The pricing of first day opening price returns for ChiNext IPOs

The pricing of first day opening price returns for ChiNext IPOs We study the listing day opening price return and compare it with the closing price return for ChiNext IPOs after the China Securities Regulatory Commission (CSRC) adopted a new “Chinese-style” bookbuilding process. We start from a traditional OLS model by screening a set of potential variables, characterized in the existing literature. Through a variable reduction process, we identify 7 significant variables for each of the return series. We further utilize a GARCH-M model with an ARMA(1,1) adjustment in the residuals to correct possible autocorrelation in the returns and cross-correlation between the return and its conditional variance to improve the model. We find that the opening price synthesizes the overall market demand for new shares from institutional and individual investors as the subscription ratios from both sectors are highly significant (oversubscriptions). In addition, the market condition over the past 21 trading days prior to listing a ChiNext IPO (market momentum), offer size (size effect), and conditional return variance (asymmetric information) are also significant. We find similar significant variables that affect the closing price return except the subscription ratio from individual investors. Overall, the opening price return contains valuable information to predict the closing price return. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

The pricing of first day opening price returns for ChiNext IPOs

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Publisher
Springer US
Copyright
Copyright © 2015 by Springer Science+Business Media New York
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1007/s11156-015-0500-x
Publisher site
See Article on Publisher Site

Abstract

We study the listing day opening price return and compare it with the closing price return for ChiNext IPOs after the China Securities Regulatory Commission (CSRC) adopted a new “Chinese-style” bookbuilding process. We start from a traditional OLS model by screening a set of potential variables, characterized in the existing literature. Through a variable reduction process, we identify 7 significant variables for each of the return series. We further utilize a GARCH-M model with an ARMA(1,1) adjustment in the residuals to correct possible autocorrelation in the returns and cross-correlation between the return and its conditional variance to improve the model. We find that the opening price synthesizes the overall market demand for new shares from institutional and individual investors as the subscription ratios from both sectors are highly significant (oversubscriptions). In addition, the market condition over the past 21 trading days prior to listing a ChiNext IPO (market momentum), offer size (size effect), and conditional return variance (asymmetric information) are also significant. We find similar significant variables that affect the closing price return except the subscription ratio from individual investors. Overall, the opening price return contains valuable information to predict the closing price return.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Feb 11, 2015

References

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