Algorithmic Trading Evolves: More Data is Not Enough
An increasing number of retail investors are outperforming professional returns, while the role of algorithms grows. Compute power alone no longer guarantees an edge.
Individual investors have emerged as a significant force in financial markets, challenging the traditional dominance of institutional players. By 2025, retail investors accounted for a record 20–35% of trading volume, with analyses showing they are outperforming even broadly managed index funds.
This shift is compelling institutional investors to adapt. Up to 74% of institutional investors have started using alternative data within the last five years, and the use of social sentiment data is expected to increase significantly. Investors are broadly seeking signals, monitoring social media discussions alongside traditional financial news and analyst reports.
Algorithmic and high-frequency trading now constitute at least half of U.S. equity trading volume. Even prominent skeptics have acknowledged the importance of machine learning and algorithms. However, with increased competition and growing data volumes, sheer compute power is no longer sufficient to maintain a competitive edge. Industry players often converge on similar strategies and data sources, reducing the discovery of unique signals.
Prospero.ai, initially an app for retail investors, has evolved into an ecosystem aiming to democratize the information used by institutional investors. A community of over 200,000 monthly users provides feedback and behavioral data that refines trading signals. The new Aethon Fund expands this model to an institutional scale, with the goal of publicly sharing valuable signals and supporting investor education.