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JOURNALS // Informatika i Ee Primeneniya [Informatics and its Applications] // Archive

Inform. Primen., 2020 Volume 14, Issue 4, Pages 83–90 (Mi ia701)

Estimating the fair value of options based on ARIMA–GARCH models with errors distributed according to the Johnson's $S_U$ law

A. R. Danilishina, D. Yu. Golembiovskyab

a Department of Operations Research, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, 1-52 Leninskie Gory, Moscow 119991, GSP-1, Russian Federation
b Department of Banking, Sinergy University, 80-G Leningradskiy Prosp., Moscow 125190, Russian Federation

Abstract: In continuation of the article ‘`Risk-neutral dynamics for the ARIMA–GARCH (autoregressive integrated moving average – generalized autoregressive conditional heteroskedasticity) random process with errors distributed according to the Johnson’s $S_U$ law," this paper presents the experimental results for the ARIMA–GARCH (autoregressive integrated moving average – generalized autoregressive conditional heteroskedasticity) models with normal (N), exponential beta of the second type (EGB2), and $S_U$ Johnson (JSU) error distributions. The fair value of European options is estimated by the Monte-Carlo method based on the results obtained in the specified article by using the extended Girsanov principle. The parameters of the ARIMA–GARCH-N, ARIMA–GARCH-EGB2, and ARIMA–GARCH-JSU models were found by the quasi-maximum likelihood method. The efficiency of the resulting risk-neutral models was studied using the example of European exchange-traded options PUT and CALL on basic assets DAX and Light Sweet Crude Oil.

Keywords: ARIMA, GARCH, risk-neutral measure, Girsanov extended principle, Johnson's $S_U$ distribution, option pricing.

Received: 01.10.2019

DOI: 10.14357/19922264200412



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