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The Accuracy Paradox in AI Equity Markets: A Regime-AwareTrading Strategy using XGBoost and Walk-Forward OptimizationBy Yash Upadhyay, Krishna Garg, Aayush Srivastava, Aniket Kumar Singh, Vikram Kapoor
Abstract: This study investigates the “Accuracy Paradox” in algorithmic equity trading by examining whether a machine learning model with near-random directional prediction accuracy can still generate profitable trading outcomes when combined with effective risk- management and market-regime rules. An XGBoost classifier was developed and evaluated using approximately six years of daily market data from five major technology stocks—NVIDIA, Apple, Microsoft, Alphabet, and Meta—covering the period from January 2020 to February 2026. …
Published in NOLEGEIN Journal of Financial Planning And Management · Vol. 9, Issue 2, 2026 Read article →