Value insights: Shall we talk about Twitter?
The on/off Twitter buyout is a curious twist on the (post?) modern valuation theory that, in today’s markets, “things are valuable not based on their cashflows but on their proximity to Elon Musk”.
A well-known UK-based fund manager once said to us: “If you have to give a numerical forecast, never give a date. If you have to give a time-based forecast, never give a number.” A nice quip, highlighting that precise forecasting is notoriously difficult – notwithstanding the legions of economists, strategists, analysts and other purveyors of wisdom whose careers are dedicated to this task.
Even if the outcome of an event were known, meaning you could invest with perfect foresight, the market may react to that outcome in an unexpected way. In other words, it can be very difficult to make a profitable trade in financial markets even when your event-forecast is 100% accurate.
One reason making money from market forecasting is so hard is that the forecast has to be both correct and different from consensus. Since it is extremely difficult to estimate exactly where consensus sits, the whole exercise is massively imprecise. This is particularly apparent in the ‘big picture’ fields of macroeconomics and politics – for example, predicting how the market might respond to election results, interest-rate decisions, inflation and employment data, and other significant one-off events.
We were reminded of this earlier this summer, when JPMorgan’s global strategy team boldly published a playbook for the May print of the US Consumer Price Index (CPI). It offered five possible CPI readings, together with their associated probabilities of occurrence and the predicted price reaction of the S&P500 Index. The actual reading came in at 4%, an event within JPMorgan’s most likely range of outcomes (40% probability), for which it forecast an S&P500 Index rise of 0.75-1.25%. In reality, the market gained just 0.46% at opening and was up 0.69% at close. This was only supposed to happen with a higher CPI print, according to JPMorgan’s playbook. Nice try.
At least JPMorgan was directionally correct (i.e., the stock market went up). Market forecasting can fail even this most basic hurdle, as two memorable events in 2016 highlighted. When the UK voted in June to leave the European Union, the overwhelming consensus was that UK stocks would plummet. In fact, after initial declines, within just one week of the vote both the FTSE100 Index and broader FTSE All-Share Index were trading higher than prior to the referendum result. Both indices rose a further 10% before the year was out.
Even more extreme in some ways was the reaction to the US Presidential election later the same year. A win for Donald Trump was expected to have disastrous implications for value equities generally, and for our own global value portfolios specifically. The reality? A huge rally in cyclical value stocks, from industrials to financials, both of which we had significant exposure to at the time, and substantial outperformance by the portfolio vs. the benchmark during the fourth quarter of 2016.
None of this is to diminish the utility that more company-specific forecasting can provide, for example in relation to financial metrics or corporate actions. But we will leave the macro musings to the professionals. And if we are ever pushed to give a numerical macro forecast, just don’t ask us to put a date on it.
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