Volatility modeling and prediction : the role of price impact

Jiang, Y, Cao, Yi, Liu, X and Zhai, J ORCID: https://orcid.org/0000-0002-2746-7749 2019, 'Volatility modeling and prediction : the role of price impact' , Quantitative Finance, 19 (12) , pp. 2015-2031.

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Abstract

In this paper, we are interested in exploring the role of price impact, derived from the order book, inmodeling and predicting stock volatility. This is motivated by the market microstructure literature thatexamines the mechanics of price formation and its relevance to market quality. Using a comprehensivedataset of intraday bids, asks, and three levels of market depths for 148 stocks in the Shanghai StockExchange from 2005 to 2016, we find substantial intraday impact from incoming bid and ask limitand market orders on stock prices. More importantly, the permanent price impact at the daily levelis 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 aheadforecasting horizon. These volatility predictions also offer economic gains to a mean-variance utilityinvestor in a portfolio setting.

Item Type: Article
Additional Information: Original title of article was 'Order book events : the price impact and its implication for volatility'
Schools: Schools > Salford Business School > Salford Business School Research Centre
Journal or Publication Title: Quantitative Finance
Publisher: Taylor & Francis
ISSN: 1469-7688
Related URLs:
Funders: National Social Science Foundation of Education Bureau, China
Depositing User: J Zhai
Date Deposited: 15 Jul 2019 09:07
Last Modified: 04 Feb 2020 10:45
URI: http://usir.salford.ac.uk/id/eprint/51792

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