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Optimization approaches in risk mana...

Wang, Chung-Jui.

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Optimization approaches in risk management: Applications in finance and agriculture.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimization approaches in risk management: Applications in finance and agriculture./
Author:	Wang, Chung-Jui.
Description:	90 p.
Notes:	Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1308.
Contained By:	Dissertation Abstracts International69-02B.
Subject:	Economics, Agricultural. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3300800
ISBN:	9780549456810

Optimization approaches in risk management: Applications in finance and agriculture.
Wang, Chung-Jui.

Optimization approaches in risk management: Applications in finance and agriculture. - 90 p.

Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1308.

Thesis (Ph.D.)--University of Florida, 2007.

Along with the fast development of the financial industry in recent decades, novel financial products, such as swaps, derivatives, and structure financial instruments, have been invented and traded in financial markets. Practitioners have faced much more complicated problems in making profit and hedging risks. Financial engineering and risk management has become a new discipline applying optimization approaches to deal with the challenging financial problems.

ISBN: 9780549456810Subjects--Topical Terms:

626648
Economics, Agricultural.

Optimization approaches in risk management: Applications in finance and agriculture.
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100 1 $a Wang, Chung-Jui. $3 1685111
245 1 0 $a Optimization approaches in risk management: Applications in finance and agriculture.
300 $a 90 p.
500 $a Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1308.
500 $a Adviser: Stanislav Uryasev.
502 $a Thesis (Ph.D.)--University of Florida, 2007.
520 $a Along with the fast development of the financial industry in recent decades, novel financial products, such as swaps, derivatives, and structure financial instruments, have been invented and traded in financial markets. Practitioners have faced much more complicated problems in making profit and hedging risks. Financial engineering and risk management has become a new discipline applying optimization approaches to deal with the challenging financial problems.
520 $a This dissertation proposes a novel optimization approach using the downside risk measure, conditional value-at-risk (CVaR), in the reward versus risk framework for modeling stochastic optimization problems. The approach is applied to the optimal crop production and risk management problem and two critical problems in the secondary mortgage market: the efficient execution and pipeline risk management problems.
520 $a In the optimal crop planting schedule and hedging strategy problem, crop insurance products and commodity futures contracts were considered for hedging against yield and price risks. The impact of the ENSO-based climate forecast on the optimal production and hedge decision was also examined. The Gaussian copula function was applied in simulating the scenarios of correlated non-normal random yields and prices.
520 $a Efficient execution is a significant task faced by mortgage bankers attempting to profit from the secondary market. The challenge of efficient execution is to sell or securitize a large number of heterogeneous mortgages in the secondary market in order to maximize expected revenue under a certain risk tolerance. We developed a stochastic optimization model to perform efficient execution that considers secondary marketing functionality including loan-level efficient execution, guarantee fee buy-up or buy-down, servicing retain or release, and excess servicing fee. The efficient execution model balances between the reward and downside risk by maximizing expected return under a CVaR constraint.
520 $a The mortgage pipeline risk management problem investigated the optimal mortgage pipeline risk hedging strategy using 10-year Treasury futures and put options on 10-year Treasury futures as hedge instruments. The out-of-sample hedge performances were tested for five deviation measures, Standard Deviation, Mean Absolute Deviation, CVaR Deviation, VaR Deviation, and two-tailed VaR Deviation, as well as two downside risk measures, VaR and CVaR.
590 $a School code: 0070.
650 4 $a Economics, Agricultural. $3 626648
650 4 $a Economics, Finance. $3 626650
650 4 $a Operations Research. $3 626629
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690 $a 0508
690 $a 0796
710 2 $a University of Florida. $3 718949
773 0 $t Dissertation Abstracts International $g 69-02B.
790 1 0 $a Uryasev, Stanislav, $e advisor
790 $a 0070
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3300800