Scholarlink

<p>The concept of information cost has evolved over time and has been applied to various decision problems, including currency option pricing. This research delves into the impact of dynamic information costs on the currency option pricing model, innovatively developed by Dammak et al. (J Econ Asymmetries 28:e00337, 2023a <a href="https://doi.org/10.1016/j.jeca.2023.e00337">https://doi.org/10.1016/j.jeca.2023.e00337</a>, Global Finance J, 2023b <a href="https://doi.org/10.1016/j.gfj.2023.100897">https://doi.org/10.1016/j.gfj.2023.100897</a>). We utilize the Differential Evolution algorithm to calibrate the novel information cost parameters, using data from various currency call options pairs from January 1, 2018, to November 24, 2022. A satisfactory approximation of real market currency option prices is achieved through this methodology. Additionally, we harness the power of machine learning to predict the values of effective domestic and foreign interest rates within a changing information cost landscape. By partitioning our dataset into training and test sets, our study demonstrates that the new model, incorporating dynamic information costs, generates more accurate and stable pricing outcomes. This research marks a substantive contribution to the evolving field of option pricing, emphasizing the potential of machine learning techniques in solving complex financial problems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Enhancing Currency Option Pricing Models: Incorporating Dynamic Information Costs and Machine Learning Techniques

  • 期刊论文

  • 发表日期：

    2025年5月3日

查看全文
  • Wael Dammak,
  • Ali Ben Mrad,
  • Christian de Peretti,
  • Salah Ben Hamad

摘要

The concept of information cost has evolved over time and has been applied to various decision problems, including currency option pricing. This research delves into the impact of dynamic information costs on the currency option pricing model, innovatively developed by Dammak et al. (J Econ Asymmetries 28:e00337, 2023a https://doi.org/10.1016/j.jeca.2023.e00337, Global Finance J, 2023b https://doi.org/10.1016/j.gfj.2023.100897). We utilize the Differential Evolution algorithm to calibrate the novel information cost parameters, using data from various currency call options pairs from January 1, 2018, to November 24, 2022. A satisfactory approximation of real market currency option prices is achieved through this methodology. Additionally, we harness the power of machine learning to predict the values of effective domestic and foreign interest rates within a changing information cost landscape. By partitioning our dataset into training and test sets, our study demonstrates that the new model, incorporating dynamic information costs, generates more accurate and stable pricing outcomes. This research marks a substantive contribution to the evolving field of option pricing, emphasizing the potential of machine learning techniques in solving complex financial problems.