Automated Day Trading: Feasibility, Challenges, and Profitability as the Core Priority

Reddit users highlight a split on automated day trading feasibility:

• Feasible for simple strategies
  : Users with coding skills report success automating rule-based strategies (e.g., 3/3 conditions for shorting) using tools like Claude [2].
• Profitability is the real barrier
  : Emotions are often an excuse—automation reveals the lack of a profitable system as the core issue (high agreement among users).
• Challenges
  : Discretion (critical for some strategies), coding complexity, and adapting to changing market conditions are key hurdles [5].

• Market growth
  : Algorithmic trading market is projected to grow at a 9.25% CAGR to $33.76B by 2035, with 60-75% of equity volume now algorithmic [1].
• Performance edge
  : AI-driven systems outperformed passive ETFs by 7-9% annually (2023-2024) and avoid emotional pitfalls like over-trading [6].
• Retail vs Institutional gap
  : Retail requires $5k-$20k initial capital vs $250k+ for HFT; institutional players dominate due to better infrastructure/data [4].

Both Reddit and research align on profitability as the top priority—automation solves emotional issues but only if the underlying system is profitable. Simple rule-based strategies are feasible for automation (Reddit + research), but complex/discretionary ones struggle. Institutional success with automation (e.g., Jim Simons’ funds) contrasts with retail challenges due to resource gaps [3].

• Risks
  : Retail traders face high failure rates (profitable systems are rare), coding barriers, and market adaptability issues [8].
• Opportunities
  : AI tools lower coding barriers; momentum strategies (systematic, rule-based) are ideal for automation [9].