2025/03/02 by Xiangdong Liu, Liu, Xiangdong, Sicheng Fu +4 · 1 voice
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Economics and business #Market Dynamics and Volatility #Risk Management (q-fin.RM) #q-fin.RM
paper · pdf · doi:10.48550/arxiv.2503.00851
openalex publication_date 2025/03/02 · arxiv published 2025/03/02 · openalex created_date 2025/10/12 · arxiv updated 2025/11/03 · openalex updated_date 2026/07/28
Volatility forecasting in financial markets is a topic that has received more attention from scholars. In this paper, we propose a new volatility forecasting model that combines the heterogeneous autoregressive (HAR) model with a family of path-dependent volatility models (HAR-PD). The model utilizes the long- and short-term memory properties of price data to capture volatility features and trend features. By integrating the features of path-dependent volatility into the HAR model family framework, we develop a new set of volatility forecasting models. And, we propose a HAR-REQ model based on the empirical quartile as a threshold, which exhibits stronger forecasting ability compared to the HAR-REX model. Subsequently, the predictive performance of the HAR-PD model family is evaluated by statistical tests using data from the Chinese stock market and compared with the basic HAR model family. The empirical results show that the HAR-PD model family has higher forecasting accuracy compared to the underlying HAR model family. In addition, robustness tests confirm the significant predictive power of the HAR-PD model family.