multi-market-strategy

Cross-market backtesting requires calendar alignment and market-specific execution rules. This strategy relies on the CompositeEngine to align dates and apply per-market rules, while generating per-symbol trading signals for a mixed portfolio spanning different asset classes.

Portfolio allocation prevents high-volatility assets from dominating by applying volatility-adjusted signal weighting. This strategy scales signal strength by inverse volatility so that higher-volatility assets do not consume an outsized share of the risk budget.

You can backtest mixed asset class combinations like A-shares plus crypto. The strategy detects the market type per symbol and computes signals using market-specific parameters to handle the distinct characteristics of each asset class.

Generating trading signals for multi-asset portfolios requires per-market indicator parameterization and volatility adjustment. This strategy detects market types per symbol and applies risk-balanced weights to target signals across different exchanges.

Multi-market backtesting requires the CompositeEngine to align trading calendars and apply per-market rules such as T+1 or funding mechanics. This strategy focuses on target signal generation and relies on the engine for execution and capital allocation.

Multi-market signals fail to align due to differing trading calendars and volatility profiles. This strategy addresses the issue by using the CompositeEngine for date alignment and applying volatility-adjusted signal weighting across the cross-market portfolio.