By decomposing close to close returns into close to open returns (overnight returns) and open to close returns (daytime returns), we test the predictability of overnight information, which is captured by absolute values of close to open returns, on daytime return volatility. Applying the stochastic volatility model, we find that overnight price changes contain important information to predict daytime volatility. The predictive power is highest at market opening and declines gradually over the trading day. Moreover, the predictive power is higher for inactive traded stocks than for actively traded stocks.
|School:||Singapore Management University (Singapore)|
|Department:||Lee Kong Chian School of Business|
|School Location:||Republic of Singapore|
|Source:||MAI 49/06M, Masters Abstracts International|
|Keywords:||Inactive stocks, Overnight information shocks, Return on investment, Securities analysis, Stock exchanges|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
supplemental files is subject to the ProQuest Terms and Conditions of use.