Category Archives: Stock markets

The weird stock market. Part I: Facts and wrong explanations

The behavior of the stock market during this recession has been perplexingly. To understand it, we need to answer three main questions: (i) why did stock markets fall so spectacularly during February/March, (ii) why did stocks rebound so spectacularly during April/May, and (iii) why is the stock market currently at its pre-crisis level? This blog post explains why these stylized facts are so difficult to understand jointly. In my next blog post (to be published next week), I will offer my view on this.

Observing the stock market during this recession has been a like watching a roller coaster. The fall in late-February/early-March was the fastest bear market in history, the rebound has been historically fast, too, and – in spite of the worst recession ever – the stock market is currently back at pre-recession levels. Somebody leaving for the moon in January and returning now would not be able to see any trace in the stock market of the worst recession ever. This is in stark contrast to normal recessions. People interested in financial markets and the economy should be puzzled.

The problem – in a nutshell – is that if you claim that you understand why stocks are currently at pre-recession levels, then you face a challenge explaining why we needed to go through the fastest bear market ever during February/March. On the other hand, if you claim that the fast fall and rise in markets was just a short-lived technical blip (perhaps due to funding squeezes and fear), then you face a challenge explaining why that technical blip should result in a loss to the tune of USD 20 trillion (link). Finally, if you claim that you understand why markets fell so fast in February/March (perhaps because we were facing the worst recession ever – which, by the way, is a good explanation), then you face a challenge explaining why markets recovered so strongly in April/May/June, as the recovery cannot be explained by a brighter economic outlook. In fact, we have seen continuous downgrades of the economic outlook. E.g., the IMF WEO in June lowered its April forecasts for global economic output to –4.9%, from –3.0%. A huge downgrade. Strange that stocks recover in spite of this.

In this post, I describe the facts. I also review a couple of suggested, but wrong, explanations. In my next post (that I will publish next week), I will offer my view on what has been going on.

The facts

Here is an updated version of a graph that I have presented earlier. It shows the Danish, US, emerging market, and world stock markets (MSCI), normalized to one on January 1, 2020:

Stock markets since January 1, 2020. MSCI indices.
Data source: Thomson Reuter Datastream via Eikon.

Stock markets reached a temporary peak on February 19, after which they tanked dramatically. As mentioned here (link), it was the fastest US bear market in history.

The rebound has been equally spectacular. The US stock market is already back at its January 1 level. World and emerging markets are still a few percentages behind, but, basically, they have also recovered from the crisis.

In the US, it was the fastest bear market ever, as mentioned. In this graph, I document that it has also been one of the fastest recoveries. I calculate rolling 11-week gains/losses in the SP500 during the last 50 years.

S&P 500, 11-week percentage changes.
Data source: Fed St. Louis Database

As you can see from the encircled peak on the right-hand-side of the graph, from its bottom on March 23, the SP500 gained app. 45% until June 8. The graphs shows that no other 11-week period since 1970 has witnessed such a large gain (I cherry-pick the 11-week period, but the main message is that the rebound has been spectacular, and this message is robust).

Wrong explanations

You hear/read many explanations. Some of them are just not correct.

It all boils down to FAANG

Some claim that it is not the overall stock market (typically these people refer to the SP500) that has recovered. Instead, some argue, it is all due to FAANG (Facebook, Apple, Amazon, Netflix, and Alphabet’s Google). It is true that the behavior of FAANG has been impressive and has driven a significant part of the SP500’s recovery, but this is not the whole story. As you see from the first graph above, emerging markets have recovered, too. This is obviously not due to FAANG. Also, some markets, such as the Danish, have recovered even more spectacularly than the US market. Not FAANG either. Even US small-cap stock have recovered. Not fully, but significantly. The Wilshire US Small-Cap Index gained an astonishing 57% during the March 23 through June 6 period. True, small-cap stocks are still (early August) 12% below their January 1 level, but when small-cap stocks have rebounded spectacularly, too, it emphasizes that this is not all about all FAANG, even when FAANG stocks have done very well.

Markets also recovered after the 2008 financial crisis

This is a no-brainer: Markets always recover. The point here is that this rebound has just been amazingly strong. In this graph, I compare the behavior of the SP500 during autumn 2008 and the corona crisis. “0” in the figure is September 19, 2008, respectively February 21, 2020:

S&P 500, daily closing prices. Normalized to “1” 25 days before September 19, 2008, respectively February 21, 2020. September 19, 2008 and February 21, 2020 marked by vertical line.
Data source: Fed St. Louis Database

During the first couple of weeks of this spring’s crash, it looked like autumn 2008. The pain was short-lived, though. Stock markets fell for a couple of weeks and then rebounded. In 2008, stocks just continued falling.

It has taken a couple of months to recover this time around. After the financial crisis of 2008, it took more than two years. This figure shows that the US stock market was back at its summer-2008 level in early 2011 only, and the world stock market later still.

Stock markets since January 1, 2020. MSCI indices.
Data source: Thomson Reuter Datastream via Eikon.

This recession is not as bad as 2008

It should be obvious by now that this argument is very wrong indeed. I have argued myself that there is hope that, when we get a vaccine and economic activity picks up again, the economic rebound will be stronger than in 2008, the reason being that we entered this recession with a more “balanced” economy than in 2008 (in 2008, we had a housing bubble, a weak financial sector, etc.). Nevertheless, the short-run loss this time around is just so much larger than in 2008.

Last week, we got figures for GDP in the US and Europe. This graph compares the cumulative falls in real GDP in the Eurozone and the US in Q3+Q4 2008 with the cumulative drops during the first two quarters of this year.

Cumulative change in real GDP in the US and the Eurozone. “2008” is Q3+Q4 2008 and “2020” is Q1+Q2 2020.
Data source: Fed St. Louis Database

US real GDP fell by more than three percent in Q3 and Q4 2008, whereas Eurozone real GDP dropped by five percent in autumn 2008. It was a severe recession in 2008. Nevertheless, it pales compared to this recession. This time around, US GDP has fallen by more than ten percent already and Eurozone GDP is down by a staggering 15% during the first two quarters of 2020.

What about the length of the recovery? After 2008, it took around two years before economic activity had reached its pre-crisis level. This figure shows for, e.g., the Eurozone that it will last more or less equally long this time (expectations for 2020 and 2021 are from the EU Commission, Spring 2020).

Development in real GDP for the Eurozone as of Q2 2008 and as of Q4 2019. Developments after Q2 2020, i.e. after 2 quarters in 2020, are expectations from the EU commission.
Data source: EU commission.

The figure shows that Eurozone GDP was 5% lower in Q4 2008 compared to Q2 2008 whereas it is 15% down in Q2 2020 compared with Q4 2019. After eight quarters, GDP is basically back at its pre-crisis level. This means that the recovery is expected to be stronger, but this recession is just very deep.

In other words, this recession is much deeper – one can multiply the drop in 2008 by a factor of three or so to get the drop this time – and it will take several years before economic activity is back at pre-crisis levels. This means that the short-run cost to society is bigger this time around (a deeper fall stretched over the same period).

And, in spite of this very strong recession, stocks are doing fine. That is perplexing.

Above, I have presented stories that cannot explain what has been going on. Next week, I will offer my view on this.

Expected returns

The Council for Return Expectations published its forecasts of expected returns last week. There is a wide dispersion across asset classes. Returns on “safe” assets (government bonds) are expected to be very low, even negative, on the short horizon, whereas emerging markets equities are expected to return close to ten percent per year. The Council also publishes forecasts for standard deviations, correlations, and inflation.

As one of my external activities, I chair the Council for Return Expectations (link). The Council estimates expected returns, standard deviations, and correlations on ten broad asset classes. The estimates are widely used in the Danish financial sector and public discussions. Danish pension funds use the estimates when they calculate pension projections for their customers and banks use them when they make projections for how outside-pension savings can be expected to develop. Newspapers also write about them, too.

I will argue that the Danish financial sector has been a front-runner in designing a way to make such independent return assumptions. I hope the set-up helps improving the credibility of the projections banks and pension funds make.

In this blog post, I present the latest estimates from the Council. As it is the first time I present these estimates on this blog, I start out describing why the Council was established, how the Council works, and the procedure we use in the Council to find expected returns. Afterwards, I present the forecasts.

Background: The Council for Return Expectations

The Council was established (under a slightly different name) two years ago. The background was as follows.

Danes have large pension savings. Together with the Netherlands, Denmark has the largest pension savings in the world relative to GDP (We have a paper describing some of the key features of the Danish pension system here; link). Historically, pension savings have been guaranteed, meaning that pension holders were guaranteed a minimum average annual return on their pension savings. Because of low interest rates, longer life-expectancies, etc., Danish pension funds have shifted into so-called market-based pension products during the last decade or so. In these products, there is no minimum guaranteed return. This allows the pension funds to invest more freely, hopefully enabling them to secure higher risk-adjusted returns. Basically, you go from a constrained to an unconstrained (or at least less constrained) maximization problem, which should lead to a better outcome. However, when a pension holder is not guaranteed a minimum return, the expected pension payouts during retirement will obviously become more uncertain. The assumed expected returns and risks on the different assets that pension funds invest in thus become even more important (compared to a guaranteed pension product) for an individual’s expected pension payments during retirement.

A couple of years ago, I was approached by the Danish pension industry and asked whether I would help them design a set-up that could be used to generate expected returns on pension funds’ investments. The result was the following: based on inputs from international financial institutions, present expected returns over the next ten years on ten different asset classes, as well as long-run (> 10 years) expectations on two assets classes (stocks and bonds), and update these forecasts annually. The pension industry judged that an independent committee should specify and regularly update the return expectations, in order to secure arms-length. They asked me if I would chair this committee. The Committee is now called the Council for Return Expectations

Last year, banks in Denmark asked whether we (The Council) would be able to expand the set of return assumptions. The background was – probably fair to say – a scandal in the largest bank in Denmark. Danske Bank had advised some of its customers to invest in an investment product that the bank itself expected would yield a lower return than a bank deposit. I.e., the bank had advised its customers to invest in a suboptimal product, given expected returns. It led to the resignation of the interim Danske Bank CEO (link). The Danish banking sector concluded that arms-length was needed in determining return expectations used for investments outside pension savings. They asked the Council if we could include return expectations for a shorter horizon (1-5 years, in addition to the 1-10 years horizon) and a more frequent update of the return assumptions (twice a year, instead of annually). These forecasts were published last week.

Procedure for determining expected returns

We provide forecasts for nominal returns on ten broad asset classes. Having done extensive research on the determinants of expected returns myself, I know that even within a precisely defined asset class, forecasters can disagree substantially on the outlook for the asset class. When designing the set-up, I thus suggested that return expectations should be based on an arms-length principle and take estimation uncertainty into account. We do this by basing our expectations on inputs from several international investment houses.

We (The Council) receive inputs from Blackrock, J.P. Morgan, Mercer, and State Street. We are truly thankful for their help.

Blackrock, J.P. Morgan, Mercer, and State Street provide their estimates of expected returns, standard deviations, and correlations on each of the ten asset classes for each of the different horizons to the Council. The ten asset classes for which we provide expected returns are:

  • Government and Mortgage Bonds
  • Investment-grade bonds
  • High-yield bonds
  • Emerging market sovereign bonds
  • Global equity (developed markets)
  • Emerging markets equity
  • Private equity
  • Infrastructure
  • Real estate
  • Hedge funds

The horizons are:

  • 1-5 years.
  • 6-10 years.
  • 1-10 years.

Returns are nominal. Estimates are for the arithmetic average annual return per year during the different horizons.

Returns are hedged into euros, i.e. are euro returns, except from emerging market equities and local currency emerging market debt that are unhedged (emerging market debt is 50%/50% local/hard currency). The Danish kroner is pegged to the euro, i.e. euro returns are basically also Danish Kroner returns. Returns are before fees, expect from the last four asset classes (private equity, Infrastructure, real estate, and hedge funds) that are after fees to the funds that manage these types of investments, but before the fees to the Danish pension/mutual fund that in turn invests in the private equity funds, hedge funds, etc.

In addition, we provide forecasts for Danish inflation based on inputs from a number of Danish forecasters (the Danish central bank, ministry of finance, etc.).

The Council consists of three people: Torben M. Andersen (professor of economics, University of Aarhus; link), Peter Engberg Jensen (former CEO of Nykredit and current chairman of Financial Stabilitet; link ), and myself as Chairman. Our job in the Council is to specify the relevant asset classes and their characteristics, choose methods used to weight the inputs together, come up with reasonable forecasts, communicate these to the public, etc.

Forecasts of expected returns

The following table presents our forecasts of expected annual returns for the next five years, the next ten years, and years six through ten:

Source: Council for Return Expectations.

Over the next five years, we expect “safe” investments (government bonds and Danish mortgage bonds) to return a negative 0.3% per year on a pre-fees, pre-taxes, and pre-inflation basis. This is a low return. On a net-of-fees, after-tax, and real-terms basis, it is even lower. In the Danish media, much was written about this number (-0.3%). For finance professors and professionals, the number is no big surprise given low interest rates, but for ordinary investors, the publication of numbers such as these from trustworthy sources helps communicating the message that it is difficult to earn a decent return these days without taking on risk.

On a more technical term, the return on this asset class is the return to a bond portfolio consisting of 50% Danish mortgage bonds (that are triple-A rated, as you probably know), 20% Danish government bonds, and 30% Euro government bonds, with a duration of five years.

There is a wide dispersion across the different asset classes. For instance, we expect emerging market equity to yield 9.5% per year. There is thus an almost ten-percentage point difference between the expected return on the safest asset class and the asset class yielding the highest expected return.

Notice also that we generally expect higher returns after five years. We expect higher interest rates, causing capital losses and thus low returns during the first five years, but then higher returns later on. This in itself helps raising expected returns on other asset classes.

Standard deviations

In the Council, we want to stress that estimates of expected returns are surrounded by uncertainty. To the finance professionals, this is obvious (though, one might sometimes have the impression that even professionals tend to forget this), but to the ordinary investor, this is even more important to emphasize. The ordinary investor might otherwise conclude that when expected returns on emerging markets is 9.5% per annum, but government bonds are expected to yield a negative 0.3% per annum, I better put all my money in emerging market equity. We want to stress that this is a risky strategy. This ambition has guided us when it comes to our estimation of standard deviations.

The expected returns we present are constructed as simple unweighted averages of the expected returns of Blackrock, J.P. Morgan, Mercer, and State Street, asset-class by asset-class. They also provide us with their expected standard deviations. We do not use the simple averages of these as our estimates of expected returns, though. Instead, we regress the standard deviations we receive from the investment houses on the expected returns received from the same investment houses. The standard deviations the Council presents are then the fitted values from this regression. The main objective we achieve by following this procedure is that we make sure that there is a clear relation between risks and returns.

The standard deviations surrounding the estimates of expected returns are here:

Source: Council for Return Expectations.

We expect a 3.5% standard deviation of government and mortgage bonds (over the next ten years) whereas we expect a 29.6% standard deviation surrounding the estimated returns to emerging markets equity. There is thus a clear relation between expected risks and returns. This clear relation also appears from this graph that plots risks on the ten asset classes against their returns (1-10 years horizon):

Source: Council for Return Expectations.

One might say that the price we pay from estimating standard deviations in this way is that some of the individual estimates of standard deviations might differ slightly from market consensus. As an example, our estimate of the standard deviation of global equity is around 14%. Market consensus probably is that this is a little higher, at 16%-17%. On the other hand, the advantage we obtain from proceeding in this way, as mentioned, is that we secure a clear relation between risk and returns.

Correlations

We also present correlations between expected returns. Here they are for the first ten years:

Source: Council for Return Expectations

Correlations are simple averages of the correlations we receive from Blackrock, J.P. Morgan, Mercer, and State Street, asset-class by asset-class. The main thing to notice probably is that we expect all correlations to be positive. This is bad news for investors, one might argue, but we saw this during the March turmoil. In March, bonds and stocks both lost in value, i.e. bonds did not hedge the risk of stocks. Our correlations reflect this.

The correlations and standard deviations are used by the pension funds to calculate confidence intervals surrounding the individual’s expected pension income. I want to stress that it is advanced – and good! – that pension holders in Denmark not only learn about their expected pension income but also the uncertainty surrounding this expectation.

Inflation

We expect the Danish rate of inflation to be 1.2% over the next five years and 1.4% over the next ten years.

All the numbers

All the numbers – means, standard deviations, correlations, for all the horizons, etc. – are available on the webpage of the Council (link). On this webpage, addition information about the Council can be found as well.

Conclusions

We live in low-interest times. Investors might be tempted to invest more risky in order to generate a decent return. But what are decent returns? And how much extra risk do investors incur when investing more risky? In most countries, you get one set of answers when you visit one pension fund/bank/financial advisor, but another set of answers when you visit a different pension fund/bank/financial advisor. This makes investors uncertain and do not help building trust between the financial sector and investors. The financial sector in Denmark has found a cool way of presenting independent/arms-length forecasts. I hope that other countries might be inspired from this way of addressing this important issue.

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PS. In my last post (link), I wrote about a new paper I have written on the financial stability in the Nordics. The journal where the paper is published is now available (link). It contains my own article and articles on the banking union, bail-in debts, household debts, and macroprudential policy, as well as a number of enlightening discussions.

Zero-probability events that happened

Some of the events we have seen during this crisis are so unlikely that we need tricks to calculate their probabilities. This is a journey into the world of very small probabilities and very large numbers. I admit it is somewhat surreal. But it is important as these small-probability events can have long-lasting effects on economic activity.

The defining characteristic of this recession is the speed with which markets and economies started freefalling. From one day to the next, economies were shut down. Economic activity came to a complete sudden stop in some sectors. In different blogposts, I have used words such as “unprecedented”, “completely crazy”, “horrifying”, “tremendous”, etc. to describe what happened.

Using words like these is adequate, I think (I admit I was shocked by what happened), but I have come to a point where I want to be more precise. As economists, we want to put numbers on things. I want to calculate the probability of the events. This turned out to be more complicated than I had first imagined.

The probability of a 121-sigma event

On Monday, April 20, the oil price (West Texas Intermediate) closed at USD -38 for a barrel of oil. I describe this here (link). This was a drop of 306% relative to the closing price the previous trading day. Based on daily data since 1983, the average percentage change in the oil price is 0.03% and the standard deviation 2.5%. I called the event “completely crazy”, which I still believe is a fair description. Now, I want to know “how crazy” it was. What was the probability that it would happen?

The happy-go-lucky Professor of Finance, i.e. me, opens his Excel spreadsheet and enters the command used to find the probability that an event of -306 happens when data are normally distributed with mean 0.03 and standard deviation 2.5.

I press “Enter”. Excel returns “0”. The Professor of Finance thinks this look strange and increases the number of decimal places. Excel just shows “0.000….”. According to Excel, this is a zero-probability event. It could not happen.

But it did happen. I start remembering the statistic classes many years ago, and recall the discussions on low-probability events.

Luckily, I have helpful colleagues. I write CBS Professor of Statistics Søren Feodor Nielsen. He tells me that the probability I am looking for is below the “machine precision”. He also tells me that the probability itself might be extreme, but the logarithm to the probability is probably not. We calculate the log-probability (using a different statistical package than Excel). It is -7495.137, i.e. the likelihood is exp(-7495.137). This is, unfortunately, such a low number that a computer cannot calculate this either.

We then calculate the log base 10 probability. Now we have the result. The probability is 0.799 x 10^(-3255).

This is a zero followed by 3255 zeroes, and then 799. Practically zero, but not exactly zero. The event happened, but it is extremely unlikely. We can call it “completely crazy”, but we can also say that the probability is 0.799 x 10^(-3255).

There is another way to illustrate how unlikely this event was. When the probability is 0.799 x 10^(-3255), we should see this event happen every 1.2516 x 10^(3255) days. I.e., a number with 3255 numbers before the decimal place. I simply do not know what such a number is called (link). This is where it starts getting surreal.

How precise is this? We have calculated it, but Søren tells me we should not put too much faith in its precision. Tail-probabilities in the normal distribution are calculated by numerical approximations, and it is questionable how precise they are when we are that far out in tail. Admittedly, the question is of course also how important it is that it is precise that far out in the tail. The probability is unbelievably small. That is the main thing. Exactly how small is perhaps not that important.

S&P 500

This graph shows daily percentage changes in the S&P 500 throughout the last 50 years.

S&P 500. Daily data. May 1970 – May 2020.
Data source: Thomson Reuter Datastream via Eikon.

On March 13, the S&P 500 fell 12%. The average daily percentage change in the S&P 500 (calculated up until March 12) is 0.03% and the standard deviation is 1.05%.

The likelihood that we will see a 12% drop in the S&P 500 on a daily basis, given the behavior of the S&P 500 during the last 50 years, is very small, but not so small that it cannot be calculated in Excel. Excel says it is 1.0827 x 10^(-29).

These are daily data. If we assume 250 trading days per year, we should see this event happen every 3.69 x  10^(27) = 3,694,454,429,465,560,000,000,000,000 year. I.e., every 3.694 octillion year.

This is also somewhat surreal.

There are many caveats. We are again so far out in the tail that we should not put too much emphasis on the exact number of decimals and the exact number after all the zeroes. Also, all these calculations are based on the assumption of normally distributed data. Given that we saw a 21% fall in the S&P 500 on Black Monday, October 19, 1987, we have seen two very unlikely crashes within the last three decades. According to these calculations, they should happen much more seldom. We use the normal distribution, but data might follow a different distribution. For most practical purposes, however, it is not necessary to know the exact distribution of these extreme events. The important thing to know is that the likelihood is very small.

Other numbers

In this post (link), I describe how the initial jobless claims soared, confidence indicators fell, GDP dropped, etc. As an example, the likelihood that we should see almost 7 million people filing for jobless claims on March 28, given the complete previous history of jobless weekly claims, is 0.97 x 10^(-841). This is again such a small probability that Excel cannot even calculate it.

Economic effects

There is a broader point to these discussions. Events like those described above might have long-lasting consequences for economic activity.

When events are unlikely, we assign low probability to their occurrence. One hypothesis is that we keep on assigning low probabilities to their occurrence. In this case, future investment decisions of firms and future consumption decisions of households are unaltered by the events we have been going through. It was a temporary shock. It has very low probability. It will not influence how we form expectations going forward.

An alternative hypothesis is that we have become so scared by the event that it will haunt us for years to come. We update our beliefs disproportionally much.

Which of the two scenarios play out is important for the recovery from this recession. Will we start consuming when economies open up or will we hold back because we have become scared?

Kozlowski, Veldkamp and Venkateswaran (2020) have an important paper on this (link). Their main point is that events like those studied above, i.e. events that are very unlikely but have large impacts, will have persistent effects on beliefs. They write that “tail events trigger larger belief revisions” and that “because it will take many more observations of non-tail events to convince someone that the tail event really is unlikely, changes in tail beliefs are particularly persistent”. This is an important insight. If this is how we form expectations, it will slow down the recovery from this recession. Kozlowski et al. also show, however, how government interventions can reduce the effect, but not eliminate it.

Conclusion

These weeks we are seeing infection rates declining in many countries and economies opening up again. These are very good news. Let us hope we can start returning to some kind of normality. It will take time before we are back to where we came from, though. Some things might even have changed for good. One thing is for sure: we will not get back as fast as economies and markets fell in March. What happened was very unlikely. But it did happen.

Is the stock market too optimistic? Or, is the market always right?

The rebound in stock markets has been spectacular. One may wonder whether it is sustainable.

What does it actually mean that the stock market is “too optimistic”? Doesn’t the stock price always reflect the average expectation of all investors? True, and, in this sense, the market cannot be “too optimistic”. On the one hand, the market is always right.

On the other hand, the legendary economist Paul Samuelson famously noticed that the “stock market has predicted nine of the last five recessions”. Stock markets also appear “excessively volatile”, as Shiller showed already in 1981. I.e., the stock market might always be right, but perhaps we are going through a period of excessive volatility where markets were overly pessimistic in March and are overly optimistic now.

In any case, if the stock market is always right, so is the futures market. Investors in the futures market expect huge drops in dividends over the next year. If stock prices behave as they usually do during recessions, stock prices should drop even more, that is dropping even more than dividends.

Market developments

Before we start this attempt to explain things and look ahead, let us review the facts. This graph shows developments in the Danish, the US, the world (MSCI All countries), and the emerging stock markets since the start of the year, all MSCI indices (Danish index is in Danish kroner, the rest in USD):

Stock markets since January 1, 2020. MSCI indices.
Data source: Theomson Reuter Datastream via Eikon.

Stock markets did well in the beginning of the year, fell dramatically from mid-February through mid-March, and have rebounded spectacularly since then. Today, the Danish stock market is above its January 1 value, the US market is 10% down, the world market is 15% down, and emerging markets are 20% down.

What could explain current stock prices?

Stock prices are by definition discounted future cash-flows. That is easy to say. The difficult part is to find the expected future cash-flows and the appropriate discount rate.

Let us start with a positive view on markets and see what is needed to support this.

To begin with, let us keep the discount rate fixed. Let us also, as a starter, assume that valuation ratios are constant. For instance, let us assume that stock prices closely follow developments in real economic activity. Under these assumptions, we would, largely, be able to understand recent market movements. These assumptions would also support a rosy view of the future. Afterwards, we discuss if this is a likely scenario.

Forecasts for economic activity in light of the corona crisis start coming in. Late April, we got the WEO from the IMF and forecasts for the US from the CBO, and this week we got forecasts for Europe from the EU-commission. This figure shows the expected path of real GDP in the US and EU:

Expected developments in EU and US real GDP. The CBO does not provide quarterly growth rates for 2021, so I assume linear growth during 2021, accumulating to the CBO forecast of 2.8% for 2021 .
Data source: EU commission and CBO.

This recession is enormous. GDP is expected to fall by 15% in Q2 this year, compared to late 2019. Luckily, economies are expected to rebound sharply after this quarter, too. The EU commission expects a strong recovery in the EU in 2021, with 6.1% growth in 2021. The CBO expects 2.8% growth in 2021 in the US. Whether this difference is realistic, I do not want to discuss here.

The economy drops by 15% in Q2. If stock prices follow GDP, as we assume for now, stock prices should have dropped by 15% in Q2. This is almost spot-on.

This theory would also predict that we have a great year in front of us. Economic activity should improve by something like 15-20% until late 2021. If stock prices follow, stock prices should also increase with something like 15-20% from here.

What about the huge drop in March? This we can also explain, I think. Basically, it had little to do with underlying economic fundamentals. Some leveraged hedge funds got squeezed, they received margin calls, they dumped everything to raise cash, there was panic, spreads widened, and markets feared a replay of 2008 (I comment on it here and John Cochrane has a nice and more detailed explanation here). Stress on markets almost reached 2008 levels, as, for instance, the St. Louis Fed Financial Stress index indicates:

St Louis Fed Financial Stress Index.
Data source: St. Louis Fed.

Central banks intervened and provided liquidity. Markets calmed down. The stress index is still somewhat elevated, but much lower than in March. Markets started looking at economic fundamentals again. With lots of liquidity around, and low yields, investors bought stocks. This was a temporary crash.

The intermediate conclusion is that if stock prices follow GDP, stock prices should drop by something like 15% during Q2, only to rebound afterwards. And, as of today, stock prices have in fact fallen by something like 15% since the start of the year, with a bumper on the road in March. If we stop here, everything would be fine and we should expect substantial stock market gains going forward. Under these assumptions, markets are expected to rebound by something like 15-20% until late 2021.

Cash-flows do not always follow economic activity

Unfortunately, we cannot stop here. We need to go back to the definition of stock prices: Discounted cash-flows. I truly believe that cash-flows relate to economic activity in the long run (I have research demonstrating this), but I also believe that there are temporary business-cycle deviations between cash-flows and economic activity. And these deviations can be substantial.

We have expectations to economic activity from IMF, CBO, EU, and so on, but how do we find expectations to cash-flows? Niels Joachim Gormsen from the University of Chicago, a smart former Ph.D. student at Copenhagen Business School, has, together with Chicago Professor Ralph Koijen, developed a method that can be used to back out expected changes in dividends from dividend futures. They also estimate a relation between dividend growth and GDP growth, such that they can back out expected GDP growth, too.

Their latest estimates are from April 20. Compared to January 1, 2020, Gormsen and Koijen estimate that US GDP will be 3.8% lower over the next year (precisely, Niels tells me, they compare expected growth from April 1, 2020 through April 1, 2021, to expected growth from January 1, 2020 through January 1, 2021). This is not far from what the CBO expects (the figure above shows that GDP will be something like 5% lower ultimo 2020 compared to primo 2020).

The scary thing is that Gormsen and Koijen show that markets expect dividends to be 18% lower over the next 12 months, i.e. drop by 13%-points more than GDP. An 18% drop in dividends is a very large drop in historical terms.

This graph shows how investors update their expectations to future dividend growth rates during the corona crisis:

Data source: Gormsen and Koijen (2020).

For the EU, Gormsen and Koijen expect GDP, respectively dividends, to drop by 6.3%, respectively 28%. The market is always right, right?

Unfortunately, we cannot stop here either.

Stock prices react excessively to cash-flows during recessions

We need to talk about the last part of the definition of stock prices: discount rates. Research shows that discount rates move counter-cyclically, increasing in bad times and dropping in good. From our definition of stock prices, this means that stock prices should fall by more than dividends in bad times, if discount rates increase in bad times.

Tim Kroencke from the Univeristy of Neuchatel has an interesting paper that studies how stock prices move in relation to dividends during recessions. The central graph in the paper is this one:

Data source: Kroencke (2020)

The graphs shows how dividends (and earnings) fall during recessions and how stock prices fall even more (there are two stock price indices. Read Tim’s paper to get the explanation for the difference. The point is that stock prices fall more than dividends.)

The figure shows that US dividends drop by 10% and US stock prices drop by ten percentage-points more, i.e. 20%, on average during US recessions. It also shows that stock prices do not drop ahead of the drop in dividends, but alongside. This is not good news.

Gormsen and Koijen’s estimates say that we should expect dividends to drop by 18% for the US and 28% for the EU over the next year. Kroencke says that on average stock prices drop by 10%-points more. This means that stock prices should drop by close to 30% in the US. If we use the 10% drop in the price-dividend ratio for EU data, EU stock prices should drop by close to 40%. Today, stock prices are down 15% globally.

Conclusion

We might hope that this recession plays out in a different way than recessions usually do. We might also hope that stock markets react in a different way than they usually do. We might hope that everybody starts spending when economies open up, companies start producing, and earnings and dividends do not suffer. In this case, the drop in dividends might not be that large. And, we might hope that stock markets do not fall by more than dividends, in contrast to what they normally do. This could for instance be because central banks are marginal investors in many markets now, driving asset prices away from what they would have been if prices were solely determined by private market participants. This is what markets hope. And, of course, this might turn out to be the case.

We might also fear, however, that companies will start facing problems given the severity of the crisis, i.e. this turns from a liquidity crisis to a solvency crisis. Should this happen, earnings and dividends will drop. The market is always right. The futures market expects dividends to drop by something like 20% for the US and 30% for Europe. If stock prices react as they normally do during recessions, stock prices should drop even more. The 15% drop since early 2020 seems small in this light.

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PS. Did you by the way notice the German Constitutional Court ruling this week? Given last week’s post on the Italian situation, I might just inform you that the Italian yield spread to Germany widened as a consequence. Not a lot – 15 basis points or so – but in the wrong direction.

The stock market and more horrifying figures

A couple of weeks ago, I collected some graphs revealing how deep this recession is (Link). Two weeks have passed. New data have arrived. They are still horrifying.

We now have aggregate numbers for Europe. In the first quarter of 2020, Eurozone GDP dropped more than it did during the worst quarter of the financial crisis of 2008:

Quarterly growth rate of Eurozone real GDP.
Data source: ECB.

GDP figures are aggregate data. They show how total economic activity has developed. That’s why they are important. They are, however, also a snapshot of the level of economic activity, collected with a lag. The latest figures deal with the first quarter of 2020. So what about asking firms and households how they feel and how confident they are? If people and firms think this will be a short-lived recession, they should be confident. The EU commission publishes confidence indices for firms in the industrial sector, the services sector, and for households in the EU. Confidence indices drop, as we have never seen before.

Monthly changes in confidence indices.
Data source: EU commission.

The industry, the service sector, and households all have no confidence in the economy.

Next, I collect trailing averages of initial jobless claims in the US during the preceding six weeks. During the past six weeks, more than thirty million Americans have lost their jobs. It is not just a historical record. It is very sad.

Initial jobless claims in the US. Rolling six-week averages.
Data source: St. Louis Fed.

Most likely the unemployment rate will come in at close to 20%.

Behind all these numbers and figures, there are real firms and real people. Firms will be forced to close. Individuals will lose their jobs. Households will struggle.

So, how does the stock market do? Given the scale of the recession, you would expect it to suffer tremendously. It does, however, great.

From its temporary trough on March 23, the SP 500 has gained 32%. It tanked heavily in late February and early March, but it is today (May 1) “only” 13% below its peak on February 19. I write “only” as the stock market often losses something like 50% in a recession (Link). This recession is unprecedented, as shown above, so you would expect unprecedented losses on the stock market. This is not what we see.

It is not unusual that the stock market starts rising before the end of the recession . And the stock market did fall very fast early in the recession. In the US, it was the fastest bear market ever (Link). But given the depths of the recession, stock markets have rebounded surprisingly fast.

True, not all stock markets have rebounded. The Spanish stock market (MSCI Spain) is 30% below its peak on February 19. So is the Italian. And, the Argentine is down 31%.

So, some stock markets have rebounded strongly, but others have not. Let us try to get an overall picture.

This is a global recession. The aggregate value of global stocks markets is USD 44 trillion on April 29 (FTSE All World Index). On February 19, it was USD 52 trillion. At the bottom on March 23, it was USD 35 trillion.

World stock market capitalization. FT All World Index. USD bn.
Data source: Thomson Reuter Datastream via Eikon

This means that 20,000 billion USD(!) was lost on the stock market from February 19 through March 23, globally. It also means, however, that almost 10,000 billion USD have been gained during the last month or so.

Given the severity of this recession, it is – frankly speaking – somewhat surprising that global stock markets have not lost more than something like 15% since mid-February. Stock markets seem disconnected from the real economy. Why?

Of course, stock markets are forward looking and all that. And, yes, luckily, it seems that the corona virus is on retreat. These are very good news and give some hope. But, given the depth of the recession, I think it will leave scars. It will take time before unemployment in the US reaches 4% again, as an example.

The reason why stock markets in many countries have done great during the last month, when economy activity has suffered like never before, is actually rather simple. Central banks exercised the “central bank put”.

Central banks were every fast to enact even very large rescue packages. They started doing so in mid-March. This helped stabilize financial markets, depress yields, and flooded markets with liquidity. The goal, of course, was to support the real economy. It saved stock markets, too. Shortly after the announcement of all these comprehensive measures, the stock market started rising.

With lots of liquidity around, and low yields everywhere, markets convinced themselves that central banks would save the world. Markets bought stocks, and stock markets surged.

This is what I believe explains it. Otherwise, I cannot make sense of the fast rebound in the stock market. But I do believe markets have thereby become somewhat disconnected from the real economy. And this is strange to witness.

V, U, W, or L? The stock market votes “V”.

How will this recession play out and how will the recovery look? Will we get a short recession with a fast rebound (V), will we get a longer recession before the recovery (U), will we get a new lockdown in autumn resulting from a second wave of the Corona virus (W), or will economies remain depressed for a long time (L)?

Nobody knows, particularly this time around when the shape of the recovery will be determined by a virus and how this develops.

Supporting the V-shaped recovery, this recession is not caused by economic imbalances, such as an overvalued housing sector, too much debt, a fragile banking sector, or the like. Also, we know from history that recessions last longer and are deeper if they are caused by financial crises. This is also not the case this time around, in contrast to 2008, for instance. This means there is hope for a reasonably fast rebound, if we manage to get the virus under control.

On the other hand, if we get a second outbreak, e.g., in autumn, and economies are shut down again, the path of economic activity will probably take the shape of something like a W.

What we do know is that the depths of the recession is unprecedented. The fall in economic activity and the increase in unemployment is mind-blowing, and very scary (link).

This makes one fear that the recession could drag out. When economies open up, it will take time to find jobs for those who get unemployed during the recession. Firms will probably be reluctant making new investments until we have a vaccine. Consumers want to go to restaurants, cinemas, on vacation etc., but will probably hold back until they feel on safe ground, too. Uncertainty abounds.

In this environment, one would imagine that the stock market suffers tremendously. With a recession impeding, and with so much uncertain surrounding the future path of economic activity, one would imagined that stock markets, like economic activity, would be in freefall. This is not the case.

In the beginning of the lockdown, the stock market tanked. It was the fastest bear market ever (link). It reminded us very much about the dark days of autumn 2008. This graph shows the SP500 on a daily basis during the 2008 financial crisis and this crisis. “0” in the figure is September 19, 2008, respectively February 21, 2020.

S&P 500, daily closing prices. Normalized to “1” 25 days before September 19, 2008, respectively February 21, 2020.
Data source: Fed St. Louis Database.

Financial markets were in stress in mid-March, when even yields on safe assets increased (link). Fearing a replay of 2008, central banks and governments came to the rescue, and the stock market started its recovery. Since the bottom on March 23, the S&P 500 has gained an astonishing 28%. This is remarkable, given all the uncertainties and the depth of the recession. The contrast to the autumn of 2008 is stark. The stock market kept on falling throughout 2008 and early 2009, only to start its recovery in March 2009.

The stock market seemingly believes this recession will result in a V-shaped recovery. Let’s hope it is right. One might fear that it is not.