How Intelligent Machines Are Reshaping Investing

Takeaways

• Machine learning is a type of artificial intelligence (AI) that uses computer algorithms to analyze and learn from data
• Machine learning algorithms can draw insights from data faster and more efficiently than humans and, within set parameters, can make unique insights and observations that could be non-intuitive to a human observer
• Machine learning in investing is helping people find new investment opportunities, removing bias from decision-making and tailoring financial advice to individuals 

Investors are always on the hunt for new ways to make smarter investment decisions. Many rely on “quantitative” strategies, or mathematical models, to predict the success of their decisions. But machine learning in investing offers a novel, more efficient way to make better investment decisions – without investors ever having to lift a finger.  

Just take Q.ai, for example. Q.ai leverages artificial intelligence to maximize investors’ returns and minimize risks by automatically adapting to market conditions.

Download Q.ai for iOS for more investing content and access to over a dozen AI-powered investment strategies. Start with just $100 and never pay fees or commissions.

AI and machine learning: What’s the difference?

“Artificial intelligence” is a catch-all phrase that refers to computer algorithms that make smart decisions. One simple example is the chatbot services that pop up on most websites to offer assistance. Based on the keywords you use, these simple AIs can spit out quick answers to your questions. 

But this basic AI is only the tip of the iceberg. In fact, AI is an entire field of computer science that splinters into sub-specialties, such as deep learning and neural networks. Each type of AI gathers, analyzes and uses data in different ways.

Machine learning is one type of AI that uses complex algorithms to process huge amounts of data quickly. Then, the machine uses this data to make predictions, gather insights and learn. The more information these algorithms process, the more intelligent they become – hence the name “machine learning.” 

Though still new, machine learning has already made advancements in engineering, healthcare and computer science. The financial services industry stands to benefit, too, due to the sheer volume of data generated each day. 

And one area that’s finally getting the attention it deserves, thanks to systems like our very own Q.ai, is the use of machine learning in investing. 

The benefits of machine learning in investing

While machine learning has been around for some time, retail investors have only recently been given the opportunity to take advantage of it. And investors are already seeing the benefits as we discover new and creative ways that machine learning can improve profits and potential. 

Algorithmic trading opportunities

The amount of data that investors need to make truly informed trading decisions is astronomical. But due to the limits of the human brain, investors can only process so much information at once. 

But algorithmic trading can increase an investor’s access to quality market insights. 

As you may guess by the name, algorithmic trading uses complex algorithms to make investment decisions. Unlike humans, these machine learning algorithms can process enormous volumes of data nearly instantly. And because they can learn from this data, they make better informed and more efficient suggestions all the time.

Investors can capitalize on this potential by using machine learning to analyze historical and current market data to find profitable investments. Then, they can use algorithmic insights to recommend investments or even execute trades automatically. 

Increased access to investments

Using algorithmic trading is one way to increase your investment prowess. However, most investors don’t have access to their own machine learning algorithm. 

Fortunately, AI-backed robo advisors like Q.ai are here to help investors take advantage of machine learning. 

Such platforms rely on complex algorithms for their expertise and data crunching abilities to make investment decisions and trade securities. Then, they pass these benefits onto investors in the form of personalized portfolios and passive investment opportunities. 

Many also provide automated financial advice to investors based on brief sign-up surveys. Using information like a person’s age, risk tolerance and financial situation, AI-backed advisors can offer tailored financial recommendations. 

Robo advisors also offer several perks that human-based financial advisors often can’t. For instance, they’re often cheaper than human advisors, and many require a smaller initial investment than large asset management firms. 

Plus, robo-advisors permit 24/7 access to your account, sidestepping the need for office hours and holidays off. (Though, as automated investment services, robo-advisors also don’t require the oversight that your manned portfolio may.) 

Smarter retirement planning

Retirement planning is an enormous reason why many people invest. Many asset managers take a holistic approach to retirement, looking at your age, finances, assets, and earning potential to design your retirement portfolio. Then, they periodically adjust your investments to match your risk tolerance as you age and your financial situation changes over time. 

Just like other human-based investment services, this style of retirement planning can be costly and inefficient. But here, too, machine learning is making strides. 

As artificial intelligence models learn and develop, they’ve become more adept at helping investors build retirement portfolios and enact smart money strategies. Using short surveys, historical market data and predictive analysis, machines can build several personalized retirement plans for a single investor. Then, all that’s left for the investor is to select the plan that suits their needs and fund their investments. 

Decreased human bias in investment decisions 

As humans, we’re innately emotional and, sometimes, make irrational decisions. In investing, this often leads to “avoidant” behaviors, as investors often avoid negative outcomes rather than take the risks needed to see positive ones. 

One excellent example is investor behavior amid market volatility in early 2020. Many investors cashed out their portfolios when the market crashed to avoid losing everything. However, those that dove headfirst into the market crash saw their portfolios recover within less than six months – and then charge straight into a bull market that saw their gains increase even further. 

Investing in quality securities at a discount is the epitome of “buy low, sell high.” But many investors panic during market volatility, leading to poorer outcomes than if they’d left their money alone. 

But machine learning and algorithmic trading models don’t ascribe to human irrationality. As such, they make the perfect impartial judges to guide investors toward smarter investment decisions – whether that’s leaving money in the market, shuffling funds around or even adding to investments during a market crash. 

Untapped investment opportunities

Machine learning algorithms don’t always look for linear relationships in data. That is to say, they don’t stop analyzing data when a straight-line “cause and effect” relationship becomes clear. Instead, they examine the data from all sides, which may lead them to find investments that the market has overvalued or undervalued. 

Due to their unique abilities to identify new relationships, machine learning models are the perfect tools to identify new investment opportunities. Investors can use this potential to gather market insights and make novel investments based on factors like your risk tolerance and financial situation. Over time, these new investment opportunities may even prove profitable. 

The potential for greater returns

There are no guarantees in investing, even when you’re using artificial intelligence. However, when looking at all the benefits we’ve presented thus far, it’s plausible that machine learning in investing may lead to greater investment gains. 

After all, machines can crunch real-time data faster than humans, and use this information to spit out insights and even make trading decisions. And as these models learn from new data, they’re likely to decrease the number of mistakes they make. Not to mention, machine-based investment advisors come at a much smaller price tag than most human advisors. 

When you add these factors together, it’s reasonable to anticipate that machine learning could lead to better portfolio outcomes – at least eventually. And as investors make fewer mistakes, overcome their irrational biases and broaden their horizons with AI, they also increase their potential for success (and wealth). 

Machine learning in investing: a unique chance to improve

Machine learning is upending the investment industry by providing investors with unparalleled access to cheap, efficient investments. As more portfolios, robo-advisors and investment managers move toward machine learning techniques, investors will gain greater access to their benefits. 

If you’re ready to get started with machine learning in investing, look no farther than Q.ai’s own AI-backed platform. With Q.ai, you’ll get access to risk-adjusted portfolios, one-of-a-kind Investment Kits, and even our AI-managed hedging feature, Downside Protection. Best of all, it’s quick and easy to get started.

Download Q.ai for iOS for more investing content and access to over a dozen AI-powered investment strategies. Start with just $100 and never pay fees or commissions.