On March 11, 2020, the World Health Organization declared the outbreak of the COVID-19 (i.e., the coronavirus disease) a pandemic, which means this epidemic has spread worldwide.
Since then, the United States (US) suspended for a month all flights from mainland Europe and declared the state of emergency.
Canada closed its borders to foreign nationals, except its permanent residents, diplomats, and US citizens.
The European Union also locked down for a month its borders to all non-member countries.
Throughout the world, schools and universities are closed, and mass gathering (including religious celebrations) are called off.
The various measures taken to put an end to this global health crisis and the panic caused by the situation are affecting the global economy.
On March 9, trading on the New York Stock Exchange (NYSE) paused for 15 minutes, after an initial 7% decline in its benchmark S&P 500.
(This halt is the first level of the market-wide circuit breakers, which are a set of three emergency mechanisms aiming at curbing rapid and massive panic selling of securities.)
On March 12, the plunge of many benchmark indices reached levels unobserved since the Black Monday (i.e., October 19, 1987).
For a second time, trading on both the NYSE and the Toronto Stock Exchange (TSX) paused temporarily, as the S&P 500 and the S&P/TSX composite fell by 9.5% and 12.3%, respectively.
On March 16, these two benchmarks respectively fell by 12% and 9.9%, which triggered the first tier of the circuit breakers for the third time in eight days.
To measure the turmoil on stock exchanges, I suggested, in my post The Impacts of the Coronavirus on the Global Economy, the use of the financial turbulence score, which is a multivariate distance measure in standard units proposed by
Mark Kritzman and Li Yuanzhen (2010).
(In Statistics, the square root of this measure is known as Mahalanobis distance.)
I will now be referring to the time series I produced in the above-mentioned post, as global financial turbulence score as it consists of capital gains/losses computed using the benchmark indices of 12 of the 20 largest exchanges in the world.
In this post, I update this time series in order to keep following the situation.
The figure below plots the square root of the global financial turbulence weekly time series.
Last week, due to the fact that the circuit breaker halted twice stock trading on the NYSE and the TSX, turbulence on the major exchanges was higher than the week before.
On March 13, the level of the global financial turbulence score was 12.9, versus 9.7 during the week ending on March 6.
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| Global Financial Turbulence Scores, Jan 1, 2000 - Mar 14, 2020 |
Last week, the turbulence score on the major stock exchanges far exceeded 4.3, which is the level expected during high volatility periods.
This is the highest score recorded over the reference period.
Many central banks (including the Federal Reserve Bank, the Bank of Canada, and the Bank of England) cut their key interest rates, to stimulate their economies.
These emergency measures have not yet succeeded to eliminate panic from financial markets, since the economic activity is still paralyzed by the border restrictions and the imposition of self-isolation (or social distancing).
On March 18, the NYSE halted stock trading, for a fourth time in two weeks.
As a matter of fact, travel agencies and tour operators, the transportation and warehousing sector, the arts, entertainment and recreation sector, and the accommodation and food services sector are suffering severely from the restrictions imposed to stop the spread of the coronavirus.
The stocks of listed companies operating in these sectors will keep losing value as long as investors are not seeing any prospect of profit.
Dataset and Code
| Date | Score |
|---|---|
| Feb 14, 2020 | 1.36 |
| Feb 21, 2020 | 6.23 |
| Feb 28, 2020 | 3.68 |
| Mar 6, 2020 | 9.74 |
| Mar 13, 2020 | 12.89 |
The components indices of the global financial turbulence score
(1) NYA: the New York Stock Exchange composite index, (2) IXIC: the NASDAQ composite, (3) N225, the Tokyo Stock Exchange average index, (4) FTAS, the London Stock Exchange FTSE all share, (5) HSI, the Hong Kong Stock Exchange index, (6) N150, the Euronext Next 150 index, (7) GSPTSE, the Toronto Stock Exchange composite index, (8) BSESN, the Bombay Stock Exchange sensitive index, (9) GDAXI, the Frankfurt Stock Exchange performance index, (10) AXJO, the Australian Securities Exchange S&P 200, (11) SSMI, the SIX Swiss exchange mid-cap index, and (12) IBOVESPA, the Brazil Stock Exchange index.Formula
where denotes the turbulence score,
the vector lists the current growth rates of the benchmark indices,
the vector their historical averages,
and designates their variance-covariance matrix.
For further details, see Mark Kritzman and Li Yuanzhen (2010).
