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Asset owners that are long-term investors should be wary of the conventional model of assessing the stock-bond correlation that is based on several “implicit assumptions”, said Stanford University Professor of Finance John Cochrane.

In a keynote speech at the Fiduciary Investors Symposium, Cochrane instead proposed a method that considers the economic situations which determine bonds’ status as a hedge or a risk.

Investors are conventionally trained to use statistical models to determine stock-bond correlations and look for the time-varying alphas and betas relative to that correlation, Cochrane said, but this model assumes a particular type of investor.

“You are assuming you’re talking to – or you are – an investor who cares about the mean variance of your portfolio, who holds only the market portfolio of stocks, has no job, no income, no liability stream, and cares only about one year,” Cochrane, who is also a senior fellow at the Hoover Institution, said.

“That’s a particularly bad assumption about bonds, because the one thing you need to know about bonds [is] when the price goes down, the yield goes up. A long-term bond, when you suffer a loss, you know it’s going to make it up in the long run.

“For a long-run investor with no immediate cash needs, who cares about mean variance?”

Cochrane encouraged the symposium to instead look at economic events when bonds were either hedges or risks, and to think about if they would have wanted to hold bonds ahead of time and how much they would be willing to pay.

“Just hedges or risks is not alone the question; the question is, are you the one who should be hedging or taking risk more than everybody else, because the average investor holds the market portfolio,” he said.

“I like to think about that in terms of fundamentals: where am I relative to everybody else who’s driving prices, rather than just statistical models, which I have learned over many years not to trust.”

The 2008 financial crisis is a classic case of bonds as a hedge, Cochrane said, because with inflation and interest rates both down, long-term government bonds got both a price and a real value boost “just as everything else was falling apart”.

But he said long-term bonds are risks when inflation comes into the picture, referencing how the $5 trillion US government fiscal expansion during COVID has been a “catastrophe” for long-term bond holders.

“The US government printed up $3 trillion, borrowed another $2 trillion, and sent it out as cheques to people,” he said.

“Whether good or bad, that $5 trillion, about half of it came from a 10 per cent haircut on long term bonds.

“The risk that happens is inflation. The risk that happens is the government decides we’re going to inflate away some of your debt in order to pay for something important.”

Instead of thinking about stock-bond correlations as fixed facts, Cochrane said investors will be better off with a simpler mindset – which is finding a stable economic structure and “understand changing times being we have different kinds of shocks”.

Responding to an audience question about the research view that it is the volatility of inflation and growth – instead of the level or the direction of them – that determines the stock-bond correlation, Cochrane said whether people need to care about it depends on what kind of investors they are.

“If you’re in a microsecond, millisecond, highly leveraged trading, short positions, long positions, posting collateral [kind of role], then you got to worry about these high frequency correlations,” he said.

But for long-term investors, “setting up the portfolio and thinking about the economic risks that your clients can handle should take more time than buying and selling at high frequency,” Cochrane said.

Analyses of the economic impact of artificial intelligence (AI) too often start with a top-down view of economies, industries or businesses, when a more accurate picture of the impact can be gained by examining the individual tasks that are bundled together to form jobs, the Fiduciary Investors Symposium has heard.

The Jerry Yang and Akiko Tamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centred AI, Erik Brynjolfsson, said that “too often [we] think about how AI is affecting the whole economy, or industries or companies or jobs”.

“None of that is the right way to think about it,” Brynjolfsson told the symposium.

“You need to go all the way down to individual tasks. And when you do it at that level, you can get a much better understanding. Every occupation, every job, is a bundle of tasks.”

Brynjolfsson, who is also a director of the Stanford Digital Economy Lab, said that radiologists, for example, “do maybe 27 different tasks”.

“Or you can make it even more fine-grained than that, financial managers, economists, truck drivers, nurses, everybody does a whole bunch of individual tasks,” he said.

“Once you break it down to individual tasks, you can start understanding…the implications of AI for those specific tasks. Some of them it’s going to help with, and others it’s not. Then you can roll them back up, weight them by wages or value added, and you start getting an image, a picture of what’s happening in the company or the whole economy.”

Brynjolfsson said a task-based analysis makes it clearer that there are some tasks that humans can do better and some tasks that machines can do better, but he said his research has not found a single job in the economy where machine learning or AI did every single task better than a human.

“On the other hand, we didn’t find a single job where there was no effect at all of machine learning,” he said.

“So the takeaway is that instead of mass unemployment [or] mass joblessness, from these technologies, [or] complete elimination of occupations, what we’re seeing instead is mass restructuring, mass reorganisation.

“As some of the tasks get done by humans [and] some get done by machines, managers and entrepreneurs have to rethink how they organise the economy. That’s what we’re going through right now – the biggest transformation in the economy that I think we’ve ever seen as more and more opportunities, more and more places for machines to help out and supplement what humans are doing.”

Brynjolfsson said AI is the general-purpose technology (GPT – before ChatGPT appropriated the acronym) of our time, and it follows previous GPTs such as the internal combustion engine, electricity and the steam engine in moving the dial on economic growth and wealth creation.

“Tim Bresnahan and Manuel Trajtenberg, here at Stanford, defined GPTs as having these three characteristics: pervasive, able to be improved over time, and able to spawn complementary innovations,” Brynjolfsson said.

“That last one is probably the most important one: they trigger a whole bunch of complementary innovations.”

Brynjolfsson said there is a threshold that any new technology crosses where it becomes better, faster and cheaper than the process or technology it is designed to replace.

“That threshold is important because, just like when water crosses the boiling point and changes from a liquid to a gas, it’s a threshold,” Brynjolfsson said.

“It is a phase transition that’s happening in the economy. When you have two ways of doing something and one of them becomes significantly better, faster, cheaper than the other way, then managers, entrepreneurs, are going to switch over from one to the other.”

Brynjolfsson said we’re starting to see “this phase transition of machines outperforming humans in a broader and broader array of tasks”.

However, he said, it’s not yet true of all tasks and we’re still some way off developing artificial general intelligence, but “there are a lot of concrete tasks where we now have machines outperforming humans”.

This has profound implications for the occupations and sectors it touches, but not always in obvious or expected ways. Brynjolfsson said one example is medical imaging, where applications built on machine learning outperform humans in identifying pathologies. Around 10 years ago it was firmly believed this would lead to declining demand for radiologists. In fact, the number of radiologists has almost tripled, because while reading medical images is what radiologists do, they do a lot of other things as well.

“You end up having more demand for some of the other tasks, some of the complementary tasks,” Brynjolfsson said.

“And as the price goes down, if you’ve got a downward sloping demand curve, remember, from economics 101, lower price leads to greater quantity. So more medical images are being read than ever before, and they continue to require humans in the loop.”

Developing long-duration storage and digitisation of the whole energy system remain key challenges as the world struggles to slow the growing impact of climate change.

While the global energy transition raises these issues relating to technology, policy and financing, it also represents an enormous economic opportunity as industry races to unlock solutions, Professor Yi Cui, faculty director at Stanford Doer School of Sustainability, told the Fiduciary Investors Symposium at Stanford University.

Many scientists believe the world has already reached 1.5 degree Celsius warming compared to pre-industrial revolution levels, and at a 2 parts-per-million (ppm) per year increase of carbon emissions we will get to 2.0 degrees of warming in roughly 15 years, Cui said.

“This is a gigantic transformation we are facing that needs to be done within about 30 years,” he said. “This is very, very urgent.”

Over the past 20 years, the energy transition has recorded a number of successes. The primary one is clean electricity generation, with solar and wind power now being generated for cents per kilowatt hour, meaning there is no need to burn coal anymore, although coal-fired power plants still exist because they had already been built, Cui said.

Other related to long distance transmission lines, which are capable of transmitting electricity more than 2000 kms with very high efficiency; and low-cost LED lighting technology. Finally, the development of lithium-ion battery-powered electric cars over the past decade has been a major development.

Key Challenges

Despite these successes, the most important test for the energy industry relates to long-duration energy storage. It is the question of how to extend the storage of clean electricity from hours to days and weeks and months.

“If this works, you will help decarbonise the electricity sector and the transportation sector,” Cui said.

“That is basically 60 to 70 per cent of carbon emissions already. So it is a big deal.”

Cui said that in order to stop emissions rising in the next 15 years, we will also need negative carbon technology to capture and remove carbon and other greenhouse gasses like methane from the air.

The world must also develop a circular economy at scale to take care of reuse and recycling needs. For example, electric vehicles, existing gasoline cars, concrete, and steel will need to be recycled much more efficiently.

Another looming issue on the horizon is how to power the growing usage of artificial intelligence. Cui quoted Nvidia’s Jason Huang saying that power is very likely to limit AI’s development, given that by 2050 half of all electricity generated globally will be used to power AI.

“How do you build the AI power?” Cui said.

“Do you use nuclear reactor for the AI computing centre? Or do you build solar plus storage? This remains to be seen. And how do you build a transmission line to get to the AI centre? Depending on which country you are in, the degree of difficulty will be very, very different.”

Ambitious Plans

Cui said developing high-energy-density lithium-ion batteries is key to how much electrification is possible, with current innovations attempting to develop higher performing prototypes using new types of materials to store greater charge.

“The motivation is very simple, but it’s very, very hard,” he said.

“If you could do that, we can go from the bottom, that’s current technology, all the way up to being able to store four times more energy per weight of the batteries.”

Once this level reaches about 500 watts per hour per kilogram (Wh/kg), all ground transportation could potentially be electrified. If you get to 1000 Wh/kg then domestic flights, of about three hours’ duration, “I think it’s a done deal”, he added.

The second key requirement for decarbonising the entire energy industry is to make long-duration energy storage work, at a low enough cost and a large enough scale.

“The capital cost per kilowatt hour of the battery needs to be lower. We are very far away from that,” Cui said.

“That will be the technology that can give you very safe electricity storage, with a very long lifetime. These batteries could last for 30 years, and the initial cost will be low.”

The influx of capital and interest into the private credit market has spawned new managers and offerings, but asset owners are increasingly alert to the fact that not every one of them is built equal, and even tiny losses during the credit cycle can eat significantly into long-term returns.

During a panel at the Fiduciary Investors Symposium at Stanford University, HOOPP senior managing director of structured and private credit Jennifer Shum warned of the danger of “compound losses”.

“There’s a lot of managers out there that haven’t been through a full cycle. We have,” Shum said.

“The losses are going to be interesting, because right now, every single private [credit] manager that you talk to says, I don’t have any losses – it’s 0.5 or 0.8 basis points. Everyone has the same deck.

“If a manager has tiny little nicks over time during the credit cycle, those compound losses are going to get you.”

HOOPP has been investing in private credit for more than a decade and Shum said the most attractive aspect of the asset class is the current income. The presence of covenants also protects lenders and brings the board to the table when things don’t go according to plan.

“We are the debt investor, [so] we’re going to be able to have a conversation with the borrowers on the private equity side, so there’s really interesting downside protections on private credit versus private equity,” Shum said.

Illinois Municipal Retirement Fund (IMRF) chief investment officer Angela Miller-May said the $52 billion fund is similarly bullish on the asset class and has painstakingly gone through a manager selection process for that part of the portfolio.

It completed an asset liability study in 2022 and established a three-year implementation plan to reach a 4 per cent allocation to direct lending, asset backed lending, and opportunistic private credit, funded by reducing equities, Miller-May said.

“We evaluated various strategies across the credit spectrum to really look at managers that could complement each other, could diversify the portfolio, and have unique strategies with a competitive edge,” she said.

“We put out an RFP in April of 2023 we got over 200 applicants…we came down to 13 managers.”

Miller-May said the fund is expecting its position to change over the credit cycle, hence the number of managers it hired as the base of the portfolio. Now, the fund sees appealing income generation and risk-adjusted return prospects, and the role of private lenders as providing capital where it is scarce.

“Plus the exit environment that we’re experiencing in private equity, where private equity companies are seeking financing solutions as well to infuse capital or provide distributions to liquidity constrained investors,” she said.

“We think that increases the opportunity set for private credit.”

Looking ahead, though, HOOPP’s Shum said private credit has somewhat become “a victim of our own success” as with the capital injection, investors are seeing some “lighter covenants”.

David Geenberg, managing director and head of North American investment team at opportunistic credit manager Strategic Value Partners, said the winds of change are already blowing in the leveraged credit markets.

“We are already seeing an increased restructuring cycle,” he said.

“It started about a year and a half ago. You can see significantly elevated restructuring rates, where it is visible in syndicated leveraged markets and leveraged loans, and high yield.”

Depending on which data points investors are looking at, defaults rates for the LSTA US Leveraged Loan Index is between 4 and 6 per cent, Geenberg said. It was within that range last year, and SVP is expecting that to be the case next year.

“You’re going to see over three years, 10 to 12 per cent cumulative restructuring in these portfolios,” he said.

“In the US and Europe – just in corporates, private equity, leveraged loans, direct lending – there are ten trillion dollars. So we think you’re looking at a trillion dollars’ worth of assets that get touched however they’re touched by the cycle.

“We think that it has both been a profound opportunity for investors like ourselves, but it is also a profound risk. We’re not telling you it’s going to cause a giant economic cycle, but it is going to affect portfolios.”

The changing nature of geopolitical risks has made them harder to manage, even though the adversaries to an American-led world order have remained nearly the same over the decades, according to Stephen Kotkin, the Kleinheinz Senior Fellow at the Hoover Institution.

These risks can still be managed between the extremes of appeasement and provocation, and will require allies and friends to work with US, as well as fiscal power to undergird the challenge, the Top1000funds.com Fiduciary Investors Symposium at Stanford University heard.

“The world has changed a lot less than it seems,” Prof Kotkin, who is a specialist on geopolitical risk and authoritarianism, said. “So it’s manageable, it can be done; and if it’s not managed, then it’s unpriceable geopolitical risk.”

The geopolitical world, and America’s adversaries, are largely the same as in 1945 when the US-led order was created. It’s no longer Russia as the senior partner in the Eurasian bloc that’s opposed to US power now, instead it is China. On the other hand, Iran, which was part of the US-led order before the Islamic revolution in 1979, has now flipped.

Kotkin said the US bloc has remained vulnerable to conflict since 1945, in three places across the world – Crimea, Israel and the South China Sea.

At the time, the Soviet bloc formed “borders of victory” after winning World War II and taking over Eastern Europe, and a chunk of the Korean Peninsula. By contrast, the current conflicts centre around “borders of defeat”.

“They used to have it, they don’t have it, they want it back,” he said, referring to territorial conflicts in Ukraine and the South China Sea.

“It’s a lot harder to stabilise the other side when it wants the land back, unlike the Soviet case, where they had what they were after.”

Another key difference is that everything that happens everywhere is now potentially interconnected. While it took the world a while to master radio and TV technology, the power of the internet has been much harder to control.

“This interconnectivity, which is so empowering, is also massively destabilising, and we don’t know how to manage it. It’s relatively new,” Kotkin said.

Another key contrast to the old state of world affairs is the growing problem of “dual-use” technology, he added.

Back in the Soviet days, technology could either be classified as of use to the military industrial complex, or for consumer goods.

“Now, the rocket and the refrigerator, it’s the same. It’s all just a bunch of semiconductors and other dual-use technology,” Kotkin said, giving the example of a small private company that may simply come up with an innovation in computerisation, but which could be potentially considered as having military industrial applications.

These are the major differences in the world we live in now compared to 30 to 40 years ago. Otherwise, it’s the same problematic with the US led world order, like it or not, he said.

“In real life, it’s not justice and equality and sovereignty. It’s a US-led order with warts and all, or it’s the other guy’s order, and so solving that problem is really hard with these three big changes that have happened.”

Investment heads at large global funds are reorganising their portfolios as they look to future-proof against global macro risks on the horizon and take advantage of potential opportunities.

Changes in strategies include cutting down on risk, higher allocations to equities and a shift to focusing on absolute returns, the Fiduciary Investors Symposium at Stanford University has heard.

James Davis, chief investment officer at the $25 billion Canadian pension fund OPTrust, says while asset owners are pretty good at managing short-term bouts of volatility, his bigger concern is a period of sustained inflation over the longer term.

“If we have a period where government finances are more problematic, and we know historically, one of the ways you deal with that is for governments to inflate their way out,” he said.

“What is that going to do to asset values over the long term, especially if there’s no real inflation protection built into them. And how is that actually going to impact an overall pension plan.”

Davis said his fear stems from the fact that his pension plans liabilities are fully indexed to inflation, so a scenario where asset values drop but liabilities rise would be “like the worst case”.

Another long term worry is about potential changes in regulatory policy setup that would require financial institutions like pension funds to bear unnecessary inflation risk because they are forced to own long term bonds.

Portfolio Risks

Jay Willoughby, chief investment officer at TIFF Investment Management, says while his fund follows an endowment model and an active management approach, his concerns regarding risks are similar.

One of the issues is on the fiscal side, he said, with a $35 trillion US budget deficit, a $27 trillion off balance sheet liability to the Social Security fund, and a $42 trillion off balance sheet liability to the Medicare Trust fund. Western countries have also used their control of the SWIFT banking system and frozen assets from the east.

“I don’t know what’s going to happen with the value of currencies. That’s one thing that hasn’t been talked about from an investment standpoint. But there’s a number of places in the world that are trying to use fewer dollars in their transactions and trades,” he said.

If artificial intelligence can increase productivity, the US might be able to bail out long-term bond holders and keep inflation down. But that would also result in a significant amount of opportunity in the stock market.

“So my best guess is that that it’s going to be harder to make money,” he said. “Maybe there’s not so much opportunity in bonds. We don’t see any fat pitches in to try to take advantage of and we’re a little late on the bond side.”

Alison Romano, the CEO and chief investment officer of the San Francisco Employees’ Retirement System (SFERS) says her team was extraordinarily successful taking active risk to reach its 7.2% return target and it worked for a long time, until the market shifted.

“So we’re changing. We’re not clamping down on risk, but we’re making sure that where we choose risk that aligns with our skill set,” she said.

That will mean increasing allocation to fixed income, given that the fund has reached a 97% funded status and has the opportunity to not chase returns.

“It’s really making sure that we know why we’re doing what we’re doing, and that the components of the return together will diversify and have each component acting as we’d expect, because I can’t predict what what’s going to happen,” she said.

Absolute Return Focus

With portfolio construction being harder under the current circumstances, the CIOs see advantages in shifting to a focus on absolute returns, rather than simply seeking to outperform benchmarks.

“We’re moving in that direction increasingly. So we’ve got in our portfolio, it’s basically divided into two large components. There’s the illiquid assets, and there’s liquid assets,” OPTrust’s Davis said.

He says historically, he would have used something more akin to a traditional SAA type framework to decide what that liquid mix should be, and then allocate to teams to generate alpha.

“Not sure that’s as effective as it could be. It’s certainly not consistent with our total portfolio approach. And what we find is the teams tend to focus more on alpha than they do on actually generating the best returns for the fund.”

TIFF, meanwhile, is turning to a hedge fund approach to generate portfolio gains regardless of market conditions. It is also betting on a higher allocation to equities.

“In the future, whatever your asset allocation is, push yourself to think about owning more stocks and fewer bonds. If currencies are going to become more important, you might own those stocks overseas,” Willoughby said.

While SPERS has a 10 per cent allocation to absolute return, Romano says the fund will continue to evolve asset allocation, as the markets evolve. That includes looking at how to utilise leverage better, and bringing in more analytics into the decision making.

“We talk a lot about markets, but it is a people business, and so there’s a lot of change management and working with the team and making sure that as we shift that there’s buy in,” Romano says.

“So, it’s both, responding to the markets, but also making sure we have a system where we have really good idea generation.”