Identifying the relative importance of stock characteristics
French, Declan; Wu, Yuliang; Li, Youwei
Professor Youwei Li Youwei.Li@hull.ac.uk
There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.
|Journal Article Type||Article|
|Journal||Journal of Multinational Financial Management|
|Peer Reviewed||Peer Reviewed|
|APA6 Citation||French, D., Wu, Y., & Li, Y. (2016). Identifying the relative importance of stock characteristics. Journal of Multinational Financial Management, 34, 80-91. https://doi.org/10.1016/j.mulfin.2016.01.002|
|Keywords||Stock characteristics; Factor models|
|Related Public URLs||https://pure.qub.ac.uk/en/publications/identifying-the-relative-importance-of-stock-characteristics|
|Additional Information||This article is maintained by: Elsevier; Article Title: Identifying the relative importance of stock characteristics; Journal Title: Journal of Multinational Financial Management; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.mulfin.2016.01.002; Content Type: article; Copyright: Copyright © 2016 Elsevier B.V. All rights reserved.|
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