Systematic Liquidity Risk and Stock Price Reaction to Large One-Day Price Changes: Evidence from London Stock Exchange.
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AuthorAlrabadi, Dima W.H.
KeywordSystematic liquidity risk
Large one-day price changes
Efficient market hypothesis
London Stock Exchange
Rights© 2009 Alrabadi, D. W. H. This work is licensed under a Creative Commons Attribution-Non-Commercial-Share-Alike License (http://creativecommons.org/licenses/by-nc-nd/2.0/uk).
InstitutionUniversity of Bradford
DepartmentSchool of Management
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AbstractThis thesis investigates systematic liquidity risk and short-term stock price reaction to large one-day price changes. We study 642 constituents of the FTSALL share index over the period from 1st July 1992 to 29th June 2007. We show that the US evidence of a priced systematic liquidity risk of Pastor and Stambaugh (2003) and Liu (2006) is not country-specific. Particularly, systematic liquidity risk is priced in the London Stock Exchange when Amihud's (2002) illiquidity ratio is used as a liquidity proxy. Given the importance of systematic liquidity risk in the asset pricing literature, we are interested in testing whether the different levels of systematic liquidity risk across stocks can explain the anomaly following large one-day price changes. Specifically, we expect that the stocks with high sensitivity to the fluctuations in aggregate market liquidity to be more affected by price shocks. We find that most liquid stocks react efficiently to price shocks, while the reactions of the least liquid stocks support the uncertain information hypothesis. However, we show that time-varying risk is more important than systematic liquidity risk in explaining the price reaction of stocks in different liquidity portfolios. Indeed, the time varying risk explains nearly all of the documented overreaction and underreaction following large one-day price changes. Our evidence suggests that the observed anomalies following large one-day price shocks are caused by the pricing errors arising from the use of static asset pricing models. In particular, the conditional asset pricing model of Harris et al. (2007), which allow both risk and return to vary systematically over time, explain most of the observed anomalies. This evidence supports the Brown et al. (1988) findings that both risk and return increase in a systematic fashion following price shocks.
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