Essays in Financial Econometrics and Game Theory.

摘要

My thesis analyzes two different topics: the estimation of the equity risk posed by the "too-big-to-fail" banks during the period encompassing The Great Recession; and a comparative analysis of the welfare effects of two different classes of affirmative action mechanisms. Both essays have been inspired by a desire to analyze currently enforced policies and to attempt to improve upon them by using arguments from Financial Econometrics and Game Theory respectively.;The first essay is titled "The Empirical Foster-Hart Risk of the Global Banking Stock Market" and measures how much equity risk the too-big-to-fail banks posed on the common public during the recent financial crisis. In this essay I use an "ARMA(1,1)-GARCH(1,1)-Normal Tempered Stable" statistical model to capture the skewed and leptokurtotic nature of stock returns; and employ the "Foster-Hart risk measure" to better capture equity risk. This union of sophisticated risk modeling with fat-tailed statistical modeling bears fruit, as the paper is able to measure the equity risk during the Great Recession much more accurately than is possible with current techniques.;The second essay is titled "Quotas versus Handicaps: A Game Theoretic Analysis of Affirmative Action Policies in India". In this essay, I analyze and compare the Quota Policy --- in which preference is given to the disadvantaged section of the populace by reserving a certain fraction of jobs for them; and a hypothetical "Handicap Policy" --- in which the performance index of the disadvantaged is given an added boost, by means of an additive handicap. After modeling this situation as a game, I am able to conclude that on many important metrics of performance, Quotas and Handicaps can be shown to be equivalent to each other.