Essays on Financial Econometrics

<p>This dissertation contains my research results on two topics of nancial econometrics.</p><p>The rst topic is jump regression where the observation selection procedure can be</p><p>viewed as the analogy of dimension reduction for the classical big "P" problem in</p><p>statistics to the big "N" problem in nancial econometrics. The second topic is about</p><p>estimation and testing of time series models for Value-at-Risk (VaR) and Expected</p><p>Shortfall (ES), which is the average return on a risky asset conditional on the return</p><p>being below some quantile of its distribution, namely its VaR.</p><p>The rst chapter, which is joint work with Jia Li, Viktor Todorov and George</p><p>Tauchen, develops an ecient mixed-scale estimator for jump regressions using highfrequency</p><p>asset returns. A novel bootstrap procedure is proposed to make inference</p><p>about our estimator, which has a non-standard asymptotic distribution that cannot</p><p>be made asymptotically pivotal via studentization. The Monte Carlo analysis indicates</p><p>good nite-sample performance of the general specication test and condence</p><p>intervals based on the bootstrap. When the method is applied to a high-frequency</p><p>panel of Dow stock prices together with the market index dened by the S&P 500</p><p>index futures over the period 2007{2014, we observe remarkable temporal stability</p><p>in the way that stocks react to market jumps.</p><p>The second chapter is co-authored with Andrew J. Patton and Johanna F. Ziegel.</p><p>We use recent results from statistical decision theory to overcome the problem of</p><p>\elicitability" for ES by jointly modelling ES and VaR, and propose new time series</p><p>models for these risk measures. Estimation and inference methods are provided for</p><p>the proposed models and conrmed via simulation studies to have good nite-sample</p><p>properties. We apply these models to daily returns on four international equity</p><p>indices, and nd the proposed new ES-VaR models outperform forecasts based on</p><p>iv</p><p>GARCH or rolling window models.</p><p>The third chapter is my single-authored paper which proposes a consistent speci-</p><p>cation test of dynamic joint models for VaR and ES. To overcome the intractability</p><p>problem of the asymptotic distribution of the test statistics under the null hypothesis,</p><p>the subsampling approximation is used to get the asymptotic critical values. A</p><p>Monte Carlo study shows that the proposed test has better empirical size and power</p><p>performance in nite samples than other existing tests.</p>

Author dc:creator

• CHEN, RUI

Advisor dc:contributor.advisor

• Patton, Andrew

• Economics

Handle dc:identifier.uri

https://hdl.handle.net/10161/21518

OAI identifier oai:identifier

oai:dukespace.lib.duke.edu:10161/21518