Modeling SSE 50 ETF Returns and Option Pricing: Evidence from a Score-Driven GARCH-Jump Approach

Mingfu Shi, Chuanhai Zhang (), Qingqing Chen and Wolfgang Karl Härdle
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Mingfu Shi: School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, China
Chuanhai Zhang: School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, China
Qingqing Chen: School of Marxism, Zhongnan University of Economics and Law, Wuhan 430073, China
Wolfgang Karl Härdle: School of Business and Economics, Humboldt University of Berlin, 10099 Berlin, Germany

Mathematics, 2025, vol. 13, issue 20, 1-21

Abstract: Modeling stock returns and option pricing in the presence of jumps remains a central challenge in financial economics. This paper employs a novel score-driven GARCH-jump model to analyze SSE (Shanghai Stock Exchange) 50 ETF returns and option pricing. The main findings are as follows. First, we use 50 ETF spot returns to estimate conditional volatility and jump intensity, and find that the SDSDJ (score-driven separate dynamic jumps) model significantly outperforms conventional GARCH-jump models in model fitting. Second, we evaluate both in-sample and out-of-sample pricing performance using data from 50 ETF options, and find that the SDSDJ model achieves the lowest in-sample pricing error among all benchmarks, while its simplified variant—the SDJ (score-driven jumps) model—delivers the most accurate out-of-sample results. Third, the superior pricing performance of both models is robust across different levels of moneyness and DTM (days-to-maturity).

Keywords: SSE 50 ETF option; score-driven time series models; option pricing; jumps (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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