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 III The Global Financial Turbulence Score and the VIX

I have taken another pulse of the stock markets by recalculating the global financial turbulence scores using the latest weekly benchmark indices and compared them to the VIX, a volatility index, published by the Chicago Board Options Exchange (CBOE). An option is a contract that gives its owner the right to buy (in the case of a call option) or to sell (in the case of a put option) an underlying asset (e.g., a stock) at a specified price and date. The CBOE is the world's largest options exchange. Figure 1, below, plots both the turbulence scores and the VIX. The VIX is also known fear index.

Figure 1: Global Financial Turbulence Scores and VIX, Jan 8, 2000 - Mar 21, 2020

The global financial turbulence score is backward-looking, as it is based on historical benchmark indices. On the other hand, the VIX is an implied volatility index, as it is the market expectation of the next 30-day fluctuations in the S&P 500 that results from solving numerically an option pricing model. While the VIX has the advantage of being forward-looking, it has the disadvantage of being derived from a theoretical model that might not always hold true empirically.

At the end of last week (i.e., on March 20), both the turbulence score and the fear index went down, respectively, from 12.9 to 9.4 and from 66.04 to 61.59. This means that, even if the global financial crisis caused by the outbreak of the COVID-19 is still going on, stock markets became less volatile and investors that were betting on the future evolution of stock prices by trading options also became somewhat less pessimistic. Since the outbreak of the COVID-19, the highest values of both the turbulence score and the fear index were recorded on March 13. (Recall that trading paused on March 9 and 12 on the New York Stock Exchange, as its benchmark S&P 500 plunged below the 7% threshold of the market-wide circuit breakers.) Both the turbulence score and the fear index date the on-going financial crisis back to February 21, where their values rose sharply, respectively, from 1.4 to 6.2 and from 17.08 to 40.11.

It appears in Figure 1 that there is a co--movement between the turbulence score and the fear index. In general, when stock markets are very turbulent, investors are also very pessimistic about the future. For example, during the 2007-08 financial crisis and the on-going health crisis, both time series reach a peak. However, during the oil price crash, the turbulence index quadrupled going from 2.74 to 11.57 on January 9, 2015, whereas the fear index only rose from 17.55 to 20.95 (which represents a 19.3% increase). On November 10, 2017, whereas the turbulence score was decreasing, the fear index rose. Figure 2 shows the scatter plot of both time series.

Figure 2: Scatter Plot of the Global Financial Turbulence Scores and the VIX, Jan 8, 2000 - Mar 21, 2020

The correlation coefficient between the turbulence score and the fear index is .64. However, as it appears in Figure 1, during quiet periods, the relationship between these two time series is not as strong as it is during turbulent periods.

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

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).