Intraday Volatility-Volume Joint Modeling and Forecasting: A State-Space Approach

Intraday volatility is a crucial indicator for short-term price movements of financial assets, playing a pivotal role in risk management and other financial applications in the era of high-frequency algorithmic trading. However, existing methods fail to capture complex intraday volatility patterns, leading to inadequate forecast capabilities. To address these shortcomings, we propose a novel multiplicative component framework that leverages the close relationship between volatility and trading volume to analyze intraday volatility. We further introduce a state-space approach to implement this framework for modeling and forecasting. Empirical experiments demonstrate that our proposed method outperforms traditional models by providing more comprehensive insights and achieving higher forecasting accuracy for intraday volatility.