TY - JOUR
T1 - Option pricing under GARCH models applied to the SET50 index of Thailand
AU - Arunsingkarat, Somphorn
AU - Costa, Renato
AU - Misran, Masnita
AU - Phewchean, Nattakorn
N1 - Publisher Copyright:
© 2021 World Scientific and Engineering Academy and Society. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Variance changes over time and depends on historical data and previous variances; as a result, it is useful to use a GARCH process to model it. In this paper, we use the notion of Conditional Esscher transform to GARCH models to find the GARCH, EGARCH and GJR risk-neutral models. Subsequently, we apply these three models to obtain option prices for the Stock Exchange of Thailand and compare to the well-known Black-Scholes model. Findings suggest that most of the pricing options under GARCH model are the nearest to the actual prices for SET50 option contracts with both times to maturity of 30 days and 60 days.
AB - Variance changes over time and depends on historical data and previous variances; as a result, it is useful to use a GARCH process to model it. In this paper, we use the notion of Conditional Esscher transform to GARCH models to find the GARCH, EGARCH and GJR risk-neutral models. Subsequently, we apply these three models to obtain option prices for the Stock Exchange of Thailand and compare to the well-known Black-Scholes model. Findings suggest that most of the pricing options under GARCH model are the nearest to the actual prices for SET50 option contracts with both times to maturity of 30 days and 60 days.
KW - GARCH model
KW - Option pricing
KW - Stochastic assets
UR - http://www.scopus.com/inward/record.url?scp=85104636632&partnerID=8YFLogxK
U2 - 10.37394/23206.2021.20.12
DO - 10.37394/23206.2021.20.12
M3 - Article
AN - SCOPUS:85104636632
SN - 1109-2769
VL - 20
SP - 112
EP - 121
JO - WSEAS Transactions on Mathematics
JF - WSEAS Transactions on Mathematics
ER -