An analytical approximation of option prices via TGARCH model

An option is a financial contract that can be used to reduce risks in an investment. It is widely known that a fair price of this contract depends significantly on the volatility of an underlying asset price, which may be affected differently by positive and negative information. Therefore, the fair...

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Main Authors: Warunya Hongwiengjan, Dawud Thongtha
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Ekonomska Istraživanja
Subjects:
Online Access:http://dx.doi.org/10.1080/1331677X.2020.1805636
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spelling doaj-6d54af9ac79044f594fde1b2493132112021-06-02T08:05:30ZengTaylor & Francis GroupEkonomska Istraživanja1331-677X1848-96642021-01-0134194896910.1080/1331677X.2020.18056361805636An analytical approximation of option prices via TGARCH modelWarunya Hongwiengjan0Dawud Thongtha1Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT)Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT)An option is a financial contract that can be used to reduce risks in an investment. It is widely known that a fair price of this contract depends significantly on the volatility of an underlying asset price, which may be affected differently by positive and negative information. Therefore, the fair price of option has been studied through various methods. In this research, an analytical formula for European option pricing via the TGARCH model is derived based on an Edgeworth expansion of the density of cumulative asset return. Furthermore, the accuracy of the proposed method is investigated by comparing numerical results with the GARCH model, TGARCH model, analytical approximation via the GARCH model and Monte Carlo technique. The results reveal that in the case of in the money (ITM) with the proposed method performed better than the others. The behaviour of the proposed method is also discussed.http://dx.doi.org/10.1080/1331677X.2020.1805636edgeworth expansionoption pricingthreshold garch (tgarch) model
collection DOAJ
language English
format Article
sources DOAJ
author Warunya Hongwiengjan
Dawud Thongtha
spellingShingle Warunya Hongwiengjan
Dawud Thongtha
An analytical approximation of option prices via TGARCH model
Ekonomska Istraživanja
edgeworth expansion
option pricing
threshold garch (tgarch) model
author_facet Warunya Hongwiengjan
Dawud Thongtha
author_sort Warunya Hongwiengjan
title An analytical approximation of option prices via TGARCH model
title_short An analytical approximation of option prices via TGARCH model
title_full An analytical approximation of option prices via TGARCH model
title_fullStr An analytical approximation of option prices via TGARCH model
title_full_unstemmed An analytical approximation of option prices via TGARCH model
title_sort analytical approximation of option prices via tgarch model
publisher Taylor & Francis Group
series Ekonomska Istraživanja
issn 1331-677X
1848-9664
publishDate 2021-01-01
description An option is a financial contract that can be used to reduce risks in an investment. It is widely known that a fair price of this contract depends significantly on the volatility of an underlying asset price, which may be affected differently by positive and negative information. Therefore, the fair price of option has been studied through various methods. In this research, an analytical formula for European option pricing via the TGARCH model is derived based on an Edgeworth expansion of the density of cumulative asset return. Furthermore, the accuracy of the proposed method is investigated by comparing numerical results with the GARCH model, TGARCH model, analytical approximation via the GARCH model and Monte Carlo technique. The results reveal that in the case of in the money (ITM) with the proposed method performed better than the others. The behaviour of the proposed method is also discussed.
topic edgeworth expansion
option pricing
threshold garch (tgarch) model
url http://dx.doi.org/10.1080/1331677X.2020.1805636
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