Volatility modeling and prediction: the role of price impact
In this paper, we are interested in exploring the role of price impact, derived from the order book, in modeling and predicting stock volatility. This is motivated by the market microstructure literature that examines the mechanics of price formation and its relevance to market quality. Using a comp...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Routledge
2019
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/59571/ |
| _version_ | 1848799648194494464 |
|---|---|
| author | Jiang, Ying Cao, Yi Liu, Xiaoquan Zhai, Jia |
| author_facet | Jiang, Ying Cao, Yi Liu, Xiaoquan Zhai, Jia |
| author_sort | Jiang, Ying |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In this paper, we are interested in exploring the role of price impact, derived from the order book, in modeling and predicting stock volatility. This is motivated by the market microstructure literature that examines the mechanics of price formation and its relevance to market quality. Using a comprehensive dataset of intraday bids, asks, and three levels of market depths for 148 stocks in the Shanghai Stock Exchange from 2005 to 2016, we find substantial intraday impact from incoming bid and ask limit and market orders on stock prices. More importantly, the permanent price impact at the daily level is a significant determinant of stock volatility dynamics as suggested by the panel VAR estimation. Furthermore, when we augment traditional volatility models with the time series of daily price impact, the augmented models produce significantly more accurate volatility predictions at the one-day ahead forecasting horizon. These volatility predictions also offer economic gains to a mean-variance utility investor in a portfolio setting. |
| first_indexed | 2025-11-14T20:39:00Z |
| format | Article |
| id | nottingham-59571 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:39:00Z |
| publishDate | 2019 |
| publisher | Routledge |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-595712019-12-11T03:19:40Z https://eprints.nottingham.ac.uk/59571/ Volatility modeling and prediction: the role of price impact Jiang, Ying Cao, Yi Liu, Xiaoquan Zhai, Jia In this paper, we are interested in exploring the role of price impact, derived from the order book, in modeling and predicting stock volatility. This is motivated by the market microstructure literature that examines the mechanics of price formation and its relevance to market quality. Using a comprehensive dataset of intraday bids, asks, and three levels of market depths for 148 stocks in the Shanghai Stock Exchange from 2005 to 2016, we find substantial intraday impact from incoming bid and ask limit and market orders on stock prices. More importantly, the permanent price impact at the daily level is a significant determinant of stock volatility dynamics as suggested by the panel VAR estimation. Furthermore, when we augment traditional volatility models with the time series of daily price impact, the augmented models produce significantly more accurate volatility predictions at the one-day ahead forecasting horizon. These volatility predictions also offer economic gains to a mean-variance utility investor in a portfolio setting. Routledge 2019-07-25 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/59571/1/Volatility%20modeling%20and%20prediction%20the%20role%20of%20price%20impact.pdf Jiang, Ying, Cao, Yi, Liu, Xiaoquan and Zhai, Jia (2019) Volatility modeling and prediction: the role of price impact. Quantitative Finance, 19 (12). pp. 2015-2031. ISSN 14697688 Market Microstructure; Chinese Stock Market; Panel Vector Autoregression; Volatility Modeling https://doi.org/10.1080/14697688.2019.1636123 doi:10.1080/14697688.2019.1636123 doi:10.1080/14697688.2019.1636123 |
| spellingShingle | Market Microstructure; Chinese Stock Market; Panel Vector Autoregression; Volatility Modeling Jiang, Ying Cao, Yi Liu, Xiaoquan Zhai, Jia Volatility modeling and prediction: the role of price impact |
| title | Volatility modeling and prediction: the role of price impact |
| title_full | Volatility modeling and prediction: the role of price impact |
| title_fullStr | Volatility modeling and prediction: the role of price impact |
| title_full_unstemmed | Volatility modeling and prediction: the role of price impact |
| title_short | Volatility modeling and prediction: the role of price impact |
| title_sort | volatility modeling and prediction: the role of price impact |
| topic | Market Microstructure; Chinese Stock Market; Panel Vector Autoregression; Volatility Modeling |
| url | https://eprints.nottingham.ac.uk/59571/ https://eprints.nottingham.ac.uk/59571/ https://eprints.nottingham.ac.uk/59571/ |