When I say (or write?) contented life, I mean people would rate their well-being as at least eight out of ten.

The charts below show you what Americans guessed other people needed. As you can see in the top chart, Americans consistently underestimate how much money other Americans need. The bottom chart shows the same effect for beliefs about low-income households.

Indeed, 85% of Americans underestimated how much money the average American needs to live a contented life and 86% of Americans underestimated what a low-income family needs. Ironically, when asked about their own needs, Americans consistently gave higher numbers for their own income needs than what they thought others needed.

How much do you think others need to live a contented life?

Source: Lepinteur and Powdthavee (2025)

Such are the results of a survey of Americans by Anthony Lepinteur and Nattavudh Powdthavee. On average, Americans underestimated the needs of the average American by 12% and the needs of a low-income American by 14%.

This has significant policy consequences, because if you think other people need less money to live than they really do, you will complain about welfare queens and support less government redistribution than if you know how much people really need to live on.

The policy question then becomes whether one can adjust the beliefs of people to more correctly reflect the true needs of other people. The sad news from the study (which has significant limitations in this bit because it only uses a short, written intervention) is that ordinary people don’t change their opinions when they learn how much money other people need to live a contented life.

But under the surface, there is some hope. While the average person did not change their opinion, a significant minority did: those who felt the information given to them was trustworthy and personally relevant.

If you have had personal experiences of being poor or cash-strapped in the past and if you trust the source of the information, you are much more likely to adjust your views and turn in favour of more government redistribution.

I don’t want to go all social justice warrior here, but I very much sympathise with this view. When I had long periods of no income in the middle of my career and was significantly cash-strapped, my views about people struggling to make ends meet changed significantly. In my case, I became much more willing to pay more taxes and much less understanding of people who try too aggressively avoid taxes (or people who move to a tax haven or low tax jurisdiction to save on taxes).

On the other hand, this is why the decades of erosion of trust in politicians, the media and other sources of information are so poisonous for society. As Hannah Arendt observed in “The Origins of Totalitarianism”, the trick of dictators and totalitarian rulers is to undermine the belief of ordinary people in all sources of information. This is why dictators still hold rigged elections. Everybody knows the elections are rigged, but that is the point. Because these rigged elections allow dictators to tell their people that the other elections in other countries are rigged as well.

And this is why the trend towards segregation between different classes of people is so dangerous. When rich people no longer have to mix with poor people (except when they hire them as staff), when the children of rich people no longer go to the same schools as the children of poor people, mutual understanding goes out the window. Rich people no longer have any experience of what it means to live an ordinary life or what ordinary people need to live a content life. And that tilts their political views not only away from reducing inequality but towards efforts to get the most from the government for themselves in the form of lower taxes, etc.

Does that remind you of somewhere?

No, stocks are not a good inflation hedge

LONDON, April 23 (Reuters) - Equities are often viewed as a good inflation hedge, but history shows that real returns on U.S. stocks tend to drop quickly once inflation rates top 3%.

While Wall Street has recently hit record highs amid relief about the U.S.-Iran ceasefire announcement and the related decline ​in crude prices below $100 a barrel, that deal is proving fragile. With inflation already well above the Fed’s 2% target - and more energy-driven increases likely - investors shouldn’t bank on ‌stock markets to protect them from further price increases.

Read the full post here: https://www.reuters.com/markets/us/no-stocks-are-not-good-inflation-hedge-2026-04-23/

To me, there are two provisions in the regulation (and I admit, I read it via Google Translate since no official English translation is available), that I find important and that will likely come into focus in future trade disputes with China.

First, the law establishes an early warning and emergency response system similar to what the EU already has in place. This system monitors potential supply disruptions to Chinese companies in key sectors (which aren’t defined in the law but encompass ‘raw materials, technology and equipment’). If such a disruption is detected, the Chinese government can prohibit Chinese companies from doing business with foreign firms that discriminate against China.

The obvious case where this applies is the current export restrictions by the US and other countries on advanced semiconductors and semiconductor manufacturing equipment. In response to these export restrictions, China can now order any Chinese company that supplies the likes of ASML and TSMC to stop doing business with them.

These anti-sanctions rules are one thing, but more concerning, the new rules can also be triggered by commercial decisions, such as a Western business trying to replace Chinese suppliers with suppliers from other countries. If the Chinese government deems these actions as potentially threatening to Chinese ‘industrial security’, it can place exit bans on foreign businesses and foreign and Chinese individuals. And that is quite an alarming possibility, as the European Union Chamber of Commerce in China has warned. It essentially means that China may prohibit foreign companies from leaving the country, even if they are doing rational things like trying to diversify their supply chains.

If the Chinese government deems these actions a potential threat to industrial security and stability (easy to argue given the larger overcapacity of Chinese exporters in many industries), it can take them hostage or force remaining Chinese suppliers of these companies to stop doing business with them.

If you think the trade war is yesterday’s news, think again. It will come to the boil again; we just don’t know when or where.

Clearly, a commodity like helium is used only in very specific applications, like semiconductor manufacturing, where it can cause a lot of disruption to supply chains. But from a macroeconomic perspective, helium is used so little that it hardly influences consumer prices overall.

Meanwhile, crude oil is used almost everywhere, so being cut off from its supply creates a large impact first on energy inflation and then on consumer price inflation in general.

Niccolo Consonni and Glenn Magerman did something interesting. They tried to identify the commodities and imports in the EU that had the biggest influence on sector inflation and, from there, on overall consumer price inflation. Hence, they tried to identify the combined effect of import dependency, price elasticity to changes in supplies and price elasticity to changes in varieties of imports. The resulting number is what they call the Strategic Dependency Index for each import, and it puts into perspective how much different commodities matter.

The chart below shows the top 20 strategic products imported to the EU as of 2019 (the last year for which full data is available). Note that I had to cut the bar for crude oil short because its strategic importance is (in this case literally) off the scale. For the EU, disruptions in crude oil supply are eight times more important than disruptions in LNG supplies and a hundred times more important than almost all other imports.

Top 20 strategic imports in the EU

Source: Consonni and Magerman (2026)

But once you look beyond crude oil and Liquefied Natural Gas (LNG), you start to get some surprises. Coffee is the fourth most strategically important product for the EU, and cocoa is the fifth. You may laugh about this, but if coffee and cocoa supplies get disrupted, it really matters for inflation in the EU because we drink so much coffee and eat so much chocolate that the impact is quite sizeable.

And we don’t even want to start mentioning all the rioting in the streets when we can’t get our morning coffee anymore. In the Second World War in Germany, people survived on ‘Muckefuck’ (no, it’s not pronounced that way), which was a coffee substitute made from grain or beets, you can still buy something like it in German supermarkets as Caro coffee substitute, and it was so important that it was one of the most important rations during the war in Germany in order to keep morale up. Coffee truly is strategically important, whether you like it or not.

A group of German researchers got access to data from some 27,000 real-world meetings between financial advisers and their clients. Additionally, they anonymously sent actors to 539 advisers to get financial advice. The chart below shows the mystery shopper profiles. Note that in each row, you have a man and a woman with a very similar profile, where the only reasonable difference is the gender of the client.

Client profiles in mystery shopping experiment

Source: Bucher-Koenen et al. (2025)

As you might have guessed, the advice differs by gender:

• Women are some 6% less likely to receive a rebate on a fund they invest in, and if they get a rebate, the rebate for men tends to be some three percentage points larger than the rebate offered to women.

• Women are some 5% more likely to get a recommendation to invest in an in-house fund (where the bank tends to make more money in fees) than men, and a roughly 3% higher likelihood of being recommended an in-house multi-asset fund, and the amount invested in these in-house multi-asset funds is on average a 3.5 percentage points larger share of the total portfolio.

• Within each fund category, 63.3% of men get a recommendation to invest in one of the most expensive funds in its category, but 73.2% of women do.

So, women tend to get fewer rebates and invest in more expensive funds. This is, by the way, not a result of male advisers exploiting female clients. Female advisers do that as well. Instead, the analysis suggests that advisers use gender as a proxy for financial sophistication and consciously, or subconsciously, assume that women are less sophisticated than men. Plus, advisers are incentivised to sell higher margin products, so if you encounter a less sophisticated client, the temptation is to sell them a seemingly simpler, but more expensive product like an in-house multi-asset fund.

But there is one group of companies that seems to benefit from the misguided belief among retail investors that ESG investments help reduce greenhouse gas emissions: asset management firms offering ESG funds.

Florian Heeb, Julian Kölbel, and Camilla Weder surveyed 189 academics and more than 2,000 retail investors in Germany about their beliefs on ESG investments and green funds. The basic disagreement between experts and retail investors is shown in the chart below, which shows how many respondents agree or disagree with the statement that “investing €10,000 for ten years in a green fund makes a relevant contribution to reducing global greenhouse gas emissions”. Most retail investors think so, while most academics disagree.

Do investments in green funds reduce greenhouse gas emissions?

Source: Heeb et al. (2025)

Indeed, if you ask experts and retail investors how much a €10,000 investment in a green fund offsets the average German’s greenhouse gas footprint, most academic experts say zero, with the average expectation a 2% offset or less. Meanwhile, the average retail investor expects that such an investment would offset his or her greenhouse gas emissions by about 10%.

How much does an investment in green funds offset personal greenhouse gas emissions?

Source: Heeb et al. (2025)

Of course, one could educate the public about the lack of impact of investment in the average green fund. But I guess fund managers will not be leading the charge on that one. When the researchers informed retail investors about the true impact of their investment in green funds, the willingness to pay for a green fund declined significantly. They were still willing to pay more for a green fund than a conventional fund, and when given the choice, 55% of retail investors would still choose the green fund rather than the conventional fund, but the premium they are willing to pay for a green fund shrinks by about a quarter.

Willingness to pay for a green fund

Source: Heeb et al. (2025)

“Despite challenges, I always remain hopeful about the future.”

The respondents could rate their answer on a scale from 1 to 10.

If you look at the 22 countries involved in the study, you see that the UK ranks near the bottom in average hope among the population, along with Sweden and Hong Kong. Japanese feel particularly hopeless, while Latin Americans and Southeast Asians show a particularly hopeful disposition.

Average hopefulness across countries

Source: Counted et al. (2026)

A closer analysis of the data shows that the key driver of feeling hopeful is religiosity. People who attend religious ceremonies more often are significantly more hopeful than people who don’t attend any ceremonies at all.

That is a common result in happiness surveys. People who are more socially connected to a group of people with common interests (e.g., your local church community) tend to be more content in life.

But maybe there is something else at play. If you plot the degree of hope in a country against the average income inequality in a country, you also find a pretty decent correlation of 0.38. Countries like Japan, Sweden or the UK have relatively low income inequality and simultaneously low degrees of hopefulness. Meanwhile, countries in Latin America, Africa and Southeast Asia tend to have high inequality, high religiosity and a host of other confounding factors.

Hope vs. income inequality

Source: Panmure Libeerum, Counted et al. (2026)

What causes what, or whether all these variables are only correlated with each other and caused by something else altogether, is completely unclear. I hope some people sit down and try to find out.

And no, this is not what ‘always happens’. In the past, banks lowered their loan rates after a while when interest rates declined. In this cycle, they didn’t do it and that allowed them to gain abnormal profits in recent years.

UK credit card interest and official policy rates

Source: Panmure Liberum, Bank of England

I think banks continue to keep short-term loan rates high because they can. Neither customers nor the media seem to pay any attention to this issue, and as a result, banks keep minting money. Once the public (or enough customers) paid attention to this disconnect, banks would likely reduce their loan rates. At least that is what banks in the US do.

Xu Lu and Lingxuan Wu performed a fascinating analysis on how banks in the United States set the interest rates on bank deposits. They measured how much attention bank customers paid to their accounts via two channels. First, they looked at the share of customers who moved money from one bank to another after the Fed hiked interest rates. The higher this share, the more fickle a bank’s customers are.

Then, they also checked how spending patterns changed if customers got an unexpected windfall from a tax refund or a government stimulus check during the pandemic. If you compare this spending to the regular spending pattern after customers get their salaries, etc., you can estimate how quickly customers realise that they have more money in their bank account.

Combine these two measures, and you get a measure of the average attention a bank’s customers pay to their deposits. If a bank has customers who pay more attention, it tends to pay higher interest on deposits because it knows that if it doesn’t, more of its depositors will leave the bank to get a better deal.

Depositor attention and bank deposit interest

Source: Lu and Wu (2026)

As you can see in the chart, the difference in deposit rates varies over the cycle and gets larger when interest rates are higher. But in the long run, the authors of the study estimate that the difference between banks with attentive and banks with inattentive customers is some 18 cents of extra income for the bank for every dollar deposited.

I have done the math just like other people have. My models come to roughly the same conclusion as the German Council of Economic Experts. The investments in infrastructure and defence should boost Germany’s GDP by about 6.5 percentage points in the next seven years, or almost one percentage point of additional GDP growth per year. This is why I think Germany may well show the largest GDP growth of any G7 country over the coming decade.

Growth boost from German fiscal stimulus

Source: German Council of Economic Experts

But most of this growth will be funded by new debt, and the psychology of debt-funded stimulus is clearly different from the psychology of fiscal stimulus funded by other means (e.g. higher taxes). This is why I find a study among 9,000 households in five Eurozone countries by Jing Cynthia Wu and her colleagues so fascinating.

They asked these households how they think fiscal spending funded by debt or by higher taxes influences growth and their household spending. If households expect fiscal stimulus to create more growth, it will lead to more household spending since fears of losing their jobs decline. These animal spirits then compound the growth impact of fiscal spending.

Household expectations for GDP growth from fiscal stimulus

Source: Wu et al. (2026). Note: Blue diamonds indicate debt-funded fiscal stimulus, orange diamonds indicate tax-funded fiscal stimulus.

The results are clear. Households think that growth accelerates more if fiscal spending is fuelled by new debt rather than higher taxes, both in the short term (next year) as well as in the long term (next five years). However, the higher the debt burden of a country, the less additional growth is expected for debt-funded fiscal stimulus.

The diamonds in the two charts above represent, from left to right, the Netherlands (debt-to-GDP: 56%), Germany (67%), France (103%), Spain (107%), and Italy (138%). People in Spain, France and Italy understand that their debt situation is critical and that any debt-fuelled spending will eventually come back and haunt them in the form of higher taxes. German and Dutch households, meanwhile, are less concerned about debt-fuelled fiscal spending. They know it creates growth, and their country can afford the extra debt.

This tells us not only that Germany can afford its massive debt-fuelled fiscal splurge, but that it will likely create a lot of positive knock-on effects from increased household optimism. Extra debt-fuelled fiscal spending in the UK, with its debt-to-GDP ratio similar to France, is much less likely to awaken animal spirits.

According to Preqin’s Institutional Allocation Study 2024, the share of assets allocated to private equity has increased from 4.3% in 2019 to 6.9% in 2024. Aviva’s Private Markets Study 2026, meanwhile, states that among their respondents, the average allocation to private equity within private assets is 21.5%, about the same as real estate at 22% and way ahead of any other private asset.

When asked why they like to invest in private equity, institutional investors typically mention that private equity has higher volatility than other private assets, but also higher returns. So, the extra risk is worth it. Or is it?

Of course not, as Noel Amenc and his colleagues at EDHEC show for the first time. They collected comprehensive quarterly private equity data from 2013 to 2024 and calculated the risk of investing in this asset class for different time horizons. The first chart shows what investors already know: No matter how long you invest in private equity, it is always more volatile than investing in listed equities and long-dated Treasuries. At least the volatility of private equity investments declines as the investment horizon increases, indicating that there is mean reversion in returns, i.e. periods of poor returns are followed by periods of good returns and vice versa.

The term structure of risk in private equity

Source: Amenc et al. (2026)

And now for the bad news. The study also simulates the excess return created from investing in private equity, listed equity and Treasury bonds. The good news is that, on average, private equity almost doubles excess wealth over a risk-free investment after five years (1.90x). The bad news, as you can see in the charts below, is that it has about the same returns as listed equity.

Cumulative excess wealth

Source: Amenc et al. (2026)

So, private equity really isn’t such a great deal compared to listed equity. But most experienced investors know that already. And they know why institutional investors are still willing to pile into private equity and private assets in general: Lower volatility on paper, which seemingly creates lower correlation to other asset classes and the illusion of a liquidity premium.

A group of economists from the World Bank and IMF went into great detail to sum up all the explicit subsidies given to producers of fossil fuels across 170 countries. They calculate that explicit subsidies amount to $725bn worldwide or some 0.6% of global GDP. Meanwhile, they calculate that there are an additional $6.7 trillion (5.8% of global GDP) provided in implicit subsidies by not taking into account the damage fossil fuels cause to the environment and human health.

To give you an idea, let me focus on the price of petrol and diesel to run cars and lorries. The chart below shows the actual retail price in $/litre across 25 countries (red diamond) and compares it to the true cost to society. This true cost consists of the cost to supply petrol, the global warming costs caused by burning the petrol in a car or lorry, the cost to human health from road accidents, the damage done to the road from driving on it, local pollution near roads, the cost to society from congestion and the taxes charged on the fuel.

True cost of petrol (left) and diesel (right)

Source: Black et al. (2026)

All in all, petrol and diesel are too cheap everywhere except the UK, which currently has fuel costs that roughly match the actual cost to society. In the US, meanwhile, fuel prices need to more than double from $3 per gallon to about $6 to $7 per gallon to reflect the true costs of burning petrol and diesel.

Of course, the problem is that if you charge the true cost of these fuels, you are punishing mostly low-income households. High-income households can easily afford to pay more for fuel because for them, fuel costs are just a small part of their household expenses; for poorer households, that is not the case. Charging the true cost of fuel would reduce low-income households’ purchasing power by 4%. Eliminating just the explicit government subsidies to fossil fuels would still reduce their purchasing power by 1.8%, while high-income households would see their purchasing power shrink by just 0.2%.

Yet, the authors argue that these distributional effects are better dealt with by other government subsidies like means-tested tax rebates or fuel allowances for low-income households. The current system of blanket government subsidies, in contrast, ensures that most of the subsidies flow to the richest households, who least need them.

A team of researchers let different genAI models answer a battery of tests that have historically been used to demonstrate behavioural biases in humans:

• Diminishing sensitivity to gains

• Loss aversion

• Subjective probability weighting

• Narrow framing

• Ambiguity aversion

• Hyperbolic discounting

Then there are seven additional questions on things like sample size neglect, base rate neglect, the gambler’s fallacy, anchoring, etc. I won’t explain all these biases; you can Google them or ask ChatGPT, Claude or Gemini to explain them to you.

When you give these tests to an AI model, it will either answer rationally or as many humans do. Or it might get all confused and give you some weird, unclassifiable answer. Below is the kind of answer you get from the different models on the first six tasks (preference-based tasks, left-hand column) and the seven belief-based questions (right-hand column).

Proportion of AI responses

Source: Bini et al. (2026)

Note a couple of things. First, belief-based questions typically involve maths and statistics, and genAI models tend to be really good at maths, so they give the rational answer almost all the time.

Second, when it comes to expressing preferences for one option or another, all they can rely on is what they have learned from the output of other humans. And that is where human-like behaviour comes in. In particular, the most popular genAI models GPT, Claude and Gemini show clear human-like biases in many of the tasks they were asked to perform.

The one big outlier is Llama, which tends to give more rational answers in preference-based tasks but more human-like answers in belief-based tasks. I wonder what happens there…

Every four years, I write a note that has many more readers than anything else I publish. It all started 12 years ago when I used an economic model to forecast the winner of the World Cup in Brazil. I thought it would become an exercise in showing the hubris of economists who think they can forecast anything with a model, even if it is effectively a random outcome.

And then I got it right. And again in 2018. And a third time in 2022.

After being right three times in a row, I have been inundated by requests over the last four years to forecast the Euros, the Olympics, the Rugby World Cup, etc. And somehow, what was meant to show that economic models cannot be trusted is starting to show why fund managers that have been outperforming for a while suddenly become ‘star managers’ even if their achievement is almost entirely due to luck rather than skill.

So here it is, very much tongue in cheek. By popular demand, my forecasts for the FIFA World Cup 2026:

https://panmureliberum.com/media/3179/strs_1031724.pdf

One trend in the US economy has been the declining share of labour in the economy. Capital has increasingly replaced labour as an input and driver of corporate profits. This shift from labour to capital has happened right about the same time as US stock market valuations have started to lift off, Andrew Atkeson and his colleagues show with the chart below. The chart shows free cash flow generation of US businesses relative to their profits (Gross Value Added, GVA) in blue. The red line shows one minus the compensation of employees over GVA. As compensation for employees declined, more cash remained available to shareholders.

Cash generation increased as labour compensation declined

Source: Atkeson et al. (2026)

But if there is more free cash flow to shareholders, the valuation of the company increases even when profits remain constant. Ergo: valuation multiples increase and remain permanently high.

Or rather, they remain high as long as nothing changes, which brings me to the question of why the labour share of GVA or the labour share of the economy has declined so much.

Atkeson and his colleagues give several possible explanations:

• Investment is mismeasured in the economy, and somehow, there has been a major increase in investments in things like intangible capital that are hidden from standard macro measurements.

• Employee income is mismeasured. More and more employees are compensated through corporate stocks and stock options, which do not count as labour income and may thus lead to an underestimation of the labour share in the economy.

• Companies in certain industries like social media, AI, and other tech spaces have become virtual monopolies and exploit these monopolies (or oligopolies) to extract rent from customers to generate supernormal profits.

Personally, I am on the record for favouring the third option, since something that has become obvious is that companies like the Mag7 in the US enjoy profit margins that are way above normal levels and are no longer mean-reverting because there is no competition emerging that could undermine their profit margins. If there is a competitor that could become a danger, the big tech companies tend to simply buy that rival, thus creating a kill zone around them.

Plus, Cory Doctorow’s Enshittification thesis claims that, besides the lack of competition, a lack of antitrust enforcement has enabled these companies to lock in both consumers and advertisers, thus creating virtual monopolies that they can extract to the benefit of the owners of these companies.

This third driver also explains one crucial shortcoming of the analysis of Atkeson and his colleagues. They only look at the US stock markets and the declining labour share in the US. But as we know, the labour share has declined in the vast majority of all major economies, yet only in the US are stock market valuations untethered from long-term averages. The main difference between the US and these other countries with declining labour shares is that only the US has tech companies that are globally dominant.

Of course, it is impossible to forecast if and when the US government will impose export bans on US goods to China for national security reasons. But once that happens, the stocks of companies that are affected by these export bans drop immediately. Just think of telecom hardware suppliers in the wake of the ban on Huawei and ZTE in the US.

In the months after a Chinese company is put on the ‘US entity list’ (thus proscribing US businesses from dealing with the company), the returns of affected US equity funds decline, and the volatility of the funds increases.

Impact of US export ban on US equity funds

Source: Crosignani et al. (2025)

Fund managers react to such a shock by reducing the positions they hold in the affected companies or selling them altogether. This increases portfolio concentration and thus volatility, unless the freed-up cash is reinvested in diversifying new portfolio holdings.

But rather than investing the money into stocks that diversify the now more concentrated portfolio, fund managers are trying to play catch-up with their benchmark. Hence, they tend to invest some of the cash they got from selling the affected US stocks in lottery stocks in the hope of generating ‘alpha’ in the next couple of months that can make up for the losses. As the chart below shows, the positions of lottery stocks in the portfolio of affected funds increase by about 4% relative to before the shock.

The result is that a fund that has been hit by a geopolitical shock tends to become more concentrated, more volatile and riskier in the months after the event. Not because of the increased risks in markets or individual stocks, but because of the desperation of fund managers.

Change in lottery stock holdings after a geopolitical shock

Source: Crosignani et al. (2025)

But memories are intensely personal. And while most investors experience high returns when the market has a great day, how these returns are evaluated depends very much on the context in which they are perceived by investors.

For example, if an investor has had lots of high-performing stocks in her portfolio in the past, a strong performance on day X should be less likely to trigger profit-taking than in the case of an investor with a lot of poor performers in the portfolio. On the other hand, if an investor had lots of duds in their portfolio in the past and now experiences another major loss in an existing portfolio holding, they should be more inclined to pull the trigger on a stop loss than someone who had more positive experiences in the past.

This propensity to sell stocks faster after both extremely positive and extremely negative returns for investors with a worse past performance is exactly what Julia Brettschneider and her colleagues find among US retail investors.

Propensity to sell after extreme returns depends on past individual performance

Source: Brettschneider et al. (2026)

Investors whose top three investments in the past had an average return above 50% were more likely to sell stocks that had an extreme positive return after such an event. But the probability of selling increased from 1.4% to about 1.7%, an increase in the likelihood of selling by about 20%. Investors whose top three investments had an average return below 50%, on the other hand, saw their likelihood of a sale increase from 1.6% to 2.4%, an increase by 50%.

Of course, one of the golden rules for successful long-term investors is to let the winners run. Too often, investors sell winners to lock in past returns, but let losing stocks run in the vain hope to recover these losses, which is known as the disposition effect in behavioural finance.

The lesson for professional and retail investors alike is a simple one: Always think about when you want to sell an investment, not just when you want to buy it. The moment you buy a stock or a fund, you should have a clear idea under what circumstances you would sell it. And that sales discipline needs to include scenarios for both gains and losses. When are losses big enough to warrant a stop loss? When are profits so large that the risk/return balance becomes so unfavourable that one can no longer justify owning the stock?

Professional investors are more likely to have such sales triggers in place, but you’d be surprised how rare it is even among professional investors to be able to clearly articulate for each investment when these triggers are met. And for those professional investors who cannot express these triggers clearly for each of their investments, the risk is that they reduce their performance by opening up the door to the disposition effect and other behavioural biases.

They make an important observation about the CAPE. Traditionally, the CAPE is calculated by taking the current price of an index (e.g. the S&P 500 as in Prof. R. Shiller’s data) and dividing it by the average index earnings over the last ten years.

However, what that does is two things. First, it weighs the CAPE for the index mostly by earnings contributions to the index. A company that is highly profitable will contribute a larger share to index earnings than its market cap, while a company that is loss-making will have a negative contribution to the CAPE, even though it has a positive weight by market cap in the index.

Second, the price of the index is based on the current index constituents, but these index constituents change over time, and when a new company is added to the index, its past earnings from before it joined the index are included as well (at least during the first year of its index membership).

Both effects disturb the CAPE, and the researchers thought: “What if we calculate the CAPE for each stock in the index and then add them all up according to the market cap weight of the stock in the index?”

It turns out that this significantly increases the predictive power of the CAP ratio. Out of sample, the conventional CAPE has a correlation with future 10-year real returns of 0.68 for an out-of-sample R² of 0.4667 since 1974.

If they calculate a CAPE from the individual stocks, the correlation with future 10-year real returns increases to 0.76 for an out-of-sample R2 of 0.5752. Similarly, the mean absolute error shrinks from 3.5% to 3.1%. All of these differences are statistically significant and form a sizeable improvement in forecasting power that can have a real impact on portfolios. Now, all you have to do is find all the index members of the S&P 500 going back to 1974, including their weight in the index for each month, and create the world’s most complex spreadsheet…

Does the AI business model have a fatal flaw?

LONDON, April 1 (Reuters) - Hundreds of billions of dollars are riding on the assumption that artificial intelligence will be reliable enough for high-stakes work. New research suggests it may never be.

The AI tools that power ChatGPT and its rivals - known as large language models, or LLMs - are a genuine productivity-enhancing innovation. But they have serious shortcomings, most notably, their tendency to hallucinate, or ​make things up.

Read the full article here: https://www.reuters.com/technology/does-ai-business-model-have-fatal-flaw-2026-04-01/

The length of Parliament is governed by the Parliament Act 1911, which has been reinstated as the law of the land in this respect after the repeal of the Fixed-Term Parliament Act in 2022. That law states that a Parliament must be dissolved no later than the fifth anniversary of its first meeting. However, No. 10 is now floating the idea to repeal that act as well, thus bringing the maximum term of a Parliament back to seven years as enshrined in the Septennial Act 1715.

The ostensible reason is to give the Labour Party a mulligan after it didn’t get anything done in the first two years back in power anyway. Plus, it is probably Labour’s best chance to keep Nigel Farage out of Downing Street. Obviously, this is pure desperation, but then again, at least Labour is staying within the law. Since the UK does not have a written constitution, Parliament can change the constitution with a simple vote in Parliament. And unlike Boris Johnson, who illegally prorogued Parliament in 2019, the proposed course of action is legally sound.

Plus, Keir Starmer and the cabinet ministers can point to the public’s desire to stop the short-termism of politicians who only play to the 24-hour news cycle at the expense of the long-term benefit for the country. By prolonging the time in office of MPs, they can focus more on what is good for the country in the long run.

Academic studies support this view. A recent study from the Catholic University of the Sacred Heart of Milan showed that there is a statistically significant reduction in government spending as a share of GDP in countries that have longer terms for their heads of state. For every additional year in power, government spending declines by 6.7% of GDP on average. Downing Street will claim that this long-term incentive structure, which has become common in finance and banking after the financial crisis, will significantly reduce the need to provide government handouts to potential voters in the next couple of years.

Correlation of executive term length with government spending

Source: Cipullo (2025)

In their paper, Stoffel and Herzberg make eight recommendations, three more short-term oriented and five more long-term oriented. I will quote them here, but I have decided to re-order them from most important to least important:

1. Continue investing in European independence: “Building greater European autonomy – especially in defense, energy and trade – is the most difficult but also the most essential long-term strategy against the assertion of performative and coercive superiority and vindictive retaliation.”

2. Strengthen European coordination and unity: “In areas where Europe lacks sufficient military or economic power to deter domination tactics, coordination and unity are its strongest capital. A unified European front increases credibility and reduces opportunities for exploitation and manipulation by Washington […] As the most populous EU member state and the union’s biggest financial contributor, Germany in particular should orient itself towards Brussels rather than Washington and further tighten relations with key European partners.”

3. Do not submit to excessive demands: “European governments and the EU should avoid one-sided concessions that reinforce Washington’s status-driven tactics. Unless faced with an absolute and imminent threat to European security or prosperity, any concessions must be framed in terms of reciprocity — a classic “tit-for-tat” that is easy to communicate on the global public stage.”

4. Invest in the optics of confidence, independence and unity: “When facing narcissistic foreign policy patterns, performance and perception take on even greater importance than in regular diplomacy, often becoming the only effective way to break through such behavior. As Europe continues to build real independence and unity, its governments should also ensure that every diplomatic move already visibly communicates these traits. To this end, the chiefs of staff and offices of high-level politicians, in particular, should consider creative alternatives to standard protocol when it comes to selecting meeting venues, jewelry such as pins or broches, or gifts. On the working level, efforts for synchronized talking points and coordination with European partners should be strengthened. Shared and confident language on specific issues across official documents, speeches and direct interactions with the US could go a long way to signal strength and unity.”

5. Dare boldness: “Europe should not lose sight of its own interests. To cut through the noise of Washington’s narcissistic foreign policy patterns, European governments need to dare some boldness and choose individual moves to test out tactics that allow them to set their own agenda. For example, Europe can leverage its existing strengths to deepen ties with emerging powers, forming closer strategic industrial partnerships with India or Brazil.”

6. Leverage the power of saying (and doing) nothing: “One of the more easily implemented measures European governments can adopt to limit attention-seeking and the effects of “flooding the system” with outrageous demands and statements is simply not to respond […] [R]eactive speaking points for official government representatives facing public scrutiny should focus on options such as ‘we have not received any official communication from the US government on this matter, but are always open to dialogue. […] Not responding to every provocation limits risks of triggering vindictive retaliation, fueling attention-seeking cycles, it buys time to decide on further action, and frees resources to dedicate to European interests rather than American agenda points.”

7. Craft a policy of cordial neutrality: “Europe should deny Washington exaggerated symbolic wins and avoid being pulled into cycles of manufactured outrage, including well-meaning but destructive stunts of ‘baiting the bully’.”

8. Prepare for radical volatility: “The substance of US actions will remain unpredictable, but with a narcissism framework in mind, triggers and escalation paths become foreseeable. Decisionmakers in all policy areas should apply strategic foresight, focusing less on what issues arise and more on how dynamics are likely to play out.”

Obviously, this is all easier said than done. Getting European leaders who show their own signs of narcissistic behaviour, like Emmanuel Macron or Viktor Orbán, to ‘strengthen coordination and unity’ and ‘leverage the power of saying nothing’ is a Herculean task. Meanwhile, getting Ursula von der Leyen or Friedrich Merz to ‘dare boldness’ or act more confidently seems a lost cause from the get-go. But this is where the EU may actually have an advantage. Because there are 27 heads of state plus the European Commission, the EU can distribute roles. When it comes to displaying confidence, independence, and unity, as well as launching bold new ideas that change the policy agenda, the EU should send Emmanuel Macron. He will love doing that, and he is good at it.

Meanwhile, when it comes to crafting a policy of cordial neutrality and leveraging the power of saying nothing, who better equipped than Ursula von der Leyen? Using a ton of words to say and do nothing is in her genes.

The only problem I see is with creating greater unity and coordination among European leaders. I can’t see anyone who is good at that in the EU at the moment, but if I had to pick one politician who can unite centrists and populists (at least the ones on the right), it would be Giorgia Meloni.