Optimizing for the Wrong Goal: A Cautionary Tale of Success Rate Maximization in Hedging Strategies

This pedagogical study presents a comprehensive framework for systematic optimization of hedging trading strategies across diverse market regimes. We demonstrate that traditional parameter selection approaches often yield suboptimal results due to constrained search spaces, while systematic exploration reveals non-intuitive optimal configurations. Using a modified geometric Brownian motion process with regime-specific parameters, we generate synthetic market data across six distinct regimes and test a simultaneous long-short hedging strategy with ATR-based position sizing. Our multi-seed validation approach ensures statistical robustness, revealing that optimal parameters (stop-loss multiplier: 1.37, take-profit multiplier: 1.50) achieve 97.2% hedging success rate, significantly outperforming intuitively selected parameters. This research emphasizes the importance of broad parameter exploration, proper statistical validation, and the fundamental tradeoff between success frequency and profit magnitude in systematic trading.At the same time and even more importantly pragmatically, our analysis reveals a more fundamental methodological insight: successful optimization requires alignment between objective functions and practical goals. While we achieved "attractive" success rates, this study demonstrates how even rigorous optimization can yield practically suboptimal results when objectives mismatch real-world priorities. Because what matters is not frequency of success alone, but the fundamental relationship between profit magnitude and loss magnitude across the strategy's entire return distribution.Disclaimer: This research represents academic simulation work for educational purposes only. All trading involves substantial risk of loss, and past performance does not guarantee future results.