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Pricing Variance Derivatives Using T...

Zhao, Honglei.

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Pricing Variance Derivatives Using Trees.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pricing Variance Derivatives Using Trees./
Author:	Zhao, Honglei.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	107 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-02, Section: A.
Contained By:	Dissertations Abstracts International80-02A.
Subject:	Applied Mathematics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10808133
ISBN:	9780438241633

Pricing Variance Derivatives Using Trees.
Zhao, Honglei.

Pricing Variance Derivatives Using Trees. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 107 p.

Source: Dissertations Abstracts International, Volume: 80-02, Section: A.

Thesis (Ph.D.)--Stevens Institute of Technology, 2018.

This item must not be added to any third party search indexes.

Variance derivatives are used by practitioners to manage risk related to unexpected movements of the investment assets. Therefore, pricing these financial derivatives accurately and efficiently is important for the well-being of financial markets. In this work we propose a numerical methodology to price many types of variance derivatives. We introduce the concept of generalized realized variance including log-return realized variance, simple-return realized variance, gamma realized variance and corridor realized variance, on which typical financial contracts are built. The derivatives we price include spot-start variance swaps, forward-start variance swaps, variance swaptions, VIX futures and VIX options. Both discretely and continuously sampled generalized realized variance can be approximated by the method proposed. Furthermore, we propose Bermudan variance swaption contracts. These are the counterparts in the variance swap world to one of the most liquid fixed income derivatives: a Bermudan interest rate swaption contract. Our methodology allows us to price such contracts. Finally we show how the methodology may be applied to a local stochastic volatility model. Multiple Numerical experiments comparing with market quotations show that our framework is accurate, fast and efficient.

ISBN: 9780438241633Subjects--Topical Terms:

1669109
Applied Mathematics.

Pricing Variance Derivatives Using Trees.
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245 1 0 $a Pricing Variance Derivatives Using Trees.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 107 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-02, Section: A.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Florescu, Ionut.
502 $a Thesis (Ph.D.)--Stevens Institute of Technology, 2018.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Variance derivatives are used by practitioners to manage risk related to unexpected movements of the investment assets. Therefore, pricing these financial derivatives accurately and efficiently is important for the well-being of financial markets. In this work we propose a numerical methodology to price many types of variance derivatives. We introduce the concept of generalized realized variance including log-return realized variance, simple-return realized variance, gamma realized variance and corridor realized variance, on which typical financial contracts are built. The derivatives we price include spot-start variance swaps, forward-start variance swaps, variance swaptions, VIX futures and VIX options. Both discretely and continuously sampled generalized realized variance can be approximated by the method proposed. Furthermore, we propose Bermudan variance swaption contracts. These are the counterparts in the variance swap world to one of the most liquid fixed income derivatives: a Bermudan interest rate swaption contract. Our methodology allows us to price such contracts. Finally we show how the methodology may be applied to a local stochastic volatility model. Multiple Numerical experiments comparing with market quotations show that our framework is accurate, fast and efficient.
590 $a School code: 0733.
650 4 $a Applied Mathematics. $3 1669109
650 4 $a Finance. $3 542899
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710 2 $a Stevens Institute of Technology. $b Financial Engineering. $3 3181482
773 0 $t Dissertations Abstracts International $g 80-02A.
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793 $a English
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