Category Archives: Financial markets

2020

It’s this time of the year. This post recalls events of 2020. It has been such an unusual year, so different from what we expected. Luckily, there seems to be light at the end of the very long and dark tunnel, and – I hope – that 2021 will be considerably more joyful than 2020.

2020 started out so well. The roaring twenties and all that. Wuhan was a city I had not heard of, corona a beer people tell me is best served ice-cold with a slice of lime (I do not drink beer, tough I do enjoy wine), and social distancing words we would only get to know too well. Today, we know that Wuhan is a Chinese city with more than eleven million inhabitants and a marketplace where it presumably all started, corona also means something terrible, and social interaction is an activity we have come to miss so dearly.

At the time of writing, app. 75 million cases of corona/COVID-19/SARS-CoV-2 have been confirmed globally and app. 1.7 million people have passed away because of corona. Most countries have been in lockdowns, many still are (again), and the social and economic costs of the crisis have been enormous.

I started this blog in April 2020. This had nothing to do with corona. I had wanted to set up a blog for some years (people ask me where I find time for this, and I really do not know, but seemingly I simply like writing economic stories and analyses). Starting the blog in April this year, however, naturally implied that many of the blog posts have dealt with various economic and financial aspects of the pandemic. In this post, I will review some of the learnings from 2020.

The worst recession on record. With the highest growth rate on record

The recession started in February 2020 in, e.g., the US. Initially, it was caused by a supply shock: lockdowns were imposed and firms could not sell their goods and services and households could not go shopping. In April, when the IMF released their Spring Outlook, they labelled it “The Great Lockdown”. This was a suitable label. The IMF also noted that “This is a crisis like no other” and that “many countries now face multiple crises—a health crisis, a financial crisis, and a collapse in commodity prices, which interact in complex ways”. As unemployment and bankruptcies increased, households and firm got nervous, and demand suffered, too.

The path of economic activity has been highly unusual. This graph shows the quarterly percentage changes in US real GDP since 1947:

Quarterly percentage changes in US real Gross Domestic Product. 2020 encircled.
Source: Fed St. Louis Database

2020 is very much an outlier. On average, from 1947 through 2020, real GDP has grown by 0.8% per quarter. Until 2020, quarterly growth had never exceeded 4%. Economic activity had never contracted by more than 2.6%. Then came the Great Lockdown. During the second quarter of this year, economic activity contracted by 9%. This is almost four times more than the otherwise worst contraction on record. In this sense, it was the worst recession ever.

It has also been the weirdest recession ever. During this recession, we have also witnessed the highest growth rate on record: economic activity expanded by 7.4% during Q3. This is twice as much as the otherwise highest growth rate on record.

This puzzling feature of the recession led me wondering what a recession really is (link). I expressed sympathy with members of the NBER Recession Dating Committee. They face a particularly difficult task this year. Should they conclude that we had one V in spring, with the recession ending in late April, and then a new V now, i.e. two separate Vs (VV), or that we have had one long recession with a double dip, i.e. a double-V (W)? Does it make sense to call it a recession when we experienced the fastest rate of growth in economic activity on record? If you conclude that the economy cannot be in recession when it expands at its fastest growth rate ever, then you must conclude that the recession ended during Q2. But, the NBER Recession Dating Committee has not called the end of the recession yet, i.e., officially, the recession is still ongoing.

You may ask why it is important to know whether the recession ended in April or whether it is still ongoing. The development in economic activity is what it is, whether we call it recession or not. It is important because a “recession” is such an important concept in economics. We inform the public, business leaders, students, and others about the characteristics and consequences of recessions. If a recession can contain the by-far strongest expansion of economic activity on record, we need to change our understanding of recessions.

The very unusual behavior of economic activity during Q2 and Q3 caused very unusual, and scary, developments in unemployment and related aspects of economic activity. This graph shows the monthly change in the number of unemployed in the US:

Monthly changes in the number of unemployed in the US. Millions. 2020 encircled.
Source: Fed St. Louis Database

During March, unemployment in the US increased by 16 million. Again, this was beyond comparison. Until March 2020, the number of unemployed had never increased by more than one million over one month. In March 2020, it increased by 16 million.

As the virus contracted during summer, unemployment fell. There has never been as fast a reduction in the number of unemployed as the one occurring during this summer. In May, the number of unemployed dropped by more than three million. Until May 2020, the number of unemployed had never fallen by more than one million over one month. In May 2020, it fell by more than 3 million. So, within a year, we have had the strongest-ever increase in unemployment, but also the largest-ever fall in unemployment. By far.

Such dramatic events happened all around the world. I documented this here (link) and here (link).

Inspired by these events, I did something admittedly nerdy. I calculated the probability that we would experience events such as these, given the historical data (link). I found the unconditional likelihood that we could see the increase in newly registered unemployed that we saw in spring to be 0.97 x 10^(-841). This is a zero followed by 841 zeroes and then 97. For all practical purposes, this is a zero-probability event. But it did happen. It was just very, very unusual.

The stock market

I use some of my time (a significant part, by the way) to try to understand the stock market. This has not been a straightforward task this year.

Today, the global stock market is 13% percent above its January 1 value, the US stock market is 18% higher, and the Danish stock market 29% higher (MSCI country indices). Given that we have been through the worst recession ever, and that the recession is not officially over yet, this is not what one would have expected prior to the events.

Then, on the other hand, in hindsight it is perhaps not so strange. The recession has been the worst on record, yes. But, we have also had the fastest growth in economic activity on record. I argued (link) that if we imagine that the recession ended in late April, when economic activity bottomed out, the behavior of the stock market fits perfectly well with the historical evidence on the behavior of the stock market.

Central banks have certainly played their role, too. When markets melted down in March, central banks intervened heavily. In contrast to the financial crisis of 2008, it was not banks that were in trouble this time, but firms. Firms could not sell their goods and services due to the lockdown. The limitless purchases of government bonds that central banks have become used to during and after crises thus probably did not do much good (evidence came out that central bank purchases of government bonds are less effective than we are often told, link ). What turned things around, instead, was the announcement on March 23 that the Fed would facilitate credit to firms (link). This was a new policy tool. It led to a complete turnaround of events. I produced this graph (I still think it is a supercool graph): 

Difference between yields on ICE BofA AAA US Corporate Index and 3-month Treasuries (Left hand axis) as well as the SP500 inverted (Right hand axis). Both series normalized to one on January 2, 2020. Vertical line indicates March 23.
Source: Fed St. Louis Database

The graph shows how the stock market lined up with credit spreads. Firms were suffering, and their credit spreads started widening, in late February. The stock market suffered. The Fed announced it would provide credit to firms on March 23. Credit spreads tightened. The stock market cheered. The graph summarizes how the Fed saved credit and equity markets. And, strikingly, the Fed did so by merely announcing they would intervene. Up until today, the Fed has not intervened a lot. In this sense, it was a “Whatever it takes moment of the Fed”.

It should be mentioned that the Fed announced other initiatives on March 23, too, such as the Main Street Lending Program (link) and the Term Asset-Backed Securities Loan Facility (link). The Corporate Credit Facilities were the ones that directly targeted corporate bonds, though. Due to the nature of this crisis, the stock market lined up with credit spreads during this crisis, as the above graph reveals, emphasizing the importance of the announcement of the Corporate Credit Facilities.

Eurozone troubles, or rather no Eurozone troubles

The fact that we have not had to talk a lot about the risk of a Eurozone breakup since summer has been a positive surprise. In spring, there was talk about the risk of a Eurozone crisis. Like so often before, Italian sovereign yields rose relative to German sovereign yields. There was reason to be anxious. I argued that “Some kind of political solution at the EU level would be needed” (link).

This we got. The European Union agreed on a “Recovery and Resilience Facility” (link) that includes both loans and grants. EU has moved one inch closer towards a common fiscal policy. Who will pay is not clear, but EU has shown solidarity. I believe this is positive. At the same time, the European Central Bank continued its interventions and bought a lot of Italian debt. This has kept yields on sovereign bonds low. Here is the Italian-German yield spread during 2020:

Italian yield spread towards Germany. Ten-year government bonds. Daily data: January 2, 2020 – December 21, 2020.
Data source: Thomson Reuter Datastream via Eikon.

Italian yields have been falling continuously since summer, when the EU agreed on its recovery plan. It is positive that we have not had to discuss Eurozone troubles. We have had so many other troubles. Whether this means that we do not have to discuss Eurozone troubles again at some point, I am less sure. But, that is for another day.

Banks have been doing OK

The risk of a Eurozone breakup did not materialize. Another risk that did not materialize was the risk of systemic bank failures. This is positive as well, as economic activity suffers so much more when banks run into trouble and credit consequently does not flow to its productive uses.

During the worst days in March, stress in the banking system intensified. For instance, the spread on unsecure interbank lending increased relative to secure lending:

The TED spread. Difference between 3-Month USD LIBOR and 3-Month US Treasury Bills. Daily data: January 2, 2000 – December 14, 2020. 2020 encircled.
Data source: Fed St. Louis Database.

Stresses lasted only a few days, though. During the financial crisis in 2008, on the other hand, spreads remained elevated for much longer. This time, trust in the banking system was quickly reestablished.

I think I am allowed to claim that this was one of the predictions I got reasonably right. In autumn 2019, when nobody knew about the upcoming crisis, I wrote a policy paper on the Nordic financial sector. It was presented in December 2019 and finally published in June this year (link). I argued that banks are safer today, compared to 2008. Some doubted my conclusion and said, “just wait until the next crisis, then you will see that banks are not safer today”. Well, few months later we had the worst recession ever. Luckily, though, we have not had bank-rescue packages and we have not had to bail out banks. Banks have been withering the storm. In some instances, banks have even been part of the solution by showing flexibility towards troubled firms. I am not saying everything is perfect, but I am saying that the situation has been very different from the situation in 2008. On a personal note, this made me happy, too, as it would have been somewhat embarrassing if banks had failed at the same time I published an analysis arguing that the banking sector is safer. This, luckily, did not happen. Instead, the banking system turned out to be far more resilient than in 2008, as I predicted.

You may add that the Fed rescued markets during spring, as mentioned above, and thereby rescued firms and subsequently banks. True, but there was certainly also tons of rescue packages in autumn 2008. Banks nevertheless failed in large numbers in 2008. They did not this time around. Perhaps, thus, we did learn something from the financial crisis of 2008, and have gotten some things right. This would be no small achievement.

US election and Brexit

There have been other events, for instance the US election and Brexit negotiations. In normal years, such events would potentially have been among the most important events for markets and the economy. This year, the pandemic has certainly been more important. I did manage to write a post on the US election and the stock market, though (link). I discussed evidence that stock markets perform better under Democratic presidents. Only time will tell whether the same will happen under Biden.  

I did not manage to find space to discuss Brexit, but we got a trade agreement on Dec. 24 (link). Hopefully, the EU and UK can now move on.

The cost of the crisis

It is impossible to summarize the pandemic in one number or one word. Hence, I will not attempt to do so. But, I did present a calculation of the expected cost of the crisis in Denmark (link). I arrived at DKK 336bn, or app. USD 10,000 per Dane. This calculation generated some attention in Denmark.

One can discuss every single assumption one needs to make when calculating the expected cost of a crisis: What is the value of a statistical life? What is the value of a statistical life of those who pass away due to COVID-19, i.e. who are typically above 80? What is the past loss as well as the expected future loss in economic activity due to the crisis? Does it make sense to present one number when there is so much uncertainty? And so on. These are all fair points, but if we want to have a meaningful discussion of the impact of the crisis, we have to start somewhere.

In my calculation, I closely followed the assumptions of Cutler & Summers, such that US numbers and Danish numbers can be compared. This allowed me, for instance, to conclude that the cost of the crisis in Denmark, most likely, will be much lower than the cost of the crisis in the US.

Conclusion

I must admit I find it difficult to end this last post of 2020 on a happy note. Right now, at the time of writing, the situation is bad in the country I live, Denmark, and in many other countries in Europe and around the world. Numbers of new cases and deaths have been rising recently, or are on the rise again, and more and more restrictions and lockdowns are being imposed. Days are grey and short. The crisis has already been tremendously costly and it is clearly not over yet.

Nevertheless, I will try to end the post on a positive note. It gives me hope that several countries have started vaccinating people, and it seems to be working well. Finally, the EU also starts vaccinating people now. This has taken way too long, however, given the severity of the crisis and the fact that other countries started weeks ago. And, yes, every day counts. If it is correct, though, and I deliberately write if, that the EU has failed when it comes to the approval process and purchase of vaccines, as the normally well-informed and serious magazine Der Spiegel claims (link), it is a scandal. Biden aims to vaccinate 100m Americans within his first 100 days in office (link), close to a third of the US population. As things look now, it seems unlikely that we will be able to achieve the same in Europe. Christmas is all around us, though, so let us hope that somehow things will develop in the right direction.

Therefore, let me focus on the bright side. With the jabs, the situation will most likely start to improve within a not too distant future. I will try to convince myself that I see weak light at the end of the long and dark tunnel, even when we probably have to wait many months before things really calm down. Days are at least getting longer. I will focus on this, then.

With this, which is meant to be a positive message, let me thank you all for reading this blog and for sending me many encouraging mails with feedback. Please keep on doing so – it is highly appreciated.

I conclude by expressing hope that next year will be considerably more joyful than the one we leave behind.

Happy New Year!

Expected returns, autumn 2020 updates

Today, October 1, the Council for Return Expectations publishes its updated expectations. We expect very low – negative – returns on safe assets over the next five and ten years. We expect an equity premium around 5-7 percent.

I chair the Council for Return Expectations (link). Twice a year, we update our expectations. Today, we publish our latest forecasts.

In a June post (link), I described the history of the council, how we operate, who we are, why we publish expected returns, what they are used for, and so on. Briefly, here, the Council consists of 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. Based on inputs from Blackrock, J.P. Morgan, Mercer, and State Street (thanks!), we estimate expected returns, risks (standard deviations), and correlations between returns on ten different asset classes over the next five and ten years. We also publish expected returns on two assets classes (stocks and bonds) for investment horizons exceeding ten years.

The forecasts are important in Denmark. When Danish pension funds project how the retirement savings of their customers will most likely develop (with confidence bands), they base their projections on the Council’s return expectations. Similarly, when banks advice Danish investors on their non-retirement savings, they use the expected returns provided by the Council. I think it is fair to say that Denmark has been a front-runner in designing a system where banks and pension funds do not compete on expected returns, but all use a common set of return assumptions, determined by an independent Council.

The forecasts published today will be used for pension projections and projections for savings outside retirement accounts as of January 1, 2021. In spring 2021, we will publish updated expectations that will be used from July 1, 2021, and the following six months. And so on.

The timing is as follows. The expectations we publish today are based on market data from July 1, 2020. We use the period from July 1 until today (October 1) to determine our expectations. The expectations we publish today are then used by banks and pension companies as of January 1, 2021.

The numbers

We publish forecasts for expected returns on ten asset classes over the next five years, years 6-10, and over the next ten years. Returns are average annual returns in Euros/Danish kroner (the Danish kroner is fixed to the euro). These are our expectations:

Source: Council for Return Expectations

We expect an investment in safe assets (defined as a five-year duration portfolio of 30% Eurozone government bonds (minimum Triple-B), 20% Danish government bonds, and 50% Danish mortgage bonds – Danish mortgage bonds are triple-A rated, by the way) to lose money every year on average over the next ten years. This is noteworthy. On average, we expect such an investment to lose 0.1% per year over the next ten years. Over the next five years, we expect it to lose 1.2% per annum. The reason why we expect such low returns is that the underlying bond portfolio has a duration of five years, as mentioned, and we expect a normalization of interest rates, causing capital losses which drag down expected returns.

We expect lower returns from bond investments than we did in our June update (link). In June, we expected government and mortgage bonds to return a negative 0.3% per year over the next five years and a positive 0.3% per year over the next ten years. The reason why we expect lower returns now (-1.2% and -0.1% for the five and ten year periods, respectively) is that our forecasts today, as mentioned, are based on market data from July 1. On July 1, interest rates and credit spreads were lower than those used at our previous update. Our previous update was based on March 31 market data. In March, the corona virus had caused a hike in yields and a widening of credit spreads. Since then, yields and spreads have come down.

Global equities are expected to yield around 6% per year. This means that the equity premium is expected to be 5%-7%, depending on the investment horizon.

We expect low inflation. We expect Danish inflation to be 1.2% per annum over the next five years and 1.5% over the next ten years.

For investment horizons above ten years, we expect equities to return 6.5% per annum and bonds 3.5%. This is the same as we expected last year (we update long-run expectations once a year). Over the coming year, we will make a thorough evaluation of these long-run expectations.

We also publish standard deviations for all asset classes and for all horizons, as well as correlations and fees. Standard deviations are high for high-return assets; nothing comes for free. We thus publish many numbers. You can find all these numbers on the webpage of the Council: link.

Conclusion

We (The Council for Return Expectations) expect that Danish investors will lose money – even before fees and inflation – if investing in safe assets over the next ten years. You can expect positive returns on other asset classes, but then you need to take on risks.

Historically, the risk-free real interest rate has been around 2% per annum and the nominal interest rate around 4%. Investors would see their savings grow, even without taking on risk. This is not what investors should expect going forward. The fact that you cannot expect your portfolio to grow without taking on risk tells us a lot about the low-return world we are living in.

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.