Machine Learning in Derivatives Trading : Does it Really Work?

Sammanfattning

The rapid advancement of artificial intelligence (AI) has broadened its applications across various sectors, with finance being a prominent area of focus. In financial trading, AI is primarily utilized to detect patterns and facilitate trading decisions. However, challenges such as noisy data, poor model generalization, and overfitting due to high variability in underlying assets continue to hinder its effectiveness. This study introduces a framework that builds on previous research at the intersection of AI and finance, implemented at AP1. It outlines the benefits and limitations of applying AI to trade derivatives rather than single company stocks and serves as a guide for building such trading algorithms. Furthermore, the research identifies an under-explored niche at the intersection of AI and derivative trading. By developing and applying this framework, the study not only addresses this gap but also evaluates the role of AI algorithms in enhancing derivative trading strategies, demonstrating their potential and limitations within this domain.