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  • 标题:A modification term for Black-Scholes model based on discrepancy calibrated with real market data
  • 本地全文:下载
  • 作者:Xiaozheng Lin ; Meiqing Wang ; Choi-Hong Lai
  • 期刊名称:Data Science in Finance and Economics
  • 电子版ISSN:2769-2140
  • 出版年度:2021
  • 卷号:1
  • 期号:4
  • 页码:313-326
  • DOI:10.3934/DSFE.2021017
  • 语种:English
  • 出版社:AIMS Press
  • 摘要:The Black-Scholes option pricing model (B-S model) generally requires the assumption that the volatility of the underlying asset be a piecewise constant. However, empirical analysis shows that there are discrepancies between the option prices obtained from the B-S model and the market prices. Most current modifications to the B-S model rely on modelling the implied volatility or interest rate. In contrast to the existing modifications to the Black-Scholes model, this paper proposes the concept of including a modification term to the B-S model itself. Using the actual discrepancies of the results of the Black-Scholes model and the market prices, the modification term related to the implied volatility is derived. Experimental results show that the modified model produces a better option pricing results when compare to market data.
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