In investment, over-confidence about our ability to forecast events can be a pitfall. It is very difficult to forecast major macroeconomic events, such as political elections, and even harder to forecast their effect on the stock market. After both the UK’s Brexit vote and Donald Trump’s election, shares, contrary to the expectations of many, rose.
Humans are good at forecasting some things, but bad at forecasting others. The ability to anticipate immediate events is hardwired into us by evolution. The speed and agility with which sportspeople anticipate the motion of a flying ball, for example, is often astounding. Yet when it comes to large-scale, complex systems – such as large weather systems, ecosystems, economies, or financial markets – we may be worse at forecasting than we would like to believe.
A tale of two hikes
Lets take a concrete case. In December 2015 the US Federal Reserve raised interest rates. Over the next two months the S&P 500 fell by 8%. Was this forecastable? After all, standard economic theory tells us that a rise in interest rates increases the cost of borrowing, so may inhibit consumer expenditure and dampen company profits: so it makes sense that a rate hike should produce a downwards market reaction.
In December 2016 the US Federal Reserve raised interest rates again. This time, over the next two months, the S&P 500 rose, by 4%. The market seemed take this hike in its stride, perhaps because investors were pleased the US Federal Reserve considered the economy strong enough to withstand it. So similar macro events (a hike in interest rates by a central bank) in December 2015, and December 2016, had opposite market effects.
Source: Bloomberg, as at 10 May 2017
On 15 March 2017, the Fed hiked rates again. What will happen this time? As at 10 May 2015, when this was written, two months had not quite gone by, but the S&P 500 was up just 2%. If we are honest with ourselves, we may conclude that not only is it difficult to forecast macro events, but it is also difficult to forecast how the market will react to them.
The double pendulum
Schoolchildren are familiar with the simple pendulum, a weight suspended by a rod, swinging to and fro. They are taught about its oscillations in physics class. They may not be quite so familiar with the double pendulum: a pendulum with another pendulum attached to its end.
The double pendulum: an example of a complex system
Give the upper pendulum enough energy, and the lower pendulum can easily flip right over. Its motion is chaotic. Trying to predict the motions of the stock market on the basis of macroeconomic events is rather like trying to predict the motions of a double pendulum: not only must you get the macro forecast right (the upper pendulum), but you must also correctly forecast its effect on the market (the lower pendulum).
Complex systems have elements of both chaos and regularity: they are not easy to predict, and may be highly sensitive to initial conditions. Simplistic models about them are often proved inadequate. In investment, overly simplistic models abound, and this can be a pitfall for investors. When investing, we should try to be humble before the facts, be as objective as we can, and be conscious of our own fallibility.