Alexey Afanassievskiy, Executive Director and Head of Portfolio Management at Mind Money
Today, the market is changing very fast. New products appear nearly every day, and the main reason for their creation is the ongoing digital transformation. With the appearance of so many new options on the market, investors can doubt: Can we really trust these financial tools?
It is a tricky question. But I will try to answer this in this article. I will delve into the world of, although not innovative, but comparatively new robo-advisors and algorithmic trading. We will explore their benefits, potential traps, and the investment strategies to use these tools.
What is the sense of robo-advising? To be short and simple, robo-advising is like a trade without human participation. But in fact, this solution, although not meaningless, is highly advertised. It is a mass story where a person answers questions about risks and desired profitability. Then, based on algorithms such as Markovitz or other similar methods, a portfolio of several assets is formed. It is not high-tech trading; the principle is more simple, one asset is more reliable, and the other is more profitable. The result is a set of assets, like a basket.
Algorithmic trading (or algotrading) is different from robo-advising. It uses advanced systems to trade at very high speeds, often within a fraction of a second. These algorithms can also analyse vast amounts of market data in real-time and identify patterns. Unlike robo-advising, which is only for stable overtime return or a simple asset allocation, algorithmic trading can focus on catching short-term market inefficiencies. Algotrading can also be used for various trading styles, from day trading to high-frequency trading (HFT).
These products, sometimes perceived as something new, are actually long-standing technologies. Algotrading has been used for decades, and robo-advising was more fashionable about ten years ago. These tools are definitely not something revolutionary or exciting to the world. They are not a panacea but only a combination of different approaches.
With robo-advisors, investors can create a product similar to an "ETF" that will trade and rebalance. As there is no manager but a robot, investors can also save money on low commissions. Nonetheless, many traditional products also have low commissions but more potential for returns. Sometimes, the total fees are reduced, but you still pay the broker for robo-advising, which is configured for a sufficient number of transactions, regardless of your result.
Algorithmic trading can be indeed a profitable opportunity. If with its help investors can find market inefficiencies, then they are able to benefit from the tool. However, it does not guarantee success -- the results heavily depend on many conditions, such as the quality of the algorithms and the market state. It can be more advantageous than traditional trading methods, but do not forget -- it also comes with higher risks. Especially investors should be careful when employing complex, black-box models where the inner workings are not fully understood.
What algotrading and robo-advising have in common is that they both are still dependent on an investment strategy and need a human hand in it. They are not universal pills to high profits, and the success of investing ultimately depends on your decisions. So, in the end they do not guarantee high or even any returns.
As for now, there are not many growth prospects for robo-advising. Although this tool was on hype a few years ago and is predicted to grow not that fast, its era will come to an end one day. The matter is that robo-advising lacks actual users. As its pieces of advice are mostly primitive, it is more targeted to the young and inexperienced layer of investors.
Robo-advising might be better than other risky investments. But here, I want investors to understand that it is just one neutral instrument. They usually cannot make much money on it unless they are lucky.
The algotrading industry is predicted to grow fivefold by 2032. Its development continues, and although AI can become an important component for some tasks, such as predicting certain trends, it is definitely not a breakthrough solution in algotrading.
These AI systems will operate at high speeds, but at the same time, they will be inferior in performance to traditional HFT strategies, which are based on superiority in hardware speed. However, they will coexist with classic HFT.
We can also expect the emergence of strategies based entirely on AI and neural network approaches. But it won't be a direct use of architectures like large language models (LLM).
Robo-advisors and algotrading can have more sense in the investment strategy when used in the long run. For robo-advising, this means regular rebalancing returns over the long run. In algotrading, having a long-term plan can help you neutralise volatile market periods and profit from a long-term plan.
Before actually relying your funds on these technologies, try to test them with the help of historical data. See how the algotrading algorithms would have performed under different market conditions. Similarly, robo-advisors often offer simulation features that allow you to test potential portfolios based on your inputs.
Although these tools are automated, as I have said, your personal input remains important. Robo-advisors typically require you to fill in a questionnaire: Indicate your financial goals, risk tolerance, and time horizon. Make sure these inputs reflect your situation. For algotrading, the strategy you choose should, again, align with your goals and risk tolerance.
In summary, although advanced, both robo-advising and algorithmic trading still need human input to be effective tools. Investors indeed can use them to maximise profits, but they have to approach them carefully, with a clear strategy and a goal.
The technology will develop further, so investors should stay away from systems where they do not understand how things work. This is especially true for complex products with optional designs and an unwritten algorithm.
Simply relying on technology to do the work for you is the wrong approach, whether in life and or in investing and trading. If you have proven tools and an understanding of how to use them, this will certainly help, but these instruments alone do not guarantee profitability. Only your knowledge, efforts, and your own decisions can lead to success.
Better choose tools with a clear prospectus and principle of operation. Again, do not treat any technology like a fashionable and safe thing where a robot will decide everything for a human investor.
Alexey Afanassievskiy is the Executive Director and Head of Portfolio Management at Mind Money, a European investment technology firm. With over 30 years in the stock market and 20 years in algorithmic trading, he is a seasoned expert in financial engineering. Known for his work in developing advanced trading technologies, Alexey has traded across global exchanges and co-created the RTS-standard index, a key benchmark for the Russian stock market. He is a strong advocate for AI in finance and has lectured extensively on algorithmic trading and risk management strategies.
