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Portfolio Optimization with Stochast...

Varga, Katherine Yvonne.

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Portfolio Optimization with Stochastic Dividends and Stochastic Volatility.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Portfolio Optimization with Stochastic Dividends and Stochastic Volatility./
作者:	Varga, Katherine Yvonne.
面頁冊數:	119 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-10(E), Section: A.
Contained By:	Dissertation Abstracts International77-10A(E).
標題:	Mathematics education. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10113008
ISBN:	9781339761282

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility.
Varga, Katherine Yvonne.

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility. - 119 p.

Source: Dissertation Abstracts International, Volume: 77-10(E), Section: A.

Thesis (Ph.D.)--North Carolina State University, 2015.

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman equation, which we proceed to prove existence of a classical solution. Our value function is chosen to maximize the expected total discounted HARA utility of consumption. In the Verification Theorem, we prove that the solution to the HJB equation is equal to the value function.

ISBN: 9781339761282Subjects--Topical Terms:

641129
Mathematics education.

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility.
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500 $a Adviser: Tao Pang.
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520 $a We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman equation, which we proceed to prove existence of a classical solution. Our value function is chosen to maximize the expected total discounted HARA utility of consumption. In the Verification Theorem, we prove that the solution to the HJB equation is equal to the value function.
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