Retail Traders Are Building AI Trading Bots Once Reserved for Hedge Funds

§ 01 Executive Snapshot

• What: Retail traders are now able to develop AI trading bots that were previously only accessible to hedge funds.
• Who: Retail traders, software engineers (example: Jake Nesler), Coalition Greenwich, and various AI trading tool providers like Composer, Alpaca, and QuantConnect.
• Why it matters: This trend signifies a democratization of trading technology, but raises concerns about risk management and market behavior.

§ 02 Key Developments

• Retail traders can now automate trading strategies without needing extensive coding skills, thanks to tools like Composer and QuantConnect.
• The algorithmic trading market was valued at $12.14 billion in 2020 and is projected to reach $31.49 billion by 2028.
• U.S. listed options volume hit a record of 15.2 billion contracts in 2025, showing increased activity in retail trading.

§ 03 Strategic Context

• Historically, only institutional traders had access to sophisticated trading algorithms, but advancements in AI are now making these tools available to retail investors.
• The trend towards automation in trading is growing, with only 10% of surveyed buy-side traders currently using AI, indicating room for adoption in professional settings.

§ 04 Strategic Implications

• The immediate consequence is that retail traders can now compete on a more level playing field with institutional traders, but this may lead to increased market volatility.
• Long-term, if more traders use similar AI tools without proper risk management, it could result in homogenized trading behaviors that destabilize market dynamics.

§ 05 Risks & Constraints

• There is a significant risk that retail traders may not implement adequate risk controls, leading to detrimental trading outcomes.
• Increased reliance on similar AI models among traders could create correlated behaviors that amplify market reactions during critical times.

§ 06 Watchlist / Forward Signals

• Upcoming developments to monitor include regulatory responses to the rise of automated trading and potential guidelines on risk management for AI in trading.
• The success or failure of retail trading bots will depend on the implementation of effective risk management practices by individual traders.