Demystifying the trend of the healthcare index: Is historical price a key driver?
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摘要
This paper formulates next-day open-direction prediction for healthcare indices (S&P 500 and S&P BSE healthcare) as a supervised one-step-ahead classification problem and achieves high empirical performance (accuracy > 0.8, MCC > 0.6) on held-out tests [page::0]. The authors design three feature groups—intrinsic OHLC prices, volatility-based historical bands (Donchian, Bollinger, Keltner), and novel nowcasting features formed by log-ratios of same-day OHLC to open—and show that nowcasting features dominate predictive power per Shapley explainability, while historical band features have inconsistent or negligible contribution [page::7][page::20]. The study spans Apr 1, 2019–Mar 31, 2024 across two markets, highlights model interpretability via Shapley values, and emphasizes transparency by using only public OHLC data [page::4][page::20].
