{"title":"Hedge Error Analysis In Black Scholes Option Pricing Model: An Asymptotic Approach Towards Finite Difference","authors":"Agni Rakshit, Gautam Bandyopadhyay, Tanujit Chakraborty","doi":"arxiv-2405.02919","DOIUrl":null,"url":null,"abstract":"The Black-Scholes option pricing model remains a cornerstone in financial\nmathematics, yet its application is often challenged by the need for accurate\nhedging strategies, especially in dynamic market environments. This paper\npresents a rigorous analysis of hedge errors within the Black-Scholes\nframework, focusing on the efficacy of finite difference techniques in\ncalculating option sensitivities. Employing an asymptotic approach, we\ninvestigate the behavior of hedge errors under various market conditions,\nemphasizing the implications for risk management and portfolio optimization.\nThrough theoretical analysis and numerical simulations, we demonstrate the\neffectiveness of our proposed method in reducing hedge errors and enhancing the\nrobustness of option pricing models. Our findings provide valuable insights\ninto improving the accuracy of hedging strategies and advancing the\nunderstanding of option pricing in financial markets.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Risk Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.02919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Black-Scholes option pricing model remains a cornerstone in financial
mathematics, yet its application is often challenged by the need for accurate
hedging strategies, especially in dynamic market environments. This paper
presents a rigorous analysis of hedge errors within the Black-Scholes
framework, focusing on the efficacy of finite difference techniques in
calculating option sensitivities. Employing an asymptotic approach, we
investigate the behavior of hedge errors under various market conditions,
emphasizing the implications for risk management and portfolio optimization.
Through theoretical analysis and numerical simulations, we demonstrate the
effectiveness of our proposed method in reducing hedge errors and enhancing the
robustness of option pricing models. Our findings provide valuable insights
into improving the accuracy of hedging strategies and advancing the
understanding of option pricing in financial markets.