Artificial intelligence (AI) is a growing part of stock market trading, but it has not replaced human traders. AI systems read large amounts of price, fundamental, and news data, find patterns, and can execute trades without manual input. They still depend on the data they are trained on and can fail when conditions change. The sections below trace how trading moved from exchange floors to algorithms to AI, and what AI does better and worse than people.
Try it in your own spreadsheet
Get the free MarketXLS sample workbook (.xlsx).
No account needed. MarketXLS live data requires a paid plan. Preview workbook
Explore more videos
Back when there were no computers or internet, trading took place in a chaotic fish market setting. The stock exchanges had active trading floors filled with traders and brokers, and trade took place by shouting or using hand signals to convey their buy or sell orders.
Then came computers that helped change the archaic system of trading on floors of exchanges and made it possible for individual investors to invest in markets on equal footing.
The Algorithmic or Automated Trading Era
Then came the algorithmic or automated trading era wherein computers were programmed to trade on their own if specific criteria were met. Investors and brokers were able to plot their strategies in advance and manage risk with the help of automated stop-loss orders. With the stop-loss feature, investors don’t have to monitor their holdings daily, and it limits an investor’s loss on a security position that makes an unfavorable move.
Automated trading was taken to the next level by allowing computers to trade based on a variety of price signals analyzed in real time. And since computers can execute a limitless number of trades instantly, high-frequency trade to exploit every minute price movement became usual.
Traders could use platforms like MarketXLS to backtest their strategies against historical market data. This helped them to know their strategy’s odds of success and failure of an investment before putting real money into it.
Enter Artificial Intelligence
Automated trading has its imperfections. It’s more conditional; we can tell the computer to do A when B occurs. Computers are programmed by humans, they specify conditions, and in advance, computers perform when those conditions are met. But this pre-programming falls apart during the occurrence of contradictory or unexpected data.
AI trading goes a little further, as its solutions can train on multiple types of data in order to understand markets. Applying AI will help computers in figuring out A and B conditions themselves and with its help the role of human intervention is decreased massively.
“Machine learning is evolving at an even quicker pace and financial institutions are one of the first adaptors,” Anthony Antenucci, vice president of global business development at Intelenet Global Services, recently said.
Human Intelligence Vs Artificial Intelligence
AI trading systems process more data, faster, than a human trader can. They can combine sentiment, technical, and fundamental inputs in one model, though the output is only as good as the data and the model design.
Another benefit that AI has over Human Intelligence is that it is not driven or affected by emotions, unlike human traders. And, it approaches situations with more rationality which helps in exploiting market movements that run counter to underlying data.
AI also protects traders from making fat finger trading mistakes. Fat finger errors may seem harmless but they can have a significant market impact. A huge number of tasks can be performed without human intervention, which was impossible earlier.
How Much Has AI Changed Trading?
AI has changed how many firms research and execute trades. Humans remain a big part of the process, but the role of AI is increasing.
According to a study by a UK research firm called Coalition, 45% of revenues in cash equities trading have resulted from electronic trading. Many investment firms and hedge funds use AI-powered analysis for research and portfolio ideas.
Robo advisors use algorithms to build and rebalance portfolios automatically, and analysts use AI models to help with forecasts.
However, analysts need to be careful since an AI model can only provide accurate predictions when the primary dataset it learns from is diverse, and developers must utilize training methods that don’t leave the AI with blind spots or inherent biases.
The Bottom Line
AI has a large and growing influence on the stock market. Even at this early stage, AI-powered trading tools can reduce the time, in-depth knowledge, and intuition
necessary to build a strong portfolio for the long term. There’s still time in reaching the point where human traders become irrelevant, but today’s AI has closed the gap between casual investors and professional traders considerably. How far AI goes from here is still an open question.
