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Essays in Empirical Asset Pricing.

Pimenova, Irina.

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Essays in Empirical Asset Pricing.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Essays in Empirical Asset Pricing./
Author:	Pimenova, Irina.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	114 p.
Notes:	Source: Dissertation Abstracts International, Volume: 80-02(E), Section: A.
Contained By:	Dissertation Abstracts International80-02A(E).
Subject:	Economic theory. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10837979
ISBN:	9780438424159

Essays in Empirical Asset Pricing.
Pimenova, Irina.

Essays in Empirical Asset Pricing. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 114 p.

Source: Dissertation Abstracts International, Volume: 80-02(E), Section: A.

Thesis (Ph.D.)--University of Pennsylvania, 2018.

In this dissertation, I revisit two problems in empirical asset pricing. In Chapter 1, I propose a methodology to evaluate the validity of linear asset pricing factor models under short sale restrictions using a regression-based test. The test is based on the revised null hypothesis that intercepts obtained from regressing excess returns of test assets on factor returns, usually referred to as alphas, are non-positive. I show that under short sale restrictions a much larger set of models is supported by the data than without restrictions. In particular, the Fama-French five-factor model augmented with the momentum factor is rejected less often than other models. In Chapter 2, I investigate patterns of equity premium predictability in international capital markets and explore the robustness of common predictive variables. In particular, I focus on predictive regressions with multiple predictors: dividend-price ratio, four interest rate variables, and inflation. To obtain precise estimates, two estimation methods are employed. First, I consider all capital markets jointly as a system of regressions. Second, I take into account uncertainty about which potential predictors forecast excess returns by employing spike-and-slab prior. My results suggest evidence in favor of predictability is weak both in- and out-of-sample and limited to a few countries. The strong predictability observed on the U.S. market is rather exceptional. In addition, my analysis shows that considering model uncertainty is essential as it leads to a statistically significant increase of investors' welfare both in- and out-of-sample. On the other hand, the welfare increase associated with considering capital markets jointly is relatively modest. However, it leads to reconsider the relative importance of predictive variables because the variables that are statistically significant predictors in the country-specific regressions are insignificant when the capital markets are studied jointly. In particular, my results suggest that the in-sample evidence in favor of the interest rate variables, that are believed to be among the most robust predictors by the literature, is spurious and is mostly driven by ignoring the cross-country information. Conversely, the dividend-price ratio emerges as the only robust predictor of future stock returns.

ISBN: 9780438424159Subjects--Topical Terms:

1556984
Economic theory.

Essays in Empirical Asset Pricing.
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300 $a 114 p.
500 $a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: A.
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502 $a Thesis (Ph.D.)--University of Pennsylvania, 2018.
520 $a In this dissertation, I revisit two problems in empirical asset pricing. In Chapter 1, I propose a methodology to evaluate the validity of linear asset pricing factor models under short sale restrictions using a regression-based test. The test is based on the revised null hypothesis that intercepts obtained from regressing excess returns of test assets on factor returns, usually referred to as alphas, are non-positive. I show that under short sale restrictions a much larger set of models is supported by the data than without restrictions. In particular, the Fama-French five-factor model augmented with the momentum factor is rejected less often than other models. In Chapter 2, I investigate patterns of equity premium predictability in international capital markets and explore the robustness of common predictive variables. In particular, I focus on predictive regressions with multiple predictors: dividend-price ratio, four interest rate variables, and inflation. To obtain precise estimates, two estimation methods are employed. First, I consider all capital markets jointly as a system of regressions. Second, I take into account uncertainty about which potential predictors forecast excess returns by employing spike-and-slab prior. My results suggest evidence in favor of predictability is weak both in- and out-of-sample and limited to a few countries. The strong predictability observed on the U.S. market is rather exceptional. In addition, my analysis shows that considering model uncertainty is essential as it leads to a statistically significant increase of investors' welfare both in- and out-of-sample. On the other hand, the welfare increase associated with considering capital markets jointly is relatively modest. However, it leads to reconsider the relative importance of predictive variables because the variables that are statistically significant predictors in the country-specific regressions are insignificant when the capital markets are studied jointly. In particular, my results suggest that the in-sample evidence in favor of the interest rate variables, that are believed to be among the most robust predictors by the literature, is spurious and is mostly driven by ignoring the cross-country information. Conversely, the dividend-price ratio emerges as the only robust predictor of future stock returns.
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