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Title: Essays on comovement
Author: Liao, Yixin
ISNI:       0000 0004 7654 5429
Awarding Body: University of Essex
Current Institution: University of Essex
Date of Award: 2019
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This thesis consists of three essays on comovement between individual stocks and the S&P 500 index, each constituting a separate chapter. These essays provide use with new angles to see the comovement. First, they find that comovement does not always change as people predict. Secondly, they find the motivation to use 3- and 4-factor models to estimate excess comovement. Finally, they use PE ratios to test the reason behind the comovement. The first essay (Chapter 2) finds that the univariate betas of 36-46% of our sample of 733 added stocks 1976-2015 decrease each year following addition. Moreover, a majority of the 192 deleted stocks increase rather than decrease each year at monthly frequency. This chapter develops a stylised model in which leverage constrained investors like pension funds are index trackers but unconstrained investors like hedge funds employ a betting-against-beta (BAB) strategy to capture this. Decreasing betas can be explained by hedge funds shorting the high beta stocks to be included in the index and this effect more than counters the index tracking effect. The second essay (chapter 3) finds that returns on the S&P 500 index, small-minus-big, high-minus-low, and momentum factors are cross correlated and hence that 3- and 4-factor models are more appropriate to estimate excess comovement. This chapter finds significant changes in beta even when 3- and 4-factor models are used. It further confirms that momentum plays an essential role in comovement. The final essay (chapter 4) use a new method to investigate the role sentiment plays in the comovement. The chapter develops an equation to show how the PE ratio pattern should be in an efficient market and find empirical evidence to reject the null that the market is efficient. The chapter confirms that the sentiment plays essential roles in comovement.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HG Finance