A1637
Title: Examining volatility roughness in the Japanese stock market
Authors: Xuzhu Zheng - The University of Osaka/MPX, Inc. (Japan) [presenting]
Masato Ubukata - Meiji Gakuin University (Japan)
Kosuke Oya - Ritsumeikan University (Japan)
Abstract: The existence of rough volatility, which has recently attracted considerable attention and is characterized by volatility dynamics that cannot be fully captured by conventional volatility models, is examined. Specifically, the analysis investigates whether the observed roughness in volatility is merely an artifact induced by microstructure noise inherent in high-frequency price data, or whether such rough behavior persists after accounting for noise effects. The empirical analysis utilizes high-frequency data from the Nikkei 225 index and two actively traded individual stocks. Applying several representative volatility estimators, volatility series are constructed and their Hurst exponents are estimated using a nonparametric procedure. The results show that, regardless of microstructure noise, the estimated Hurst exponents consistently take low values, indicating persistent rough behavior. Furthermore, the predictability of log volatility constructed from these alternative volatility measures is evaluated using the rough fractional stochastic volatility model, the autoregressive model, and the heterogeneous autoregressive model under a unified p-ratio criterion. The analysis compares forecasting performance across models and volatility measures, while examining factors that may account for differences in predictive accuracy from the perspective of rough volatility.
