The impacts of the coronavirus on the global economy: Part VIII: The stock markets

Some stock exchanges are recovering faster than others from the financial crisis caused by the outbreak of the coronavirus disease. On April 28, the NASDAQ composite index and the SIX Swiss exchange mid-cap index were respectively only 5.1 % and 7.3 % below their levels of January 6. On the other hand, the year-to-date return of the Brazil stock exchange index was -30.43 %. Those of the London Stock Exchange FTSE All Share, the Euronext N150, the Bombay Stock Exchange sensitive index, and the Australia Securities Exchange index were about -22 %.

Between January 6 and April 28, capital loss on the Hong Kong Stock Exchange went as low as -25.3 % (this value is the percentage change between the lowest and the highest values of the benchmark index). On the NASDAQ, the range of the capital los was 30.1 %, but this exchange is recovering faster than the Hong Kong Stock Exchange. Why capital loss has been more important on some stock exchanges than the others and why some exchanges have recovered faster than the others? There are two possible explanations. The first one is the sensitivity of the exchange to factors affecting the global economy (the systematic risk) and the second one is the structure or the composition of the exchange.

In the table below, it appears that the systematic risks on the New York Stock Exchange (NYSE) and the Brazil Stock Exchange (Bovespa) are very high during turbulent periods (actually, they are greater than 1). This means that these two exchanges are more exposed to global risk than the other major exchanges. This explains why the year-to-date returns of their benchmark indices are very low. The systematic risk on the Hong Kong Stock Exchange is only .55 and the year-to-date decrease in its benchmark index is less than those on the NYSE composite and the Bovespa index.

Table: Year-to-Date Returns on Apr 28, 2020 and Systematic Risk during Turbulent Periods of some Stock Exchanges.

Stock Exchange	Year-to-Date Return	Systematic Risk
NYSE	-18.81 %	1.11
NASDAQ	-5.11 %	1.11
Tokyo Stock Exchange	-14.80 %	.55
London Stock Exchange	-21.99 %	.83
Hong Kong Stock Exchange	-12.93 %	.51
Euronext	-21.79 %	.88
Toronto Stock Exchange	-13.49 %	.87
Bombay Stock Exchange	-21.05 %	.54
Frankfurt Stock Exchange	-17.76 %	.98
Australian Securities Exchange	-21.12 %	.59
SIX Swiss exchange	-7.28 %	.72
Brazil Stock Exchange BOVESPA,	-30.43 %	1.06

The systematic risk on the NYSE is the same as on the NASDAQ, but the latter exchange is recovering faster than the former. This means that the systematic risk is not the only factor explaining returns on the exchanges. The activity sector and the performance of the main companies in the benchmark indices also explain their year-to-date returns. Half of the companies in the NASDAQ composite operate in the technology sector and 11 % in the healthcare sector. As I show in my previous post [here], these are the two sectors that are performing better during this crisis. Likewise, more than half of the components of the Swiss exchange mid-cap index operate in the healthcare, the technology or the telecommunication sector.

On April 24 the global financial turbulence score rose from 4.38 to 4.62 (a 5.3 % rise). After keeping falling since March 20, The VIX (the implied volatility index) rose by 3.5 % to 37.19, on April 24.

Figure : Global Financial Turbulence Scores and VIX, Jan 8, 2000 - Apr 24, 2020

Dataset and Code

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The Latest Global Financial Turbulence Scores.

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
Mar 20, 2020	9.37
Mar 27, 2020	8.03
Apr 3, 2020	7.70
Apr 10, 2020	4.10
Apr 17, 2020	4.38
Apr 24, 2020	4.62

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

$$d_t² = (r_t - μ ) Σ ^-1 (r_t - μ )',

where $d$ denotes the turbulence score, the vector $r$_t lists the current growth rates of the benchmark indices, the vector $$ μ their historical averages, and $$ Σ designates their variance-covariance matrix. For further details, see Mark Kritzman and Li Yuanzhen (2010).

The impacts of the coronavirus on the global economy: Part VI The oil market

On January 24, 2020, a barrel of the West Texas Intermediate (WTI) crude oil for delivery on May 20 was traded at US$ 55.54, on the New York Mercantile Exchange (which is the largest physical commodity futures exchange in the world). At that time, the spot price of the WTI crude oil was US$ 54.09. This means, the cost of carry (i.e., the interest rate plus the storage cost minus the convenience yield) of the crude oil was 8.3 % per annum. One month before the delivery date (i.e. on April 20), the closing price of the May WTI crude oil fell to $ -2.60 and its spot price went further down to $ -36.98, which is unprecedented (see Figure 1).

Figure 1: Daily Spot and May Futures Prices of the WTI Crude Oil, Jan 24, 2020 - April 21, 2020.

First, the spot price of the WTI and its futures price both became negative, on April 20, and, second, they diverged suddenly. The law of supply and demand explains the decrease of the spot price of WTI crude oil into negative territory. The overproduction of crude oil (i.e., the increase in its supply) and the simultaneous drop in its demand due to the lockdown of economies worldwide result in the drop of its spot price. When he spot price of the WTI was $ -36.98, its futures price went as low as $ -39.44. The reasons for this important drop are: (1) there was no longer a convenience yield from holding inventories of crude oil compared to holding its futures contracts and (2) the storage cost of this commodity increased due to its overproduction. The divergence between the closing price of the May WTI crude oil and its spot price simply resulted from the fact that traders anticipated that the situation was temporary since the spot price of the alternative Brent crude oil was US$ 17.36 that day. This then caused the futures price of the WTI to rise.

Stock markets keep recovering from the crisis caused by the outbreak of the coronavirus. Between April 3 and April 10, the global financial turbulence score fell again, going from 7.7 to 4.1 (a 46.8 % decrease). As for the VIX, the implied volatility index, it went down from 41.67 to 38.15 (an 8 % decrease). The global financial turbulence score has been falling since the peak of March 13. One can wonder if the market bottom is reached, with this important fall.

Figure 2: Global Financial Turbulence Scores, Jan 8, 2000 - Apr 10, 2020.

Is the financial crisis over?

It is true that the high turbulence characterizing a financial crisis went down considerably. In my first post dedicated to the impacts of the coronavirus on the global economy [here], I predicted that the probability of a high turbulence in stock markets across the globe would decrease to 32 % by May 29. This probability remains unchanged, given the new available data. As one could see in Figure 2, the current level of the global financial turbulence score is still well above 3.4, which is the level expected during a turning point (represented by the green dotted line). By the end of the month of May, the probability of exiting the financial crisis would be 21.4 % and the probability of returning into it after a short recovery would be 33.7 %. Thus, the financial crisis is not over yet!

Dataset and Code

The Latest Global Financial Turbulence Scores.

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
Mar 20, 2020	9.37
Mar 27, 2020	8.03
Apr 3, 2020	7.70
Apr 10, 2020	4.10

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

$$d_t² = (r_t - μ ) Σ ^-1 (r_t - μ )',

where $d$ denotes the turbulence score, the vector $r$_t lists the current growth rates of the benchmark indices, the vector $$ μ their historical averages, and $$ Σ designates their variance-covariance matrix. For further details, see Mark Kritzman and Li Yuanzhen (2010).

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The impacts of the coronavirus on the global economy: Part V Is a comparison with the Great Depression possible?

More and more commentators and economists are comparing the current economic crisis to the 1929 depression (also known as the Great Depression). For some of them, the current crisis is even worse. Are they right? In my humble opinion, they are wrong.

First of all, the Great Depression was caused by a stock market crash (that started on October 24, 1929). On the other hand, the current economic crisis is voluntarily induced by governments as a policy response to a global health crisis. Thus, the turbulence we are observing on stock exchanges around the globe is the consequence but not the cause of the current economic situation. The causes of the stock market crash of October 24, 1929 were mainly consumerism, easy credit, and speculation. Its consequences were mainly bank failures, hoarding, massive job losses, and poverty. Second, if the causes of the Great Depression and those of the current crisis are not the same, their consequences are not similar either. Currently, investors have fear, but they have not lost confidence in financial institutions. Millions of people are not currently employed, but they have not definitely lost their jobs. Third, the Great Depression lasted almost a decade (from 1929 till the outbreak of World War II), whereas the current crisis is hopefully coming to an end, since governments have started preparing plans to exit the lockdown restrictions they imposed some months ago.

It is true that the stock markets have been very turbulent since the outbreak of the coronavirus disease. On March 13, the situation on the major exchanges was the worst record over the past two decades (see Figure 1). Since then, it has been gradually improving. Between March 27 and April 3, the global financial turbulence score fell from 8.03 to 7.70 (a 4% decrease). The decrease in the VIX, the fear index, was much higher. This latter index went down from 46.8 to 41.67 (an 11% decrease). This situation is explained by the rise in the major benchmark indices. On the New York Stock Exchange, the NASDAQ, the Bombay Stock Exchange, the Toronto Stock Exchange, and the Brazil Stock Exchange, the benchmark indices increased by more than 10%.

Figure 1: Global Financial Turbulence Scores and VIX, Jan 8, 2000 - Apr 3, 2020

Oil markets are also suffering severely from the on-going crisis. On March 13, in the heat of the financial turbulence, the spot price of the West Texas Intermediate (WTI) and the Brent fell by 28.9% and 33.5%, respectively. (The WTI and the Brent are both sweet light crude oil serving as benchmark in pricing.) The following week they further declined by 25.3% and 23.9%, respectively. As one can see in Figure 2, the prices of these crude oil keep falling. This price crash is due to thee overproduction of oil and the decrease in its demand after the lockdown of several economies. This situation is affecting not only oil producing firms and the industries depending directly on this activity, but also public finance. In Canada, the provinces of Alberta and Newfoundland and Labrador are the most affected by this unexpected oil price crash.

Weekly Cushing, Oklahoma WTI and Europe Brent Spot Prices, Jan 1, 2000 - Apr 3, 2020

Dataset and Code

The Latest Global Financial Turbulence Scores.

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
Mar 20, 2020	9.37
Mar 27, 2020	8.03
Apr 3, 2020	7.70

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

$$d_t² = (r_t - μ ) Σ ^-1 (r_t - μ )',

where $d$ denotes the turbulence score, the vector $r$_t lists the current growth rates of the benchmark indices, the vector $$ μ their historical averages, and $$ Σ designates their variance-covariance matrix. For further details, see Mark Kritzman and Li Yuanzhen (2010).

The impacts of the coronavirus on the global economy: Part II

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.

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

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The Latest Global Financial Turbulence Scores.

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

$$d_t² = (r_t - μ ) Σ ^-1 (r_t - μ )',

where $d$ denotes the turbulence score, the vector $r$_t lists the current growth rates of the benchmark indices, the vector $$ μ their historical averages, and $$ Σ designates their variance-covariance matrix. For further details, see Mark Kritzman and Li Yuanzhen (2010).