Title page for ETD etd-050212-113640

Document Type masters report

Author Name Shen, Chen

Email Address shenchen at wpi.edu

URN etd-050212-113640

Title Risk Management Project

Degree MS

Department Mathematical Sciences

Advisors
Blais, Marcel Y., Advisor

Keywords
ARMA-GARCH
Chi-square test
Expected Shortfall
Value-at-Risk
Risk Management
AIC
Portfolio Optimization
BIC

Date of Presentation/Defense 2012-04-30

Availability unrestricted

Abstract
In order to evaluate and manage portfolio risk, we separated this project into three sections. In the first section we constructed a portfolio with 15 different stocks and six options with different strategies. The portfolio was implemented in Interactive Brokers and rebalanced weekly through five holding periods. In the second section we modeled the loss distribution of the whole portfolio with normal and student-t distributions, we computed the Value-at-Risk and expected shortfall in detail for the portfolio loss in each holding week, and then we evaluated differences between the normal and student-t distributions. In the third section we applied the ARMA(1,1)-GARCH(1,1) model to simulate our assets and compared the polynomial tails with Gaussian and t-distribution innovations.

Files
cshen.pdf

Browse by Author | Browse by Department | Search all available ETDs

Questions? Email etd-questions@wpi.edu
Maintained by webmaster@wpi.edu

Document Type	masters report
Author Name	Shen, Chen
Email Address	shenchen at wpi.edu
URN	etd-050212-113640
Title	Risk Management Project
Degree	MS
Department	Mathematical Sciences
Advisors	Blais, Marcel Y., Advisor
Keywords	ARMA-GARCH Chi-square test Expected Shortfall Value-at-Risk Risk Management AIC Portfolio Optimization BIC
Date of Presentation/Defense	2012-04-30
Availability	unrestricted
Abstract In order to evaluate and manage portfolio risk, we separated this project into three sections. In the first section we constructed a portfolio with 15 different stocks and six options with different strategies. The portfolio was implemented in Interactive Brokers and rebalanced weekly through five holding periods. In the second section we modeled the loss distribution of the whole portfolio with normal and student-t distributions, we computed the Value-at-Risk and expected shortfall in detail for the portfolio loss in each holding week, and then we evaluated differences between the normal and student-t distributions. In the third section we applied the ARMA(1,1)-GARCH(1,1) model to simulate our assets and compared the polynomial tails with Gaussian and t-distribution innovations.
Files	cshen.pdf