cross-market-strategy

Backtest multi-market portfolios by using a unified signal engine that handles calendar alignment and applies market-specific indicator parameters across heterogeneous asset data like equities and crypto.

Volatility-adjusted position sizing dynamically scales position sizes based on asset-specific volatility, preventing high-volatility assets from dominating the shared risk budget across your portfolio.

Cross-market backtesting evaluates a single trading strategy across disparate asset classes like A-shares, crypto, and forex, needed when managing a unified portfolio subject to different market rules.

Yes, pandas and numpy are required dependencies to perform calendar alignment and execute signal calculations across heterogeneous asset data within the portfolio.

Yes, the composite engine automatically applies market-specific indicator parameters and shared capital allocation to assets like BTC-USDT and A-shares simultaneously.

Manage risk by implementing volatility-adjusted weighting that dynamically scales position sizes, ensuring high-volatility assets do not dominate the shared risk budget across forex and crypto markets.