How Machine Learning and AI Can Eliminate The Emotional Aspect Of Investing Money

The investment market has gained tremendous popularity over the past couple of years. However, the investment population is not much big and that is because of the age-old practices that conglomerates follow. Another major reason is the emotional aspect — when making an investment, people look at the stock, not the money.

Emotions play a major role in the way we make investments. We tend to choose things that we are emotionally connected with; however, that shouldn’t be the case in buying stock market. In investing, people tend to make decisions for many different reasons; however, whether it’s based on stock analysis, detailed reports, or what they ate for breakfast that morning, there is always emotion involved. But that shouldn’t be the case all the time — especially in investing. Why? The stock you love might not give you the profit you seek, or you might even end up losing a significant of money.

A gerric research says “Which is why only 2% of the entire investing population makes money and around 98% of people end up losing money. If one looks into the deeper aspect of this, 2% of the population uses logic and a very practical approach.”There are many instances when people have made some of the worst investment decision just because they had an emotional thought at the back of their head. But today, technology has evolved to a great extent, and technologies like machine learning, artificial intelligence can help you make the correct investment.

The Rise Of The Machines

The use of technology in investment, not something really new. Over the years, the computer algorithm has helped a lot of investors make investments in hedge funds. According to a source, 25 best-paid hedge fund managers pocketed $13bn in 2015, it was a sum that exceeds the gross domestic products of many nations. And interestingly, most of the big winners relied more than ever on algorithms to make their money.

The critical thing in investing is being able to gauge confidence in the market or certain asset values. And this where computer algorithms come into the scenario. An investor cannot do historical research of a particular stock, but the algorithm can and that makes it easier for an investor to make a decision.

Another example of technology being used in the investment sector is “robo-advisors”. As people seek low-cost, automated investment opportunities, Robo-advisors have become really popular. They are basically investment platforms that use technology like ML and AI to help investors with their money. One just needs to fill some details such as personal information, investment goals and risk tolerance. After that, the platform curates a customised portfolio for the user and manage it. There are platforms available that also give the user access to wealth management services.

oday, these sought after technologies like ML and AI are making a huge impact on the investment sectors. From interpreting human behaviour to making a decision, the financial sector is working day in and out to make the most out of AI and ML — machine learning algorithms are making better financial decisions by eliminating the emotional aspect. 

Each consumer is unique in terms of making investments – it could be the difference in their sector preferences, market cap, the amount of money to be invested, risk profile etc. Thus, a singular strategy may not necessarily work for all consumers. And this where machine learning come in.

A machine uses necessary sets of information and with the help of complex algorithms, it generates a customised portfolio for all consumer. Talking about data collection to curate customised portfolio, many companies rely on the consumer itself, while there are many other companies that keep a close track of the entire industry. Also, not to mention, this customised portfolio is as good as a model portfolio as it takes into account multiple parameters and is not a result of an emotionally induced decision. So, basically, it is the machine that is explaining to the consumer when to invest or buy or sell the stock, ensuring that the consumer makes doesn’t make a wrong move.