Agent skill

hft-quant-expert

Quantitative trading expertise for DeFi and crypto derivatives. Use when building trading strategies, signals, risk management. Triggers on signal, backtest, alpha, sharpe, volatility, correlation, position size, risk.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/hft-quant-expert-barissozen-claude

SKILL.md

HFT Quant Expert

Quick Formulas

python
# Z-score
zscore = (value - rolling_mean) / rolling_std

# Sharpe (annualized)
sharpe = np.sqrt(252) * returns.mean() / returns.std()

# Kelly fraction (use 0.25x)
kelly = (win_prob * win_loss_ratio - (1 - win_prob)) / win_loss_ratio

# Half-life of mean reversion
half_life = -np.log(2) / lambda_coef

Common Pitfalls

  • Lookahead bias - Using future data
  • Survivorship bias - Only existing assets
  • Overfitting - Too many parameters
  • Ignoring costs - Gas + slippage
  • Wrong annualization - 252 daily, 365*24 hourly

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