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Optimal Hedging Under Time-Scaled Fractional Ornstein-Uhlenbeck Volatility.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Optimal Hedging Under Time-Scaled Fractional Ornstein-Uhlenbeck Volatility./
作者:	Yan, Guangchu.
面頁冊數:	1 online resource (87 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-10, Section: A.
Contained By:	Dissertations Abstracts International84-10A.
標題:	Finance. -
電子資源:	click for full text (PQDT)
ISBN:	9798379419981

Optimal Hedging Under Time-Scaled Fractional Ornstein-Uhlenbeck Volatility.
Yan, Guangchu.

Optimal Hedging Under Time-Scaled Fractional Ornstein-Uhlenbeck Volatility. - 1 online resource (87 pages)

Source: Dissertations Abstracts International, Volume: 84-10, Section: A.

Thesis (Ph.D.)--University of California, Irvine, 2023.

Includes bibliographical references

In recent years, there has been growing interest in modeling volatility as a stochastic process driven by a non-Markovian process, due to empirical evidence showing that the autocorrelation function of volatility decays as a power function. This paper investigates the use of a time-scaled fractional Ornstein-Uhlenbeck process to model volatility and applies this model to derive an optimal delta hedging strategy. By incorporating non-Markovian processes into our model, we aim to provide insights into the behavior of volatility in financial markets and explore potential benefits for option pricing and risk management strategies.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379419981Subjects--Topical Terms:

559073
Finance.
Subjects--Index Terms:

Optimal hedgingIndex Terms--Genre/Form:

554714
Electronic books.

Optimal Hedging Under Time-Scaled Fractional Ornstein-Uhlenbeck Volatility.
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504 $a Includes bibliographical references
520 $a In recent years, there has been growing interest in modeling volatility as a stochastic process driven by a non-Markovian process, due to empirical evidence showing that the autocorrelation function of volatility decays as a power function. This paper investigates the use of a time-scaled fractional Ornstein-Uhlenbeck process to model volatility and applies this model to derive an optimal delta hedging strategy. By incorporating non-Markovian processes into our model, we aim to provide insights into the behavior of volatility in financial markets and explore potential benefits for option pricing and risk management strategies.
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538 $a Mode of access: World Wide Web
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653 $a Optimal hedging
653 $a Autocorrelation function
653 $a Volatility decays
653 $a Power function
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