Are robots better for making money in investment markets?


GUEST REVIEW: Can AI make better investment decisions than humans? Maybe, but the answer is a bit more complicated than that.

AI is already widely used in investment markets, and we’ve now seen all forms of “algorithmic trading” used by large-scale hedge funds and specialist fund managers. In fact, by some estimates, algorithmic trading accounts for more than 60% of trades on US stock markets alone. The Australian market, being smaller and less liquid, most likely accounts for a lower percentage of algorithmic trading activity, but it is still significant nonetheless.

Despite this trend, there is still a lot of “grey area” when it comes to whether it “outperforms” human decision-making.

Quick and unbiased decision making

The main benefit of relying on AI for investment or decision-making is that the trade is executed, literally, within nanoseconds of the release of price-sensitive information. It’s something a human just can’t do. Besides reaction time, humans have bathroom breaks, long lunches, and sick days. The algorithm, on the other hand, does not.

There are other advantages that an algorithm, or an investment robot or “bot”, has over humans. An algorithm-driven robot shows no emotional bias. Most humans, when making trading and investing decisions, are driven by emotions such as fear, greed, and prejudice. In fact, a recent survey found that 66% of investors regretted an impulsive or emotionally charged investment decision. Alarmingly, 32% admit to having traded while intoxicated.

Some of these biases that we see in humans, which are not prevalent in “robots”, include:

  • Confirmation bias: The tendency of an investor to selectively seek information that supports their existing opinions and to ignore or dispute information that does not support their existing opinions.
  • Anchoring : This is the natural tendency of investors to rely on irrelevant, outdated or incomplete information to make investment decisions.
  • Herd mentality: People are predisposed to a herd mentality. When it comes to investments, that means they often base their decisions on the consensus of a larger group, rather than what makes the most sense. As the smartest investors in the world know, it’s not the crowd that makes money, it’s the individuals that make it.
  • Loss aversion: Psychologists tell us that there is a natural tendency among investors to prefer avoiding a loss to realizing again. An algorithm knows that, logically, the financial result is the same. However, humans tend to avoid taking a loss, even though there are times when it defies logic. A common example is investors reviewing their investment portfolio and refusing to sell their “losers” but insisting on keeping their “winners”. No logic justifies a decision on this basis.

Investment Decisions vs Trading Decisions

Is algorithmic trading relevant for investment decisions, as opposed to trading decisions? Evidence suggests that many of the features and benefits of AI inherent in high-frequency algorithmic trading are relevant to investment decision-making.

The elimination of emotional conflicts, the speed of execution and the ability to quickly and objectively analyze and assimilate large amounts of investment-related data are among the main advantages of “robots” used in investment decisions. These data points can include macroeconomic statistics such as inflation, interest rates, employment figures, commodity price movements, currency and leading GDP indicators such as GDP surveys. consumer confidence and job vacancies. All of these factors have an impact on stock price movements in the short term, as well as in the medium and long term.

That said, investment decisions have a longer time horizon and may have different objectives taking into account certain factors, such as tax treatment, liquidity needs, capital security and regulatory issues. In other words, investment decisions are usually based on qualitative factors while business decisions rely more on quantitative analysis.

So the answer to AI being “better for humans” when it comes to long-term investing is not as clear cut as stock trading, where AI is already firmly entrenched.

Put the augmented in AI

Maybe if not artificial intelligence, then augmented intelligenceis the future role of algorithms in investment decision making.

In this way, a degree of collaboration between artificial intelligence and human intelligence, without replacing human intelligence, could very well be the way of the future when it comes to scaling an outlet effective investment decision. As the saying goes, “Money never sleeps”.

About the Author

Michael Kodari is the founder and CEO of Kodari Securities (KOSEC), a leading provider of investment services to a large and diverse clientele, including corporations and ultra-high net worth individuals. With over a decade of fund management and stock brokerage experience, Michael has worked with some of the world’s leading value investors and financial institutions. A philanthropist and leading stock market expert, CNBC Asia called him “the most brilliant wealth management entrepreneur of the 21st century.”


KOSEC – Kodari Securities is a leading provider of investment services to a large and diverse clientele, including corporations and ultra-high net worth individuals. Established in 2010, KOSEC exists to give investors the best investment opportunities, knowledge, tools and resources, as well as to provide the highest level of product/service offerings to help them make better and better investment decisions. more enlightened.

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