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Forecasting
July, 2019
“If you spend more than 13 minutes analysing economic and market forecasts, you’ve wasted 10 minutes”.
This is a quote from Peter Lynch, the Fund manager of Fidelity’s Magellan fund. During his tenure, the fund had an annualised return of 30% over a 13-year period. While this quote carries a hint of hyperbole, its message is clear: spending too much time on economic and market forecasting is not a good use of one’s time. There is however only one scenario when looking at certain economic metrics can be useful – when the metrics look abnormal and most importantly, linking this abnormality back to the fundamentals of a business.
What do we mean by abnormal? This is when a metric is at historical highs or lows. Over the last 5 years, we have seen three examples of this – the oil price near all-time highs above $100 a barrel, oil selling at lows of about $30 a barrel and interest rates in most developed countries currently at all-time lows.
At the time crude oil was trading above $100 in 2014, analysts and commentators were extrapolating prices from the recent past into the future. When Crude oil was trading at all time lows of $30 a barrel, analysts were predicting that prices will fall as low as $10 a barrel. Of course no one actually knows where oil prices will be in the future. This is not because of a lack of effort or intelligence from the analysts but simply that prices are affected by a multitude of variables that interact in complex ways making prediction impossible.
An alternative to making precise predictions is simply to assume that prices will revert to normal levels. For example, if crude oil is at $30 a barrel, the earnings of oil companies will be low so the price to earnings multiple will be artificially high and the stock will look expensive. With oil at $100 a barrel, airlines will have higher costs and report lower profits so again, the price to earnings multiple will look artificially high. In both of these examples, it is important to assume that oil prices will revert to normal historical levels in order to understand how cheap or expensive a sector of the economy truly is.
Using normalised earnings is important when researching cyclical industries whose performance depends on an externality that cannot be accurately forecast. How have we used this practically at Tacit? Our current aversion to highly indebted companies is a good example. With years of record low interest rates, corporate debt to GDP levels in the developed world have increased dramatically, however default rates remain artificially low. Many of these companies are being kept afloat by low interest rates. However, if interest rates are to revert to historical levels, default rates will increase dramatically.
Peter Lynch was right in his assessment of the importance of economic and market forecasts – they are largely unhelpful except for when the numbers look abnormal.