| dc.identifier.uri | http://hdl.handle.net/11401/76349 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Dissertation | |
| dcterms.abstract | Quantifying the risk of the uncertainty in the future value of a portfolio is a key task in risk management. For decades many researchers have been trying to formalize sophisticated risk measures and apply them in the real financial world. In view of that this dissertation is dedicated to investigate the development of risk measures along with the applications in risk management, particularly in partial hedging under stochastic interest rate. In this dissertation we assess the partial hedging problems by formulating hedging strategies that minimize conditional value-at-risk (CVaR) of the portfolio loss under stochastic interest rate environment. The combination of stochastic interest and CVaR hedging method makes the valuing approach more complex than the existing model with constant interest rate. We take up two issues in searching the optimal CVaR hedging strategy: given the initial capital constraint we minimize the CVaR of the portfolio loss; by prescribing a bound on the risk, we also minimize the hedging cost. As an illustration of this hedging technique we derive hedging strategies for a European call option with the Black Scholes setting under HJM framework; explicit formulas are presented. We also investigate CVaR hedging problems by using the real financial data. The last chapter in this dissertation investigate nominal and robust portfolio optimization by employing difference version of CVaR as the risk measure. We assume that the return only known to follow a distribution set. High frequency data is used to test the performance of CVaR optimization and Worst CVaR optimization with contrast to a equally weighted portfolio. | |
| dcterms.available | 2017-09-20T16:50:04Z | |
| dcterms.contributor | Rachev, Svetlozar | en_US |
| dcterms.creator | Tsao, Angela | |
| dcterms.dateAccepted | 2017-09-20T16:50:04Z | |
| dcterms.dateSubmitted | 2017-09-20T16:50:04Z | |
| dcterms.description | Department of Applied Mathematics and Statistics. | en_US |
| dcterms.extent | 102 pg. | en_US |
| dcterms.format | Monograph | |
| dcterms.format | Application/PDF | en_US |
| dcterms.identifier | http://hdl.handle.net/11401/76349 | |
| dcterms.issued | 2015-08-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:50:04Z (GMT). No. of bitstreams: 1
Tsao_grad.sunysb_0771E_11854.pdf: 7117557 bytes, checksum: a01eb4fd38639f98544d87f4206c650e (MD5)
Previous issue date: 2014 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Mathematics | |
| dcterms.title | Monetary Risk Measure with Applications in Portfolio Management-Partial Hedging | |
| dcterms.type | Dissertation | |
