swing-trading

Multi-day swing trading strategies are managed by applying regime-aware position sizing, trend and reversal filters for entries, and disciplined risk exits to capture medium-term market moves across holding periods.

Volatility-based sizing is a risk management technique that adjusts position sizes based on current market volatility, ensuring trades held across multiple days maintain disciplined risk controls and appropriate per-trade exposure.

Yes, you can run diagnostics scripts on your input data to calculate specific metrics including win rate, expectancy, gap risk, and holding period analysis for your multi-day swing trading strategies.

Yes, algorithmic trading workflows are supported through the application of trend, reversal, and catalyst filters for entries, combined with volatility-based sizing and regime-aware risk management for multi-day holdings.

The best way to enforce portfolio stop thresholds is by implementing disciplined risk exits alongside per-trade controls, ensuring that multi-day positions are closed before exceeding defined portfolio risk limits.

Swing trading strategies fail to capture medium-term moves when lacking regime-aware sizing or proper holding period controls, causing premature exits or insufficient trend and catalyst filters for entry timing.