Artificial Intelligence is reaching into almost every facet of the way we live, work, and play as it reshapes society, industries and businesses. The opportunities for investors are immense, but so are the potential pitfalls. As fiduciaries for hundreds of millions of individuals whose retirement savings they invest, AI may be the greatest challenge and opportunity facing the current generation of institutional asset owners. Top1000funds.com takes a deep dive into the world of machine learning and how and why the world’s leading asset owners are embracing AI in their assessment of investments and their own internal efficiencies.

One of the greatest challenges assessing the potential impact of artificial intelligence (AI) on large institutional asset owners is not identifying the things it might be useful for, nor the investment opportunities it may reveal, but first of all defining what AI even is.

The potential for AI to help identify new investment opportunities, to revolutionise whole industries and to streamline processes and enhance productivity has been extraordinarily well hyped. But it’s better at doing some things than doing others and working out whether it’s even worth trialling it in a particular task or function relies on a clear understanding of what it is.

IBM says AI is “a field, which combines computer science and robust datasets, to enable problem-solving”. McKinsey says it is “a machine’s ability to perform the cognitive functions we usually associate with human minds”. Elsewhere, AI has been defined as “a poor choice of words from 1954”.

Jacky Chen, director of total fund completion portfolio strategies at the $C25 billion ($18.4 billion) OPTrust, says AI is “systems, tools and machines that are programmed to think and act or learn like humans”.

“Essentially, [it] is trying to replicate human abilities,” Chen says. “But it’s all mostly done by a machine.”

A central element of Chen’s definition of AI includes the technology’s ability to learn, or at least appear to learn, by refining and revising its own rules or algorithms as it goes along. He says this makes it “quite different” from other forms of technology, even very highly powered computing solutions, that run to a fixed algorithm defined and written by humans.

“That really allows the system to learn from data and improve continuously by observing patterns,” he says.

“That is quite different from some of the traditional techniques [where] you just basically have some rule-based, human-decided rules programmed into the machine and try to make the machine do some things that are human-like.”

The $C244 billion ($180 billion) PSP Investments’ managing director of digital innovation and private markets solutions Ari Shaanan says computing is moving away from deterministic outcomes to probabilistic outcomes. In a deterministic model, a given input is subject to a set of rigid and defined rules and produces a predictable outcome. In a probabilistic model, a given input can result in a range of outcomes – and those outcomes may change over time as the rules change.

“It is actually much closer to the way the human brain works, in the sense that if you give someone the same inputs, if you give them the same core set of environments and contexts, people will react differently, depending on whatever is the day, the time, the hour, the additional thousands of potential inputs in there,” Shaanan says.

“We’re somewhat non-deterministic. You can’t always – sometimes you can but not always – just predict how people work, and software it’s the same thing. AI is that shift away from deterministic code, where if you put in one, press enter, you know exactly what the output is going to be. Machine learning is much more you put in one, and you have a probability of where it’s going to go, but [it’s] not determined, [it’s] not for sure.”

Human and machine interaction

Shaanan says a critical and relatively recent development in AI is how humans interface with it, which is why language-based models, such as ChatGPT, have captured the public imagination.

“You can now have much more natural interactions with models,” Shaanan says. “You can still run deterministic things on the back end – for example, true math problems, or statistical models, regressions, whatever you’re trying to do on the back end. But instead of having to see for, example, data tables, it can be communicated back in language. It just facilitates interactions between people and computers. It’s the next evolution.”

Global head of digitisation and innovation for the EUR508 billion ($549 billion) APG Asset Management, Peter Strikwerda, says APG’s definition of AI is “The ability of computer systems to execute cognitive tasks that require human intelligence, without human intervention”.

APG’s definition of AI is: “The ability of computer systems to execute cognitive tasks that require human intelligence, without human intervention”.

At the Fiduciary Investors Symposium at Stanford University in September last year, Fei Fei Li, inaugural Sequoia Professor in the Computer Science Department at Stanford University, and co-director of Stanford’s Human-Centered AI Institute debunked the notion that AI is a fad.

“One thing I take a lot of pride as a Stanford professor is we’re not in the business of hype, we’re scholars and technologists,” she said.

“My answer to all my friends in investment is that, as far as I can see, this is a genuine inflection point of technology. I’ve been in this field long enough, I’ve seen hype cycles, I’ve seen a lot of misinformation. But I do genuinely believe that AI’s moment has arrived, in the sense that this technology is ready to really transform businesses, to deliver products and services that would really have mass value.”

AI has existed in some form or another for half a century or longer. But the implications of this wave of AI are profound for asset owners. As the ready availability of vast oceans of data combines with exponential increases in computing power, they must obviously understand and assess the impact AI will have on the companies in whose shares they invest and whose debt they buy. But they must also recognise and exploit the opportunities AI presents for themselves as fiduciaries charged with stewarding the retirement savings of hundreds of millions of individuals around the world.

Asset owners embracing AI

“The largest part is and will be investment-related,” APG’s Strikwerda says.

“So that’s our investment department, portfolio management trading. Responsible investing is a very interesting and important area, I think, for AI. But we also see activity in reporting, in risk management, and even some in operations also – for example, clearing and settlement-type of preventing breaches. But I think in the bigger picture, let’s say, the whole core investment process is the starting point for us.”

Shaanan says the biggest impact of AI for PSP will be on the assets held within its portfolios but says developing in-house AI expertise helps to support analysts and portfolio managers in their understanding of the where AI is headed, and its potential ramifications.

“That part is important to PSP and it should be important to everyone,” Shaanan says. “We spent a lot of time actually sharing the knowledge that my team has gained on these AI projects with our investor teams, to think through the impact it could have on the portfolio.

“We’ll share knowledge from our projects, but we’ll also interface a lot with our partners in what they’re doing on AI in their portfolio. And then we’re trying to bring that back again to our investors and actually more just stimulate sort of a PSP-wide level discussion around AI and upskill everybody in terms of knowledge on the topic, how to use it, where it’s valuable, where it can make a difference, where it’s going to impact society.

“We’re really trying to raise PSP’s game in this from a knowledge perspective, more than anything.”

Chen says that AI is currently being evaluated within OPTrust and used initially to manage risk. He says it is particularly well-suited to analysing vast volumes of data and very quickly identifying patterns or relationships within the data, which are then brought to the attention of the fund’s investment teams.

Chen says OPTrust has formed internal working groups to help the organisation understand better how it can harness AI to make it more productive, and to train staff on using AI-enabled tools so that when new applications become apparent it has the internal capabilities to capitalise on them.

“And that is on top of what we have been doing while we continue to use machine learning to enhance our investment process,” he says.

“What we’re essentially doing is using machine learning to understand market patterns, to see whether there’s increased uncertainty in the market that potentially informs higher risk of certain assets. And as a result of that, we can act [on] that information that was summarized by the machine.”

PSP’s Shaanan says the application of AI in any of the fund’s operations must pass a rigorous use-case test and have the clear potential to deliver enhanced returns, lower risk, or lower costs. There are no formal hurdles or thresholds for these measures, except to say the benefit must clearly exceed the cost.

The application of AI in any of the fund’s operations must pass a rigorous use-case test and have the clear potential to deliver enhanced returns, lower risk, or lower costs.

It’s difficult to prove in some cases, and these tend not to get off the ground; in others it’s relatively easy to forecast: one or two better investments made in private markets, for example, can easily compound to tens or even a hundred million dollars of additional return for a fund the size of PSP.

“Those things scale very quickly on the $500 million tickets that we write,” Shaanan says. “That’s why it’s hard to prove it with an exact science of it’s this [exact] threshold; but you do need to be able to say, yes, it’s got potential for hundreds of millions [of dollars] of impact, if you make two better investment decisions.”

Shaanan says there is no shortage of ideas put forward for AI enhancements; the trick is separating out those that will generate the greatest bang for the buck. PSP works in three phases: ideation, incubation, and then – when the use-case is proven – implementation.

Projects create their own momentum. Shaanan says that once his team has worked with one area of PSP’s business and demonstrated results, it often prompts other areas of the business to want the team to do the same for them.

“And that’s a major piece, I call it major idea stimulation,” he says.

“You’ve proven success somewhere, where else could we scale it, where else could we apply it? Yes, absolutely.”

Impact on costs and performance

But as more asset owner organisations take up AI and it becomes part of business as usual, it’s increasingly unlikely it can deliver a sustained competitive advantage. Some organisations may steal a march on competitors, even if only temporarily, as they discover new or innovative applications. But not utilising it effectively will almost certainly put an organisation at a competitive disadvantage.

And there’s another issue, too. As more and more investors use AI to analyse ever-increasing amounts of data in a bid to eke out additional investment returns, their actions will make investment markets more efficient – making it even more difficult to extract meaningful alpha.

Japan’s ¥158 trillion ($1.4 trillion) Government Pension Investment Fund (GPIF) uses AI to improve the selection of active asset managers, addressing the issue of spending tens of millions of dollars in management fees for no or even negative alpha.

The $700 million Abu Dhabi Investment Authority (ADIA) is spending heavily on in-house technology following the realisation that a reduced capacity to generate alpha was linked to a lack of investment in big data and AI.

The technology is being used by the $200 billion Teacher Retirement System of Texas (TRS), where a managing director, Mohan Balachandran describes its use as “a giant leap forward”, and is using it to identify signals found in large data sets that are then passed to a portfolio management team for further evaluation.

And it’s far from only the giant funds that are tapping into the potential of AI. The DKK217 billion ($30.6 billion) Industriens has developed algorithms to support a range of investment-related activities, including optimizing asset allocation, uncovering anomalies in data, performing automated text analysis, minimizing tracking errors and maximize Sharpe ratios. However, the fund’s investment risk and data manager Sommer Legaard cautions that human oversight is still critical, and that “we never use our models or programming without some human validation”.

“Everything we do we try to automate, but we also vet things manually to check if it looks right,” she says.

For asset owners the impact of AI is potentially at least threefold. It presents opportunities to invest in companies that themselves will benefit from the increasing adoption of AI, like semiconductor manufacturers, cloud computing providers, and companies that produce cables and colling systems. AI also has the potential to make asset owners’ internal processes more efficient, thereby lowering costs and improving net returns. And, of course, it facilitates the analysis of reams of data to uncover new investment opportunities and sources of alpha across all investment markets and asset classes.

Failing quickly

APG’s Strikwerda says that around eight out of every 10 trials of AI end up being killed off. But APG is adept at killing them off before the investment has been too significant. It starts by breaking down the potential use case into small, manageable chunks and funding those, so if it becomes apparent an idea is not going to work as it gets built out further “we manage the risk of investing in something that may not be worthwhile in the end”.

“We only scale it up, meaning we put in some serious investments, if we have proven that there is enough value, that it can be done, that it is within certain confines of risks and policies, what have you, or we kill it, if it proves not to work. We’ve done this for about seven years, and we’ve run I think close to 100 initiatives in this methodology.”

Despite the best intentions and brightest initial promise, “sometimes it just doesn’t work”, Strikwerda says.

“It also needs to be adopted in the end internally. If we have something brilliant that nobody needs or wants to buy, so to speak, it’ll sit on a shelf. It’s [about] proving that there is value, proving that it can be done at reasonable investments, costs, risks, et cetera, and having someone at enough senior level owning it.”

“An interesting example of an AI experiment that we ran a while ago…was that we would be able to predict, let’s say societal turmoil, based upon Twitter. Being pensions investors, we typically are on the radar when something happens, and then could lead to bad press.

“The hypothesis was that Twitter would be early signals, and the interesting part was that we were almost there. We used billions of tweets and quite advanced AI to process that and to predict. What we found out, as I flag it always, is that we were able to predict that there would be a fire in Amsterdam, but not exactly where. It’s quite good but it’s not actionable, so we kill it.”

But when it works, it can be spectacular. APG’s work on how individual company products contribute to the UN’s Sustainable Development Goals led to the spin-off of Entis, now a stand-alone business.

“Fast forward five years, it’s a very mature offering which we share with like-minded investors, which has been commercialised to the market – which is not our primary goal, let me be clear there,” Strikwerda says.

“It has to be a healthy financial situation, but we’re not in it for the profits.

“It’s very advanced AI that has been used, it’s been ever-evolving, it’s getting better and better [using] enormous amounts of data, structured unstructured, coming from everywhere. This is a classic and a very interesting one; they produce alpha factors for us. From the same data, we also bring in hypotheses, like if we combine this and this and this, could we find some alpha factors? That has started to pay off, too. This is quite a big one.

“This has become a whole business model, a multi-million-dollar business model.”

Productivity improvements

Sometimes an AI revolution has more humble, though no less impactful, origins. The $A75 billion ($49.3 billion) Rest superannuation fund is taking part in the Microsoft 365 Copilot Early Access Program (EAP), which embeds AI into the Microsoft 365 suite, including those stalwarts of businesses worldwide, Word and Excel.

Rest is one of the first organisations in Australia and one of only 600 in the world to be invited to take part in the program, and the fund’s chief technology and data officer Jeremy Hubbard believes AI is already delivering personal productivity improvements and serving as a good introduction of AI to the fund’s workforce.

“It sets us up for the next phase, which is our Phase Two mode: can we start using Rest data to tailor that model in a way that it’s able to help our business with the context of Rest information – information about our policies, procedures, standards, our systems, et cetera?” Hubbard says.

Hubbard says Rest has built its own version of Chat GPT, dubbed RestGPT, a “little Teams bot using [Microsoft’s] Open AI GPT 3.5 model, which enabled us to give access to all of our business via a very simple interface, being Microsoft Teams, and ability to interact with a Chat GPT-like solution, but using Microsoft’s enterprise security”.

Hubbard says Rest currently has a small dedicated internal innovation team, “but with a broader sort of virtual team”.

“We’re trying to build a community around that AI team,” he says.

“Given it’s quite a small investment at the moment, we haven’t set hard targets that we need to deliver to, but for me, what we need to be delivering to is multiple what we call proof-of-value experiments. RestGPT would be one, and I would say that adoption and usage of it is good, definitely a good example.”

There are other areas where it may be easier to put figures on the value provided to the fund and its members, Hubbard says, particularly in the software engineering space.

“There are some really prime examples we’ve found that we’re just currently experimenting with,” he says.

“If we’re upgrading a development framework, and we have to do a fairly simple rewrite of all the code to work on the new function, we will be able to automate some of those pieces.

“For me, what’s exciting there is we can estimate with our estimating methodology, this is how long it would have taken a team of developers to update, and then we can do the same thing with AI. And we’ll be able to have, I think, a really black-and-white view that this saved us x hours or x weeks, and x hundreds of thousands of dollars. That’s emerging, but that’s another space where I think we can prove very tangible value.”

At this stage, and for the foreseeable future, AI will not be autonomously making investment decisions based on what it learns. One hurdle, among a number, to using AI this way is a relative lack of data to train on. That might sound ridiculous, given how much financial data is created every second of every day, but it pales into insignificance compared to the entire contents of the internet, which is effectively ChatGPT’s training ground.

At this stage, and for the foreseeable future, AI will not be autonomously making investment decisions based on what it learns

Chen says that financial data is “not as rich compared to other areas, especially during some of the stress environments because you don’t get financial crises that often”.

“Those are the periods that really matter to us from an investment program,” he says.

“Something that I think is a great opportunity for generative AI is to help us to build synthetic data, simulated or synthetic data. So what that means is data that is not entirely the same as the one we have observed in the history, but still plausible scenarios that potentially can help us to analyse our investment strategies.

“There is some progress actually being made on this. I have actually read a paper on this recently, that you can actually use simulated data, use AI to generate something that is similar to real data that you can test on.

“That is still, not easy to be doing, because you essentially have to be able to understand the different markets and simulate all this all together. There’s still some ways to go but I think that will be really important for asset managers to have better data and better potential scenario analysis tools,” Chen says.

AI is best understood at least by the public though large language models like Chat GPT. It’s relatable, because it feels human, and it’s “a good way of expressing or showing how capable this technology is”, Chen says.

“That’s why I think a lot of people have been focusing on this. But if you’re really looking at the research that [is] ongoing, there’s many other breakthroughs in AI that is not necessarily large-language models as well.

“Just thinking about how you currently unlock your iPhone, there are a lot of deep-learning analysis involved in detecting your face, and those are things that are probably not as tangible from a user perspective.”

Regulations and ethics

Chen says these less visible developments are eventually as likely to have as great an impact on how large asset owners operate as any of the visible developments to date. But he says asset owners will be subject to the same ethical considerations and regulatory requirements as any developers as they figure out the best uses for AI.

Chen is also an adjunct professor at the University of Toronto Rotman School of Management, where he teaches an innovation course and is engaged with the school’s Financial Innovation Hub, and his research focuses on the applications of machine learning techniques for portfolio hedging, derivatives pricing, and risk management. He says AI undoubtedly is “providing a lot of benefits to us”.

“But on the other hand, it’s important to have the regulatory frameworks and all the ethical guidelines,” he says.

“If you really think about the positive of AI, it’s a lot of ground-breaking innovations that are happening, from healthcare to environmental science. And these advancements are not simply a technological evolution, it’s also actually going to enhance our capabilities and improve our life quality. It’s important to keep that positive going.

If you really think about the positive of AI, it’s a lot of ground-breaking innovations that are happening, from healthcare to environmental science.

“But at the same time, strong regulatory frameworks and ethical guidelines will be crucial. That requires us, as a society, to see collaboration between industry, governments, and also the public. We are all stakeholders in this, in these discussions, and we need to make sure that there is a collaborative effort that helps us to shape the landscape going forward, and we [that] are not just wanting to focus on the innovative side. We need to make it inclusive.”

Stanford’s Li told the Fiduciary Investors Symposium that when the university’s Human-Centered AI Institute was founded “our mission statement did not put a national boundary” around the possibilities for AI, nor around the responsibilities of those that develop it.

“I think this technology is fundamentally universal,” she said.

“I think doing good to all humanity is fundamentally important. The geopolitics today at the human level is reality but it’s also sad, but there’s many things that this technology can do, whether it’s healthcare, or climate, or scientific discovery [that] transcends or geopolitics, transcends national boundaries.

“At Stanford, we’re really privileged. We educate students from all over the world, and we build technology that I hope can be used to benefit people from all over the world.”

Industriens, the DKK 217bn ($30.6 billion) Danish pension fund, is using advanced technology and exploring  AI models to bring sweeping advantages to its risk management processes.

The hope is the benefits will do much more than speed up analysis and end having to manually hunt for errors in Excel. Instead, the technology will allow the investor to optimize its asset allocation, uncover anomalies in data, perform automated text analysis and put in place restraints, for example around ESG at a level impossible to replicate in Excel.

Elsewhere, the technology can support assimilation, minimize tracking errors, maximize sharpe ratios and feed in sentiment analysis, lists Julia Sommer Legaard, investment risk and data manager at the pension fund for the last year, brought in to help bridge the gap between IT and programming, and portfolio management.

“The idea is to develop a few generalized functions in Python, which can be used for multiple purposes,” she says. “We can find errors much faster and check for abnormalities in the market value or duration of an investment, for example.”

Data gathering is step one when it comes to developing powerful models, says Sommer Legaard. Much of her time (she works in a team of eight, including two students) is spent extracting, analysing, and validating data. It is the lifeblood of the models and solutions which provide risk management across the portfolio, spanning everything from duration risk in bonds to investment limits in sectors and countries, credit, solvency, ESG and counterparty risk, regardless of the asset class.

Diving into the detail, Sommer Legaard says successfully building a model involves optimising the code to ensure it can handle different tasks, data types and fields – warning if the data she feeds in is invalid, it scrambles the process.

Once, she recalls, the code in the model couldn’t correctly read the data because it had been set up to search for numbers rather than letters. “You can’t get a good result from the model if your input is not valid,” she explains. Real data is messy – cleaning it can be 80 per cent of the work. “There is a difference between knowing a bit of Python and applying it on real data sets. I always check if the data is valid before saving it to the database.”

Part of her job is outlier detection. Determining if an outlier is valid or not is something that requires human expertise. “We never use our models or programming without some human validation,” she says. It’s easy to think something deviates from the norm particularly during bouts of volatility, and only closer, human examination reveals that it doesn’t. Data drawn from periods of market volatility might have multiple outliers in which only one is valid. It will require looking into each one, she says. “Everything we do we try to automate, but we also vet things manually to check if it looks right.”

For investors new to technology or developing in-house models, she suggests starting slow, and phasing in support around how the code works. “A lot of it is about trust,” she says. It is often hard to trust a model because it is rooted in such complex maths, but she finds comfort by constant back testing to check how well it would have performed.  “Working with programming daily, it is important to be able to explain what your code does and what is behind the models used for AI to make it transparent.”

A key challenge is the shortage of historical data because the model’s demands often supersede the availability of data. Moreover, historical data often quickly becomes out of date because the technology is moving so fast.

Other hazards lurk too. Like the risks of using data at a time regulators, artists and media organizations (amongst others) are increasingly questioning the use and risks of data being consumed by the technology. “European General Data Protection Regulation is a case in point. You must make sure the data you are using is safely secured and that it is only used to feed the model.”

ESG FOCUS

Data gathering to support ESG integration at the pension fund brings another layer of complexity. Issues include navigating mismatches with the model’s fields and data from the pension fund’s external vendors, including ESG data providers. It often results in time consuming excel comparisons and even calculating some numbers herself.

Some of the benefits are already obvious. For example, the technology may be able to help approximate the ESG data points in the private equity allocation. Still, the need for companies to draw on ever larger lakes of data for ESG integration raises important questions around the very process of integrating ESG risk – and if AI goes against the mission of ESG.

“The amount of computer power required to store the data is unsustainable,” she says. “Investors need to minimise their computer power, but the models demand ever more data. We need to take ESG into consideration when we think about future tech advancement.”

As AI becomes more prevalent, she believes retail investors will increasingly harness the technology, potentially muting the investment edge the data is meant to give. She predicts this will lead investors to rebalance more frequently as the market will catch up with strategies faster.

She concludes that success also depends on portfolio teams grasping the technology.

Although many of her colleagues still need encouraging when it comes to programming, she questions whether pension funds really need external companies to develop AI models and applications on their behalf. “It is becoming increasingly easy to use Python so investors might not rely so much on external vendors. It is a question of pushing internally – and I am a pushy person!”

 

 

 

In a year forecast to be volatile, and with the spectre of recession still very much on the cards, Top1000funds.com finds CIOs exploring new strategies, paring back on active equity, investing in technology and wrestling with the many disparate approaches to sustainability.

“We will get through it, even if bad things happen,” said Richard Hall, president, CEO and CIO at the University of Texas Investment Management company (UTIMCO), the $69.2 billion asset manager and of one of the largest public endowments in the US, voicing the uncertainty many investors feel heading into 2024 in a recent board meeting. 

Against the backdrop of contrasting analysis from UTIMCO’s trusted advisors, amongst which JPMorgan and PIMCO predict a soft landing but BlackRock and Bridgewater Associates skew to a hard landing where high rates pitch economies into recession, Hall’s team are maintaining a neutral position – alongside modelling how much the S&P500 could potentially decline should corporate earnings take a pounding. 

UTIMCO’s correlation to equity means that in a worse-case scenario if the stock market falls 20-50 per cent it could equate to an $11-24 billion decline in the value of assets under management. 

“It’s a lot of money,” warned Hall, whose preparation for a recession includes ensuring UTIMCO has ongoing liquidity to make distributions; is not over its skis in terms of capital calls and commitments and has the firepower on hand to invest in opportunities. 

Asking Top1000funds.com interviewees focused on the long-term to share their thoughts on the year ahead is often met with reluctance, given commentary is so quickly out of date. While gathering opinions mid-December, the Fed signalled extensive rate cuts through 2024. But Hall’s advice to “hope for the best but prepare for the worst” in a likely volatile year echoes broad CIO sentiment where others counsel on the importance of diversification and warnings that AI and ESG will continue to fuel inflation. 

Exploring different strategies

With inflation still not firmly beaten, growth elusive, and allocations that worked in the past no longer as effective, asset owners will increasingly integrate different strategies to fit the new economic regime. Take Helmsley Charitable Trust, the New York-based $7 billion charitable trust, now exploring convertible bonds offering bond-like characteristics alongside an upside kicker that is less volatile than equities. 

Helmsley is also hunting buyout opportunities in Japan, opening up thanks to governance reforms that are forcing Japanese companies to embrace efficiencies and accept the tough, hands-on approach these managers deploy. 

In another reflection of uncertainty ahead, investors are boosting their ability to take advantage of opportunities as they arise by increasing and readying their tactical asset allocation. Like the $38 billion Iowa Public Employees Retirement System (IPERS) where CIO Sriram Lakshminarayanan said the ability to tactically invest requires a change in mindset that is rooted in constant communication with managers and their views on the market. 

Although there is a growing consensus that borrowing costs will fall in 2024 (“monetary tightening is over,” declared Timo Löyttyniemi, CIO of Finland’s VER in a LinkedIn post) for now higher rates continue to impact the interplay between cash and bonds. 

For the first time in years, many investors go into 2024 holding more in cash and will continue to do so as long as rates stay high. If recession comes into view and the Federal Reserve and other central banks lower rates, the environment will become better for bonds and worse for cash and asset owners will likely position to benefit from the price appreciation in bonds. 

For now, higher borrowing costs will continue to impact how pension funds approach leverage in 2024 which remains more expensive than in the past and by extension, less beneficial. It’s something front-of-mind at the $71.9 billion Pennsylvania Public School Employees’ Retirement System, PSERS and Canada’s TTC Pension Plan (TTCPP), the $7.8 billion defined benefit fund for employees of Toronto’s public transport network. 

Some investors spoke about paring back on active equity in 2024, arguing it is difficult to pick winners in a market dominated by the leading tech stocks. “We are hoping to implement decent-sized passive allocations by year-end,” said New York-based Geeta Kapadia, CIO of Fordham University’s $1 billion endowment. “I don’t think looking for long-only US equity managers that outperform is a great use of our time. I’d rather take active risk in private markets than in public equities or credit.” 

But even if investors question the value of active equity, there is much talk of enduring and compelling US equity opportunities. Technological leaps like LLM (large language models) powering the AI revolution and the new generation of life-changing drugs will continue to offer unprecedented opportunities in public markets. 

“A rising tide will lift all boats, just be invested in boats, just be invested in equity,” said Charles Van Vleet, CIO of the Textron pension fund, who will run an active stock picking strategy through 2024 but says passive allocations will also benefit from unprecedented corporate innovation. 

“Who is going to reap the benefits of this productivity? It’s not going to go to labour – it’s going to go to the capital providers; to the equity investors, and it’s already priced into the market.” 

Adjustments in private equity

Investors predict a mixed year ahead for private equity – an asset class Norges Bank Investment Management, investment manager of Norway’s $1.5 trillion wealth fund Government Pension Fund Global, hopes it will finally get a green light to invest in after years of petitioning the Ministry of Finance. 

Higher interest rates mean a higher cost of doing business that will continue to impact portfolio companies’ performance and multiples, and may not feed into valuations until 2025-2026. Meanwhile, investors are unclear if exit strategies via IPO and M&A activity will open up in 2024. 

“I have to remind our senior managers and board that returns will be more challenging going forward.  Yes, private equity is the best performing asset from an absolute return perspective, but you must also look at it from a risk adjusted basis, and private equity is the most risk-taking allocation in the fund,” said Suyi Kim, global head of private equity at Canada’s CPP Investments. 

Many asset owners go into 2024 overweight their allocations because of capital appreciation in the underlying programme and GPs sitting on companies because they don’t like current valuations, and don’t want to write them down. It means the year begins with many LPs choosing fewer managers with whom to re-up as well as selling assets in the secondary market. Still, one LP’s challenge will be another’s opportunity. For some, 2024 will open the door to invest with sought-after GPs for the first time and support fee negotiation. 

Recruitment and talent acquisition, particularly around technology, will be a key issue through 2024. At ADIA, tech prowess can be seen in its purest form in the quantitative research and development team and the asset owner says it will continue to recruit globally respected experts in diverse areas such as machine learning, strategy development and portfolio construction through 2024. 

Elsewhere Industriens, the DKK 217bn ($30.6 billion) Danish pension fund, will spend 2024 continuing to explore AI models to optimize its asset allocation, uncover anomalies in data, perform automated text analysis and put in place restraints, for example around ESG at a level impossible to replicate in Excel. Meanwhile the quest to fill CIO openings at US public pension funds including CalPERS is likely to get easier as the tide finally turns in favour of recruiters. 

Will asset owners increase their allocation to China? Investors respond that strained geopolitics, complex regulation, the increasing cost of doing business not to mention the inability to forecast exits makes direct investing in private assets in China challenging. 

Sustainability in 2024

This year may see the term ESG increasingly give way to more coherent themes around sustainability. Elsewhere, investors look forward to applying new tools to support sustainability in their large allocations to sovereign debt. 

The investor-led ASCOR project (Assessing Sovereign Climate-Related Opportunities and Risks) has just published its first independent academic assessment of 25 countries’ climate targets and policies. The analysis offers investors data and insights spanning the extent to which emissions are declining to a country’s regulatory focus. 

Adam Matthews, co-chair of ASCOR and chief responsible investment officer at Church of England Pension Board, believes it is one of the most important sustainability initiatives in years. “Investors haven’t had an academically rigorous, transparent and publicly available holistic lens through which to assess climate mitigation and adaptation in their sovereign holdings until now,” he said. 

Sustainability teams will also spend 2024 wrestling with their approach to emerging markets. For many pension funds on a net zero trajectory, emerging market holdings have a disproportionate impact on their total carbon footprint, explains Mirko Cardinale, head of investment strategy at USS. 

“The easiest way to reduce that footprint would be to sell carbon intensive companies in emerging markets, but this does little for the real world impact. We are keen to see real world change and that’s why we continue encouraging the highest emitting companies we invest in to reduce their carbon emissions.” 

The focus for investors this year will be engagement with national issuers, but also recognising the importance of emerging markets being treated fairly in current frameworks. 

“We need differentiated pathways for companies in emerging markets,” concludes Matthews. 

In 2023, readers embraced our in-depth analysis and Investor Profiles as we continue our quest for a deeper understanding of institutional investment best practice and driving the industry to produce better outcomes for stakeholders. Thank you to all our interview subjects, readers and supporters over the last year. Below is a look at the most popular stories of 2023.

One of our defining characteristics, and main objectives, at Top1000funds.com, is to provide behind-the-scenes insight into the strategy and implementation of the world’s largest investors. Our access to senior investment professionals globally and our understanding of the context of their decisions is unequalled.

In 2023 we continued to deliver in-depth Investor Profiles showcasing the thinking of global CIOs, and we focused in on some new initiatives including our Asset Owner Directory and the Global Pension Transparency Benchmark.

We now have readers at asset owners from 95 countries, with combined assets of $48 trillion, and we are also pleased to say that in 2023 we significantly increased our pageviews and our user base with our readers spending more time on our site.

ESG remained a key focus for institutional investor readers this year, a subject we have been writing about since 2009. But as investors in the US in particular came under greater political scrutiny for their decisions around ESG we explored the topic from a number of new angles.

A candid interview with Utah Retirement Systems’ CIO John Skjervem was the most read story of 2023, Utah Retirement Systems: Why ESG is a waste of time. In the interview Skjervem said the only way to solve the climate emergency is to keep investing in fossil fuels. He said divestment doesn’t work, Scope 3 reporting will tie companies in regulatory knots and ESG integration threatens pension funds’ long-term returns and their ability to finance the transition.

Our deep dive into The politicisation of investments at US public funds revealed the complexity of the impact of partisan politics on the ability of CIOs to do their jobs. The analysis highlights the need for improved governance practices particularly around delegated authority to prevent the undue political influence over investment decisions.

“From an investment perspective I’m trying to use every tool I can to make better investment decisions – any other CIO will say the same thing,” says Andrew Palmer, CIO of the $63 billion Maryland State Retirement and Pension System. “Politicians are taking the ESG bat and hitting each other with it. And that has made the life of people trying to make investment decisions more difficult.”

On a more practical level the UK’s Universities Superannuation Scheme has produced new climate scenarios that are more informative for investors by focusing on shorter-term scenarios and switching the focus from temperature pathways to the complex interplay of physical and human factors. See How to rewrite Modern Portfolio Theory to integrate climate risk. After a University of Exeter commissioned report, the £75.5 billion fund aims to develop a long-term investment outlook informed by the scenarios and draw out investment implications for capital markets expectations, top-down portfolio construction, and country/sector preferences.

Other stories that readers were most interested in this year included the search for CalPERS’ next CIO, which at the time of writing had still not been resolved; celebrating the successes and evolution of the CFA institute; and the results from our CIO Sentiment Survey which is released every February with our partner Deloitte/Casey Quirk.

From an investment perspective the work of CPP Investments’ active equities team; and the new team structure at CalSTRS were of most interest as investors around the world grapple with the tough macro economic conditions and organisational pressures.

Last year we launched the Asset Owner Directory which is an interactive tool to give readers an insight into the world of global asset owners. It includes key information for the largest asset owners around the world such as key personnel, asset allocation and performance. Importantly, for context and depth, the Asset Owner Directory also includes an archive of all the stories that have been written by Top1000funds.com about these investors over a period of more than 12 years, allowing readers to better understand the strategy, governance and investment decisions of these important asset owners. This initiative was very well received by the industry and is now the most visited part of our site.

The third edition of the Global Pension Transparency Benchmark , a collaboration between Top1000funds.com and Toronto-based CEM Benchmarking, revealed that increased scrutiny on public disclosures is driving measurable improvements. More than three-quarters (77 per cent) of the reviewed organisations improved their total transparency scores in this year’s iteration of the results which look at four factors: governance and organisation; performance; costs; and responsible investing; which are measured by assessing hundreds of underlying components. We focused on transparency because we believe transparency and accountability go hand in hand and lead to better decision making, and ultimately better outcomes.

In 2023 we hosted three in person events in Singapore, Stanford and Oxford, bringing together asset owners from all over the world to discuss investment risks and opportunities.

One of the defining aspects of our event programs is the integration of academia alongside our industry thought-leaders and next year we will introduce our Research Hub which will be a curated resource showcasing the work of all the academics we partner with across our event programs.

All of our initiatives are aimed at providing a deeper understanding of best practice and driving the industry to produce better outcomes for stakeholders. Thankyou to all our speakers, spsonsors and delegates that made those events such a massive success. We’re going to do it all again next year and kick off our event calendar with the Fiduciary Investors Symposium in Singapore from March 12-14. Hope to see you there.

Helmsley Charitable Trust is meeting a cohort of new investment managers, many of whom it has never invested with before, with an eye on developing different strategies in response to the new economic regime.

Inflation looks difficult to tame; growth elusive, and the strategies that worked in the past at the $7 billion charitable trust set up in 2009 by colourful real estate billionaire Leona Helmsley who bequeathed most (not all though – her dog also inherited millions) of her and her late husband Harry’s vast wealth to pioneering healthcare initiatives, no longer apply.

Convertible bonds offering bond-like characteristics alongside an upside kicker that is less volatile than equities but will help the trust achieve its return objectives are on the list, says CIO Roz Hewsenian speaking in an interview with Top1000Funds from her New York office on the eve of her retirement after 13 years in charge.

She is also meeting managers to discuss private equity opportunities in Japan where Helmsley hasn’t ventured for years. She believes opportunities for Japanese buyout managers are finally coming into view (after a long wait on the sidelines) thanks to overhauls in Japanese corporate governance. That could mean more companies embrace efficiencies and accept the tough, hands-on approach these managers deploy, she predicts.

“Many buyout managers went there already but it was too early because Japanese corporates’ management style has only recently changed; managers are only now able to buy into companies and effect change.” she says.

Elsewhere she is interested in meeting speciality fixed income managers with strategies that could benefit from the economic rebound after the gap out in rates. “We are waiting for investment spreads to gap out,” she says, explaining. “When credit declines in value enough so that relative to Treasuries you are getting paid to take the risk, we will invest in credit.”

New managers must navigate Hewsenian’s forthright style. For example, she will only meet hedge fund managers that have demonstrated alpha in their short book. “It eliminates so many candidates I can’t tell you,” she says. “We are only interested in returns from the short book and if they aren’t there, we see no reason to pay 2:20 and offer the manager a long-only mandate for half the fees. Not surprisingly, I’ve never had a taker!”

Moreover, the process reveals how many hedge fund managers don’t understand how to short stocks. “It’s not the opposite of buying long, it’s a different kind of trading strategy. The mindset is different, and many managers don’t get that.”

Managing manager relationships in private capital has become one of the most challenging corners of the portfolio. Rules decree that US foundations must allocate 5 per cent of their assets annually to chosen causes or lose their tax exemption, and Helmsley’s overweight in private markets is having an impact on these liquidity priorities.

It means the team have grown much pickier when it comes to choosing which managers with whom to re-up and are also selling assets in the secondary market. Helmsley’s 35 per cent target allocation to private equity is currently 42 per cent because of capital appreciation in the underlying programme, exacerbated by the selloff in public equity although she has reduced public equity exposure.

The problem is compounded because exits strategies in private capital are limited, she continues. Many managers don’t like current valuations, so they are sitting on companies because they don’t want to have to write them down.

“There is a lot of embedded value in our private capital portfolio that is not being recognised and won’t be until there is an IPO or M&A. Managers are saying the company is too attractive to go out at this price, but if they don’t exit, it’s very hard for us to rebalance.”

The decision when to sell is wholly at the manager’s discretion. She says all Helmsley’s GPs are well versed in the fund’s liquidity constraints and know sitting tight on assets impacts their ability to raise the next fund as money remains locked up [in the previous fund.] “One of the problems is that M&A has slowed because it requires debt, and debt is more expensive,” she adds.

She is also wary of managers talking their own book. “We are having interesting conversations with new mangers, but they all believe what they are selling will do really well. It only gets interesting when we take what each of them says, getting the pros from one manager and the cons from another, and then applying our own thinking with our own resources.”

In another sign of the times, Helmsley is also exploring investment opportunities in environmental technology, forecasting a spike in demand for green tech solutions as companies integrate net zero. “Our focus is on investing in green tech that can help companies that have committed to net zero targets reduce their carbon footprint.”

Still, she says most of Helmsley’s venture and sustainability exposure is focused on healthcare, in line with its mission.  “Sustainability can be expressed in several ways, and we express it through our mission in healthcare and medical research. Of course, our trustees are mindful of environmental impacts, and thankfully that is not at odds with our investments that focus on our mission.”

It leads her to reflect on the risk inherent in shifting investment strategy away from a foundation or trust’s core mission. One of the biggest challenges facing peer foundations is pressure to divest from fossil fuels, she says.

Foundation boards have become activist and are using the assets to drive home a point about which they are passionate that may or may not relate to the foundation’s mission. It leaves investment teams divesting from fossil fuels and undoing their investment programmes in line with the board’s objectives – all the while trying to earn back what is spent every year when divestment can hurt returns.

Like others, she also argues that divestment of fossil fuels is short-sighted because it puts assets in the hands of less scrupulous investors and raises the price of energy going forward. “Impeding access to capital for fossil fuel companies means that the price of energy will go up, which will impact people on fixed incomes the most.”

Helmsley’s board has been a constant and steady support of the investment team, headed by celebrated investor Linda Strumpf, former CIO of the Ford Foundation who chairs Helmsley’s investment committee.

“Linda has sat in the chair and can deal with anything; she has been a stalwart supporter of staff, and Helmsley; she believes in what we stand for and truly supports the investment team to do its best. I couldn’t ask for better.”

Something her team surely say about her, too.

Joshua Fenton, director of investments, will assume the role on January 1, 2024.

 

 

 

In the ever-changing investment landscape, the role of traditional bonds is challenged by declining returns as global central banks unwind their excess monetary stimulus to boost interest rates after the pandemic.

Fixed income, once a stabilising force for asset-rich Japanese corporate pension funds, now struggles to counter stock and currency volatility. They are also reducing fixed income and heavily diversifying their portfolio in asset class alternatives as high currency hedging costs prompt caution, with them seeking shelter in short-term strategies amid uncertainties surrounding rising global interest rates and central bank policies.

The question of the expected role of fixed income investments was generally the same one for any investors in the past when they allocated most of their funds into traditional four assets – domestic and foreign bonds and equities.

However, this traditional strategy doesn’t work now as expected returns on fixed income have declined and global central banks’ unprecedented monetary stimulus has undermined expected returns on bonds. In addition, the increased correlation with stocks has made it almost impossible to control the volatility of equities with conventional bonds.

Many Japanese corporate pension funds treat fixed income as core assets with bonds accounting for more than 30 per cent of domestic corporate pension funds’ total assets. This indicates both domestic and foreign, including non-hedged bonds, and there is no doubt that this is an important asset for the pension industry.

Shifting into alternatives

However, the 538.6 billion yen ($3.6 billion) Daiwa Houses Industry Pension Fund, has already slashed its allocations for fixed income while the fund has diversified its portfolio excessively by sharply pouring into alternative investments.

“For my part, I think it would be better not to have the same excessive expectations for bond investments as we had in the past,” Toru Yamane, investment management director of Japan’s largest homebuilder, said in a panel discussion during the second day of the 17th Global Fiduciary Symposium in Tokyo on November 14, 2023.

“Our domestic and foreign bond allocation for both domestic and foreign bonds only accounts for 5.5 per cent of our entire assets,” Yamane told a panel discussion. “From anyone’s eyes, this doesn’t look like a core asset, but this doesn’t mean that we treat the asset class as unnecessary.”

He went on to explain the fund’s strategy in fixed income, saying the pension fund considers bonds as one of the components to diversify its portfolio but it also takes exposures in fixed income through alternatives on top of traditional bond investment of 5.5 per cent, bringing the overall total of bond products to 11 per cent.

Normal yield curve

A chief investment officer of a corporate pension fund based in western Japan, who spoke on the condition of anonymity, said he was looking for an opportunity to take exposures to traditional US bond investment. High currency hedging cost has made the pension fund difficult to buy US fixed income, forcing the fund to park their assets into short-term US MMF.

The chief investment officer is now looking for the timing for the yield curve to normalise to start full-fledged investment in US fixed income.

“Pension funds should take a long-term strategy but it’s not appropriate to their strategy frequently,” he said. “We have to wait until the yield curve normalises and if that happens, we’ll start investing in US long-term bonds.”

Rising global interest rates and currency hedging costs have given headaches to other portfolio managers, prompting them to refrain from currency-hedged foreign bond investments and seek shelter from Japanese government bonds. They were closely watching the Bank of Japan’s monetary policy to see when the bank would start raising its interest rates.

As for Gakuji Takahashi, chief director at Nikkei Pension Fund, he recently parked about two billion yen worth of funds from proceeds gained from domestic and foreign equities into domestic bonds.

Potentially, there is more of a likelihood of dealing capital loss from domestic bond investment as the BOJ is expected to alter its excessive monetary stimulus policy and see raising interest rates, with uncertainty prevailing about when the Japanese interest rates will settle down.

“In any case, domestic bond investment could deal capital loss,” Takahashi said. “In such a condition, we chose the strategy to focus on short-term domestic credit. Until the BOJ’s monetary policy is clear, we’re planning to take such a strategy as a precautious measure.”