High-frequency volatility modeling: A Markov-Switching Autoregressive Conditional Intensity model

Yifan Li, Ingmar Nolte and Sandra Nolte (Lechner)

Journal of Economic Dynamics and Control, 2021, vol. 124, issue C

Abstract: We develop a Markov-Switching Autoregressive Conditional Intensity (MS-ACI) model with time-varying transitional probability, and show that it can be reliably estimated via the Stochastic Approximation Expectation–Maximization algorithm. Applying our model to high-frequency transaction data, we detect two distinct regimes in the intraday volatility process: a dominant volatility regime that is observable throughout the trading day representing the risk-transferring trading activity of investors, and a minor volatility regime that concentrates around market liquidity shocks which mainly capture impacts of firm-specific news arrivals. We propose a novel daily volatility decomposition based on the two detected volatility regimes.

Keywords: Regime switch; Intensity modeling; Invariance; Stock return volatility (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:124:y:2021:i:c:s0165188921000129

DOI: 10.1016/j.jedc.2021.104077

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