AI Projects Low Odds for Day Trading Success

 

Of course we already knew that the odds of day trading success are low, largely impacted by the low barrier for entry that will result in a higher failure rate than if there was a skill level qualifier to reduce participants.

I asked Google AI on the odds of day trading success, and the result was it stating pretty stark odds of success.

This is what it presented:

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The odds of success in day trading are very low; academic studies and broker data consistently show that 90% or more of individual day traders lose money, and less than 1% to 3% are consistently profitable over the long term. 

The Reality of Day Trading

While day trading can be profitable for a small, highly skilled minority, it is exceptionally challenging for the average person. Most individuals who attempt day trading end up with financial losses, often quickly. 

• High Failure Rate: Studies across various markets (U.S., Taiwan, Brazil) show a failure rate of over 80% within a typical six-month period, with some research on persistent traders (those who trade for more than a year) indicating a loss rate of up to 97%.
• Active Trading Underperforms: The most active individual traders consistently underperform simple, passive buy-and-hold investing strategies (like an S&P 500 index fund) by significant margins after accounting for commissions and fees.
• Few Make a Living: Only a very small fraction, around 4%, manage to make a living from day trading, and even then, the income can be volatile and may not be substantial. 
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Reasons for High Failure Rates

Most traders fail due to a lack of discipline, poor risk management, and unrealistic expectations. 

• Emotional Decisions: Trading based on fear, greed, or excitement ("revenge trading" after a loss) often leads to poor outcomes.
• Lack of Plan/Strategy: Many traders lack a well-defined trading plan with specific entry/exit rules and risk management protocols (like stop-loss orders).
• Insufficient Capital/Knowledge: Success requires substantial starting capital, sophisticated tools, and extensive knowledge and screen time, which most beginners lack.
• High Transaction Costs: Frequent trading generates significant commissions, fees, and taxes, which eat into any potential gross profits.

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Then I asked the odds of using AI for day trading success. The answer was also not very rosy:

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The odds of success using AI for day trading are complex and highly dependent on the user's skill and the quality of the system; off-the-shelf solutions often fail, while custom, professionally developed systems can be highly effective, especially for institutional investors. 

Key Considerations

• Institutional vs. Retail Access: Large financial institutions and hedge funds use sophisticated, multi-million dollar custom AI systems to gain an edge, and a significant portion (60-70% of US equities) of trading volume is already algorithmic. The average retail trader generally does not have access to this level of technology.
• Performance Metrics: AI trading bots often report significantly higher win rates (60-80%) and faster execution speeds than human traders (40-55% win rate), attributed to their ability to process massive datasets 24/7 without emotional influence.
• Risks and Limitations for Average Users:
  • No Guarantee of Profit: Even with AI, there is no guarantee of making money, and losses are possible.
  • Complexity: Truly effective AI requires significant expertise in programming, data analysis, and market dynamics to build and fine-tune; off-the-shelf bots are often overfitted or ineffective.
  • Market Volatility: AI can struggle to navigate extraordinary market events or crashes, which can lead to significant losses if not properly monitored and adapted.
  • The "Edge" Problem: If a highly profitable AI algorithm is shared widely, its edge will quickly be normalized as other market participants adapt or use similar tools.
  • Scams: The market is flooded with scam AI trading apps and services that promise high returns but do not deliver. 
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Summary

While AI demonstrably provides advantages in speed and data processing, successfully leveraging it for day trading as a retail investor is challenging. Success generally requires the user to have substantial knowledge and be capable of developing or heavily customizing their own robust, risk-managed system, not simply buying a generic bot. 

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At least it was being honest about it being very difficult either way.