portfolio-optimizer

Stock portfolio optimization without an API key is possible using a no-API-key fallback chain with online sources like yfinance and akshare, or offline CSV input when network access is unavailable. The tool fetches historical prices and applies allocation constraints to produce optimal weights.

Yes, backtesting asset allocation strategies supports China A-shares and Hong Kong stocks alongside US stocks. The system automatically detects multi-market tickers, fetches historical prices, and runs rolling-rebalance backtests with trading costs to evaluate strategy performance.

The best way to compare max Sharpe and minimum variance allocations is to generate multiple strategies side by side. The optimizer evaluates max Sharpe, minimum variance, risk parity, maximum diversification, and equal-weight allocations to identify the optimal risk-adjusted split.

Portfolio optimization reports include comprehensive risk metrics such as Sharpe ratio, Sortino ratio, Calmar ratio, Value at Risk (VaR), Conditional VaR (CVaR), maximum drawdown, and concentration metrics to provide full risk insight for the allocated portfolio.

To set allocation constraints for portfolio optimization, you provide instructions alongside your ticker list, such as specifying no single stock above 30%. The optimizer applies these allocation constraints to the historical price data to calculate optimal weights within your limits.

Yes, portfolio optimization works with offline CSV price data as a fallback when network access is unavailable. The system uses a no-API-key fallback chain with online sources first, then seamlessly switches to offline CSV input to ensure continuous data retrieval for backtesting.