8. Backtests module

Module link: https://my.whalepro.org/backtests/ 

 8.1. Purpose 
 The “Backtests” module is designed to test previously created Alerts over a historical interval for a trading pair. 
 Attention: if you do not have alerts created, this module will not work! 
 When creating a backtest you can select up to two Alerts and a history interval of up to 7 years. 
 If two alerts are selected, they are checked separately: the system first finds points where all conditions for the first alert are met, then for the second alert. So we get separate points for each alert. 
 Note: currently access to backtests is available only on the Professional plan. 

 8.2. Overview 
 
 
 
 
 
 1 — Start buttons for running a backtest. 
 Backtests with 1 or 2 alerts are supported. 
 2 — List of completed backtests with controls. 
 Controls: 
 3 — “Edit backtest” icon 
 Opens the backtest edit form. Important: saving deletes previous results because the system treats the edited backtest as “new”. 
 4 — “Copy backtest” icon 
 Opens the create backtest form using the existing one as a template. 
 5 — “Delete backtest” icon 
 6 — “View backtest settings” icon 
 7 — “Open backtest results chart” icon 

 8.3. Adding a backtest 
 Let’s create a backtest for a single alert. 
 Click “New backtest 1 alert”. 
 The backtest settings menu opens 
 
 
 
 
 
 1 — Name 
 2 — Period 
 3 — Start, End dates 
 Alert section 
 4 — Alert selection 
 5 — Position size 
 6 — Entry lag 
 7 — Leverage 
 8 — “Entry filters” section 
 9 — Position change on repeated alert trigger 

 Backtest configuration parameters 
 Name — any name for easier identification in the list. 
 Period — the time interval to test over. Choose from presets (1m, 3m, 6m, 1y, etc.) or set custom start/end dates. 
 Alert selection — choose a pre-created alert to test on historical data. Alerts are created in the “Chart” module. 
 Position size — the amount used to open a position when the alert triggers. 
 Entry lag — delay between alert trigger and position open, modeling real-world conditions. 
 Leverage — leverage size used when opening positions in the backtest. 
 Entry filters — extra conditions that must be met to open a position in addition to the main alert. 
 Position change on repeated alert — behavior when the alert triggers again while a position is open: ignore, increase position, close and reopen. 

 8.4. Viewing results 
 After starting a backtest, the system analyzes historical data and finds all points where the alert conditions are met. For each such point, a position is modeled according to parameters and subsequent price changes are tracked. 
 Results are presented as: 
 
 Chart with entry/exit points 
 Table with per-trade statistics 
 Summary performance metrics 
 
 Key metrics to analyze: 
 
 Total profit/loss 
 Win rate 
 Average profit per trade 
 Maximum drawdown 
 Risk/reward ratio 
 
 To view results click the “Open backtest results chart” icon in the list. 

 8.5. Example 
 Example: create and analyze a backtest for an alert tracking buy volume spikes on BTCUSDT. 
 
 Create an alert in the “Chart” module that triggers when buy volume exceeds a threshold. 
 In “Backtests” click “New backtest 1 alert”. 
 Name it “BTC volume test”. 
 Select the last year as the test period. 
 In the “Alert” section select your buy-volume alert. 
 Set position size to 1000 USDT. 
 Set entry lag to 1 hour. 
 Set leverage to 1x. 
 In “Entry filters” add a condition that 24h change is between -2% and +2%. 
 Click “Save and run”. 
 
 After completion analyze results: 
 
 Check overall strategy return 
 Analyze distribution of winners/losers 
 Study periods of best performance 
 Adjust alert parameters or entry conditions based on findings 
 Run a new backtest and compare 
 
 This iterative process helps optimize a trading strategy before applying it to a real account.