One Big Reason Traders May STILL Be Underestimating Coronavirus Risks
One Big Reason Traders May STILL Be Underestimating Coronavirus Risks
While each of the above events are heartbreaking in their own way, the biggest concern for traders this week will be the spread of coronavirus. Markets have seemingly woken up to the risks posed by the virus over the weekend, with major stock indices in Europe and the US shedding 1-2% across the board, gold on track for its highest close since 2013, and risk sensitive currencies like the Australian and New Zealand dollars dropping about -1% against “safe havens” like the Japanese yen and Swiss franc.
Despite today’s dramatic market moves, there’s still a risk that traders are dramatically underestimating the risks posed by coronavirus.
The (Apocryphal) Invention of Chess
In the words of US physics professor Al Bartlett, “The greatest shortcoming of the human race is our inability to understand the exponential function.” In their day-to-day lives, most people are accustomed to linear functions (y=mx) in mathematical parlance), but relatively little experience with fast-growing exponential functions (y=mx).
A classic example of underestimating exponential growth comes from the (likely apocryphal) story of the invention of chess. India’s emperor, enamored with the game, asked the inventor to name his reward for creating such a compelling pastime. The inventor asked for “just” one grain of rice on the first square of the chessboard, two grains on the next square, four grains on the following square, and so on, with the grains of rice doubling on each of the 64 squares (y=264). The emperor, failing as many of us do to comprehend the exponential function, agreed instantly. After running the numbers, his treasurer informed him that he had just agreed to grant the inventor an incomprehensible 18 quintrillion grains of rice, equivalent to centuries of rice production!
Official Coronavirus Data Paints a Grim Picture Moving Forward
Viruses spread by the same general principle: One person can infect multiple people, who can in turn infect multiple people and so on. Recent reports that this particular strain of coronavirus may be transferred during its incubation period, which lasts up to 14 days and may present no symptoms whatsoever, suggests that the outbreak is likely to get worse before it gets better. The inauspicious timing of the outbreak during the travel-heavy Chinese New Year celebration could further accelerate the spread of the disease across the country and beyond in the coming weeks.
The below table shows the confirmed number of coronavirus cases from Chinese authorities, and the daily percentage growth rate in green-shaded cells. With anti-government backlash growing in China, it’s worth noting that authorities may have an incentive to downplay or underreport the spread of the disease, so these numbers may be viewed as a minimum number of actual cases. The blue-shaded cells simply take a naïve average of the daily growth rate in coronavirus cases over the last week and projects forward the number of infections over the next two weeks based on that average:
Source: Chinese National Health Commission, GAIN Capital
Please note that I sincerely hope that the spread of the disease is brought to a halt immediately, and I’m by no means an epidemiologist (though some epidemiological models are even more dire). That said, if the virus continues to spread at anywhere near the same rate over the next week or two, traders are clearly underappreciating the risks to global markets. For reference, the 2003 SARS outbreak ultimately infected nearly 8,100 people, killed 800, and is estimated to have shaved 1-2% of China’s global GDP growth. At its current growth clip, coronavirus could exceed the SARS infection figures by Wednesday and more than double them by Friday.
We’ll focus on the market implications and specific trading opportunities as the week develops, but it’s clear that like the credulous Indian emperor, traders may still be underestimating coronavirus’s potential to drive massive market volatility.
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