To a man with a hammer, every problem looks like a nail. This essentially means that people are biased to use the tools they possess to solve problems, regardless of whether such tools are appropriate for the problem at hand. For most analysts working in finance, the “hammer” is forecasting and the “nail” is uncertainty. These analysts try to make precise forecast about macro-economic trends or a company’s earnings and give buy or sell ratings based on this.
To understand the difficulty in making accurate short-term forecast, consider this: Imagine there was a drought in China or India – the two largest rice producers in the world. This could cause food prices to increase since rice is the most popular staple food in the world. A rise in food prices could lead to inflation which will in turn lead to central banks raising interest rates and mortgage payments increasing. This could but pressure on discretionary spending such as restaurants and travel and companies in these industries are slapped with a “sell” rating. Now consider an equally plausible outcome from the drought: rising food prices could lead to a reduction in imported rice which in turn reduces shipping congestion. The price for shipping coal and natural gas falls which leads to deflationary pressures and central banks respond by slashing interest rates. Mortgage payments fall and the consumer has more income for discretionary spending. Companies in the travel and restaurants industries are now rewarded with a “buy” rating by analysts. Which outcome is more likely and where should I put my money?
Amos Tversky – the great psychologist and grandfather of behavioural economics famously said that “reality is not a point but a cloud of possibility”. It is incredibly difficult to make accurate short-term predictions about macro-economic trends or a company’s earnings and acting on such forecast can have bad outcomes considering most analyst forecasts are wrong. Even in the unlikely case that the forecast is correct, it may not be useful if everyone is paying attention to it because its effects will already be priced in. For a forecast to be useful, it needs to be contrarian and correct.
So, what is one to do if forecasting is fraught with so much danger? Focusing on long term results and trying to mute out short term noise is a good start. Also being able to say “I don’t know” when faced with uncertainty. This is the best way to navigate through an uncertain world without transforming into men with hammers, looking for nails.