Hope and fear. These two fundamental emotions govern financial markets. Rising prices cause people to buy into the asset in the hope of further rises or the fear of missing out. Falling prices have the opposite effect. The result being the average investor usually makes nothing. Is there a strategy which can negotiate emotionally driven markets to deliver superior returns?

Notwithstanding the Nobel Prize for efficient markets, the weight of research in behavioural finance points to a market where an understanding of crowd psychology is often more useful than an understanding of the CAPM model. Even the father of modern portfolio theory, Harry Markowitz, ignored his own thesis and crudely split his investments half-and-half between stocks and bonds. He was fearful of missing out on a rising stock market, but equally feared being overexposed in case of a crash.

The great scientist and mathematician Sir Isaac Newton was driven to exclaim that he could calculate the movement of stars but not the madness of men when he lost money in the South Sea bubble burst in 1720. He had invested at the start of the meteoric rise in the company’s share price and exited soon after doubling his money. However, the siren song of rising prices enticed him to re-enter with a substantially larger investment in the hope of repeating his earlier performance. Unfortunately, the bubble burst soon after wiping out his entire investment. How many of us have had similar experiences (although hopefully not on the same scale) where we’ve cashed out early, re-entered near the top and compounded the mistake by holding on to losses for too long? These three linked behaviours are all due to our inherent biases—disposition effect is responsible for the first, herd behaviour, overconfidence and confirmation bias result in the second and regret avoidance leads to the third.

It is the confluence of these emotions and behavioural biases amongst market participants that makes financial markets so treacherous. The difference between failure and success as a trader ultimately boils down to the ability to keep our emotions and biases in check. In essence, the secret of success is ironically becoming a calculating machine in an emotionally driven market. While this is exceedingly difficult for us to follow since our brains are structured for survival on the savannah not on the stock market, it is simple for actual machines.

Even though some still find the idea of machines trading on financial markets futuristic, the era of machine trading has already dawned. There are increasing number of companies (Virtu, Getco being the more famous ones) where all trading is done electronically by computer programs. Algorithmic trading, as it is generically called, is being used to buy and sell assets across equity, bond, commodity and currency markets. Although human programmers are involved in constantly updating the trading algorithms, the trading itself is based on a set of rules and requires no human intervention, thus cutting out the emotional element. Apart from a lack of emotion, computers also have the advantage of being able to process vast amounts of information quickly. So how successful are algorithmic traders?

While there are a variety of algorithmic strategies, they fall into two broad categories—high-frequency trading and systematic trading (this is a gross simplification but the intention of the article is not to go into the nuances of algorithmic trading). The former makes money primarily by utilizing computing speed. Success requires quick information processing and execution. It is similar to a human trader seeing breaking news and reacting to it (more gross simplification, same reason). Systematic trading on the other hand utilizes the information processing capability of computers, crunching large amounts of data on things like cross-market correlations, historical prices, etc., to develop a trading strategy. It is closer to a trader performing financial and technical analysis before taking a position.

Depending on the quality of the algorithm, both these strategies can be very successful. For example, Virtu, the high-frequency trader, had only one loss-making day from 1 January 2009 to 31 December 2013 for a win percentage of 99.92%. Similarly, one of the most successful hedge funds, Renaissance Technologies Medallion fund, which uses systematic trading strategies, has delivered average returns in excess of 35% since it started in 1988. These returns are exceptional. Even Warren Buffet’s record doesn’t come close.

However, this does not imply that algorithmic traders are superior and you should close down your brokerage account and try to figure out how to invest in an algorithmic trading company. For one, the data above is based on top performers. Just like humans, not all algorithmic traders are alike. The other Renaissance funds have not performed as well as Medallion. In addition, computers can also make mistakes. Knight Capital, an HFT, lost $440 million in under an hour due to a software glitch and had to let itself be acquired to avoid bankruptcy.

Moreover, there are two areas where we have the edge over the machines. First, while being swayed by emotion is a weakness, the ability to gauge the mood of the market is a huge strength. Asset prices are ultimately based on real activity and set by humans, which inherently makes them susceptible to crowd psychology. Second, the deterministic nature of algorithms is a weakness. Although they can evaluate and analyse a vast amount of data, they are restricted to a given set of inputs which may not capture all variables affecting prices. Moreover, the relationship between various variables changes unpredictably. What worked yesterday may not work today. Markets are complex systems which are difficult to forecast a great extent into the future. Like the weather, no amount of computing power can provide an accurate forecast a month out. That is why most algorithmic trading strategies have short-term horizons. They may beat the day trader but are unlikely to beat the long-term investor with a multi-year horizon who can spot market turning points. Most systematic traders were blind-sided by the great financial crisis while hedge fund managers like Paulson made billions betting the right way.

While machine trading looks set to grow, it is unlikely to displace the human trader. Analysis, discipline and timing, i.e. waiting for the opportune moment, are all within our ability. After all, it is the human brain that is uniquely capable of recognizing the genius of Steve Jobs or interpreting the stock tips of a shoeshine boy.

Shashank Khare is an investment professional and writer. After studying engineering at IIT-D and business administration at IIM-A, he entered the world of credit derivatives before CDS became a four-letter word. Having successfully batted through the crises, he now indulges his passion for economics, finance and policy.

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