We have entered a brave new world in investing. Before modern computer technology, if a person wanted to make a trade, it was necessary to call a stockbroker and place an order. Commission rates for selling and buying stocks were set in stone. By today’s standards, these rates were exorbitant because there was not the proliferation of information that is available.
Through the 80s and 90s, online trading happened. As computers became more powerful, high-frequency trading and Forex trading happened. Now, within minutes, a person can be online and trading. They can deposit funds, withdraw money, and scan documents in seconds. And it seems like we are just starting to see the impact that AI technology and machine learning are going to have on investing.
Let’s look at some ways technology is impacting investing now and what the future might bring.
Technology has lowered the barrier to entry for investing
One way that we see this is looking at how technology has lowered the barrier for entry into investing. The number of people who own stock or who trade have increased exponentially over the last few decades.
Thanks to the Internet and the advance of online trading platforms and apps, anyone who wants to invest can. There is no longer the need to interact face-to-face with someone or even talk to them on the telephone.
You can go to a website, download an app, create an account, upload your credit card information, and start investing. Couple that with the fact that there are several investments that can start with small amounts of money and you can see that the barriers to entry into the world of investment have been all but destroyed.
Online trading platforms took off in the United Kingdom and United States during the pandemic when millennial’s decided to start investing in order to increase their income over time. The fact that some trading platforms have no commission fees is what encouraged people to enter the world of investment.
The role of AI in investing
Artificial intelligence has disrupted financial institutions that have been stuck doing things the same way for decades. Many firms are using AI to change the way they analyse securities and the way they make investment decisions. Others see artificial intelligence as a good way of improving core operational processes. Artificial intelligence has shown itself to be an excellent tool that investors can use to minimise errors, improve predictions, and work with greater efficiency.
There are quantitative hedge funds and asset managers that are using AI. The use of AI is growing. Many companies, be them large, medium, or small, are seeing how they can incorporate artificial intelligence technology in their operating models.
Whether a firm is on the buy side or the sell side, they are seeing artificial intelligence as something that can help them manage portfolios, execute trades more efficiently, and provide improved service to their clients.
Even proponents of AI understand that AI has its limits. It cannot supplant investment firms. Artificial intelligence has not and likely will never reach the point where it will replace people completely. It seems that artificial intelligence is highlighting the need to include humans in the process. Humans lead AI-based processes, which lead to increased profitability.
The role of machine learning in investing
Machine learning has gone beyond something that is used for programming self-driving automobiles. It has found its place in the investment management space. And little by little, the true potential of this technology is emerging.
Really, machine learning is a subset of artificial intelligence. Artificial intelligence can pull on massive amounts of data to solve challenging problems. Machine learning complements this ability by allowing a computer to learn without there being an explicit program. This allows computers to make adjustments when new data is presented.
Machine learning is changing investment strategies and how these strategies are administered by managers of all types. For example, machine learning’s ability to build structured data is being used to extract topic and sentiment from text sources, including SEC filings, earnings calls, social media, etc. Again, machine learning does not remove the human equation. Humans are still a vital part of risk management. However, much of the strategy innovation process is becoming automated.
Mobile technology is changing investing
More than three billion people use smartphones around the world for all kinds of things – communication, listening to the music, payments, playing games, etc. Mobile technology has become part of everyday life. The investment community noticed this shift, so now several websites are addressing the investing needs of mobile savvy investors.
One way this has impacted investors for the good is that traders can get up-to-date details regarding their holdings in just a few seconds. Traders can make trades 24 hours a day regardless of where they are.
The low barrier to entry and the use of mobile devices has had some unexpected negative impacts on the markets. Since just about anybody with a smartphone and a few dollars can start investing, there are now several people entering the marketplace with little experience in online investing. This means that seasoned professionals must contend with the knee-jerk reaction of sceptical novices.
Novice traders making knee-jerk reactions are not new. What is new, thanks to mobile technology, is the number of novice investors on the scene. In times past, this would have been limited to just a small portion of the entire trading population. Today, more than half of US households have some investment in the stock market, and it is now estimated that upward of 50 percent of investors are new to the market. This means that these knee-jerk reactions are having a greater impact on share prices and sentiment than they did in the past. The result is increased volatility.
Because there are so many people interested in using mobile solutions for trading, major markets are creating mobile options at a phenomenal pace. These tools are giving users the ability to access the history of a specific holding, charting tools, social media trading feedback, and overall market sentiment instantaneously. This is allowing new and experienced traders to make informed decisions quickly. As a result, the learning curve of investing has reduced dramatically.
Technology and finance are two things that are constantly moving forward. More and more each sector depends on the other. It will be exciting to see how they continue to influence each other moving forward.
