Can Technical Indicators Predict Daily Price Direction? Walk-Forward Evidence from Bitcoin, the S&P 500, and Gold

Abstract

Background. Technical analysis remains among the most accessible forms of market decision support, but its incremental predictive value depends on design choices, and repeated model selection can create spurious backtest performance. Objective. This study evaluates whether widely used technical indicators, reconstructed from public formulas, can predict the next daily price direction of Bitcoin, the S&P 500, and gold. Methods. Daily data from 1 January 2015 to 14 July 2026 are examined using a chronological walk-forward design. Every signal observed at the close of day t is matched only with the sign of the close-to-close return from t to t+1. The main out-of-sample period begins in 2019, with 2019–2022 used for model selection and 2023–2026 reserved for confirmation. Performance is measured primarily by balanced accuracy and supplemented by accuracy, directional recall, stationary-bootstrap confidence intervals, and after-cost trading outcomes. Results. The best single indicator, Ichimoku 9/26/52, produced a macro balanced accuracy of 50.9%, while the best predetermined combination, Volume Confirmed, reached 50.8%. A new ridge-logistic hybrid indicator, SPAH-1, achieved 51.9% in validation and 51.3% in confirmation. Its confirmation balanced accuracy was 49.8% for Bitcoin, 49.2% for the S&P 500 proxy, and 55.0% for gold; only gold's bootstrap interval excluded 50%, but its predictions were strongly biased toward the upward class. After trading costs, Volume Confirmed underperformed buy-and-hold for all three assets. Additional selective experiments did not support an 80% daily prediction target. Conclusion. Technical indicators may assist regime description and decision confirmation, but they do not provide a robust universal next-day forecasting edge.