The performance of Chinese equity securities investment funds

Simple item page
dc.check.date10000-01-01
dc.check.embargoformatNot applicableen
dc.check.infoIndefiniteen
dc.check.opt-outNot applicableen
dc.check.reasonThis thesis is due for publication or the author is actively seeking to publish this materialen
dc.check.typeNo Embargo Required
dc.contributor.advisorO'Sullivan, Niallen
dc.contributor.advisorSherman, Meadhbhen
dc.contributor.authorGao, Jun
dc.date.accessioned2017-11-21T11:40:06Z
dc.date.available2017-11-21T11:40:06Z
dc.date.issued2017
dc.date.submitted2017
dc.description.abstractUsing a dataset of all surviving and non-surviving Chinese equity securities investment funds between May 2003 – May 2014, this study examines numerous risk-adjusted performance models in three classes: (i) unconditional models, (ii) conditional beta models and (iii) conditional alpha-beta models. Findings from all performance measures suggest no evidence of statistically significant stock selection skills on average. Higher frequency weekly data are employed to improve statistical estimation – a difficulty with much of the extant work in Chinese securities investment funds. Based on the statistical significance of the individual parameters and the Schwartz Information Criterion (SIC), a single ‘best-fit’ model from each of the classes is selected This study also evaluates the performance of funds using a bootstrap methodology to distinguish skill from luck in performance. Unconditional, conditional beta and conditional alpha-beta performance models are considered. This study also examines the performance persistence of Chinese funds by applying the recursive portfolio formation methodology of Carhart (1997). The results from sorting funds either by past 4-factor alphas or by t-statistics of past alphas suggest that the top ranked decile portfolio yields statistically and economically significant forwarding looking alphas. In addition, this study applies the recursive portfolio formation methodology for alternative ‘smaller’ portfolios of a fixed size and finds that almost all the smaller portfolios of past winning funds produce positive and statistically significant forward looking alphas. Hence an active portfolio strategy of selecting a small number of past outperforming funds may earn positive abnormal returns. This study also examines the market timing performance of Chinese funds using the parametric tests of Treynor-Mazuy and Henriksson-Merton as well as the Jiang (2003) non-parametric test. Based on the non-parametric approach, the study finds that most funds do not time the market. This conclusion is robust when controlling for publicly available information in evaluating ‘private’ timing ability.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationGao, J. 2017. The performance of Chinese equity securities investment funds. PhD Thesis, University College Cork.en
dc.identifier.endpage167en
dc.identifier.urihttps://hdl.handle.net/10468/5077
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2017, Jun Gao.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectFund performanceen
dc.subjectEmerging marketen
dc.subjectChinese fund marketen
dc.subjectMarket timingen
dc.subjectPerformance persistenceen
dc.subjectBootstrap strategyen
dc.thesis.opt-outfalse
dc.titleThe performance of Chinese equity securities investment fundsen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD (Commerce)en
ucc.workflow.supervisorniall.osullivan@ucc.ie
Files
Original bundle
Now showing 1 - 4 of 4
Thumbnail Image
Name:
GaoJ_PhD2017.pdf
Size:
4.68 MB
Format:
Adobe Portable Document Format
Description:
Full Text E-thesis
Thumbnail Image
Name:
GaoJ_PhD2017_Abstract.pdf
Size:
174.09 KB
Format:
Adobe Portable Document Format
Description:
Abstract
Thumbnail Image
Name:
FW Withdraw the submission of PhD thesis.txt
Size:
13.55 KB
Format:
Plain Text
Description:
E-mail Communication
Thumbnail Image
Name:
JunGao.pdf
Size:
62.01 KB
Format:
Adobe Portable Document Format
Description:
Letter for publisher
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
5.62 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Doctoral Theses
College of Business and Law - Doctoral Theses
Economics - Doctoral Theses