[-] Show simple item record

dc.contributor.advisorO'Doherty, Michael S.eng
dc.contributor.authorKothari, Patrikeng
dc.date.issued2019eng
dc.date.submitted2019 Springeng
dc.description.abstractIn this dissertation, I consider two topics in return predictability and performance evaluation in active management. In the first essay, I propose a production based asset pricing model with labor inputs. In this model, to either maintain the current size of the workforce (by replacing departing workers) or change the size of the workforce, firms advertise job openings and hire new workers each period. Changes in labor inputs are subject to stochastic adjustment costs coming from search-matching frictions in labor markets. The adjustment costs represent resources spent on hiring activities and increase convexly with the job openings rate (i.e., the ratio of the number of vacancies to the size of the workforce). The expected return for the rm is a ratio of marginal benefits to marginal costs. Accordingly, the model predicts a negative relation between the job openings rate and expected return in the subsequent period. Empirical tests con rm the model's prediction and show that the job openings rate is a strong negative predictor of returns. The job openings rate also outperforms 16 other popular forecasting variables. Forecasts obtained from the job openings rate also leads to large gains in returns for investors who consider it in making asset allocation decisions. In the second essay, I reexamine the relation between managerial activeness and mutual fund performance. Several recent studies argue that investors can use ex ante observable proxies of managerial activeness (e.g., active share, active weight, return gap, and R2) to predict net of fee risk adjusted performance of mutual fund managers. Using a sample 11 such managerial activeness proxies, first, I show that the predictive power of the activeness proxies is largely concentrated in a three year period from 1999 to 2001 and excluding this period, only two activeness proxies significantly predict net alpha. Second, none of the activeness proxies are significantly predictors in out-of-sample tests. Third, the characteristic-sorted portfolios formed using the activeness proxies have positive exposures to profitability and investment factors. Using the Fama and French (2015) five-factor model as the benchmark, net alpha for these portfolios reduces by about 80% on average.eng
dc.identifier.urihttps://hdl.handle.net/10355/69958
dc.titleEssays on return predictability and active managementeng
dc.typeThesiseng
thesis.degree.disciplineBusiness administrationeng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.namePhDeng


Files in this item

[PDF]

This item appears in the following Collection(s)

[-] Show simple item record