用Claude Code配合gs-quant做量化分析

this repository is f*cking BROKEN goldman sachs pays each quant up to $300k a year, all thanks to this repo It's called gs-quant, developed and maintained by Goldman Sachs' own quant team, and it already has 13.5k stars First, get how it works: 1. Goldman Sachs' quants built this toolkit on 25 years of their own risk experience: pricing, risk, backtesting, swaps, swaptions, FX options, timeseries - all in there. It even ships a skill that teaches Claude Code how to use it. 2. Every time Claude writes gs-quant code, it runs Goldman's risk math right in your notebook: volatility, drawdown, z-score, beta, RSI. 3. Pair it with Machine Learning for Trading (21.6k stars) - 27 chapters that take you from data sourcing to live execution. Together it's the exact stack a quant interview tests. Here's how you can run it for free yourself: 1. Open Claude Code, install Goldman Sachs' library: pip install gs-quant 2. Add the skill: python -m gs_quant.skills install --global 3. Have Claude pull 5-year daily prices for GS and SPY with free yfinance data 4. Run Goldman Sachs' risk math on it: volatility, max drawdown, z-score, Bollinger Bands, RSI 5. Check 60-day beta and correlation to SPY. Is it the stock moving, or the whole market? 6. Mark every day the z-score drops below -2. That means the price is 2 standard deviations below normal 7. Backtest a rule: buy below -2, sell when back at 0, including fees. Claude writes the code and runs it 8. Walk-forward it the ML4T way. If it doesn't beat buy-and-hold after fees, it's not an edge i won't say anything more: Сarm1ne: these 10 GitHub repos are the most DANGEROUS thing in trading right now together they give you a full AI hedge fund: a research desk, an investment committee and an execution desk in this article I've shown EXACTLY how to build it from scratch https://x.com/i/article/2113219739837243392