Looking at Coronavirus Cases per Million, by Country

Further to yesterday’s Coronavirus (COVID-19), post, Tracking the Trajectory and Peak of Coronavirus Cases, I want to make sure we are thinking not just in terms of the absolute number of confirmed cases, but also cases per million. 

The graphic below highlights the countries which have been hit hardest on a per capita basis.  Using this criterion, Iceland is the country where the coronavirus is most prevalent, followed by Italy, South Korea, Iran, China and Switzerland.  These six countries stand out as having passed an inflection point.  Given the data out of Western Europe in the past 48 hours, it appears as if Spain, Sweden, France and Denmark are not far behind.  The U.S. currently ranks 41^st in terms of cases per million, with just 1/100^th of the penetration in Iceland.

[source(s):  Wikipedia, VIX and More]

Assuming the distribution of new cases continues to trace a parabolic path, being able to reasonably estimate the terminal penetration rate – which will no doubt vary by country – could help to set expectations about the progress and timeline of new cases.

Finally, to follow up on yesterday’s post, I am now dating the first day of 100 new cases in the U.S. at March 7^th.  Using the 8-14 day window for 100 new cases to peak new cases means the U.S. could see peak new cases in the March 15^th – March 22^nd time frame, with an outside shot of the peak extending out to March 29^th.  Of course, this projection are merely an extrapolation from the experience in other countries and will be largely dependent upon the rate at which testing is ramped up in the U.S.

Further Reading:

Tracking the Trajectory and Peak of Coronavirus Cases

Volatility During Crises

Forces Acting on the VIX

A Conceptual Framework for Volatility Events
Bird Flu Stocks and Volatility
VIX Sets New Record with Nine Up Days in a Row
Fear Poll: Fed/QE, Ebola and Technicals Top Worry List

HOGS Gets Slaughtered

For those who may be interested, you can always follow me on Twitter at @VIXandMore

Disclosure(s): none

Tracking the Trajectory and Peak of Coronavirus Cases

I have seen a lot written about the Coronavirus, a.k.a. COVID-19, but I have yet to see any informed discussion about the trajectory of cases in various regions, the cycle time to peak new cases or meaningful predictions about the future course of the spread of the virus.

So here are some thoughts on the subject, using historical data from Wikipedia that is more standardized in time and collection methodology than any other data I have been able to find on the Web.  First, I examined the entire history of case data by country and found inflection points that roughly correspond to 10 new cases and 100 new cases per day.  As identification of initial cases is somewhat problematic given the variable protocols for testing, availability of testing kits, timing of nearby positive cases, etc. I elected to use the 100 new cases per day threshold.

It turns out that there have been seven countries so far that have logged 100 new COVID-19 cases in a single day.  In order of reaching that 100 new cases threshold, they are:  China (January 21^st), South Korea (February 21^st), Italy (February 26^th), Iran (February 27^th), France (March 5^th), Germany (March 6^th) and Spain (March 6^th).  The U.S. has come close to the 100 new case threshold and may indeed hit that mark today or tomorrow.

The graphic below shows the daily number of new cases in each of the seven 100+ new case countries.  Note that it is reasonable to expect some sort of parabolic pattern for new cases with a steep jump in new cases that eventually flattens out, peaks and declines in a similar fashion.  This pattern probably would have been the case in China, except that on February 10^th, China changed the methodology for counting new “confirmed” cases from relying strictly on the basis of a positive result from a lab testing kit to cases that included patients where CT scans for pneumonia allowed for a “confirmed” case clinical diagnosis for likely COVID-19 cases without having to wait for a lab test and results.

[source(s):  Wikipedia, VIX and More]

To summarize the data in the graph, three of the four countries that are at least ten days from the initial 100-case day have seen what appears to be a peak in new cases.  In China, it was 22 days from 100 cases to peak new cases, though it is possible that peak new cases might have been 14 days if China had not expanded the methodology for defining new cases to include a clinical diagnosis.

In South Korea, a concerted effort to ramp up testing as quickly as possible is probably responsible for the fact that South Korea saw a peak in new cases just 9 days after the first 100-case day.

While the peak in new case data in Iran should be considered provisional, the current peak in new cases was only 8 days after the first 100-case day, perhaps aided by the steep trajectory in new cases during the first five days.

Italy is the outlier in that there are no signs of a peak some ten days after the first 100-case day, though it is reasonable to expect that the newly implemented national lockdown and public gathering measures will help to slow the rate of new cases going forward.

The remaining three Western European countries – France, Germany and Spain are only 3-4 days into their post-100 timeline, so it is too early to talk about a peak.

The first quick takeaway is that the time from 100 new cases to peak new cases seems to cluster around 8-14 days or perhaps 8-22 days if you overlook the changes in the methodology for counting new cases in China.

Second, with the U.S. new case count hovering just below 100, it is reasonable to expect that the 8-14 day window for new cases will also apply to the U.S. putting a likely peak count in the March 17^th – March 24^th time frame, with an outside shot of the peak extending out to April 1^st.  This assumes, of course, that the U.S. follows a similar trajectory to the other countries.  Along those lines, it will be interesting to see if Italy’s new cases peak during the next week.

Obviously, there are a number of factors that can affect how successful a country can be in containing the COVID-19 outbreak, conduct an appropriate number of tests and other factors. Japan, for instance, had its first case almost two months ago and has yet to approach 100 new cases in a day.

More to come on the COVID-19 global outbreak, the VIX, volatility and more.

Further Reading:

Volatility During Crises

Forces Acting on the VIX

A Conceptual Framework for Volatility Events
Bird Flu Stocks and Volatility
VIX Sets New Record with Nine Up Days in a Row
Fear Poll: Fed/QE, Ebola and Technicals Top Worry List

HOGS Gets Slaughtered

For those who may be interested, you can always follow me on Twitter at @VIXandMore

Disclosure(s): none

The Year in VIX and Volatility (2015)

Every year one of my most-read posts is my annotated overview of the year in VIX and volatility.  Now that I have been doing this for the past eight years, the aggregated view of volatility from 2008 to the present makes for a fascinating concise history not just of volatility, but more broadly of the financial markets and of economic activity in general.

The graphic below captures most of the highlights from 2015 and from a volatility perspective, it was a year for the record books.  During August we saw the largest one-week VIX spike (+113%) that resulted from unprecedented back-to-back days of VIX spikes of more than 45%!  The cumulative jump in the VIX pushed the VIX to a high of 53.29 – the only time outside of the 2008-09 financial crisis since the launch of the VIX in 1993 that the VIX has topped 50.

[source(s): VIX and More]

While most investors pointed to China as the proximate cause of the record VIX spike(s), a VIX and More fear poll one week after the big VIX spike also highlighted “market structural integrity (HFT, flash crash, exchange issues, etc.)” as almost on par with China concerns, with “market technical factors (breach of support, end of trend, etc.)” not that far behind.

The balance of the year saw a wide variety of events that moved the markets, including the Fed’s first rate hike in nine years; crude oil plummeting to $34/bbl.; shock waves in the high-yield bond market due to low oil prices; chilling terrorist attacks in Paris and in California; Puerto Rico announcing it will default on some of its debt; turmoil in the currency markets when the Swiss National Bank ended the peg of the Swiss franc to the euro; a dramatic boom-bust cycle in Chinese A-shares – and a flurry of ineffective interventions on the part of the Chinese government to restore stability; a proxy war between Saudi Arabia and Iran in Yemen; and the European Central Bank committing to $1.2 trillion of quantitative easing.

As noted previously, even with all of the volatility, Every Single VIX ETP (Long and Short) Lost Money in 2015.

Finally, since 2011, I have been maintaining a proprietary Macro Risk Index that measures volatility and risk across a broad range of asset classes, including U.S. equities, foreign equities, commodities, currencies and bonds.  In 2015, the Macro Risk Index was consistently higher than it has been during any year since the 2011 inception.

What does high volatility in 2015 mean for 2016?  During the past two weeks, Barron’s published two opposing (but not necessarily inconsistent) perspectives on volatility in 2016.  For the case for rising volatility and what to do about it, try Jared Woodard’s Prepare for Rising Volatility in 2016.  I provide the contrarian point of view in The Case Against High Stock-Market Volatility in 2016.

Related posts:

• The Year in VIX and Volatility (2014)
• The Year in VIX and Volatility (2013)
• The Year in VIX and Volatility (2012)
• The Year in VIX and Volatility (2011)
• The Year in VIX and Volatility, 2010
• Chart of the Week: The VIX and Volatility in 2009
• The Year in Global Volatility (2008)
• Last Two Days Are #5 and #6 One-Day VIX Spikes in History
• China Growth and Market Structural Integrity Top List of Fear Poll Concerns
• Every Single VIX ETP (Long and Short) Lost Money in 2015

Disclosure(s): net short VIX at time of writing

CBOE Risk Management Conference Update

Today was the first full day of the CBOE Risk Management Conference and between the presentations, sidebar conversations and opportunities to meet and greet, I have to say that things hit full stride very quickly.

Today CBOE CEO Ed Tilly announced that the CBOE will roll out nearly 24 hours of trading, five days per week in VIX futures beginning on Sunday, June 22. This announcement follows another important announcement last week that options on VXST (the CBOE Short-Term Volatility Index) will commence on April 10. Clearly, things continue to move forward on the volatility product front and at the end of the year, I suspect we will lock back on these two developments as critical milestones in the volatility space.

Today I had the opportunity to listen to Marvin Zonis give a keynote address on “New Insights into Geopolitical Risk: Examining Geopolitical Risk Hot Spots and the Implications for Trading Strategies and Risk Management.” For anyone wondering about what it might take to drive the VIX higher over the course of the next few years, Zonis had a laundry list of grave concerns (Ukraine, Japan/China, Korean Peninsula, Pakistan, Iran/Israel/nuclear weapons, Egypt/Syria/Turkey, China, political stagnation, etc.) and summarized the situation by saying, “We are in the age of major, major political risk.”

Another featured speaker was Maneesh Deshpande, who talked extensively about the evolution of the demand for volatility products as well as the evolution of the supply for volatility products. Maneesh had a number of interesting observations about new players and new strategies in the volatility space. He also expressed concern about the crowded VIX short trade and the potential for the next crisis that does not mean-revert quickly to lead to a sharp second VIX spike as shorts scramble to cover their positions.

Also of interest was a two-part presentation with Dominic Salvino discussing VXST and other volatility index products (he expects interest in VXST futures will pick up dramatically after the options are launched in less than a month) as well as a detailed description of the VIX settlement process (VIX SOQ) by Bill Speth of the CBOE

Other sessions I attended today included:

• a panel on volatility as an asset class that produced considerable debate on the proper answer to that question as well as a good deal of criticism of tail risk strategies
• two speakers on trading volatility across asset classes that shared details on the methodology they use to generate trade ideas as well as quite a few cross-asset class pairs trades

Last but not least, I had the opportunity to meet quite a few people who have been regular readers of VIX and More over the years, many of whom nudged me to ramp up my posting frequency – which I certainly intend to do in 2014, starting this week.

Related posts:

• Be Greedy When Others Are Fearful (Barron’s)
• Charting the Recent Decline of the BRIC Components
• Using DXJ to Monitor Developments in Japanese Equities, Currency and Risk
• VXEEM as a Measure of Emerging Markets Volatility and Risk
• Chart of the Week: EGPT and Collateral Damage
• VIX March Futures and Options Expiration on Monday, Not Tuesday
• The New VXST and VXST:VIX Ratio

Disclosure(s): CBOE is an advertiser on VIX and More

Guest Columnist at The Striking Price for Barron’s: Why I Am Short Fear

Today I am a guest columnist for The Striking Price on behalf of Steven Sears at Barron’s, weighing in with Be Greedy While Others Are Fearful.

The Barron’s article is a quick summary of some of the reasons I am short fear. Essentially, I am short fear not because I have a Panglossian view of the world and am unconcerned about events in Spain, China, Iran and other global flash points, but rather because fear is almost always overpriced – and by a wide margin. Between the volatility risk premium and persistent negative roll yield, long VIX strategies generally face an uphill battle.

I spell out the details of my thinking in the Barron’s article, but readers can find some similar themes in the links below.

Related posts:

• VIX Premium to SPX Historical Volatility at Record High in Q1
• S&P 500 Index 20-Day Historical Volatility Hits 39-Year Low
• VIX and Historical Volatility Settling Back into Normal Range
• The Gap Between the VIX and Realized Volatility
• Chart of the Week: No More Free Lunch for Volatility Sellers?
• Availability Bias and Disaster Imprinting
• VIX Data to Support Availability Bias and Disaster Imprinting Hypothesis
• Thinking About Volatility (First in a Series)

A full list of my Barron’s contributions:

• Be Greedy While Others Are Fearful (May 3, 2012)
• Ways to Turn Volatility into an Asset Class (January 12, 2011)
• There’s Opportunity in Uncertainty (November 18, 2010)
• Will Market Volatility Return to Crisis Levels? (September 15, 2010)
• The Perils of Predicting Volatility (May 20, 2010)
• Take a Longer View on Volatility (July 2, 2009)

[source(s): StockCharts.com]

Disclosure(s): short VXX at time of writing