← Back

Strategy Harvest

Built

Signature capability

It runs the whole thing on its own. In one unattended run it cloned three strategy repos, pulled 12 strategies off Freqtrade's dependency graph into a self-contained pandas/TA-Lib engine, backtested and ranked them, and spat out production strategy files plus a 16-strategy by 6-pair deployment script.

What it is

Strategy Harvest scrapes proven open-source crypto strategies (Freqtrade official, NostalgiaForInfinity, nateemma's PCA/DWT/Kalman set) and strips them out of Freqtrade's heavy runtime into a minimal `simple_backtest()` engine built on pandas and TA-Lib. Each converted strategy exposes `calculate_indicators()` and `generate_signals()` returning {1 long, 0 flat, -1 short}, plus a `STRATEGY_CONFIG` block of risk params. It backtested 12 strategies on 30 days of ETHUSD 1h data, computed Sharpe / return / drawdown / win-rate, ranked them, wrote the top 3 as standalone production files, and generated a `deploy_strategy_army.py` that fans 16 strategies across 6 pairs with per-tier capital multipliers. Notably the output docs self-flag the statistical thinness rather than hide it.

Highlights

  • Repo harvest: cloned 3 open-source repos totalling ~40 strategies (Freqtrade 24, NostalgiaForInfinity 5, nateemma 10+) and normalised them to one signal interface
  • Dependency-strip: converts Freqtrade strategies into a self-contained pandas/TA-Lib backtester (no Freqtrade runtime), ~1,474 lines of tooling across converter, batch tester and deploy script
  • Deployment layer: deploy_strategy_army.py defines 16 strategies in 3 tiers with capital multipliers (1.25x/1.0x/0.8x) fanned across 6 pairs, backed by a SQLite results store
  • Intellectual honesty: the harvest report explicitly calls out the red flags itself, only 30 days of data, single pair, 1-13 trades per strategy, long-only, and warns live Sharpe will be well below backtest
  • Grounded expectations: projects a realistic $500 to $550-650 over 90 days rather than the headline backtest numbers

Tech · Python 3.11, pandas, NumPy, TA-Lib, ccxt (data pull), SQLite, Freqtrade strategy sources