量子期权定价与数据分析

IF 3.2 Q1 BUSINESS, FINANCE
Wenyan Hao, C. Lefèvre, Muhsin Tamturk, S. Utev
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引用次数: 5

摘要

本文提出用量子力学技术来处理金融模型。该方法依赖于狄拉克矩阵形式和费曼路径积分方法。这导致我们在这个框架下重新审视Cox-Ross-Rubinstein和Black-Scholes的经典期权定价模型。此外,金融数据根据某个可观察到的范围进行分类,然后使用有监督的机器学习工具进行分析,以识别价格跳跃。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum option pricing and data analysis
The paper proposes to treat financial models using techniques of quantum mechanics. The methodology relies on the Dirac matrix formalism and the Feynman path integral approach. This leads us to reexamine in this framework the classical option pricing models of Cox-Ross-Rubinstein and Black-Scholes. Moreover, financial data are classified with respect to the spectrum of a certain observable and then analyzed to identify price jumps using supervised machine learning tools.
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来源期刊
CiteScore
0.30
自引率
1.90%
发文量
14
审稿时长
12 weeks
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