Signal Lab · Trading research
Trading strategy research.
Tests trading strategies with walk-forward evaluation, multi-year timestamped data, configured execution costs, and documented criteria for allocating capital.
Recent closed signals
| Symbol | Direction | Strategy | Outcome | R-multiple |
|---|---|---|---|---|
| SPY | long | ts_momentum | SL hit | — |
| SPY | long | ts_momentum | SL hit | — |
| SPY | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
| QQQ | long | ts_momentum | SL hit | — |
How it works
Hypothesise
Define a trading strategy and its parameters
Validate
Rolling walk-forward tests with execution costs
Shadow
Generate signals, log outcomes, no broker orders
Promote
Evaluate each stage: shadow → micro → normal → scale
Backtested setups — best performer per market
Stocks · sma_slope_acceleration on Communication Services · 15 filled trades
Follow the research
Join the free Telegram channel for project updates, selected signals, and closed-trade outcomes from the validation pipeline.
Join free TelegramCapital-allocation research project, not financial advice. All signal outcomes are from a paused shadow-mode pipeline — no live trading is active. No sizing, balances, or broker details are published.