Price Action Meets Volatility: A Dual-Factor Strategy for Nifty Gap Forecasting

This study investigates the predictive effectiveness of technical signals derived from the India VIX (volatility index) and daily candlestick patterns in forecasting next-day market gaps in the Nifty index. Using a dataset of 3,802 daily observations spread over 2010 to June, 2025, the research evaluates three types of signal models: (1) based solely on the direction of change in VIX, (2) based on the colour of the daily candlestick (GREEN for bullish, RED for bearish), and (3) a joint signal incorporating both volatility and price action. Statistical analysis reveals that while both VIX-based and candlestick-based signals individually achieve marginally better-than-random accuracy of 50% (approximately 53.1% and 52.8% respectively), their combination improves predictive precision slightly to 54.4%. Notably, bullish setups—characterized by a GREEN candle coupled with a decline in VIX—yield the highest success rate (~69.6%), while bearish signals (RED candle and rising VIX) demonstrate significantly lower reliability (~39.8%). The findings suggest that market optimism is more predictive and consistent than fear-driven scenarios, reflecting structural bullish tendencies in Indian equity markets. Although limited in standalone predictive power, these signals may serve as useful components in multi-factor forecasting models or rule-based trading strategies. The study contributes to the understanding of how behavioural and technical indicators interact in shaping short-term market movements. By contributing to the empirical validation of widely used technical and sentiment indicators, this study adds to the growing body of literature at the intersection of technical analysis, behavioural finance, and market microstructure.