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L8 · Classroom Station Route complete

TRL Backtesting

A backtesting lab for trading strategies, from back when I wanted to be a quant.

OPENED
APR 2026
COURSE
Software Engineering
SOURCE
Public on GitHub
Trading Research Lab results dashboard: final equity of 10,678.74, 6.79% total return, 15.55% annual return, 1.18 Sharpe, -8.13% max drawdown, 30% win rate, and the equity curve and monthly returns below.
A real backtest on the sample BTC dataset: moving-average optimization and results against 10,000 starting capital.

ROUTE · L8 Classroom · 6 stations

  1. DEC 2025 · Heritage station Meteo ESP32
  2. YOU ARE HERE TRL Backtesting
  3. MAY 2026 · Extension underway SistemaIVR
  4. MAY 2026 · Heritage station botAsesorCarreras
  5. MAY 2026 · Route complete metaheuristics-lab
  6. SEP 2026 · Under construction AmortizaCore

Why it exists

It tests trading strategies against historical data: simple and walk-forward backtests, parameter tuning with random search, grid search or a genetic algorithm, and a dashboard to compare runs. FastAPI backend, React frontend, data in Parquet.

That was when I wanted to be a quant. I didn't understand much, but it worked. Like several of my school projects, it was already in the grave until Cursor came along and brought it back. It's an educational tool, not financial advice.

How it's built

  • FastAPI
  • React
  • Vite
  • SQLite
  • Parquet
  • algoritmo genético