Bets against market volatility and an excess of confidence among investors might be amplifying the rout beyond rational calculations of the outbreak’s spread
By Jon Sindreu
Forget the 2007 collapse and the dot-com bubble bursting in 2000: The coronavirus has now officially engineered the fastest-ever correction in U.S. stocks from their peak. Investors may take solace in the fact that, if this seems a bit exaggerated, it is because it could be.
On Thursday, the S&P 500 suddenly dropped 4.4%, as fears about the viral outbreak’s impact on the global economy turned into full-blown panic. Equities are now down more than 10% from their all-time high—analysts’ definition of a correction—which was only last week.
The potential hit to corporate earnings as a result of the health crisis shouldn’t be taken lightly, but there are signs that not all of the market’s moves have been caused by such rational calculations.
The Cboe Volatility Index or VIX, also known as Wall Street’s fear gauge, rose above 44 Friday, the highest level since 2011. Most of this simply reflects the scale and speed of the selloff.
Yet it is also reminiscent of the highs recorded by the VIX in February 2018, when a number of exchange-traded vehicles dedicated to profiting from low volatility imploded. Until this week, it was that volatility-fuelled selloff that held the record for the fastest correction.
While no specific volatility product has taken the spotlight this time around, similar forces are likely at play.
Up to the very point when stocks started plummeting on Feb. 20, there were signs that investors were very overconfident. Their earnings expectations were too optimistic and surveys of fund managers suggested that they were foregoing precautionary cash holdings.
A data analysis by market research firm ModernIR suggests that this week’s rout was sparked by a fall in the price of derivatives, and that active fund managers have mostly followed the lead of rules-based traders and algorithms.
Indeed, the options market—on which the VIX is built—was showing signs of investors betting heavily against volatility. Data by the U.S. Commodity Futures Trading Commission showed that positioning against VIX futures was hovering around the same level as in February 2018.
By buying options, investors can protect themselves against the price of an asset going up or down too much, in exchange for paying regular premiums. But because interest rates are so low, most investors have taken to collecting the premiums rather than insuring their portfolios—thus betting against market volatility.
Unlike in home insurance, though, in financial markets the very fact of selling insurance against an event can make that event appear less frequent. That is because banks are the ones usually taking the other side of those trades, and then offsetting them by trading in the actual stock market. This can create a false sense of stability. When some unexpected factor prompts an unraveling of these wagers, investors are forced to sell, thus amplifying drawdowns.
The data was long suggesting that just such a bump was overdue, and that buying some protection was wise. Ray Dalio’s jumbo hedge fund Bridgewater Associates was prescient, having bought roughly $1.5 billion in options as insurance against a near-term equity selloff back in November.
Now, funds that target volatility or follow trends may have already taken the bulk of the hit. Their leverage is down to 20%, from about 60% at the start of the year, estimates Pravit Chintawongvanich, equity derivatives strategist at Wells Fargo.
So there may be a flip-side to this week’s market pain: Corrections exaggerated by technical factors tend to be easy to recover from. Historical data shows that most bear markets don’t start with a bang, but tend to happen over longer stretches.
Of course, the big unknown is how nasty the economic impact of the coronavirus will be. If the disease starts spreading fast in the U.S., the hit to growth may end up justifying the scale of the selloff. But investors also need to bear in mind that recent stock moves don’t offer a strictly rational reflection of the outbreak’s expected magnitude.
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