hft-quant-expert

kasyap1234/delta-go · updated Apr 8, 2026

$npx skills add https://github.com/kasyap1234/delta-go --skill hft-quant-expert
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summary

Quantitative trading expertise for DeFi and crypto derivatives.

skill.md

HFT Quant Expert

Quantitative trading expertise for DeFi and crypto derivatives.

When to Use

  • Building trading strategies and signals
  • Implementing risk management
  • Calculating position sizes
  • Backtesting strategies
  • Analyzing volatility and correlations

Workflow

Step 1: Define Signal

Calculate z-score or other entry signal.

Step 2: Size Position

Use Kelly Criterion (0.25x) for position sizing.

Step 3: Validate Backtest

Check for lookahead bias, survivorship bias, overfitting.

Step 4: Account for Costs

Include gas + slippage in profit calculations.


Quick Formulas

# 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

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.536 reviews
  • Naina Garcia· Dec 20, 2024

    hft-quant-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Dec 16, 2024

    I recommend hft-quant-expert for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ishan Huang· Dec 4, 2024

    hft-quant-expert fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ava Abebe· Nov 23, 2024

    I recommend hft-quant-expert for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chinedu Gonzalez· Nov 15, 2024

    Registry listing for hft-quant-expert matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kiara Chawla· Nov 11, 2024

    Solid pick for teams standardizing on skills: hft-quant-expert is focused, and the summary matches what you get after install.

  • Rahul Santra· Nov 7, 2024

    hft-quant-expert fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Pratham Ware· Oct 26, 2024

    hft-quant-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Diego Johnson· Oct 14, 2024

    Solid pick for teams standardizing on skills: hft-quant-expert is focused, and the summary matches what you get after install.

  • Chinedu Khan· Oct 6, 2024

    Useful defaults in hft-quant-expert — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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