Humans are emotional creatures. We have an ingrained response to pursue the things that make us feel good, and avoid the things that can harm us. In marketing we often appeal to the emotional side of our customers, playing a little with the promise that humans are not ruthless, calculating automatons - they have sentiments, worries, and aspirations, and we try to find ways to appeal to those. Emotions are part of what make us human, and guide many of the decisions we make in our lives - even when they shouldn't.
In investing, people make decisions for many different reasons, but whether it's based on stock analysis, detailed reports, or what they had for breakfast that morning, there is always an element of emotion involved. It's our "fight or flight" response parading as "fear" and "greed."
Have you ever been to a casino and put money into a slot machine? You pick a machine that’s “hot” or “due for a win,” hoping you’ll be the one to win the jackpot. Emotions are high, so when it doesn’t perform, fear kicks in, and your natural tendency is to play until you win your losses back. On the flip side, if it performs well, overconfidence kicks in and greed takes over. Your emotions are in charge. If enough individuals mimic the decisions of a larger group, "herd mentality" takes over, and the market is pushed one direction or the other (becoming a self-fulfilling prophecy).
Machine Learning to the Rescue
Computer algorithms have been helping hedge funds make their trades for decades now, but deeper machine learning - 'robo investors' - are now gaining traction. Earlier this year, Hong Kong-based startup Aidyia launched a hedge fund run entirely by AI, adding to a growing list of investment groups who rely on machine learning to make a majority of their trades. According to Preqin, a leading source of investment data, approximately 1,300 hedge funds are actively using AI driven investment models, including companies like Sentient Technologies, Two Sigma and Renaissance Technologies.
Companies use artificial intelligence to interpret human behavior for many reasons. In marketing we use smart machines to mimic human behavior, for targeted advertising. In the financial sector, AI can do the opposite - algorithms can help us make better financial decisions by removing the fallibility of human emotion.
For example, the peer-to-peer lending startup company, LendingRobot.com uses unique algorithms to manage loan investments at lightening speeds. They also take care of reinvestment and diversification, so you don't have to. These automated funds allow us to analyze human emotions, and form educated opinions based on trends, forecasting and raw data, not fear and greed.
The sheer amount of market data is too much for any one person to take in and process, and traders are turning to machine learning to guide their portfolios. These programs can analyze years of data, and remove the human biases attached to patterns. The stock market isn't just about numbers - it's also about how we react to the news, other people, and general market noise. Machine trading quiets that noise to make reliable forecasts, analyze stock trends and even include the effect of human emotions on the market - to predict highly accurate outcomes.
Just as simple computers can maintain the temperature in your house, they can also keep unproductive emotions out of investing. Let computers use finely-tuned software to make the decisions and leave high-risk gambling where it belongs.