maximum RR, Minimum RR and Step. So in this example I can test (3-1) / 0.1 = 20 Takes of different sizes. There are additional tips in the settings.
━
* Soon you will start to understand how the system works and things will become much easier.
* If something doesn't work, just reset the engine settings and start over again.
* Use the tips I have left in the settings and on the Panel.
━ Details:
Sort ━ Sorting results by Score, Profit, Trades, etc..
Filter ━ Filtring results by Score, Profit, Trades, etc..
Trade Type ━ Ability to disable Long\Short but only from statistics.
BackWin ━ Backtest Window Number of Candle the script can test.
Manual Start ━ Enabling it will allow you to call a Stop from a selected point. which you selected when you started the engine.
* If you have a real open position then this mode can help to save good Stop\Take for it.
1 - 9 Сheckboxs ━ Allow you to disable any stop from Auto mode.
Ex Source - Allow you to test Stops/Takes from connected indicators.
Connection guide:
//@version=6
indicator("My script")
rsi = ta.rsi(close, 14)
buy = not na(rsi) and ta.crossover (rsi, 40) // OS = 40
sell = not na(rsi) and ta.crossunder(rsi, 60) // OB = 60
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, "🔌Connector🔌", display = display.none)
* Format the signal for your indicator in a similar style and then select it in Ex Source.
⭕️ How it Works
Hypothesis of Uniform Distribution of Rare Elements After Mixing.
'This hypothesis states that if an array of N elements contains K valid elements, then after mixing, these valid elements will be approximately uniformly distributed.'
'This means that in a random sample of k elements, the proportion of valid elements should closely match their proportion in the original array, with some random variation.'
'According to the central limit theorem, repeated sampling will result in an average count of valid elements following a normal distribution.'
'This supports the assumption that the valid elements are evenly spread across the array.'
'To test this hypothesis, we can conduct an experiment:'
'Create an array of 1,000,000 elements.'
'Select 1,000 random elements (1%) for validation.'
'Shuffle the array and divide it into groups of 1,000 elements.'
'If the hypothesis holds, each group should contain, on average, 1~ valid element, with minor variations.'
* I'd like to attach more details to My hypothesis but it won't be very relevant here. Since this is a whole separate topic, I will leave the minimum part for understanding the engine.
Practical Application
To apply this hypothesis, I needed a way to generate and thoroughly mix numerous possible combinations. Within Pine, generating over 100,000 combinations presents significant challenges, and storing millions of combinations requires excessive resources.
I developed an efficient mechanism that generates combinations in random order to address these limitations. While conventional methods often produce duplicates or require generating a complete list first, my approach guarantees that the first 10% of possible combinations are both unique and well-distributed. Based on my hypothesis, this sampling is sufficient to determine optimal testing parameters.
Most generators and randomizers fail to accommodate both my hypothesis and Pine's constraints. My solution utilizes a simple Linear Congruential Generator (LCG) for pseudo-randomization, enhanced with prime numbers to increase entropy during generation. I pre-generate the entire parameter range and then apply systematic mixing. This approach, combined with a hybrid combinatorial array-filling technique with linear distribution, delivers excellent generation quality.
My engine can efficiently generate and verify 300 unique combinations per batch. Based on the above, to determine optimal values, only 10-20 Parts need to be manually scrolled through to find the appropriate value or range, eliminating the need for exhaustive testing of millions of parameter combinations.
For the Score statistic I applied all the same, generated a range of Weights, distributed them randomly for each type of statistic to avoid manual distribution.
Score ━ based on Trade, Profit, WinRate, Profit Factor, Drawdown, Sharpe & Sortino & Omega & Calmar Ratio.
⭕️ Notes
For attentive users, a little tricks :)
To save time, switch parts every 3 seconds without waiting for it to load. After 10-20 parts, stop and wait for loading. If the pause is correct, you can switch between the rest of the parts without loading, as they will be cached. This used to work without having to wait for a pause, but now it does slower. This will save a lot of time if you are going to do a deeper backtest.
Sometimes you'll get the error “The scripts take too long to execute.”
For a quick fix you just need to switch the TF or Ticker back and forth and most likely everything will load.
The error appears because of problems on the side of the site because the engine is very heavy. It can also appear if you set too long a period for testing in BackWin or use a heavy indicator for testing.
Manual Start - Allow you to Start you Result from any point. Which in turn can help you choose a good stop-stick for your real position.
* It took me half a year from idea to current realization. This seems to be one of the few ways to build something automatic in backtest format and in this particular Pine environment. There are already better projects in other languages, and they are created much easier and faster because there are no limitations except for personal PC. If you see solutions to improve this system I would be glad if you share the code. At the moment I am tired and will continue him not soon.
Also You can use my previosly big Backtest project with more manual settings(updated soon)
Walk Forward PatternsINTRO
In Euclidean geometry, every mathematical output has a planar projection. 'Walk Forward Patterns' can be considered a practical example of this concept. On the other hand, this indicator might also be viewed as an experiment in 'how playing with Lego as a child contributes to time series analysis' :)
OVERVIEW
This script dynamically generates the necessary optimization and testing ranges for Walk Forward Analysis based on user-defined bar count and length inputs. It performs automatic calculations for each step, offers 8 different window options depending on the inputs, and visualizes the results dynamically. I should also note that most of the window models consist of original patterns I have created.
ADDITIONAL INFO : WHAT IS WALK FORWARD ANALYSIS?
Although it is not the main focus of this indicator, providing a brief definition of Walk Forward Analysis can be helpful in correctly interpreting the results it generates. Walk Forward Analysis (WFA) is a systematic method for optimizing parameters and validating trading strategies. It involves dividing historical data into variable segments, where a strategy is first optimized on an in-sample period and then tested on an out-of-sample period. This process repeats by shifting the windows forward, ensuring that each test evaluates the strategy on unseen data, helping to assess its robustness and adaptability in real market conditions.
ORIGINALITY
There are very few studies on Walk Forward Analysis in TradingView. Even worse, there are no any open-source studies available. Someone has to start somewhere, I suppose. And in my personal opinion, determining the optimization and backtest intervals is the most challenging part of WFA. These intervals serve as a prerequisite for automated parameter optimization. I felt the need to publish this pattern module, which I use in my own WFA models, partly due to this gap on community scripts.
INDICATOR MECHANICS
To use the indicator effectively, you only need to perform four simple tasks:
Specify the total number of bars in your chart in the 'Bar Index' parameter.
Define the optimization (In-Sample Test) length.
Define the testing (Out-Of-Sample Test) length.
Finally, select the window type.
The indicator automatically models everything else (including the number of steps) based on your inputs. And the result; you now have a clear idea of which bars to use for your Walk Forward tests!
A COMMONLY USED WINDOW SELECTION METHOD: ROLLING
A more concrete definition of Walk Forward Analysis, specifically for the widely used Rolling method, can be described as follows:
Parameters that have performed well over a certain period are identified (Optimization: In-Sample).
These parameters are then tested on a shorter, subsequent period (Backtest: Out-of-Sample).
The process is repeated forward in time (At each step, the optimization and backtest periods are shifted by the backtest length).
If the cumulative percentage profit obtained from the backtest results is greater than half of the historical optimization profit, the strategy is considered "successful."
If the strategy is successful, the most recent (untested) optimization values are used for live trading.
OTHER WINDOW OPTIONS
ANCHORED: That's a pattern based on progressively expanding optimization ranges at each step. Backtest ranges move forward in a staircase-like manner.
STATIC: Optimization ranges remain fixed, while backtest ranges are shifted forward.
BLOCKED: Optimization ranges are shifted forward in groups of three blocks. Backtest ranges are also shifted in a staircase manner, even at the cost of creating gaps from the optimization end bars.
TRIANGULAR: Optimization ranges are shifted forward in triangular regions, while backtest ranges move in a staircase pattern.
RATIO: The optimization length increases by 25% of the initial step’s fixed length at each step. In other words, the length grows by 25% of the first step's length incrementally. Backtest ranges always start from the bar where the optimization ends.
FIBONACCI: A variation of the Ratio method, where the optimization shift factor is set to 0.618
RANDOM WALK
Unlike the window models explained above, we can also generate optimization and backtest ranges completely randomly—offering almost unlimited variations! When you select the "Random" option in the "Window" parameter on the indicator interface, random intervals are generated based on various trigonometric calculations. By changing the numerical value in the '🐒' parameter, you can create entirely unique patterns.
WHY THE 🐒 EMOJI?
Two reasons.
First, I think that as humanity, we are a species of tailless primates who become happy when we understand things :). At least evolutionarily. The entire history of civilization is built on the effort to express the universe in a scale we can comprehend. 'Knowledge' is an invention born from this effort, which is why we feel happiness when we 'understand'. Second, I can't think of a better metaphor for randomness than a monkey sitting at a keyboard. See: Monkey Test.
Anyway, I’m rambling :)
NOTES
The indicator generates results for up to 100 steps. As the number of steps increases, the table may extend beyond the screen—don’t forget to zoom out!
FINAL WORDS
I haven’t published a Walk Forward script yet . However, there seem to be examples that can perform parameter optimization in the true sense of the word, producing more realistic results without falling into overfitting in my library. Hopefully, I’ll have the chance to publish one in the coming weeks. Sincerely thanks to Kıvanç Özbilgiç, Robert Pardo, Kevin Davey, Ernest P. Chan for their inspiring publishments.
DISCLAIMER
That's just a script, nothing more. I hope it helps everyone. Do not forget to manage your risk. And trade as safely as possible. Best of luck!
© dg_factor
Machine Learning IndexesMachine Learning Indexes Script Description
The Machine Learning Indexes script is an advanced Pine Script™ indicator that applies machine learning techniques to analyze various market data types. It enables traders to generate adaptive long and short signals using highly customizable settings for signal detection and analysis.
Key Features:
Signal Mode: Allows the user to choose between generating signals for "Longs" (buy opportunities) or "Shorts" (sell opportunities).
Index Type: Supports multiple index types including RSI, CCI, MFI, Stochastic, and Momentum. All indexes are normalized between 0-100 for uniformity.
Data Set Selection: Provides options for analyzing Price, Volume, Volatility, or Momentum-based data sets. This enables traders to adapt the script to their preferred market analysis methodology.
Absolute vs. Directional Changes: Includes a toggle to calculate absolute changes for values or maintain directional sensitivity for trend-based analysis.
Dynamic Index Calculation: Automatically calculates and compares multiple index lengths to determine the best fit for current market conditions, adding precision to signal generation.
Input Parameters:
Signal Settings:
Signal Mode: Selects between "Longs" or "Shorts" to define the signal direction.
Index Type: Chooses the type of market index for calculations. Options include RSI, CCI, MFI, Stochastic, and Momentum.
Data Set Type: Determines the basis of the analysis, such as Price, Volume, Volatility, or Momentum-based data.
Absolute Change: Toggles whether absolute or directional changes are considered for calculations.
Index Settings:
Min Index Length: Sets the base index length used for calculations.
Index Length Variety: Adjusts the increment steps for variations in index length.
Lower/Upper Bands: Define thresholds for the selected index, indicating overbought and oversold levels.
Signal Parameters:
Target Signal Size: Number of bars used to identify pivot points.
Backtest Trade Size: Defines the number of bars over which signal performance is measured.
Sample Size: Number of data points used to calculate signal metrics.
Signal Strength Needed: Sets the minimum confidence required for a signal to be considered valid.
Require Low Variety: Option to prioritize signals with lower variability in results.
How It Works:
The script dynamically calculates multiple index variations and compares their accuracy to detect optimal parameters for generating signals.
Signal validation considers the chosen mode (longs/shorts), data set, index type, and signal parameters.
Adaptive moving averages (ADMA) and Band Signals (BS) are plotted to visualize the interaction between market trends and thresholds.
Long and short signals are displayed with clear up (L) and down (S) labels for easy interpretation.
Performance Metrics:
Success Rate: Percentage of valid signals that led to profitable outcomes.
Profit Factor: Ratio of gains from successful trades to losses from unsuccessful trades.
Disclaimer:
This indicator is for informational purposes only and does not guarantee future performance. It is designed to support traders in making informed decisions but should be used alongside other analysis methods and risk management strategies.
