How the Performance Dashboard Works
The performance metrics and Profit and Loss (PnL) figures displayed on our dashboard are the result of a rigorous and transparent backtesting simulation. This process is designed to realistically model the performance of our trading signals based on historical data. Our commitment to transparency is absolute, which is why the complete source code for this calculation engine is publicly available for independent review and verification.
You can access the source code here: Source Code Link
The Simulation Engine: A Foundation of Realism
Our backtesting engine simulates trades with a fixed and consistent set of parameters to ensure that all results are comparable and grounded in a realistic trading scenario.
Initial Capital & Leverage: Every backtest for each trading pair is simulated using a starting capital of $25,000. All trades are conducted with 1x leverage to provide a clear, unleveraged view of the strategy's raw performance.
Timeframe: The strategy operates exclusively on the 15-minute (15m) chart. All signals and subsequent actions are based on this interval.
Data Integrity: To ensure the highest degree of accuracy, the simulation uses actual historical OHLCV (Open, High, Low, Close, Volume) data. This data is fetched from a dedicated API for every 15-minute interval relevant to a trade, from entry to exit.
Core Strategy & Risk Management Rules
The logic governing every simulated trade is systematic and strictly enforced by the backtesting script. There is no discretionary decision-making involved.
Signal Execution: When a "buy" or "sell" signal is generated, a new position is opened at the price recorded at the time of the signal.
Strict Risk Management:
Stop-Loss (SL): A hard stop-loss is set at 2% against the entry price. If the price of an asset moves 2% against our position, the trade is automatically closed for a loss.
Take-Profit (TP): A two-tiered take-profit system is used to secure gains:
TP1 (Partial Profit): When the price moves 4% in our favor, half of the position (50%) is closed to lock in partial profits.
TP2 (Full Profit): The remaining half of the position is closed when the price reaches a 6% move in our favor.
Capital Protection (Break-Even Rule): After TP1 (4% gain) is hit and half the position is sold, the strategy implements a capital protection rule. If the price retraces back to the original entry price, the remaining half of the position is closed at break-even, ensuring the secured profit is protected.
Handling Reverse Signals: If an opposing signal is generated while a position is already open (e.g., a "sell" signal appears while in a "buy" trade), the existing position is immediately closed at the current market price. A new position is then opened in the direction of the new signal.
End-of-Day Protocol: The strategy operates strictly on a day-trading basis. Any positions that have not hit their SL or TP targets by the end of the trading day are automatically closed at the last available market price for that day. No positions are held overnight.
Data Processing and Transparency
The entire process, from fetching data to calculating the final PnL, is automated to ensure consistency and eliminate human error.
Data Caching: To optimize performance and ensure results are reproducible, daily PnL for each symbol is cached in a local database. This cache is cleared before each new backtest run to guarantee the data is always fresh and based on the latest available signals.
Open Source Commitment: We believe in radical transparency. The Python script that runs this entire simulation is open-source. We encourage our community to review the code, understand the logic, and verify that our results are calculated exactly as described. This ensures that the performance you see is not a black box but a transparent and verifiable outcome of our strategy.
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