What Percentage Of Stock Trades Are Made By Bots And Algorithms?

Zinger Key Points
  • Imagine AI rapidly analyzing data, spotting patterns, making precise predictions and revolutionizing predictive algorithms.
  • That's algorithmic trading, and it isn't new — it dominates global markets, with 60%-73% of equities trading in the U.S. alone.

This year’s market story has been artificial intelligence, illustrated by the recent rush into tech stocks and investor interest in any company working on, or with AI and generative AI.

While many investors think AI is here to stay and with the rise of tools such as OpenAI’s ChatGPT and others, it’s worth asking: could AI become even more prevalent in financial markets?

Algorithmic trading, which relies heavily on programmed instructions, already dominates global markets. It accounts for 60%-73% of equities trading on U.S. markets, 60% in Europe and 45% in the Asia Pacific, according to Select USA.

Algorithmic trading dates back to the 1970s with the introduction of the “designated order turnaround (DOT)” system by the New York Stock Exchange. It marked the first foray into electronic order systems, setting the stage for modern high-frequency trading.

Further advancements in the 1980s and the boom of the internet in the 1990s saw the industry embrace electronic and online trading, facilitating the creation and widespread adoption of algorithmic trading.

Algorithmic trading includes many strategies like execution algorithms, behavior exploitative algorithms, scalping algorithms and predictive algorithms, with each unique approach designed to automatically execute trades based on predetermined conditions.

Read Also: 5 Advanced Micro Devices Analyst Takeaways On AI Event: Is Chipmaker ‘Somewhat Late’ Vs. Rival Nvidia?

So, where does AI fit into this landscape? AI and machine learning could enhance existing algorithmic strategies by integrating predictive models that learn and improve over time.

AI models, theoretically, could analyze vast amounts of data at near real-time speeds, identify subtle patterns and make highly accurate predictions.

For instance, AI could revolutionize predictive algorithms, which try to anticipate future stock behavior. Predictive algorithms can benefit from machine learning techniques like deep learning and neural networks, which are capable of identifying complex patterns and trends in data.

And, again, theoretically, you can use tools like ChatGPT to help code your own algorithm. I tried it myself, prompting the AI bot to create an architecture for identifying undervalued options contracts and placing automatic orders.

Read Next: Let It Do The Work, You Collect The Cash: ‘Shark Tank’ Investor On How To Generate ‘Thousands’ In Passive Income Each Month With AI

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