The Synergistic Impact of AI-Driven Strategies on Retail Options Trading within the European Derivatives Market: A Comparative Analysis of Liquidity and Market Efficiency
Year: 2025
Type: article
Abstract: : This study analyzes the synergistic impact of AI-driven strategies on retail options trading in the European derivatives market through comparative analysis of market efficiency and liquidity compared to the U.S. setting. This study employs the mixed-methods approach, and we analyze quantitative data—daily trades volume, bid-ask spread, and volatility indices (VIX/VSTOXX)—as provided by EUREX, CBOE, CME, and Bloomberg, and qualitative data sourced from industry and scholarly publications. The findings indicate that U.S. markets, characterized by more liquid pools of liquidity (average daily SPX contracts of 1.2 million vs. 300,000 SX5E contracts) and narrower spreads (0.25% vs. 0.40%), enable AI algorithms to calculate more economically than in Europe (CBOE Global Markets, 2024; EUREX, 2024). Further, AI technologies improve price discovery chartered by a rise in options volume of 18% vs. 9% after CPI announcement (Bloomberg, 2024)—and minimize behavioral biases among retail traders. However, structural fragmentation and lower AI take-up in Europe constrain these benefits (Acuiti, 2023). We conclude that AI enhances liquidity exploitation and efficiency on both sides of the Atlantic, but that market structure is once again a significant moderator. We suggest additional research on model-specific performance, sectoral research, stress system risk, and coverage to emerging markets.
Author: Angelica Dzedulionis
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4413431237