Stochastic Calculus for Option Pricing with Convex Duality, Logistic Model, and Numerical Examination

Zheng Cao
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Abstract

This thesis explores the historical progression and theoretical constructs of financial mathematics, with an in-depth exploration of Stochastic Calculus as showcased in the Binomial Asset Pricing Model and the Continuous-Time Models. A comprehensive survey of stochastic calculus principles applied to option pricing is offered, highlighting insights from Peter Carr and Lorenzo Torricelli's ``Convex Duality in Continuous Option Pricing Models". This manuscript adopts techniques such as Monte-Carlo Simulation and machine learning algorithms to examine the propositions of Carr and Torricelli, drawing comparisons between the Logistic and Bachelier models. Additionally, it suggests directions for potential future research on option pricing methods.
期权定价的随机微积分与凸对偶、逻辑模型和数值检验
本论文探讨了金融数学的历史发展和理论构建,深入探讨了二项式资产定价模型和连续时间模型中的随机微积分。该书全面介绍了应用于期权定价的随机微积分原理,重点介绍了彼得-卡尔和洛伦佐-托里切利的《连续期权定价模型中的凸对偶性》一书中的见解。这篇手稿采用蒙特卡罗模拟和机器学习算法等技术来研究卡尔和托里切利的命题,并对 Logistic 模型和 Bachelier 模型进行了比较。此外,它还为未来可能的期权定价方法研究指明了方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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