Pillar 01 — Strategy research
Build and test the strategy in Algo Lab. Edit Pine Script, run a baseline, compare bounded changes, and keep the evidence behind the versions you decide to preserve.
Basic or ProfessionalAlgo Trade Analytics has two connected jobs: research a strategy and check what happens after the backtest. Choose the side that matches the question you have now.
Pillar 01 — Strategy research
Build and test the strategy in Algo Lab. Edit Pine Script, run a baseline, compare bounded changes, and keep the evidence behind the versions you decide to preserve.
Basic or ProfessionalPillar 02 — Live validation
Compare backtest → alerts → fills. First check whether TradingView alerts agree with the List of Trades export. When broker fills exist, review timing and price differences between alerts and those fills.
Backtest vs Alerts: all plansAfter the first result, replace the sample or starter inputs with your own strategy data. You do not need to configure webhooks, a broker, Algo Lab, and every AI feature in one session.
| Data source | What it proves | When you need it |
|---|---|---|
| TradingView List of Trades CSV | What the historical strategy run says should have happened | Backtest vs Alerts |
| TradingView alert-history CSV or captured webhooks | What the strategy emitted in real time | Backtest vs Alerts |
| Alpaca historical bars | Input data for a native Algo Lab backtest when platform data is unavailable | Algo Lab |
| Alpaca fill reports | What the broker reports as filled | Alerts vs Fills |
Algo Trade Analytics is a research and reconciliation system. It helps you inspect evidence and discrepancies; it does not place trades or guarantee returns. A high match rate means more events matched under the tolerances you selected. It is not, by itself, proof that a strategy is profitable or appropriate for live capital.