The Relationship between Unemployment Rate and Economic Growth in Canada

The unemployment rate in Canada rose from 7.8 % in March to 13 % in April, due to the lockdown restrictions imposed by the federal and the provincial governments to stop the spread of the COVID-19. The average unemployment rate in Canada is 8.2 %. The highest ever recorded unemployment rate in five decades (13.1 %) was in December 1982.

In the early 1980s, unemployment, inflation, and interest rates were simultaneously very high in the most developed countries. In Canada, the unemployment rate was steadily above 10 %, between May 1982 and December 1985 (on average, 11.4 %). The second episode of high unemployment period Canada experienced was in the early 1990s. Particularly, between February 1991 and October 1994, unemployment rate rose, as a result of the restrictive monetary policy that aimed at curbing the high inflation inherited from the 1980s.

Since May 11, several economies have started easing the lockdown restrictions. As a result, one can expect unemployment to decline in May and over the coming months. More and more people are returning to work, as some businesses are allowed to reopen. Unfortunately, it is not all the layoff employees that are returning to work. Some businesses failed, due to the COVID-19 pandemic. The travel bans and the physical distancing rules in effect keep affecting the sector of accommodation and food services, where the unemployment rate rose from 18.4 % in March to 34.3 % in April, this year. The unemployment rate in this sector was 6.1 % in February.

The data on the Gross Domestic Product (GDP) of Canada (i.e., the value of the wealth created by Canadian residents) over the first quarter of 2020 are not released yet. But, it is certain that GDP will fall over the first quarter of this year. To predict the extent of this decline, one can use an economic relationship known as Okun's law. Okun's law predicts a consistent relationship between changes in the unemployment rate and the real GDP growth rate. In the US, a 1 percentage point increase in the unemployment rate is said to result in a 2 % decline in the real GDP. Given that the data for the unemployment rate in Canada are already available for the first quarter of 2020 and even for the month of April, I can use them to predict the decline in the real GDP by estimating the linear relationship suggested by Okun.

Even though there has been some deviations from the Okun's law over the years, I use it to predict the changes to expect the real GDP because of its simplicity. The scatter plot in the figure below shows the percentage point change in the unemployment rate and the corresponding real GDP growth rate in Canada. The data points associated with the periods of economic expansion are in green and those associated with the periods of recession are in red. During periods of expansion and recession, the expected quarterly GDP growth rates are respectively .74 % and -1.07 %.

Figure: Okun's Law: Percentage Point Change in Unemployment Rate and Real GDP Growth Rate, Canada, 1976:Q1-2019:Q4

In the above figure, the line in black represents the predictions of the Okun's law that make no distinction between periods of expansion and recession. The short-run effect of unemployment on real GDP from this linear model is -1.2, i.e., a 1 percentage point increase in the unemployment rate results in a 1.2 % decline in the real GDP. This linear model predicts a -.14 % decline in the real GDP during the first quarter of 2020.

In the above figure, the blue segment lines represent the predictions of the Okun's law conditional on the state of the business cycle. The conditional short-run effects of unemployment on real GDP are respectively -.66 and -.29 during periods of expansion and recession. This conditional model (referred to as Markov-switching model) predicts that the real GDP fell by .99 % in Canada, over the first quarter of 2020.

The table below summarizes the predictions of the real GDP growth rate based on the Okun's law.

Table: Predictions of real GDP Growth Rates for Canada based on the Okun's Law.

Stock Exchange	First Quarter of 2020	April 2020
Linear Model	-.14 %	-5.84 %
Markov-Switching Model	-.99 %	-2.34 %

Given the various financial assistance programmes initiated by the Liberal government of Justin Trudeau (which includes the Canada emergency response benefit that provides for a maximum of 16 weeks a weekly pay of $ 500 to layoff employees), the prediction of a decline of 2.34 % in real GDP in April is more realistic.

The updates on the global financial turbulence score will now be available in the tab "The Financial Barometers" of this blog.

Dataset and Code

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 VII The sectors of the stock markets

To what extend the outbreak of the coronavirus disease (the COVID-19) has affected investments in the various sectors of stock markets? To find this out, I have computed the year-to-date returns of two exchange-traded funds (ETF) that track the performance of the various sectors of the United States (US) and the global stock markets. The year-to-date return of a fund is the percentage change in its market value between the first trading day of the current year and the current date. The two ETFs that I am using to proxy the performance of the sectors of stock markets are: the select sector Standard and Poor's Depository Receipt (SPDR) funds and the iShares Standard and Poor's (S&P) global. The SPDR tracks the sectors within the S&P 500 (which consists of companies based in the US) and the iShares S&P global tracks the S&P global 1200 index (which consists of companies based in 31 countries).

Energy companies followed by the financial and the industrial companies turn out to be the three sectors that are most affected by the current crisis. In the US and the global markets, energy stocks lost respectively 41.6 % and 39.7 % of their values, between January 2 and April 27 (see the table below). This situation is explained by the dramatic drop in the price of the crude oil. As a matter of fact, over this time period, the spot price of a barrel of the West Texas Intermediate (WTI) crude oil fell from US$ 61.17 to $ 12.17 (which represents an 80.1 % decrease). The price of the Brent crude oil plunged from US$ 67.05 to $ 15.17 (which represents a 77.4 % decrease). On April 20, the WTI turned negative.

Table: Year-to-Date Returns of ETFs, Jan 2, 2020 - Apr 27, 2020.

Sector	Select Sector SPDR	iShares S&P Global
Consumer Discretionary	-9.90 %	-16.61 %
Consumer Staples	-5.76 %	-7.92 %
Energy	-41.61 %	-39.67 %
Financials	-27.67 %	-29.55 %
Health Care	-.54 %	.13 %
Industrials	-23.99 %	-24.05 %
Information Technology	-4.28 %	-5.48 %
Materials	-15.67 %	-18.18 %
Telecommunication Services	-4.45 %	-9.28 %
Utilities	-7.65 %	-9.54 %

The lockdown of economies and the layoffs that followed also considerably harmed the financial sector (personal, commercial, corporate and investment banking, transaction processing services, wealth management, …) and the industrial sector (manufacturers of capital goods, …) in the US and the other markets across the globe.

Health care (pharmaceuticals; health care providers, health care equipment and supplies, …) is the only sector that has recorded a capital gain, during this pandemic. The consumer staples, the information technology, and the telecommunication services are the three other sectors where investors incurred less losses. The reasons are that: (1) consumer staples (food, beverages, home and personal care, alcohol, and tobacco, …) are essential goods and services, (2) the services provided by information technology and telecommunication companies are ways of breaking isolation and loneliness during the lockdown. As an example, during the first quarter of this year, 15,8 million new people subscribed to the movie streaming services of Netflix.

Utilities, (gas, electricity and water distribution), which are known as a defensive sector, poorly performed, as many households waiting for employment insurance benefits had to postpone the payment of their bills.

The year-to-date returns of the select sector SPDR are similar to those obtained using such other major ETFs as the Vanguard and the Fidelity index funds that rather track the MSCI US index. Unlike stock markets, the year-to-date yields of bonds are positive. The year-to-date yield of the vanguard total bond market index fund is 3.92 % and that of the Fidelity total bond ETF is 2.03 %.

After plunging to 4.10 on April 10, the global financial turbulence score rose to 4.38 on April 17 (see the figure below). As I pointed out in my previous post [here], this means that the financial crisis caused by the outbreak of the coronavirus is not over yet. Unlike, the turbulence score, the VIX (the implied volatility index) keeps falling. It went down from 38.15 to 35.93, on April 17 (which represents a 5.8 % decrease). This means that despite the fact that volatility on stock markets starts rising again, investors are less pessimistic about the future.

Figure: Global Financial Turbulence Scores, Jan 8, 2000 - Apr 17, 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

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).

The Impacts of the Coronavirus on the Global Economy

The outbreak in December 2019 of the coronavirus disease (COVID-19) is affecting now the global economy. Concerns about this disease, which was first identified in the Chinese province of Hubei, and the measures taken to stop its spread are affecting travel agencies and tour operators, the transportation and warehousing sector, financial markets, the arts, entertainment and recreation sector, and public finance. As a matter of fact, while some businesses and administrations are facing stock shortages as a result of the restrictions on exports from China, the world's factory, other businesses are coping with multiple cancellations of reservations and events. Stock and oil prices are falling. Governments are revising downward the forecasts of their economies' growth and the estimates of their budget revenue. Some commentators are already talking about a recession or worse a depression. How serious is the situation?

In this post, I take a look at the current situation in some major financial markets and compare it to historical data in order to find out if, actually, there are reasons to fear the worst. Figure 1 plots 12 benchmark indices of the following markets: (1) the New York Stock Exchange, (2) the NASDAQ, (3) the Tokyo Stock Exchange, (4) the London Stock Exchange, (5) the Hong Kong Stock Exchange, (6) the Euronext, (7) the Toronto Stock Exchange, (8) the Bombay Stock Exchange, (9) the Frankfurt Stock Exchange, (10) the Australian Securities Exchange, (11) the SIX Swiss exchange, and (12) the Brazil Stock Exchange.

Figure 1: Natural Logarithm of Some Weekly Stock Market Benchmark Indices, Jan 1, 2000 - Mar 7, 2020

How serious is the situation?

It appears clearly in Figure 1 that stock prices have been declining over the past weeks, in all these 12 major exchanges. Particularly, on January 24 and on February 21 of this year, these benchmark indices went down simultaneously, when the markets were closing. To take a measure of the situation using a single summary statistic instead of looking at 12 time series individually, I have computed financial turbulence scores following Mark Kritzman and Li Yuanzhen (2010). This statistics is given by the following relation

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

where the vector $r$_t lists the current growth rates of the benchmark indices (the capital gains or losses), the vector $$ μ their historical averages, and $$Σ designates their variance-covariance matrix.

Figure 2 plots the square root of the turbulence score (i.e., $the\; statistic$d_t ) computed using the benchmark indices of the 12 major exchanges listed above. The two horizontal lines on this figure are thresholds defining three regions: (1) in the region below 2.5 (demarcated by the green line), the global financial market is in a quiet state, (2) in the region above 4.1 (demarcated by the red line), the market is very turbulent, (3) in-between, there is an unconditional probability of 82% that the market be in a quiet state. For information, these estimates have been produced fitting a Markov-switching model to the turbulence statistics.

Figure 2: Financial Turbulence Score Based on 12 Major World Indices, Jan 7, 2000 - Mar 7, 2020

The two highest turbulence scores observed since the outbreak of the coronavirus are 6.2 (on February 21) and 9.7 (on March 6). As one could see in Figure 1, this indicates that the global financial market is currently in turbulence. But, contrary to what we were led to think, this only started on February 21. Furthermore, the situation is not comparable to the episodes of turbulence experienced during the burst of the dot-com bubble in the early 2000s, the financial crisis of 2007-08, or the oil crisis of 2015.

What to expect in the coming weeks?

An accurate answer depends on how the COVID-19 will evolve. While encouraging signs are coming from the province of Hubei in China where the virus was first identified, warning signs are coming from Italy where this mortal virus is spreading. Using the historical data, I can predict that there is a very high probability that the current state of the global financial market remain the same in the next 12 weeks. However, this probability decreases progressively going from 88% for the week ending on March 13 to 32% for the week ending on May 29.

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

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.