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Some time ago, I wrote about grit as a vital characteristic for investors. That triggered a couple of email exchanges with younger readers who are at an earlier stage of their career as financial analysts or money managers.

In general, the discussions revolved around the skills a successful analyst and investor should have. And while a passion for markets and grit are one key trait, I think there are a few that are more fundamental.

First, there are cognitive skills, i.e. the ability to think analytically and logically. Investing is a numbers game and requires analysts to make sense of the mountain of data that is available on every level, whether we are talking about the economy and markets as a whole or individual stocks and bonds. Without good cognitive skills, an analyst doesn’t have the foundation to become successful, in my view. A study by David Gill and Victoria Prowse examined the skills and traits of people during their childhood and how they influence success in different classes in school, the type of jobs they end up in and how successful they were in terms of income.

It won’t surprise you that children with high intelligence and strong cognitive skills were more likely to excel in maths, science, and English classes in school and less likely to excel in arts, sports, and practical classes like shop class (yes, those clichés are true, at least statistically).

And this training in maths and science compounds the strong cognitive skills and leads these people to choose jobs that fit their talents. As young adults, people with strong cognitive skills are more likely to end up in managerial and technical jobs and professions like medicine, teaching, engineering, finance, and law. The result is that these people also have higher lifetime earnings since managerial and technical jobs as well as the professions tend to pay better.

So, without good analytical and cognitive skills you are not going to get anywhere as an investor. But most people who work in finance as analysts or money managers are smart and skilled. So what sets the good investors apart from the average?

In my view, it is two traits.

People who are focusing on individual stocks and bonds tend to do better when they are diligent. Working your way through a financial statement with all its footnotes and being able to ask probing questions to management in earnings calls is not easy. And the more diligent analysts are, the more likely it is they will find the flaw in the story management is trying to tell. Let’s face it, no CEO is ever going to tell investors that she thinks the company is going to be in trouble or not doing well. The job of investors and analysts is to see if there knight in shiny armour really is as shiny as he appears to be.

In the most extreme cases, being diligent in your analysis and able to think critically and challenge management can uncover frauds. Think of the Enron case twenty years ago. Most analysts were hoodwinked by the management into thinking the company was doing great. Yet, a few analysts questioned the accounting practices of the firm and the use of SPV. This probing led some analysts to conclude that Enron was a fraud. These are the analysts that I want to talk to about companies because they are the ones that add value and will help you perform better. The rest of the pack that just bought into the hype you can safely ignore. They won’t make you money as an investor.

And then you have the generalists and strategists that don’t dive deep into the financial statements of companies. For this group of investors, I think diligence is less important and less of a differentiator. You can literally outsource that trait to research analysts who cover individual stocks.

But these generalist fund managers, strategist and, asset allocators need another trait. This trait makes all the difference between being average and being above average: creativity. And I am not talking about creativity in the sense of painting or being a member of an amateur acting troupe. Those are fun hobbies, but when I talk about creativity here, I mean the ability to look at data and markets in a different way than other people. Being able to put the individual pieces of information together to form novel insights.

In particular, I mean being able to deal with uncertainty and a lot of noise and navigate this noisy, uncertain environment with the required flexibility and conviction. Howard Marks put it best when he said: “You can’t do the same things as others do and expect to outperform.” But unfortunately, too many analysts, strategists and fund managers essentially do the same as others do. The amount of true creativity in the investment world is very low, in my experience. Most people are just tinkering with existing approaches to investing, adding a few additional parameters here and there but that is not the creativity that gets you additional performance. Performance is created by doing things truly differently and differentiated. What does that mean in practice? It can take on so many different forms that it is impossible to say and I won’t tell you how I try to do it because that would take my edge away. So, you’ll just have to become a client of my company and read my notes and book some meetings with me (if you haven’t already).

But going back to the study by Gill and Prowse mentioned above, they showed that being more creative has distinct advantages in life. Creative people are more likely to end up in management and technical positions. The effect is about a fifth as strong as the effect of cognitive skills, but it is a compound effect. Cognitive skills give you the foundation and creativity is the little extra that sets you apart.  

Note: This is a reprint of a post that was originally published on the CFA Institute Enterprising Investor blog.

Over the last decade or so, we have witnessed the proliferation of a new investment style: the copycat investor. The basic idea is always the same. Look at the quarterly reports of prominent investment gurus and their holdings at the end of each quarter. Then simply invest in the same stocks they hold.

There are obvious problems with that copycat investment style since holdings are disclosed only with a substantial time lag, and you don’t know which stocks an investor has bought and then sold again within each quarter. One can only see the holdings per each quarter end. But if the investment guru is a long-term investor and holds mostly stocks and very little in terms of derivatives or private assets, the copycat strategy might just work.

In the United States, where these copycat strategies have been put into action via ETFs we can by now look at a relatively long track record that – crucially – includes the bear market of 2020. To the best of my knowledge there are three such ETFs out there, all of which exclusively invest in US stocks and should thus be compared to the S&P 500: The Global X Guru Index ETF (GURU) has $74m in AUM and tracks the positions of thousands of hedge fund managers, The AlphaClone Alternative Alpha ETF (ALFA) has $32m in AUM and tracks the holdings of c.500 hedge funds, and the Goldman Sachs Hedge Industry VIP ETF (GVIP) has $220m in AUM and tracks the 50 stocks held most frequently by hedge fund managers.

Going back to the launch date of the GVIP ETF in 2016, we can see that two of these ETFs have materially outperformed the S&P 500. While GURU has underperformed the S&P 500 by 0.5% p.a. in terms of total returns, ALFA and GVIP have beaten the S&P 500 by 2.% p.a. and 2.6% p.a., respectively.

Performance of copycat ETF since 2016

Source: Bloomberg

Not bad, but that outperformance comes at the price of higher volatility and higher drawdowns during a crisis. The maximum drawdown of the S&P 500 came in March 2020 during the height of the pandemic panic. Back then, the index fell by 19.6%, while GVIP dropped 21.4% and ALFA 25.1%. As the chart above indicates, that meant that the copycat ETFs either lost all the outperformance they created from 2016 to 2020 in one month (as in the case of ALFA) or underperformed the S&P 500 after previously matching its performance (GURU and GVIP). It was only in the recovery since April last year that the copycat funds started to outperform.

And while the GVIP ETF only exists since 2016, we can use the GURU and ALFA ETFs to go back even longer to mid-2012 when these two funds were launched. With almost 10 years of performance to look at, it seems hard to conclude that these copycat funds add a lot of value. Both GURU and ALFA have underperformed by 1.3%p.a. and 1.6%p.a., respectively and had much higher volatility. Note in the chart that the copycat funds tended to do well in the upswing from 2012 to 2015 and then lost all of that outperformance and more in the 2015-2016 correction. It seems very much like these copycat funds are essentially fair weather investments, that don’t perform over an entire cycle. It seems copying from other investors misses one key ingredient for outperformance that I will talk about tomorrow: creativity.

Performance of copycat ETF since 2012

Source: Bloomberg

I love it when I can debunk long-held finance dogma with a simple chart. One such dogma is that we need to have a balanced budget. If a government runs persistent deficits for a long time, investors will become reluctant to hold government debt and demand an increasing risk premium, which will create even bigger deficits and eventually triggers either a devaluation of the bonds or the creation of inflation through money printing or other measures to devalue the bonds in real terms. Alternatively, if a government runs persistently high deficits it will have to eventually raise taxes. Investors, knowing this will reduce investment and thus growth or demand higher wages in order to save for the day when the higher taxes come to pass. Either way, there is theoretically a link between a government running deficits for a long time and inflation following suit.

In the past, I have focused on the link between money printing and inflation and trashed the notion that an increase in the monetary base leads to higher inflation because at the time, some economists pushed that idea to claim that inflation will get out of control. Now that inflation seems to be topping out and their old money printing argument doesn’t work anymore, they are claiming that fiscal deficits will create inflation.

So let’s look at the evidence in favour or against a link between government deficits and inflation. To do this, let’s start with the United States, where this argument is promoted most often. In order to check the long-term connection between government deficits and inflation, I have done what I did in my previous post on the link between money printing and inflation: I look at rolling 10-year averages. After all, the claim is that persistently high and/or rising deficits should lead to inflation, not that any individual year’s deficit will lead to inflation. This was the argument behind all the fiscal austerity measures promoted in the UK, Germany and other countries after the financial crisis and is again the argument of austerity promoters today.

As you can see in the chart below, there is hardly any connection between deficits (deficits are plotted as positive numbers in the chart below) and inflation. The high inflation in the 1970s was not triggered by high government deficits and the high deficits of the 1980s in the United States did not lead to higher inflation but to persistently lower inflation. The last time we saw somewhat of a link between higher deficits and inflation was at the end of the Second World War when price controls (in place during the war) were lifted and inflation ran rampant. This inflation came about not because the government had run massive deficits in the years before but simply because prices were kept artificially low for years and caught up to real production costs.

US fiscal deficit and inflation (rolling 10-year averages)

Source: St. Louis Fed. Note: Deficits are indicated by positive numbers.

Now, you may say that the United States is just one case and a special case at that because it was the world’s leading economy and in charge of the world’s reserve currency, which means that everybody needs to buy US Treasuries, whether they like it or not. And that may have kept interest rates on Treasuries and inflation low over the last 70 years.

It’s a weird argument, but let’s run with it and look at the UK. Thanks to the good people at the Bank of England, we can check the relationship between government deficits and inflation in the UK back to 1689. Yes, for most of that period, the British Empire was the world’s leading economy and Sterling the world’s reserve currency, but at least since the end of the Second World War, the UK was just a country amongst many without special status.

The chart below shows that during wars, the deficit of the British Empire rose substantially and in many cases this increase in deficits was followed by higher inflation. The War of the Spanish Succession (1701-1714), the Napoleonic Wars of the early 19th century, and the First and Second World War are examples. But outside of these episodes it is impossible to find any connection between deficits and inflation in the UK.

UK fiscal deficit and inflation (rolling 10-year averages)

Source: Bank of England. Note: Deficits are indicated by positive numbers.

Zooming in on the time after the Second World War when the British Empire became history and the UK lost its status as the world’s leading economy, the picture looks even worse than in the United States. In fact, the correlation between deficits and inflation is slightly negative indicating that if deficits rose, inflation tended to drop. In my previous post on the missing link between money printing and inflation, I claimed that monetarists are trying to ride a horse that has been dead for decades. The people who are claiming that deficit spending leads to higher inflation are trying to ride a horse that has never really been alive to begin with.

UK fiscal deficit and inflation since 1940 (rolling 10-year averages)

Source: Bank of England. Note: Deficits are indicated by positive numbers.

This summer, we had so many floods all over the world that it has become hard to count. But the costs to taxpayers and insurance companies are real. Aon estimates that insured losses from natural disasters worldwide in the first half of 2021 were $42bn. Then the European floods hit which added another $2bn to $3bn in losses to insurance and reinsurance companies. And those are just the insured losses. The true economic losses are likely to be about ten times higher than that. In the United States alone, taxpayers are estimated to have paid $99bn in 2020 for emergency relief. And 2021 shapes out to be even more expensive.

Yet, study after study on the assets that are most at risk of floods shows that investors and asset owners are oblivious to that risk. I am talking, of course, about property. You can’t move a house and if it is too close to the ocean or a river, it will inevitably flood after heavy rainfall or as sea levels rise. Yet, a year ago, Justin Murfin and Matthew Spiegel examined sales of coastal properties in the United States and their proximity to flood areas and vulnerability to sea level rise. The result was that they didn’t find a result, i.e. they could not see any difference in house prices between properties at higher risk of flooding and properties at a safe height. There seems to be a political effect, though, with Democrats and Democrat-leaning voters moving away from flood plains and coastal properties and Republicans and Republican-leaning voters moving in. People who don’t believe in climate change are happy to buy beach front properties while people who take climate change seriously move inland with the expectation that in 20 or 30 years, their houses will have become beachfront property. In the United States, at least, the net effect is that more and more people move to coastal regions.

And it seems that moving inland or to higher ground makes a lot of sense. A new study by Claudia Tebaldi and her colleagues estimated the share of coastal properties that are so vulnerable to sea level rise that a once in 100 years flood will start to occur every year. This study piqued my interest because while my house is located in a once in 500-year flood zone in London, I am just one block away from a once in 100 years flood zone in London. So, if the study is correct, not only will I have a much shorter walk to the riverfront, but I have to expect much higher premiums for my flood insurance.

In any way, the chart below shows that even if we manage to keep global warming at 1.5C above pre0industrial levels, in 2030 about 10% of properties worldwide will experience a once in 100 years flood event on average every year. By 2050, this will have risen to 26% and in 2100 to 66%. If we can’t keep global warming below 1.5C as seems highly likely right now, then we have to expect that by 2100, 80% of houses will be exposed to 100 times higher flood risk than today.

Share of locations where 1 in 100-year floods may happen every year

Source: Tebaldi et al. (2021)

Ignoring the societal consequences for a moment, this has significant implications for investors. First, they need to check where the property investments they buy are located. REITs that have lots of coastal properties will likely experience a larger loss in value and income from natural disasters than the average REIT and this higher risk is currently not priced into the value of these assets. Second, if you think about buying a house, please take flood information seriously. You are likely to live in your house for a long time and over time, it will become increasingly likely that flood-prone locations will sell at lower prices than safe locations. If you consider your home a form of investment or retirement savings vehicle, sea level rise can no longer be ignored as a risk factor.

And finally, should you live in an area that is at risk from sea level rise, maybe you want to develop an exit plan where at some point in the future you sell the house before these risks become priced in.

Every so often you read about yet another experiment where monkeys were used to pick stocks for a portfolio and that portfolio outperformed the ones selected by professional investors. I have written about such an experiment in jest a couple of months ago. But as is now widely known, simple equal-weighted portfolios with random assets tend to outperform more sophisticated ‘optimised portfolios’. The reason behind this phenomenon is that in practice, it is very, very hard to forecast which stock is going to outperform other stocks in the same industry, region or the market overall. There are some indications we can get from analysing a stock that allow us to shift the odds in our favour, but truth be told, the uncertainty around any kind of stock market prediction is so large that in practice the odds shift very little if at all. 

But let’s assume that through your analysis you, dear investor, are able to avoid the absolute duds in the stock market. Most likely, if you are able to do that, you are still stuck with hundreds or even thousands of stocks globally that all have some decent prospects for growth and high returns. But hardly any of us can invest in thousands of stocks (unless they simply buy a market ETF), and we want to narrow it down to a handful of the most promising stocks in our portfolio. Once you have eliminated all the obvious outliers wouldn’t it be a good idea to just select your stocks at random from the remaining stocks? The data on stock selection would support such a process but then again, the problem for many investors would be to justify such a seemingly careless course of action.

But now think about a company trying to hire a new top-level executive. Or you trying to hire a new member of your team. Obviously, we are going to select candidates with the best qualifications, some of which like academic qualifications or a track record as a portfolio manager may be measurable. But most of the qualifications needed for the jobs in today’s knowledge economy will be softer. Things like emotional intelligence, the ability to work in teams and think outside the box are hard, if not impossible to measure in an interview process. This is why the overwhelming majority of people are incapable of identifying the best candidate and why job interviews lead to terrible outcomes.

Enter Chengwei Liu who has made a radical suggestion: In some circumstances, it might be best if a company selects people based on a lottery. He argues that when companies hire senior executives the hiring managers tend to hire people that are like them. This is a well-known tendency of all of us. When we can’t decide which one of several individuals is going to perform best at a task, we tend to look for similarities to our own strengths and weaknesses. And because we are obviously successful at our jobs, the person with the most similarities to us is most likely to succeed at the task. The result is that we all have an innate tendency to hire people like us. 

But when it comes to successfully completing complex tasks (whether it is running a business or other tasks) there is a proven benefit to selecting more diverse teams. And I am not talking about ethnic or gender diversity here, but about cognitive diversity. Teams of people with a wide range of thinking and problem-solving modes perform better at complex tasks than teams of people who all think more or less alike. 

To benefit from this diversity bonus and break through our innate tendency to hire people like us, Liu suggests a simple process like the one shown below. Basically, it boils down to first eliminating the inferior candidates by looking at their skills and qualifications. Once the obviously unqualified candidates have been eliminated, one has to ask if there is a risk of making the selection worse by focussing on smaller and smaller details of the candidates’ profiles or using selection criteria that are not predictive of job performance. If that is the case, then it is best to select the candidate via a lottery.

That is, of course, if one can justify to one’s stakeholders (i.e. the boss) the selection process if the randomly chosen candidate is a dud and underperforms. And this is unfortunately the crux of the matter. Because selecting candidates via lottery (just like selecting stocks via a lottery) is so unconventional and so radical, there better be no mistakes. Because every mistake will immediately be interpreted as you not having done your job – even though technically, you have done a better job than most people. 

When is it best to use a lottery to select a job candidate

Source: Lu (2021)

We observe this phenomenon so often in real life. Statistically, it may be better to do nothing or select via a lottery, but most people are not being judged by the long-term average success rate of their choices but by each individual outcome. And if only one of these outcomes is negative (which will happen almost certainly) you will no longer be able to continue your career. This is why goalkeepers in football (soccer) jump into the corner of the goals at a penalty, even though statistically it is better to just stand still and wait until you see where the ball is going. This is why fund managers continue to select stocks based on extremely minor differences in the fundamentals of a company even though a random equal-weighted portfolio would perform better in the long run. And this is why we continue to select people based on interviews rather than lotteries even though the organisation overall would benefit more from a lottery.

Here in the UK, we have seen a massive M&A wave in 2021. Thanks to private equity firms flush with cash, low valuations for UK companies and a relatively cheap Sterling vs the US Dollar, UK small and mid-cap companies have been targeted left, right, and centre. Apart from the usual concerns about foreign takeovers of strategically important businesses, this has also rejuvenated the age-old business of predicting, which company is going to be the next takeover target.

Targeting takeover targets is a siren song that is hard to resist because the returns that can be pocketed on the announcement date of a new takeover are extremely high and can easily surpass 50%. If only there was a way to predict which companies are going to be the next target.

Well, there isn’t. Researchers have tried to identify the driving forces behind a company takeover for more than 50 years now and according to a new review by Abongeh Tunyi from the University of Sheffield we are not only unable to formulate any reliable model that predicts future takeover targets better than chance, we don’t even understand what the driving forces are behind a company becoming a takeover target. Anything from valuation to financial leverage and bankruptcy risk has been examined and researchers have come up empty-handed. In essence, it seems that selecting takeover targets is a more or less random process that has more to do with the psychology of the investor rather than fundamentals.

Yet, both retail and professional investors keep on playing the game. Newspapers write about potential takeover targets and retail investors pile into these stocks in the hope of a quick profit. Professional fund managers may not follow the advice of newspaper journalists and instead use more sophisticated analysis, but they also try to play that game. Though, admittedly, I know of no fund manager who targets takeover targets explicitly. Instead, it is one element of the analysis that may shift the odds in favour of a company. If two companies look equally attractive based on fundamental analysis, the fund manager may invest in the potential takeover target. But even so, targeting takeover targets is a losing game for fund managers. A study of c.2,500 US fund managers and their portfolios showed that the average excess return on takeover targets for fund managers was -0.04% before fees and -1.44% after fees. 

Hence, targeting takeover targets is a bit like playing roulette and putting your money on a single number. If you are lucky that number shows up and you strike it rich, but most of the time you will be a loser.

Over the past week, Chinese military aircraft have entered Taiwan’s defence airspace (which is not the same as its national airspace, by the way) no less than four times. Some aeroplanes even exited Taiwan’s defence airspace along the Bahi Channel which is of extreme geopolitical importance. The Bashi Channel connects the Pacific with the South China Sea and is the main shipping route for cargo ships between East Asia and the West Coast of the United States as well as the location of several main undersea cables that are the foundation of global communication systems.

This was clearly intended as a show of force to the world. Does it mean that we are witnessing the start of an escalating conflict that might end in a military conflict or a blockade of the South China Sea? I think not. At least not yet.

But it reminds me of crucial mistakes that contributed to the outbreak of World War I. Back in 1898, Germany had the world’s most formidable land army but a weak navy. Meanwhile, the British Empire’s global influence rested on the unassailable might of the Royal Navy. In 1898, the second-worst political leader Germany ever had, Kaiser Wilhelm II, was no longer advised by the political genius of Otto von Bismarck and decided to try to challenge the British Empire. Under Admiral von Tirpitz, German military expenditures were directed mostly to the navy in order to build more and more modern ships that could challenge British supremacy on sea.

While military expenditures overall remained largely constant, this German pivot led to an arms race between the British and the Germans over the coming decade that would sour British political leaders to Germany and tipped British sympathies in favour of France and Russia which ended in the Triple Entente and British involvement in World War I on the side of France and Russia.

Military expenditure as share of total government expenditure pre-World War I

Source: Eloranta 2005. Note System total = 16 largest military powers.

Today, China has the world’s largest army by conscription and the People’s Liberation Army is possibly the world’s mightiest land army. Meanwhile, the US Navy and Air Force are unassailable and guarantee US military supremacy around the globe. But while official military expenditure as a share of total government expenditure is declining, the Chinese are rapidly modernising their navy and air force and have entered an arms race with the United States in crucial 21st weapon technologies like drones, submarines, and military AI.

Military expenditure as a share of total government expenditure

Source: World Bank

Today, China’s navy and air force are too weak to challenge the United States and launch an outright assault on Taiwan or a blockade of the island. But in my view, China is catching up quickly and I wouldn‘t be surprised if, within this decade, China’s military can achieve parity with the United States on a regional basis.

And once that is achieved, the room for error is dramatically reduced.

Note that the United States has just suffered a massive defeat with its botched exit from Afghanistan after a long and costly war that couldn’t be won. US military supremacy in the world is increasingly questioned due to its military failures in Iraq and Afghanistan.

Similarly, the early losses of the British Army against a relatively untrained and unsophisticated army of farmers in the Second Boer War marked the end of unquestioned military supremacy of the British Empire. And let’s not forget the rather embarrassing ‘victory’ of the British in Afghanistan in 1880 or the need for an alliance of eight western armies to defeat the Boxer Rebellion in 1900.

It is only a matter of time until a rising Chinese military might miscalculate and decide to test US resolve to defend Taiwan. Just like the British Empire didn’t have a formal treaty with France and Russia to come to their aid should they be attacked by Germany, Taiwan and the United States have no formal defence alliance either. Chinese military leaders may think that the United States would shy away from military confrontation and thus make a crucial mistake that could lead to a rapid escalation of tensions to the point of war.

But as I said above, I think we are not at that point, yet. So far, Chinese leadership has been cautious not to escalate the situation too much to cross any red lines. But with waning US military leadership and a declining power gap in the South China Sea these red lines will become fainter over time.

Some time ago, I have written about Henrik Bessembinder’s analysis of stocks with extreme returns in the past. His analysis suggests that there are a couple of fundamental indicators that can be useful to narrow down the list but even so, these factors only explain 2% of the variation in stock returns. In other words, finding the next multibagger stock based on fundamental analysis is a fool’s errand and mainly a matter of luck.

But what about using simple momentum? How likely is it that a stock that has multiplied in value fivefold does so again, and again, and again? Bessembinder’s latest paper provides some interesting answers to that question.

First about 45% of all stocks that listed in the United States between 1950 and 2020 managed to get to 5x their market value from their all time lows. But once a company has multiplied by five, about three in ten of these stocks go on to multiply their market value again by 5x. Of those companies that managed to multiply by 25x, about three in ten go on to multiply their market value again by 5x (now ending up with 125x the market value of their all time low). And of these another three in ten stocks multiply once more by 5x. That means that one in eight stocks manage to multiply their market value by 25x, one in thirty stocks go to 125x and one in a hundred stocks go to 25x! Restricting the sample only to stocks with a minimum market value of $500m by the time they have multiplied 5x doesn’t change these probabilities. Only if you ask how many companies do each multiplication in less than 10 years, you get somewhat lower probabilities, but even so they stay remarkably constant for each hurdle as well.

Probability of multiplying market value 5x again and again

Source: Bessembinder (2021)

So, extreme performers aren’t that rare. And because the probability of multiplying 5x when a company has done so before is relatively high, one has to wonder if one can’t just buy stocks like Apple, McDonald’s, Walmart or Franklin Resources (all of which have managed to multiply 25x from their all-time lows) and hold on to them?

The problem with that strategy is that the extreme returns are extremely lumpy as well. The chart below shows the average return vs. the market in the 10 years before a stock hits a 5x multiple. Most of the time, these stocks perform pretty much in line with the market, and only in the two to three years before they eventually hit their 5x multiple do they start to outperform. And even so, almost all of the return comes in one year.

Average return vs. market in the years before a stock hits 5x

Source: Bessembinder (2021)

But if the first multiplication “announces itself with a couple of years of outperformance vs. the market, what happens after a stock hits 5x should make you worry. Returns are all over the place in the ten years after that. There simply is no “long-term momentum effect” that would ensure that stocks that have done extremely well in the last decade will continue to do so in the next few years or even the next decade.

In the end, it all boils down to the same message once again: Finding extreme performers is a matter of luck not skill.

Average return vs. market in the years after a stock hits 5x

Source: Bessembinder (2021)

When I talk about climate change and its impact on investments, I tend to observe more scepticism in the United States, Australia, and the Middle East than in Europe. There is obviously a pattern here in the acceptance of climate change and its impact on the planet and financial markets across different regions because, well, the United States, Australia, and the Middle East are three regions with an economy that depends heavily on the production and export of fossil fuels.

Yet, if you go and ask the leading finance professionals in academia, public and international organisations, and private organisations like think tanks the picture changes significantly. There is enormous consensus amongst the people who are at the cutting edge of research in climate finance. Johannes Ströbel and Jeffrey Wurgler from NYU asked 861 top finance professionals about their attitudes on climate change and how it impacts financial markets. Most notably, while 55% of respondents of this survey were academics, 36% were lead economists at private institutions, and 9% at public institutions like the World Bank or the IMF. And only about half of the respondents worked in climate finance, while the other half were outside observers of the field and had no personal research interest in the relationship between climate change and financial markets.

So, what do these experts on financial markets think about climate change? The responses are remarkably similar across regions and professions. Asked about the most important climate-related risk in the next 5 years, all of them came up with regulatory risks as the most important ones. No matter if you asked academics or private-sector economists, people in North America, Europe, or Asia, people who worked in climate finance or not, they all said regulatory changes like the introduction of a carbon tax are key risks for the next 5 years. Looking further ahead, there is also a consensus that over the next 30 years, physical climate change poses the biggest risk for markets and investments.

Furthermore, there is a clear consensus that these risks are currently not priced correctly in financial markets. While almost no one believes that climate risks are overpriced in stock markets at the moment (the share of respondents who believe this is generally less than 3% in each group), about three times as many experts think that climate risks are not priced enough rather than priced correctly. Also, by a margin of two to one, experts generally think that climate risks can be captured by investors in both good and bad economic times compared to good economic times only. In other words, there is a strong consensus that climate risks are underpriced at the moment, which means that active managers who can identify these risks and their impact on stocks can create additional performance, both in good and bad economic times.

Are climate risks priced correctly in stock markets?

Source: Ströbel and Wurgler (2021)

We all know that people are susceptible to soft forms of influence. Why do you think companies spend tons of money on wining and dining their clients and why more and more companies introduce rules that their employees cannot accept gifts worth more than a certain amount?

But in the world of internet purchases this social component is increasingly reduced to a couple of emails and phone calls. In many instances, particularly since the onset of the pandemic, buyers often don’t even know how the person they order from looks like. And this leads to worse outcomes for both the buyer and the seller.

A new study tried to assess the impact facial attractiveness has on the decisions of both buyers and sellers. When I read about that study, I first thought: “Here we go again. Another study that shows that attractive people are treated better than unattractive people.” But the results are more interesting than that.

The study asked participants in a lab experiment to take the role of a wholeseller, or a retail customer of the wholeseller. First, the wholeseller was asked to quote a price for the goods to sell. The retailer, once he has been quoted a price is then asked to place an order choosing how many items to order. Depending on the experimental setup, either the retailer or the wholeseller or both would see the face of their counterpart in the transaction or they would not see a face at all. Furthermore, the faces shown to them were standardised and could be either attractive or unattractive, male or female.

Faces shown to the participants in the experiment

Source: Starostyuk et al. (2021)

The first  result, and probably the least surprising, is that if people were shown faces of their counterparts in the negotiation gave significantly better conditions, that is the wholesellers were offering lower prices and the retailers ordered more items. We humans are social animals and dealing with a human (even if it is just a face on an email as in the experiment) makes us more socially minded and both sides in a trade get a better deal.

The experiment didn’t test for a difference between faces shown in an email or on a screen and personal interaction, but I am pretty sure that the work-from-home crowd does get a worse deal than the people who personally meet with their clients. Similarly, I am pretty sure that when it comes to promotions and other career benefits, the work-from-home crowd that are more remote and have fewer in person interactions with their colleagues and bosses will get fewer promotions and lower bonuses.

In any case, besides the obvious benefits of seeing someone’s face, there are also gender and attractiveness effects. First, women get a better deal, but that is not dependent on the attractiveness of a woman. Wholesellers offer a lower price to unattractive and attractive women alike and retailers order a larger quantity from women than they do from men.

But aside from this gender effect there is also an attractiveness effect, though that effect is less pronounced  than the pure gender effect and – at least in the experiment – it seems to work better for attractive men than for attractive women. Essentially, attractive women are quoted pretty much the same price by the wholeseller than unattractive women, but attractive men are quoted a lower price than unattractive men. And when it comes to the retailer’s orders it is again the attractive men that receive the bigger orders, not the attractive women. The beauty premium seems real, but it is ironically mostly a male beauty premium, not a female beauty premium.

As we head into the final quarter of this year, corporate executives and analysts have to shore up their forecasts for next year’s earnings growth. In a world where corporate guidance on earnings is common place, most analysts are taking their cue from the people who should know best what the prospects for next year are: CEOs and CFOs.

Unfortunately, forecasting is hard particularly the future and corporate executives are no exception. It’s not that they consciously mislead the market. A new paper shows that there is no systematic exaggeration of earnings forecasts by managers. Instead, managers fall for simple extrapolation bias. They look at earnings this year and then simply assume that this year’s growth is a good indication for next year’s growth. But because strong earnings growth tends to weaken over time (and weak earnings growth tends to strengthen), the managers that extrapolate the most and have the highest current earnings growth tend to make the biggest error in their forecasts. This effect is so big that in the long run, companies with the highest projected earnings growth underperform the companies with the lowest projected earnings growth.

This simple extrapolation of current earnings growth becomes particularly fraught with error after a year like 2021. After all, the growth rates many companies saw this year are extremely high and heavily distorted by the low base from the pandemic. For investors, it is worth knowing that this year corporate executives likely overestimate next year’s earnings growth by a wider margin than normal. And it is useful to know which company executives are more likely to extrapolate current earnings into the future and become too optimistic about 2022.

As I said, some fraudsters and con artists aside, corporate executives make an honest attempt at forecasting next year’s earnings accurately. And the ones that do worst are the ones that work at companies that have earnings that are particularly hard to forecast.

Managers in companies with very erratic earnings are more prone to extrapolate this year’s earnings growth into next year. After all, if your earnings are all over the place, it is difficult to make accurate forecasts and you are likely to use current earnings as a stronger anchor for your expectations.

The second group of companies that tend to suffer from extrapolation bias are companies with very salient earnings. A company that has long been loss-making but this year became profitable for the first time ever (or at least in many years) is more likely to extrapolate the success of this year into the future. On the other hand, companies that did poorly this year will be more cautious in their earnings forecasts, even if this year’s poor results were clearly a one-off and are highly unlikely to repeat next year. These are the companies that are more likely to surprise to the upside next year and outperform.

I recently wrote a post about the empirical observation that the bulk of the alpha generated by active managers is generated by their high conviction bets while their low conviction active bets tend to have a zero or even negative contribution to the portfolio’s active performance. The natural conclusion of that research is that active manages should run more concentrated portfolios focused only on their high conviction ideas. This was challenged by a reader with two interesting reports that argued that concentrated high conviction portfolios were not better due to a host of reasons. I encourage you to go to the comments section of the link above and read the posted notes and my responses.

But one challenge was really interesting. The reader pointed out the findings of the research by Hendrik Bessembinder some of which I have discussed here, here, and here. In essence, Bessembinder shows  that the performance of the US equity market is highly concentrated in a few superstar performers, while the majority of stocks have poor performance and even underperform government bonds. This, Bessembinder argues, means that more diversified portfolios should have a better chance of good performance because they cast a wider net and thus have a higher likelihood of catching these superstar stocks.

I think this is too short-sighted, because while a more diversified portfolio has a higher likelihood of being invested in these superstar stocks, the performance contribution of these stocks to the overall portfolio is smaller. This is a result of the unfortunate reality that every portfolio has capital constraints. No portfolio manager can increase her investments infinitely, either because they are long only and thus can only invest the money they manage, or because they have lending constraints and can’t borrow infinite amounts of money to invest in stocks.

So, let’s have a look at how active portfolios perform in a market where stock performance is highly concentrated. To do this, imagine a stock market with 100 stocks. 99 of these stocks have a return of 0% and one stock has a return of 1000%. The average return of the stock market with all stocks weighted equally is 10%.

Now, let’s assume there are three different investors in the market:

• The passive investor buys all 100 stocks in equal amounts and thus replicates the market.

• The diversified active manager runs a portfolio of 50 stocks all equally weighted at 2% in the portfolio.

• The concentrated high conviction active manager runs a portfolio of 20 stocks all equally weighted at 5% in the portfolio.

To get a feeling for the performance of these three investors let’s first assume that they are all unskilled and no better than chance at picking stocks. The table below shows the resulting expected return of the three portfolios (before fees and costs) and the type I and type II errors. The type I error is the probability of accepting a truly unskilled manager as skilled based on her outperformance. The type II error is to falsely classify a skilled manager as unskilled based on her underperformance. To get an idea of the size of error that can be made by investors I have (unscientifically) just added the probability of a type I and type II error (please no complaints, this is just a back of the envelope calculation).

Performance of unskilled managers with different investment approaches

Source: Liberum

As expected, the unskilled managers on average create no outperformance over the passive fund. But because the more diversified portfolio has more stocks in it, there is a 50% chance that some unskilled manager will accidentally stumble on the superstar stock and outperform the market due to the higher weight of the superstar stock in the active portfolio vs. the market. Meanwhile, in the concentrated portfolio, there is only a 20% chance that some unskilled manager will accidentally invest in the superstar stock and be identified as skilled, even though she isn’t.

Which brings us to lesson 1: In a concentrated portfolio, it is harder for unskilled managers to pass as skilled.

Now assume we have active managers who are skilled. But skill comes in different shapes. Let’s assume that the diversified active manager has 20 high conviction ideas, while the remaining 30 stocks in her portfolio are low conviction ideas. The concentrated active manager meanwhile also has 20 high conviction ideas but doesn’t invest in any stocks outside these. Now assume that the skill of the active fund manager comes in the form of a 50% better than chance likelihood of finding the superstar stock in the market and classifying it as a high conviction idea. Yet, the fund manager still continues to invest equal amounts of money in each of the stocks in the portfolio. The table below shows what happens then.

Performance of skilled managers with different investment approaches where skill comes as the ability to identify outperforming stocks

Source: Liberum

In this case, the skill of the active manager leads to outperformance vs. the passive fund. But because the weight given to each stock in the more diversified active fund is 2% while the weight given to each stock in the more concentrated fund is 5%, the expected outperformance of the concentrated portfolio is larger than for the more diversified portfolio. The probability of an unskilled manager to accidentally stumble on the superstar stock and outperform is unchanged to the first case above, but the probability of a type II error (i.e. an active manager underperforming and being classified as unskilled) is lower for the more diversified portfolio. The total likelihood of committing a type I or type II error is, however, the same in both cases.

Which brings us to lesson 2: More concentrated portfolios increase the career risk of skilled managers (i.e. being skilled but falsely classified as unskilled by asset owners).

Now, let’s go to the final iteration of our thought experiment. Assume that the active managers are skilled but not in identifying the superstar stock. Instead, they analyse each stock and based on that analysis, they put a higher weight in their portfolio on high conviction stocks. The more diversified active manager increases the weight of her 20 high conviction stocks from 2% to 3% in the portfolio and reduces the weight of the 30 low conviction stocks to 1.3%. This is not an option for the concentrated active manager because she only invests in her high conviction stocks anyway and thus invests 5% in each of these 20 high conviction stocks. The table below shows that that does to the expected return and the type I and type II errors.

Performance of skilled managers with different investment approaches where skill comes as the ability to increase the weight in high conviction stocks

Source: Liberum

Now, the outperformance of the skilled manager with the more diversified portfolio disappears while the outperformance of the skilled manager with the concentrated portfolio remains unchanged. The reason why the skilled manager with the more diversified portfolio suddenly no longer outperforms is that while the weight of the high conviction stocks increases the weight of the low conviction stocks declines. If the diversified active manager picks the superstar stock as one of his high conviction stocks, the outperformance will increase, but if she picks it as a low conviction idea, the outperformance will decline. Because there are 20 high conviction stocks in the portfolio and 30 low conviction stocks, the outperformance on average declines and in this case ends up disappearing altogether.

But the more important consequence of this phenomenon is that the probability of a type II error (falsely identifying a manager as unskilled even though she is skilled) increases. Thus, in this scenario, there is a high risk of falsely identifying an unskilled manager as skilled and a similarly high risk of falsely dismissing a skilled manager as unskilled. A diversified active portfolio becomes the worst of both worlds.

Which brings us to lesson 3: In a more diversified portfolio, a skilled manager has less room to create outperformance, which increases her career risk.

Looking at all these three cases in combination, we finally come to the final lesson for asset owners:

Lesson 4: In a more diversified active portfolio asset owners have a higher risk of falsely sticking with an unskilled manager while maintaining a significant risk of firing a skilled manager. Overall, the likelihood of making the wrong decision in selecting a fund is at least as high and sometimes higher for a diversified active portfolio as for a concentrated active portfolio.

Imagine you are an investor, and you are convinced one of the stocks in your portfolios is going to grow strongly. Then, the company beats earnings estimates at the next results season but it also revises its growth outlook downward. It’s easy to dismiss this weaker growth outlook in the light of current strength in the business and you might be tempted to hold on to the stock.

Alternatively, imagine your outlook for another stock is rather pessimistic, but at the next results presentation, the company presents shock and awe results that blow away all the estimates of professional equity analysts. If the results are strong enough, you might well be tempted to change your view of the company and even buy some of its shares given the strong results.

I am oversimplifying things here, but this is what I see happening so often in markets, particularly during results season. Companies can present blowout results that will not only make the stock leap but also change the consensus expectations about the future prospects of the company amongst investors. But is a blowout quarter or even a blowout year predictive of future success?

Meanwhile, companies can manage to beat expectations quarter after quarter and keep their share price aloft while at the same time quietly chipping away at their long-term growth prospects until, of course, one day, they can’t beat earnings expectations anymore and the disappointment amongst investors will tank the stock.

The job of equity analysts, fund managers, and investors, in general, is to analyse corporate results for signals about the future prospects of the company. The problem, however, is that a signal has two components, reliability and strength. A signal can be a reliable predictor of the future but have very low strength like the company’s assessment of long-term future growth prospects. Or it can have large strength but be an unreliable predictor of future results like shock and awe earnings growth in the past quarter.

Of course, we all would love to have signals that are both strong and highly reliable but in the real world that rarely happens. Instead, we investors have to sift through a variety of signals both strong and weak, and focus on the ones that are relevant while ignoring the ones that are not.

Unfortunately, it seems we are doing a lousy job at that. José Astaiza-Gómez has looked at the earnings estimates and buy recommendations of equity analysts and the revisions to these estimates and recommendations. He found that analysts tend to ignore evidence that contradicts their previously held belief about a stock until the signal strength becomes very large (he found a tipping point somewhere around the top 20% in signal strength). Then they revise their opinions and estimates. So, analysts react to signal strength and tend to revise only once the signal has crossed a certain threshold. But do they react to all signals or p0nly the ones that have some reliability in forecasting the future? Unfortunately, he found no evidence that analysts take the reliability of the signal into account when reacting to a signal or revising their forecasts. They are reacting to signal strength but not to signal reliability.

And that is a problem because that opens the possibility of company management manipulating the share price with shock and awe results and the market becoming inefficient because reliable but weak signals are not incorporated ion the share price. Hence, investors who are able to identify signals that have high reliability even if their strength is low can earn superior returns. 

The preferences of retail investors for sustainable investments over traditional investments are well documented. Investors are even willing to accept lower returns or higher costs for the benefit of owning sustainable investments.

And in the past, it was justifiable for advisers to charge higher fees for managing portfolios that are sustainable compared to traditional portfolios. After all, with a lack of sustainability information and a sustainable products, it required considerably more effort to build a sustainable portfolio than a traditional one.

But today, the availability of information is much better, and sustainable funds are available everywhere. The hard work today is less about identifying which stocks or funds are sustainable, but which ones of the many sustainable funds are engaged in greenwashing and which ones do a really good job.

Yet, advisers seem to continue to charge higher fees for sustainable portfolios while not exerting any more effort to manage these portfolios when compared to traditional portfolios. A recent study recruited 345 advisers in the United States for an experiment. They were asked to create equity portfolios for hypothetical clients some of which wanted sustainability criteria integrated into their portfolios while others didn’t. Once the advisers had selected the stocks for the client portfolio, they could charge the clients a fee for managing it. 

The result was that on average, the sustainable portfolios were offered at a fee 5bps higher than a traditional portfolio. You may say that this additional charge is reasonable given that advisers have to be more selective when picking their stocks and have to include additional information.

When the researchers asked the advisers before they selected stocks what the outcome of the result was, the advisers openly acknowledged that they expected sustainable portfolios to come at a higher fee, but they also expected that they would spend more time selecting stocks and constructing these portfolios.

But when the researchers tracked the work of the advisers in selecting the stocks and constructing the sustainable portfolios there was no meaningful difference. In fact, both in terms of time needed to select the stocks and construct the portfolio as well as in terms of clicks to collect the information about the stocks there was no difference visible. Unconsciously (or maybe consciously), advisers charged their clients a higher fee for the same amount of work and effort. And personally, I don’t think this behaviour is sustainable in the long run.

On Sunday, Germany will elect a new parliament and with it a successor for Angela Merkel. After the election Merkel will remain in office until a new coalition is formed and a new chancellor elected. After 16 years in office, Merkel led Germany and the European Union through three major crises, starting with the Global Financial Crisis in 2008, followed by the European Debt Crisis in 2011, and then the pandemic in 2020.

That her policies have been criticised by left-wing politicians is no surprise. After all, Merkel and her party are Germany’s conservatives and ostensibly follow centre-right policies. Yet, Merkel has invited a lot of criticism from conservatives alike and in particular from conservative pundits and politicians in the United Kingdom and the United States. Yet, despite the dire warnings of these Anglo-Saxon “experts”, the European Union is alive and well and the Euro is still around. And in my view, no one can take more credit for that than Angela Merkel.

It is instructive to see how far detached from data and facts her critics on the right have become and how ideologically blinded especially the conservative wings of the UK Conservative Party and the US Republicans have become. It shows how ideologues need to ignore reality in order to keep their ideological system intact in the face of contradicting evidence. And it shows why countries that elect ideologues and extreme parties (be it on the right or left wing of the political spectrum) always suffer economically. And it is the reason why I am a radical centrist and a technocrat when it comes to politics.

To do this, let me take a couple of quotes from an opinion piece by conservative commentator Allister Heath published in the Telegraph on 1 September 2021. What starts out as a critique of Boris Johnson quickly turns into a comprehensive takedown of Angela Merkel’s 16 years in office.

Heath writes: “The German Chancellor’s strategy was to put herself first, and to court popularity by making all sides believe she was one of them” just to add a few lines later that “her mishandling of the 2015 refugee crisis fuelled the populist Right and created a permanent fissure with Eastern Europe which, in time, will destroy the EU”.

That is an obvious contradiction though cleverly disguised by taking these two sentences apart from each other and digressing into other ad hominem attacks in between. But Angela Merkel was not a populist who put popularity above the good of her country. Her actions during the 2015 refugee crisis were severely criticised by her own party and fuelled the rise of the populist right because they were so unpopular. The chart below shows Angela Merkel’s popularity figures during her time in office and in 2015 her willingness to accept refugees with an open border policy cost her dearly in terms of popularity.

Merkel’s popularity amongst voters

Source: Politbarometer

On her economic record, Heath writes: “Its economy only survives thanks to her predecessor’s labour market reforms, and the fact that the euro is much cheaper than the Deutsche Mark would have been” and “the result is a gigantic, disastrous mess: a Germany in structural decline, the most over-rated political leader of her generation, and yet the most popular”.

To which I say that first, it is ironic that a conservative commentator credits her predecessor with labour market reforms. Did he forget that his predecessor was the centre-left social democrat Gerhard Schroder? And even so, the facts don’t prove him right. I have looked at the average annual real GDP growth in Germany during Angela Merkel’s term in office. It was 1.1% per year. That sounds like stagnation and structural decline, but it is still better than the 0.7% average growth over the same time by the Eurozone overall. And since Heath likes to think that the Brits do everything better, let me clear that up. Over the same time period, the average UK real GDP growth was 0.6% per year. Compounded over the 16 years of here chancellorship it means that the German economy has created 7% more income and wealth than the Eurozone on average and 10% more income and wealth than the UK.

Now, I can hear conservatives in the UK claim that this is all fine and well, but the UK had a Labour government until 2010 and was only governed by the Tories since December 2010. Starting in 2011, the average real GDP growth in Germany was 1.25% vs. 0.8% for the Eurozone overall and 0.8% for the UK. Over the last decade, Angela Merkel and her government have created about 5% more national income and wealth than the UK government has.

And unlike the UK government or the Eurozone overall, this growth did not come at the expense of future generations. Germany’s debt/GDP-ratio declined by 4.8 percentage points during her time in office. Over the same time, the Eurozone’s debt/GDP-ratio increased by 29.6 percentage points and the UK’s debt/GDP-ratio increased by 78.3 percentage points. When Angela Merkel became chancellor, the UK’s net debt was half that of Germany in terms of GDP. When she leaves office, the UK will have twice as much debt relative to GDP than Germany. When it comes to fiscal discipline and not living off borrowed money no country (except maybe Switzerland) even comes close.

And with regard to the point of a weak Euro let me give you some more facts. During her time in office, the Euro has appreciated(!) on a trade-weighted basis by 3.0%. Over the same time, Sterling has depreciated 25.0%. During the time of a conservative government in the UK, Sterling depreciated on a trade-weighted basis by 3% while the Euro depreciated by 1%.

It is a persistent myth in Anglo-Saxon countries that the Euro is a weak currency when in fact it is Sterling that is weak and should have given the UK economy a growth boost that has narrowed the growth gap between the UK and Germany.

Plus (and my conservative readers may forgive me for that comment), if the weak Euro was such an advantage for Germany, I suggest the UK abolishes Sterling, adopts the Euro, and re-joins the EU?

Finally, Heath states that Germany has a decrepit infrastructure and is in terrible shape and bound for structural decline. Well, the WEF’s last assessment of the competitiveness of different countries puts Germany in 7th place vs the UK in 9th. Germany’s infrastructure is ranked 8 in the world vs. the UK in 11th place. When it comes to having a skilled workforce, Germany ranks 5th, while the UK ranks 11th. And in the category of business dynamism, Germany ranks 5th, while the UK is in 9th place.

In other words, Angela Merkel leaves behind a dynamic economy that is growing at a faster pace than the majority of other European countries despite the headwinds of a stable to stronger Euro. And she did all that without the use of government deficits to inflate growth.

And in my view, the reason why she achieved that is because she is not associated with any ideology or grand plan of how the world works. Heath criticises this lack of beliefs as a negative, but in my view, it is exactly why she was so successful. Angela Merkel is at heart a technocrat and that is a good thing. Instead of dithering about keeping the economy open as so many politicians did during the first stages of the pandemic, she followed the evidence of scientists and probably saved thousands of lives. And guess what, against the dire forecasts of conservative pundits, locking the economy down in spring 2020 didn’t cause the end of the world. Germany’s economy declined, but far less than the UK economy.

Throughout her career, Angela Merkel was willing to follow the evidence and the data no matter where it took her. Did that lead to mistakes? Absolutely. We know today that austerity measures to reign in debt in Southern European countries were counterproductive and caused more harm than good. But back in 2011 it seemed like the sensible thing to do based on empirical evidence and data. Nobody knew back then that in a low interest rate world, austerity measures have a different effect than in a high interest rate world. A decade later, our knowledge has evolved and so have my views and Merkel’s views. Why else would she have agreed to the pandemic bonds and effectively the introduction of Eurobonds in spring 2020 which also means that another European debt crisis like the one in 2011 can never repeat itself?

I don’t agree with all of her policies, though. I think her appeasement politics towards Russia (e.g. the Nordstream 2 pipeline) and her exit from nuclear power in 2011 while giving in to the German energy lobby’s desires to continue to run lignite and coal power plants are a historical error. Nevertheless, Germany is at the forefront of the green revolution and will be one of the first countries in the world to become fully sustainable. In the end, her pragmatism may have led to some policy mistakes but on the whole, I think Angela Merkel was popular in Germany and abroad not because she was a populist, but because she was competent. And that is more than can be said for almost all political leaders these days.

When I was much younger than today, and still enjoyed the benefits of youth like a concave belly, we used to say that when the US sneezes, the rest of the world catches a cold. Today, that still is true, but the same can be said about China – at least if you live in Europe or Asia.

The common explanation for the steeper declines in European asset prices when there was a crisis in the US was the international trade links between Western Europe and the United States. But in 2008, the housing market collapsed in countries like the United States, the UK, Ireland, while Germany or Switzerland had no housing crisis at all. Yet, German stock markets were down more than US stock markets.

In fact, a recent study showed that only about one-third of the spillover from US crises (and I presume Chinese crises) to other countries is explained by macroeconomic ties between countries. The other two-thirds are explained by financial market integration. Countries where institutions and households own a larger share of their wealth abroad and where their assets are held all over the world experience steeper declines in asset prices.

The driver of these steeper declines is quite straightforward. First, when the US economy hits a rough spot economically, US investors think about their investment portfolio. Psychologically, they will reduce their holdings in assets they are less familiar with and that thus appear to be riskier. This means they will keep their US stocks, but sell their foreign stocks. But also, they will tend to sell more of the stocks in countries that are heavily integrated with the US stock market, that is UK, Western Europe, and developed Asia. Why? Because it makes sense. First, these markets are typically the most liquid, so it is easy to sell these stocks at a moment’s notice. Second, because these markets are so integrated with the global markets and your home market, they offer less diversification benefits. Technically speaking, their correlation to the US market is so low that there are diversification benefits to be had, but these diversification benefits are so subtle that for most investors it simply appears as if the correlation between US and European stocks is about 1.0. When the US goes down, so do the UK and Europe. And as a result of this mental shortcut, US investors tend to sell UK and European stocks more than emerging market stocks, for example. And it is this psychological effect that creates a higher correlation and becomes a self-fulfilling prophecy. Because people think European stock markets are highly correlated in a US downturn, they act as if they were and sell these stocks first. And these actions in turn increase the correlation and turn perception into reality.

So the next time something happens on the economic front in the United States of China and somebody tells you that it is all going to be contained because it is a purely domestic problem, make sure you check the list below and look at the financial integration of different countries. The countries with higher financial integration will sell off more, whether that makes sense economically or not.

Financial and trade integration of different countries

Source: Londono (2021)

On Monday I ranted a bit about benchmarking and how it turns businesses and asset managers into mediocre performers. The argument I often hear in favour of benchmarking is that it limits underperformance and the damage done by inferior managers.

On the other hand, in recent years, the evidence has mounted that fund managers generate their performance almost exclusively from their high conviction overweights. 

Average annual outperformance of US equity fund managers net of fees

Source: Panchekha (2019).

So, fund managers have started to create high conviction funds as a way to counteract the trend towards passive investing and closet indexing. But, a new study argues that a key problem for fund managers is that if you reduce the number of stocks in your portfolio you may need a different approach to identifying the right assets and constructing the right portfolio. This is true and I recommend this article as the first stop for those who want to become more active and think about what that means for their portfolios. 

But the study also argues that being active alone is not enough to create outperformance.

No kidding.

That is the whole point about being very active. Both outperformance and underperformance are more accentuated, making it easier for investors to identify which fund managers are doing a good job and which ones don’t. This way the underperformers have fewer places to hide and will hopefully exit the market instead of being able to stay around for years as closet indexers convincing their clients to give them one more chance since the underperformance so far wasn’t that bad and one can catch up in the right environment (which of course is true for a truly active manager but an illusion if the fund is a closet indexer).

If the active fund management industry wants to grow its assets it needs to weed out the unskilled managers that stick around forever and are able to dupe investors year after year. And being highly active makes it harder for the truly unskilled managers to hide and easier for the truly skilled managers to shine.

In my job at Liberum, I run 10 model portfolios with 20 stocks each, so they are highly active and highly concentrated. Yet, since I launched these portfolios in spring 2020, they have outperformed their benchmark by 15% to 35% after transaction costs (and if you are interested in getting these portfolios you have to become a research client of Liberum). Obviously, a track record of 15 to 18 months in my current role is too short to draw conclusions if I am skilled or not, though my previous track record as a fund manager from 2010 to 2016 indicates that this outperformance is no accident. 

Nevertheless, the point is that my highly active portfolios outperform their benchmarks by a wide margin after costs both on an absolute and a risk-adjusted basis. So being very active and running highly concentrated portfolios can add enormous value if done right and will mercilessly expose underperformers. And that’s how active management should be. It should be a marketplace for different opinions where fund managers put their money where their mouth is and where underperformers exit and make room for new entrants trying their luck. In my view, we should all encourage more active management but the tendency to benchmark fund managers does exactly the opposite and thus helps to keep the flows from active to passive funds alive and contributes to the demise of active management. It turns the investment world into a world full of mediocre funds.

Many fundamental investors really don’t like the momentum effect. And to be honest, it does feel a bit like an insult to one’s intelligence that after all the hard work of fundamental analysis, one can just go out and buy the stocks that have gone up in the past and buy them it will be fine.

But one criticism of momentum investing is that it is extremely prone to momentum crashes, that is sudden massive downturns that are much worse than what the market experiences at the time. In November 2020, we experienced such a momentum crash after the news of a successful vaccine trial broke, and in spring 2009 when the Fed stopped mark-to-market reporting of liabilities on the balance sheets of banks we had a similar-sized momentum crash. In each of these cases, momentum investors lost several years of outperformance vs. the market in a month or two which is why momentum investing is sometimes compared to ‘picking up pennies in front of a steam roller’.

But what if the steam roller announces its arrival with a loud siren and there was a simple way to get out of its way when it comes too close? That is what a new paper from the University of Münster in Germany suggests. The researchers did something quite simple. They looked at the typical momentum factor (WML for ‘winners minus losers’) which is constructed by buying the stocks with the highest returns from 12 months to one month ago and selling stocks with the lowest returns over the same time period. Then they split this time period into two different periods that vary for each stock. They simply looked at the returns from twelve months ago to the peak share price over the last twelve months (HTP) and the return from the peak share price to the share price a month ago (PTH). And then they sorted stocks based on these two measures and formed the usual momentum portfolios based on them.

The result was stunning. The portfolios formed on the HTP momentum factor not only had a better performance than the traditional momentum factor but showed much fewer momentum crashes. In fact, during the 2009 momentum crash, the HTP portfolios had no drawdowns at all. Most of the stocks that crash seem to be captured by the PTH factor, indicating that before they crash many momentum stocks already stop their advances and start to decline from recent peaks. And by eliminating these stocks from the momentum portfolio investors can drastically reduce the probability and severity of momentum crashes. We need to better understand the causes for this effect but it seems to me that this could be a worthwhile avenue for research since markets often seem to ‘smell a rat’ when they see one.

Avoiding momentum crashes with a simple twist to the momentum factor

Source: Büsing et al. (2021). Note: MKT is the excess return of the US stock market over 3M T-Bills, WML is the return of the traditional momentum factor, HTP is the return of the momentum factor based on historic returns to peak share price, PTH is the return of the momentum factor based on historic returns from peak share price to last month’s share price.

Note: This article originally appeared in the CFA Institute Enterprising Investor blog on 18 August 2021.

Time and again throughout my career I have ranted about the nonsense of benchmarking in all its forms. By now I have given up on the hope that we will ever leave benchmarking in business or investments behind, so I don’t expect this post to change anything except to make me feel better. So, indulge me for a minute or come back tomorrow…

I had a conversation recently with a friend about an organisation that we are both intimately familiar with and that has changed substantially over the last couple of years. In my view, one mistake the organisation made was to hire a strategy consulting firm to benchmark the organisation to its peers. Alas, the outcome of that exercise was to be more like their peers in order to be successful and as a result the organisation engaged in a cost-cutting and streamlining exercise in an effort to increase ‘efficiency’. And guess what, thanks to that effort many people now think that what made that organisation special has been lost and they are thinking about no longer being a customer of it.

The problem with benchmarking a company against its peers is that it is typically the fastest way into mediocrity. Strategy consultants compare companies that have a unique culture and business model to its peers and tell these companies to adopt the same methods and processes that made their peers successful in the past. But benchmarking a company that is about to change the world is outright stupid. In 2001 and 2002 Amazon’s share price dropped 80% or so. If Jeff Bezos had asked McKinsey what he should do, they would have told him to be more like Barnes & Noble.

Name a single company that has turned around from being a loser to a star performer or even changed the industry it is active in based on the advice of strategy consultants…

Or as Howard Marks put it so clearly: “You can’t do the same thing as others do and expect to outperform.”

Which brings me to investing, where pension fund consultants and other companies have introduced benchmarking as a key method to assess the quality of a fund’s performance.

Of course, if you are a fund manager your performance needs to be evaluated somehow, but why does it have to be against a benchmark set by a specific market index? The result of being benchmarked against a specific index is that fund managers start to stop thinking independently. Having a portfolio that strays too far from the composition of the reference benchmark means that a fund manager creates career risk. If the portfolio underperforms by too much or for too long, the manager gets fired. So, the result is that over time, fund managers invest in more and more of the same stocks and become less and less active. And that creates herding, particularly in the largest stocks in an index because fund managers can no longer afford not to be invested in these stocks.

Ironically, by now, the whole benchmarking trend has become circular because benchmarks are designed to track other benchmarks as close as possible. In other words, benchmarks are by now benchmarked against other benchmarks.

Take for instance the world of ESG investing. Theoretically, ESG investors should be driven not just by financial goals but also by ESG-specific goals. So their portfolios should look materially different from a traditional index like the MSCI World. In fact, in an ideal world, ESG investors would allocate capital differently than traditional investors and thus help steer capital to more sustainable uses.

So, I have gone to the website of a major ETF provider and looked at the portfolio weights of the companies in its MSCI World ETF with the weights in its different ESG ETFs. The chart below shows that there is essentially no difference between these ETFs, sustainable or not.

Portfolio weights of the largest companies in a conventional and several sustainable ETFs of the same provider

Source: Bloomberg

The good thing about this is that investors can easily switch from a conventional benchmark to an ESG benchmark without much concern about losing performance. That helps getting institutional investors to switch.

But the downside is that there is little difference between traditional investments and sustainable investments. If practically every company qualifies for inclusion in an ESG benchmark and then has roughly the same weight in that benchmark as in a conventional benchmark, then what’s the point of the ESG benchmark? Where is the benefit for the investor? Why should companies change their business practices when they will anyway be included in an ESG benchmark with minimal effort and don’t risk losing any of their investors?

ESG benchmarks that are benchmarked against conventional benchmarks is like benchmarking Amazon against other retail companies. It will kill Amazon’s growth and turn it into another Barnes & Noble.

CEOs aren’t the kind of people that are commonly known for their humility. Instead, many CEOs are type-A personalities who are extremely competitive. But in some instances, competitiveness can go too far and CEOs in an effort to outdo their peers start to make poor decisions. It’s the classic ‘hold my beer’ moment, where one CEO sees some other guy do something stupid and then decides he can top that.

Nowhere is this reaction more dangerous than at the high stakes game of M&A. The sums involved are large and the impact on a company’s fortunes equally so. Yet, because these are events that often attract a lot of media attention, the temptation to outdo your peers is extremely high for some CEOs. So, instead of acquiring smaller companies that may be a better fit to an existing business and can more easily be integrated into the existing corporate structure (and adopt the existing corporate culture), they are going for fewer but larger mergers and acquisitions. That might end well, just as sometimes a drunk at a bar says ‘hold my beer’ and then performs some amazing feat. 

But usually, giving a CEO a lot of liquidity to spend on M&A is like giving a drunk a barrel of beer. You know exactly what is going to happen, you just don’t know which wall he is going to hit.

Examining 751 takeovers in the UK by 202 CEOs between 2007 and 2016, Tom Aabo and his colleagues showed that some CEOs are prone to making fewer but much larger acquisitions for their firms than others. The humbler CEOs made on average three acquisitions during these ten years, each worth about £57m. The high stakes CEOs, on the other hand, made on average one acquisition worth about £351m.

By pursuing these larger takeovers, these CEOs may strike their egos but create costs for shareholders because the share price reacts much less favourably to these large takeover bids than to smaller ones. On the day of the announcement, the large takeovers on average lead to an abnormal share price increase of 0.6% while the smaller takeovers lead to an abnormal share price increase of 2.7%. and because the CEOs who acquire larger targets do so less often than the CEOs who acquire smaller firms, this effect accumulates over time and leads to a better share price performance for companies that make smaller, less costly acquisitions.

So, who are these CEOs that go for fewer but larger acquisitions? How can we identify them as investors? And how can directors of a company identify them in order to limit their acquisition budgets to avoid destroying shareholder value?

In the above-mentioned study, the CEOs that went big were the ones that showed more signs of narcissistic behaviour. And while the study measured narcissism in different ways all of which had similar outcomes, one easy way to measure it is to listen to the CEOs during earnings calls (or rather, analyse the transcripts of these calls). Narcissistic CEOs use more personal pronouns that point to them like ‘I’, ‘my’, ‘mine’ than personal pronouns that point to a group or other people. The higher this ratio of first person personal pronouns to all personal pronouns is, the more likely it is that a CEO will try to engage in dumb outsized acquisitions that will lead to lower shareholder value.

CEO personality and takeover activity

Source: Aabo et al. (2021)