A Mixed Frequency Stochastic Volatility Model for Intraday Stock Market Returns
| Autor: | Jeremias Bekierman, Bastian Gribisch |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Economics and Econometrics
050208 finance Mixed frequency Leverage (finance) Stochastic volatility Financial economics Realized variance 05 social sciences Implied volatility Asset return Volatility swap Component (UML) 0502 economics and business Volatility smile Forward volatility Economics Econometrics Stock market Volatility (finance) Finance Importance sampling 050205 econometrics Mathematics |
| Zdroj: | Journal of Financial Econometrics. 19:496-530 |
| ISSN: | 1479-8417 1479-8409 |
| DOI: | 10.1093/jjfinec/nbz021 |
| Popis: | We propose a mixed frequency stochastic volatility (MFSV) model for the dynamics of intraday asset return volatility. In order to account for long-memory we separate stochastic daily and intraday volatility patterns by introducing a long-run component that changes at daily frequency and a short-run component that captures the remaining intraday volatility dynamics. An additional component captures deterministic intraday patterns. We analyze the stochastic properties of the resulting non-linear state-space model both on the daily and the intraday frequency and show how the model can be estimated in a single step using simulated maximum likelihood based on Efficient Importance Sampling (EIS). We apply the model to intraday returns of five New York Stock Exchange traded stocks. The estimation results indicate distinct dynamic patterns for daily and intradaily volatility components, where about 50% of intraday volatility dynamics are explained by the daily component. In-sample diagnostic tests and an out-of-sample forecasting experiment indicate that already the very basic model specification successfully accounts for the complex dynamic and distributional properties of asset returns both on the intraday and the daily frequency. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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