Humans should be great traders
In theory humans should be great at trading. We have an incredible ability to absorb and react to complex data. Our capability for research and analysis is well beyond even the greatest computers. So why are algorithms now outperforming human traders, and are becoming the preference of the large financial institutions ?
One theory is our inability to work in a purely systematic way. We are subject to cognitive biases, which result in irrational behaviour. The instincts can be so strong they overwhelm any natural advantage a human may have over a computer. Simple decision-making rules become almost impossible to follow for a human trader, under certain circumstances.
It is this lack of ability to consistently follow rules, under all circumstances of profit and loss, that make us poor competitors in the financial markets.
In the 1950’s the concept of the Efficient Market Hypothesis was very popular. It was built on a framework of rational decision making based on the availability of news and information relating to investments. However, by the 1980s it became apparent, and more widely accepted, that markets were far from efficient.
Behavioral economics explained that humans are loaded with baggage from the distant past. We are instinctively wired for survival in a hostile environment, where quick thinking was better that thoughtful consideration. Hence we find it very hard to behave in a completely rational way.
This is evident to anyone who has traded the stock market and been on a losing streak. We tend to take higher risks when he have losses, when clearly the rational thing would be to reduce risk at this time. It is all to common for a small loss to result in blowing up a whole trading account, as the trader tries to ‘fight back’ against the markets. This comes from 1000’s of years of evolution, and is an example of cognitive bias at work.
Why we maximise loss, and minimise profit
Prospect theory seeks to explain why investors always seem to get it wrong when face with certain scenarios.
When a position is in a loss, most people show huge reluctance to take that loss. It is a powerful instinct, we do not see a paper loss as real until it has been crystallised. This aversion to the pain of taking the loss, means most people will let a loss run and run, in the hope it will eventually turn profitable. As soon as we crystallise a loss we believe we are ‘accepting defeat’, however it is often the rational thing to cut the loss before it becomes even bigger.
On the other side of the coin, we are not able to manage profits well. As soon as a trade is in profit there is an opportunity to confirm that are theory and analysis was correct, a justification that we have been ‘successful’. Combine this with the fear of regret, if the trade does not stay in profit, and you have a very powerful urge to close a winning trade early.
These two impulsive factors are hard to fight, and it is only through ears of trading experience that we can become more rational in how we manage loss and profit. There will always be a battle between our natural impulses, and rational decision making.
We don't like rules
As we know our instincts often lead us to make irrational decisions, then surely the answer to this is to have a set of rules to avoid poor decision making ?
This is perfectly true, except for the fact that under stressful situations we will almost always override rules in preference to our instincts. If a market is shooting up to the moon, and the trading rules say ‘statistically now is a good time to sell’, we are much more likely to instinctively go with the flow of the rising market, as it seems instinctively correct. This is why large institutions sell when the market spikes up, as the know there will be large volumes of retail traders buying into the market at that time, and gives the institution a perfect opportunity to offload their large position.
By knowing the instinctive flaws of human behavior, we can create automated strategies that work to our advantage. A systematic tradic system can not only mitigate our own flaws, it can also take advantage of the errors other human traders make. Their cognitive bias can be seen as an opportunity for an algorithm to make profit.