quant-finance-strategy-risk

What problem does it solve?

Quantitative finance teams require a unified framework to evaluate trade signals and quantify risk across strategies. This Skill delivers risk metrics, position sizing models, volatility forecasting, regime detection, and backtesting support to inform robust decision-making.

Core Features & Use Cases

• Risk metrics (Sharpe, Sortino, VaR, CVaR, drawdown) for strategy evaluation
• Position sizing models (Kelly, half-Kelly, confidence-based sizing)
• Volatility modeling (GARCH, EWMA) and regime detection
• Multi-timeframe analysis and correlation checks for risk budgeting
• Backtesting results interpretation and decision support for deployment
• Use cases: evaluate new signals, calibrate leverage, compare strategies, and enforce risk budgets

Quick Start

Run a backtest on a proposed signal and output key risk metrics (Sharpe, Sortino, VaR, CVaR) along with a recommended position size for a given balance.