TWO ESSAYS ON QUANTITATIVE FINANCE: RISK ANALYSIS AND CORPORATE RISK MANAGEMENT

Abstract

This dissertation consists of two parts. In part one, we propose a general framework to simulate risk measures, with the necessary sample size being computed using asymptotic expansions of relative errors for a wide class of dependent samples. An extensive numerical study is conducted to compare the proposed algorithm against existing algorithms, showing that the new algorithm is easy to implement, fast and accurate, even at the 0.001 quantile level. Applications to the estimation of intra-horizon risk and to a comparison of the relative errors of value-at-risk and expected shortfall are also given. In part two, we propose a tractable dynamic theoretical framework to examine the risk management strategies for a financially constrained diversified firm, coordinating cash inventory, external financing, investment, and dividend payout. The model predicts that a diversified firm's cash holding could be much lower than a specified firm's, consistent with the empirical findings in Duchin (2010). The existence, extent, and the decomposition of financial synergy for a diversified firm have been examined. We show that financial synergy in a bad state could be significantly higher than that in a good state, which is consistent with the empirical findings in Kuppuswamy and Villalonga (2016).