Run quantitative finance analysis, backtests, risk evaluation, and portfolio optimization by chat.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Quant Research Assistant" yet — see the docs or source repo.
Analyze AAPL over the past year. Report volatility, max drawdown, and Sharpe ratio, then use an HMM to identify the current market regime and explain what it means.
Returns key risk-return metrics, a market regime classification, and a brief interpretation for investment decisions.
Backtest a dual moving-average strategy on SPY using free data: buy when the 20-day MA crosses above the 50-day MA, and sell when it crosses below. Report cumulative return, annualized return, drawdown, win rate, and compare it with buy-and-hold.
Provides backtest results, core performance metrics, and a comparison against the benchmark strategy.
I have four stocks: AAPL, MSFT, NVDA, and GOOGL. Using the past three years of data, perform mean-variance portfolio optimization and provide the optimal weights, expected return, volatility, and an explanation of the diversification effect.
Returns recommended weights, estimated portfolio risk and return, and a brief explanation of the allocation rationale.
Access real-time stock quotes, fundamentals, and market status through AI.
Access stock quotes, historical data, and technical indicators through MCP.
Provides backtesting, portfolio optimization, and performance analytics for quant research.
Access live market data, trading signals, options analytics, and portfolio insights.
Access China A-share data, news, and backtesting for quantitative research.
Analyze structured products, optimize portfolios, assess risk, and run backtests in Claude.