Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process

This paper focuses mainly on issues related to the pricing of American options under a fuzzy environment by taking into account the clustering of the underlying asset price volatility, leverage effect and stochastic jumps. By treating the volatility as a parabolic fuzzy number, we constructed a Levy...

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Main Authors: Zhang, H., Watada, J.
Format: Article
Published: Institute of Electronics, Information and Communication, Engineers, IEICE 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049399168&doi=10.1587%2ftransinf.2017EDP7236&partnerID=40&md5=0233d1bf1a07e145ab229697bef73074
http://eprints.utp.edu.my/21467/
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spelling my.utp.eprints.214672019-02-20T01:59:04Z Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process Zhang, H. Watada, J. This paper focuses mainly on issues related to the pricing of American options under a fuzzy environment by taking into account the clustering of the underlying asset price volatility, leverage effect and stochastic jumps. By treating the volatility as a parabolic fuzzy number, we constructed a Levy-GJR-GARCH model based on an infinite pure jump process and combined the model with fuzzy simulation technology to perform numerical simulations based on the least squares Monte Carlo approach and the fuzzy binomial tree method. An empirical study was performed using American put option data from the Standard & Poor's 100 index. The findings are as follows: under a fuzzy environment, the result of the option valuation is more precise than the result under a clear environment, pricing simulations of short-term options have higher precision than those of medium- and long-term options, the least squares Monte Carlo approach yields more accurate valuation than the fuzzy binomial tree method, and the simulation effects of different Levy processes indicate that the NIG and CGMY models are superior to the VG model. Moreover, the option price increases as the time to expiration of options is extended and the exercise price increases, the membership function curve is asymmetric with an inclined left tendency, and the fuzzy interval narrows as the level set α and the exponent of membership function n increase. In addition, the results demonstrate that the quasi-random number and Brownian Bridge approaches can improve the convergence speed of the least squares Monte Carlo approach. © Copyright 2018 The Institute of Electronics Information and Communication Engineers. Institute of Electronics, Information and Communication, Engineers, IEICE 2018 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049399168&doi=10.1587%2ftransinf.2017EDP7236&partnerID=40&md5=0233d1bf1a07e145ab229697bef73074 Zhang, H. and Watada, J. (2018) Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process. IEICE Transactions on Information and Systems, E101D (7). pp. 1843-1859. http://eprints.utp.edu.my/21467/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description This paper focuses mainly on issues related to the pricing of American options under a fuzzy environment by taking into account the clustering of the underlying asset price volatility, leverage effect and stochastic jumps. By treating the volatility as a parabolic fuzzy number, we constructed a Levy-GJR-GARCH model based on an infinite pure jump process and combined the model with fuzzy simulation technology to perform numerical simulations based on the least squares Monte Carlo approach and the fuzzy binomial tree method. An empirical study was performed using American put option data from the Standard & Poor's 100 index. The findings are as follows: under a fuzzy environment, the result of the option valuation is more precise than the result under a clear environment, pricing simulations of short-term options have higher precision than those of medium- and long-term options, the least squares Monte Carlo approach yields more accurate valuation than the fuzzy binomial tree method, and the simulation effects of different Levy processes indicate that the NIG and CGMY models are superior to the VG model. Moreover, the option price increases as the time to expiration of options is extended and the exercise price increases, the membership function curve is asymmetric with an inclined left tendency, and the fuzzy interval narrows as the level set α and the exponent of membership function n increase. In addition, the results demonstrate that the quasi-random number and Brownian Bridge approaches can improve the convergence speed of the least squares Monte Carlo approach. © Copyright 2018 The Institute of Electronics Information and Communication Engineers.
format Article
author Zhang, H.
Watada, J.
spellingShingle Zhang, H.
Watada, J.
Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process
author_facet Zhang, H.
Watada, J.
author_sort Zhang, H.
title Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process
title_short Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process
title_full Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process
title_fullStr Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process
title_full_unstemmed Fuzzy Levy-GJR-GARCH American option pricing model based on an infinite pure jump process
title_sort fuzzy levy-gjr-garch american option pricing model based on an infinite pure jump process
publisher Institute of Electronics, Information and Communication, Engineers, IEICE
publishDate 2018
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049399168&doi=10.1587%2ftransinf.2017EDP7236&partnerID=40&md5=0233d1bf1a07e145ab229697bef73074
http://eprints.utp.edu.my/21467/
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