One year ago, we reported that in its attempt to calculate the likelihood, and timing, of the next bear market, Goldman Sachs created a proprietary “Bear Market Risk Indicator” which at the time had shot up to 67% – a level last seen just before the 2000 and 2007 crashes – prompting Goldman to ask, rhetorically, “should we be worried now?”
While Goldman’s answer was a muted yes, nothing dramatic happened in the months that followed – the result of Trump’s $1.5 trillion fiscal stimulus which pushed the US economy into a temporary, sugar-high overdrive – aside from the near correction in February which was promptly digested by the market on its path to new all-time highs (here one has to exclude the rolling bear markets that have hit everything from emerging markets to China, to commodities to European banks).
At the time, Goldman wrote that it examined over 40 data variables (among macro, market and technical data) and looked at their behavior around major market turning points (bull and bear markets). Most, individually, did not work as leading indicators on a consistent basis, or they provided too many false positives to be useful predictors. So the bank developed a Bear Market Risk Indicator based on five factors, in combination, that do provide a reasonable guide to bear market risk – or at least the risk of low returns: valuation, ISM (growth momentum), unemployment, inflation, and the yield curve.
And, as Goldman’s Peter Oppenheimer explained, while no single indicator is reliable on its own, the combination of these five seems to provide a reasonable signal for future bear market risk.
All of these variables are related. Tight labour markets are typically associated with higher inflation expectations. These, in turn, tend to tighten policy and weaken expectations of future growth. High valuations, at the same time, leave equities vulnerable to de-rating if growth expectations deteriorate or the discount rate rises, or, worse still, both of these occur together.
To aggregate these variables in a signal indicator, we took each variable and calculated
its percentile relative to its history since 1948. For the yield curve and unemployment
we took the lowest percentiles relative to history, while for the other indicators we took
the highest. We then took the average of these.
Fast forward to today, when one year later Goldman has redone the analysis (and after what may have been some prodding from clients and/or compliance, renamed its “Bear Market Risk Indicator” to “Bull/Bear Market Risk Indicator”) where it finds that the risk of a bear market – based on its indicator – is now not only nearly 10% higher than a year ago, but well above where it was just before the last two market crashes, putting the subjective odds of a crash at roughly 75%, well in the “red line” zone, and just shy of all-time highs.
