Norway’s $2 trillion sovereign wealth fund, Norges Bank Investment Management, has divested US machinery manufacturer Caterpillar and five Israeli banks from its equity portfolio because of the risk of these firms contributing to human rights violations in the Palestinian territories.

The ethics committee for the world’s largest sovereign investor, which manages the assets of the oil fund, found that Caterpillar’s yellow bulldozers were being used in the “unlawful destruction of Palestinian property” and Caterpillar has “not implemented any measures to pre­vent such use.” NBIM had a $2.4 billion investment in the company at the end of 2024, equivalent to an ownership stake of around 1.2 per cent.

Meanwhile, NBIM has divested Israeli banks First International Bank of Israel Ltd and the holding company FIBI Holdings Ltd, Bank Leumi Le-Israel BM, Mizrahi Tefahot Bank Ltd, and Bank Hapoalim BM because these businesses have provided financial services required for construction activity in the West Bank, which had been “established in violation of international law”.

Last year, the United Nations found that Israeli settlements built on territory seized in 1967 were illegal, a ruling that Israel called “fundamentally wrong” because of its historical and biblical ties to the land.

“Before deciding to exclude a company, Norges Bank shall consider whether other measures, including active ownership, may be better suited. The board’s assessment is that it is not appropriate to use other measures in these cases,” said NBIM in a statement.

Part of an ongoing purge

The latest divestments mark a step up in the oil fund’s response to growing scrutiny of whether it has been helping to finance Israel’s war in Gaza, and come in response to Norway’s Ministry of Finance asking the fund to review its investments in Israeli companies.

A letter from the Ministry of Finance in early August questioned the fund’s individual investments given the deteriorating situation in the West Bank and Gaza.

Earlier in the month, NBIM sold its eleven holdings of Israeli companies outside of its equity benchmark index and severed ties with external Israeli fund managers. It means the fund’s investments in Israel are now limited to companies that are in its equity benchmark index.

However, it won’t invest in all Israeli companies in its reference index. There were 56 Israeli companies in the benchmark index – which consists of around 9,200 global companies – at the end of the first half of the year. NBIM currently invests in 38, with a total investment value of around NOK 19 billion (approximately $1.9 billion).

“These measures were taken in response to extraordinary circumstances. The situation in Gaza is a serious humanitarian crisis. We are invested in companies that operate in a country at war, and conditions in the West Bank and Gaza have recently worsened. In response, we will further strengthen our due diligence,” said Nicolai Tangen, chief executive of Norges Bank Investment Management, speaking in early August. “The measures we are taking will simplify the management of our investments in this market and reduce the number of companies that we and the Council on Ethics monitor.”

The oil fund’s divestment strategy has also lagged Norway’s much smaller NOK 878 billion ($87 billion) Kommunal Landspensjonskasse (KLP), the fund for local government employees and healthcare workers.

In July, KLP stepped up exclusion to include US industrials group Oshkosh Corporation and Germany’s ThyssenKrupp for selling weapons including armoured personnel carriers, warships and submarines to the Israeli military.

Updated expectations

NBIM said that in 2022 and 2024 it updated the expectation document on human rights and strengthened the expectations of companies’ conduct in conflict areas to reduce the risk that they contribute to violations of human rights and international law.

Since 2020, NBIM has contacted over 60 companies about due diligence and risk-reducing measures in war and conflict areas.

“We have had dialogue with over 30 companies with operations connected to the West Bank and Gaza. This is ongoing work that is given high priority,” said the fund.

The investor monitors new companies that enter the investment portfolio on a daily basis, and since 2024 has required that external managers must have prior approval to make investments in Israeli companies that were not already included in the portfolio.

“Not all new companies that were assessed received such approval,” it said.

That includes Bet Shemesh Engines Holdings, the Israeli aerospace and defence company, which was originally assessed as a company with medium risk. The Ethics Council said it should have escalated the risk sooner after media reports uncovered the investment, prompting public outcry.

“Given the information that has now emerged, the company would have been assessed as high risk. With a broadly invested global portfolio, there will always be a risk that information is not captured early enough, or that we make assessments we, in hindsight, would have made differently,” said the fund.

China’s $420 billion National Social Security Fund is scoping out technology-related investment opportunities in domestic equities, particularly the so-called “AI+” theme that has been gathering market and political momentum.  

As a largely domestic investor with 88.5 per cent of its assets invested in China, the fund’s perspective signposts where opportunities are emerging in A-shares. Its push into AI and technology-related stock points to sectors that will benefit from policy support and domestic demand.

“AI+” refers to cases where artificial intelligence is married with traditional industries to enhance profitability, such as “AI + agriculture” where machine learning is used to monitor soil health and pest problems and “AI + manufacturing” where it is used for product quality control on the assembly line.  

It was a prominent theme at this year’s Two Sessions – China’s top political gathering – where Premier Li Qiang highlighted AI-enabled electric vehicles, smartphones, computers and robotics as key technology priorities in 2025. 

“The ‘AI+’ investment opportunities warrant attention, including how leading internet companies are integrating computing power and algorithms into consumer-end applications, how AI can enhance profitability when combined with China’s strength in traditional light industries such as furniture and toy-making, and those companies in the robotics supply chain that have already secured global orders,” according to a new research paper from the National Council for Social Security Fund (NCSSF) – the agency that manages and invests China’s strategic pension reserve – published in Chinese. 

“AI+” is the next iteration of the “internet+” strategy which the central government first backed during the Two Sessions in 2015. It homed in on transforming traditional industries with speedier connection and information exchange, which prompted the rise of e-commerce giants, mobile payment systems, ridesharing platforms, delivery services and travelling apps. 

Aside from traditional industries, the paper – authored by Li Na in the fund’s asset allocation and research department – flagged that Chinese tech giants have the potential to amplify their strengths in AI applications this year, supported by the rapid rise of domestically developed algorithms.  

It is a welcome shift from what the fund observed in 2024 when, aside from a handful of outperforming companies and short-term thematic trades, the AI sector in China’s A-share market offered little broad-based beta opportunities. 

The investor is paying close attention to technology stocks because of the resilience they showed during risk-off periods. Supporting this thesis, the NCSSF’s research examined two case studies of the US and Japan, focusing on periods when their respective 10-year government bond yields fell by 100 basis points from 2 to 1 per cent.  

Broadly, it took 8.5 years (2011-2020) for US Treasury yields to fall from 2 to 1 per cent before recovering an upward trend, and 14.5 years (1997-2010) for Japanese government bonds, the research said.  

It tallied the performance of different asset classes during these two stretches and found one commonality between the US and Japan: the technology sector (S&P 500 Information Technology and TOPIX Precision Instruments) posted strong gains relative to the broader equity markets.  

“Defensive sectors such as utilities and food also performed well. The main divergence appeared in financials: Japanese financial stocks dropped sharply, while US financials advanced,” Li wrote, concluding that during period of falling yield the technology sector still provides ample investment opportunities.  

Aside from China A-shares, Li also recommended looking out for any corrections in US tech companies which could be attractive entry points.  

“In 2024, the US equity market has been characterised by a combination of high returns, low volatility, and elevated valuations. Continuous capital expenditures by technology companies supported earnings growth for leading computing power providers, while AI firms such as Palantir translated enterprise-focused AI applications into tangible performance,” Li wrote. 

“[In 2025], AI-driven applications that lower costs and improve efficiency, as well as services and products with large market potential – such as autonomous taxi services – warrant close attention.” 

The research also recommended increasing allocation in foreign bonds which has become attractive due to the low-interest rate environment in China.  

Since NCSSF was established in 2000, its annualised rate of return was 7.36 per cent as at December 2023. It has 14 departments managing 31.2 per cent of the investment in-house and 68.8 per cent via external mandates.  

It invests in a list of asset classes approved by the State Council of China, including domestic and foreign equity, bonds, bank deposits, investment funds and foreign derivatives. 

By the evening of August 7, the same day GPT-5 was launched by Open AI, NBIM had it available to the entire organisation in a secure and scalable way. Joined on stage by CEO Nicolai Tangen at this year’s Arendalsuka, the team behind AI integration explains their aggressive approach.

Embracing the use of AI within Norges Bank Investment Management is clearly coming from the top, with CEO Nicolai Tangen, a former hedge fund manager, leading the charge.

“This is one of the most amazing things we are going to experience in our lifetime. It’s absolutely crazy,” said Tangen, speaking at this year’s Arendalsuka, Norway’s annual political gathering. “There are too many companies where it’s not happening enough, and if you’re not involved now, you’re falling behind and you’ll never get back on the offensive.”

Comparing himself to a “wasp” for “continuously irritating” staff on the matter – and likened to an AI “tornado” by NBIM’s chief technology and operating officer Birgitte Bryne who joined him on stage – Tangen said leading on AI integration involves attacking from all sides.

“Every time I get the microphone, every time we are doing something in the fund, I’m honking at everyone that ‘it’s AI that counts, it’s AI that counts, it’s AI that counts,’” he said.

There are tangible examples of AI’s deployment at the world’s largest investor, including an internally developed engine powered by AI to monitor and measure its portfolio managers’ skills, aiming to identify behavioural biases, improve decision making, efficiency of trades and save costs. (see How NBIM spots portfolio managers’ biases using AI)

Tangen has been on the record outlining the expected $400 million savings in trading costs per year, saying the fund has already achieved close to $100 million.

At Arendalsuka, he said the fund has now upped its goal to achieve a 20 per cent increase in efficiency in the hope that in two years NBIM will be almost “50 per cent more effective.”

And he’s vocal about the need for all employees to embrace AI – or get off the bus.

“We are not doing this to somehow save money, or fire people. On the contrary, we are doing this to achieve much more with the same resources. People [have to] understand that if they don’t do it, in the long run they will lose their jobs to the other person who uses AI because they are so much more efficient.”

In a presentation peppered with humour and infused with energy he said integrating AI gives employees purpose; it’s fun and is a chance to develop.

Pushing through organisational change

Taking the microphone, Bryne shared that the investor has introduced accessible training that includes mandatory 30-minute modules. This has helped create a level of knowledge amongst all employees whereby everyone “knows what we were talking about” and AI had stopped being “scary.”

NBIM has 40 specially trained AI ambassadors within the organisation. The investor recently ran a hackathon where all employees spanning offices in London, New York and Singapore gathered in small groups and were asked to solve specific tasks using AI, with the help of a technician.

Bryne said the investor has launched three tools, including a copilot/chatbot now used throughout the fund that allows staff to use AI without any knowledge of coding. Staff are supported though frequent “bumps” that often take three attempts to navigate. Meanwhile measuring AI gains includes monitoring which tools are most used, what tools people don’t use – and what it is they need to use.

“It’s very important feedback to have people themselves quantify what has helped them and what necessarily may not have helped them,” she said.

Fellow panellist Oscar Hjelde, who joined NBIM as a summer intern and is now a machine learning and AI engineer based out of NBIM’s London office, articulated the importance of “baking the cake internally” – aka in-house AI expertise. NBIM’s own tech stack enables it to be flexible introducing new solutions, and creates a proximity to the solutions the investor seeks, he said.

It has also helped build the investor’s developmental culture and allows AI integration to tap into NBIM’s “incredible number of talented colleagues.”

He said strategy involves taking the technologies “that we know are best, and make them available throughout the organization.” For example, GPT-5, the multimodal large language model developed and hosted by OpenAI was launched on August 7, 2025. That same evening “we had it available to the entire organization in a secure and scalable way.”

Hjelde reflected that the best way to predict the future is to build it – and the second-best way to predict the future is to talk to those who are building it.

It’s why the team regularly talk to Anthropic, the artificial intelligence startup backed by Amazon that allows them to “look into a crystal ball.” Proximity to companies at the cutting edge of AI also allows NBIM to have influence, and say to providers what is most important to them as a customer. “You get to be part of the latest adventure on the latest new technology and really sit at the forefront,” he said.

NBIM’s portfolio managers also regularly engage with portfolio companies on how they are investing in AI.

Bryne said that the next evolution will involve staff using technology that thinks for itself and carries out task “like an extra employee that is digital” in an “absolutely incredible boost for any business.”

It involves treating AI like a colleague and partner, rather than a tool.

Co-panellist Aleksander Stensby, founder of Norwegian AI company GritAI, said that when people think of AI as a tool they get “disappointed” when it doesn’t give the result they want. However, if they think of the technology as a partner they will give it feedback, and get the best results.

In this way people will move away from how they traditionally work on computers. Instead of typing on a keyboard and writing, they will live and talk to AI via microphones and cameras. These additional employees will share screens and press buttons in a multimodal future where they are assigned tasks.

“Nikolai can create his own little solution for whatever he struggles with during the day,” joked Stensby.

Integrating AI is not an IT project

Panellists reflected that some companies and their employees are progressive and forward-thinking AI natives. But many organisations have stalled because they lack a comprehensive strategy. They might have run pilot projects but have not strategically prioritised AI, and don’t have a belief or mission statement regarding the technology.

A successful strategy can also flounder because of a lack of urgency or shared ownership, which risks leaving people out in the cold.

Panellist Tine Austvoll Jensen, country director of Google Norway and board member, said that geopolitical unrest has also injected caution into AI strategies amongst Nordic companies concerned about the safety of American cloud solutions. Although Google and its competitors have solutions on European soil, she said uncertainty has held companies back.

Panellists concluded that such is the pace of development last year was “like the Stone Age” in relation to where AI is today.

Two ideas have recently coalesced in my mind and have started a new train of thought.

The first idea is my relatively recent discovery of the term ‘AI slop’ (there is a Wikipedia article linked here). The ‘slop’ is low-quality writing and images generated by AI.

Given that AI has only just started generating, we might heroically guess that internet content is currently 95 per cent ‘good’ and 5 per cent slop. The numbers are actually unimportant – what matters is how the proportion is likely to change.

My hunch is that in 10 years we will be swimming in a sea of slop. We could let our imaginations run a little and consider new jobs and new businesses being formed to act as slop filters. Even so, I doubt that it will be super-hard to separate financial data from fake cat photos, even if we have to shift a mountain of fake to do so.

But we should introduce the second idea.

This one came from WEF’s Global Risks Report 2025. Unsurprisingly the biggest risk for 2025 is ‘state-based armed conflict’, followed by ‘extreme weather events’ and ‘geoeconomic confrontation’ (tariffs, anyone?).

In this context, I was slightly surprised by number four: ‘misinformation and disinformation’. Surprised because it ranked higher than 29 other possible risks, and further surprised when I read on and discovered that on a two-year view (ie today’s expectation for the most important risk in 2027), it is the top-ranked risk.

On a 10-year view it ranks fifth, but is the most significant non-environmental risk. A quick internet search (note to self, can I trust the results?) reveals that the University of Cambridge held a three-day disinformation summit in April 2025. It would appear that something important is going on here. Maybe there is a genuine threat to the integrity of financial data.

Before we merge these ideas it might be worth quickly distinguishing between mis- and dis-information. Both are incorrect information, but misinformation has no malicious intent. The objective of disinformation, on the other hand, is specifically to deceive.

So, WEF’s panel of 900 experts see misinformation and disinformation as one of the most significant risks over the next two to 10 years. And we have recently invented a fantastically efficient slop-generating machine that, in all likelihood, we intend to scale up massively.

Who do we expect to be the most adept users of this machine – the good guys or the bad guys? Is it reasonable to hope that the good guys will be able to keep us safe enough, as the anti-virus providers currently do? Or have the terms of the arms race shifted in favour of one side or the other?

One angle on this – perhaps the most important one – is ownership. In our hyper-connected information ecosystem, is it wise to rely on a handful of platforms, most of which are privately owned?

While we may be relaxed about the current ownership structures of the financial data providers, this may not remain the case, and we are relying on them to deal with the mis- and dis-information on our behalf.

I am not qualified to comment usefully on the disinformation angle, and so I am restricting my concern to the misinformation side, and the volume of slop that is likely to be generated. Will we be able to keep up in terms of distinguishing fact from fiction?

To give further context to my concern, in Thinking Ahead we have recently produced a fair bit of material on systemic risk and systems, usefully summarised in The simple, and enlightening, story of systemic risk.

In it we note that reality is too complex to understand, and so we build models – simplified versions of reality – in order to make our decisions. Implicit within this is the belief that the information we are using for our model building is an accurate or, at least, unbiased reflection of some aspect of reality.

Will this belief still hold in 10 years? Will we have the tools and skills to parse and filter accurate information from the inaccurate? Will the relationship between the market price and the unobservable true price of a security remain constant? Or might it change if the true price becomes too complicated for many to bother with?

And this is before we factor in the possibility that there is a growing band of actors with the intention to deceive us.

This is, of course, just conjecture. But all thinking ahead is the attempt to peer into the unknowable future given what is reasonable to infer from the present. If this is a feasible vision of the future then certain best-practice elements like governance and beliefs are probably worth a refresh.

In terms of new practice, or revised priority, I would suggest that the idea of data provenance is introduced and made a strategic priority. So each data point that plays a role in your decision making carries a flag showing its source, and perhaps a second flag that scores the trustworthiness of that source.

In this way, if you changed your mind about the trustworthiness of a source you could change the score rather than the data point, and allow your process to down-weight the influence of that data on your decision.

While we are at it, you could also play at pre-mortems – what if we discovered this data was unreliable, how would our decision change if we down-rated or disregarded it?

It is clear to me that the quantity of slop will balloon over the decade. It is not clear to me that this will necessarily be problematic – perhaps our existing tools, or new tools, will allow us to filter it out just fine.

Nevertheless, I can’t help thinking that making data provenance a strategic priority would be a sensible precautionary step. It is possible that this might also serve as a first line of defence against disinformation. However it is highly unlikely to help with the ownership issue we noted above.

Might we conclude that it is better, if more expensive, to generate the data ourselves (or via a trusted asset manager)?

Tim Hodgson is co-founder and head of research of the Thinking Ahead Institute at WTW, an innovation network of asset owners and asset managers committed to mobilising capital for a sustainable future.

This article was published in partnership with Blue Owl Capital.

This article was published in partnership with Blue Owl Capital.

The surging interest in generative AI has triggered a technological arms race, driving demand for high-density data centres. Investors are looking to capitalize on what is often described as a generational opportunity, but as Blue Owl’s James Clarke cautions, investors need to consider several important factors as they try to determine who to partner with for the long-term. Those who have a sustainable edge, coupled with subject matter expertise, local presence, and the right partnerships will stand out from the tourists in the space.

The Challenge
In the movie 28 Days Later, London has been savaged by a raging virus. What exists is just a deserted urban landscape.

I can’t help but think that at some point in the not-too-distant future, I could be flying over Northern Virgina or Silicon Valley and look down to see hectares and hectares of decommissioned data centres. It’s a haunting and dystopic vision, but not implausible. Amid all the hype on AI and infrastructure – and the possibility of disruption – it’s worth asking, could this boom go bust?

It is challenging to cut through the clutter and make sense of the fundamentals. Data centres make major headlines almost daily – from hyperscalers committing to levels of capital expenditure never seen before to DeepSeek’s disruptive emergence as a more cost-effective competitive threat. As some in the space note, “Market participants may be faced with making unprecedented infrastructure commitments while navigating rapidly evolving technology, uncertain financial models, and intensifying geopolitical competition.” Against this backdrop, what’s the long-term investment case and how should we think about investing in data centres and digital infrastructure? The right answer is often the simplest one: find the right partner with whom to navigate the uncertainty.

The Opportunity
“Crossing the Chasm” describes the critical point in tech adoption when a product moves from early adopters to the early majority. Have we made that crossing? Is AI as big a driver of demand as the market suggests? By all measures, the answer seems to be yes.

We are living through a wave upon wave moment in which both cloud computing – think video streaming, gaming, trading, medical devices, and autonomous driving vehicles – and AI are driving the demand for compute and therefore necessitate more data centres. Cloud is its own wave, growing by 20% to 30% annually and is for many a compelling rationale alone for investing in data centres. Our own digital infrastructure business was founded nearly a decade ago based solely on the demand for data centres from cloud adoption.

While cloud was enough, the even bigger wave came when OpenAI debuted ChatGPT in 2022, bringing with it an additional step-function of demand that is growing exponentially. From October 2022 to April 2025, ChatGPT went from zero to 800 million weekly active users, from zero to 20 million subscribers, and from zero in revenue to nearly $4 billion. Given the confluence of cloud and AI, McKinsey estimates that in the US alone, the demand for data centres will grow to 80 Gigawatts (GW) by 2030, which implies a buildout of an additional 50 GW to 60 GW over the next five years. Globally, “by 2030, data centres are projected to require $6.7 trillion to keep pace with the demand for compute power with $5.2 trillion for AI and $1.5 for cloud and traditional IT applications”.

As investors seek to capitalize on the AI boom through exposure to data centres, these trends explain the potential upside. But what are the risks? Could someone deliver compute more efficiently or could there be a breakthrough in quantum computing that renders today’s infrastructure obsolete? This is where Jevons Paradox offers a comforting lens: improvements in efficiency can amplify demand and consumption, not reduce them.

This is what crossing the chasm is all about – getting to the point of mass adoption. Thus, the risk of disruption becomes an argument in favour of investing in data centres. A good partner has the foresight from experience to anticipate the paradox.

Avoiding the Tourists
Given the imbalance of supply and demand of capital in data centres, investors need to be wary of the “tourists” raising capital in the space. These tourists – opportunists swooping in given the recent market hype– likely think all it takes is buying land. But those with experience know that the land is just the beginning. You must have a ground game to understand developing in these markets, which means knowing how to navigate the dynamics amongst local stakeholders — communities, regulators, utilities, grid operators, construction companies — to see a project through. Without expertise, it’s easy to blindly misstep.

What should you look for instead? Given that hyperscalers are the primary drivers of capital expenditure and are the players involved in the race for compute, look for the market participants who have a hyperscale focus and a proven track record with a reputation for their experience, expertise and are trusted and transparent partners.

Focus on managers who develop build-to-suit instead of build-to-spec. Having a long-term (10 to 15 year) signed triple net lease with an investment-grade corporate tenant provides stability, predictability of cash flows, and downside protection. There are only a select handful of managers that can achieve this: those with scale, global reach, local presence, and vertically integrated operating platforms. Managers who have done it before and are a partner of choice for the hyperscalers and who have seen opportunities where others did not.

Finding the Path Forward
There is no question that AI is a megatrend that has the potential to radically transform economies, triggering governments, organizations, and investors to spend billions of dollars on research and development, including the build out and innovative improvement of digital infrastructure. Investment in data centres is rightly seen as a generational opportunity; it’s real and it’s here to stay. Yet, the opportunity does not always guarantee results, profits, or success.

Many of us will remember the excitement of the internet in the early 2000s – and how many of the promising start ups at the time ended up in the investment graveyard. The only hope of banishing the fear of data centres decaying into rusting shells? Choosing the right partner. Because if the lights do go out – if the servers go cold and the racks fall silent – at least your partner knew to bring a flashlight.

While we don’t know what the future holds, it is very likely that those that succeed are the players with subject matter expertise and experience; those who built investment platforms optimized to work with the hyperscalers and structure investments with a focus on cash flows and downside protection. That is the way to invest: gauging the probabilities and searching for the attractive risk-adjusted returns.

In an interview with Top1000funds.com, CalSTRS chief investment officer Scott Chan says the one fund approach has already started to produce alpha. Sarah Rundell looks at the drivers of success including the ability to move more dynamically and cross-asset class collaboration to take advantage of opportunities.

The impact of dynamic asset allocation, made possible through a one-fund approach, was manifest in CalSTRS’ recent annual results and will be an increasingly important seam to investment strategy going forward according to chief investment officer, Scott Chan.

At the beginning of this year, the $367.7 billion fund adjusted its portfolio defensively, adding more to risk-mitigating cash and fixed income strategies to ensure above average liquidity to position the portfolio ahead April’s volatility. [See Cashed-up CalSTRS positions for opportunities in volatile markets]

The ability of the team to underweight or overweight in the context of total portfolio risk is the fruition of Chan’s determination to form a total fund management division – CalSTRS’ version of a total portfolio approach that is also under consideration at CalPERS, its neighbour across the river – to leverage insights from each division, see where opportunities sit and what kind of returns can be made.

“For the first year we have generated alpha based on a more dynamic asset allocation,” says Chan in an interview with Top1000funds following the fund’s latest results.

Chan says the pension fund produced about 8 basis points of alpha last year, contributing to a figure of 76 basis points over the five years. This year in addition to the team selecting the right assets and beating the benchmark to do better than average, they also created value through dynamic asset allocation, he says.

“If we hadn’t [done this] we wouldn’t’ have produced positive alpha,” says Chan.

The ability to invest tactically to position the portfolio to benefit from volatility has required putting in place cultural and organisational structures, notably a total fund team that maps a common language of risk, and how portfolio risk is shifting.

Different teams need to be able to collaborate to truly understand where the return opportunity sits and how returns might fall in the future, continues Chan.

For example, the early 2025 decision to overweight fixed income and underweight hedge funds contrasted to previous years when fixed income was forecast to return less because interest rates were zero and hedge funds do better, took a new level of collaboration.

“It required one team to say we believe we will make more returns on a forward basis, and another to say we think we will earn less.”

One team one dream

A successful one fund approach also involves making sure CalSTRS takes advantage of its scale.

For example, three different divisions at the pension fund – real estate, infrastructure and sustainability – share expertise in data centres. By working together, they can create a level of expertise that supersedes acting individually to find the best long-term value creation.

Looking ahead, Chan believes this kind of collaboration will position the portfolio to benefit from opportunities in AI like data centres, but also the net zero build and the “huge” transfer of the banking system to long term investors in the form of private credit. Collaboration has already informed a strategy whereby CalSTRS has shifted its direct lending focus to opportunities in Europe and in asset-backed private credit in response to squeezed premiums in the US.

“This kind of collaboration is a growing element of the one fund approach. In a broader strategy than just moving the portfolio more dynamically, we are also moving our partnerships more dynamically at scale. These will both be important value drivers for CalSTRS.”

He says the one fund approach signposts a new type of portfolio construction focused on greater diversification, risk and liquidity management, and dynamic asset allocation, and is a response to an investment environment now characterised by different geopolitical and trade relationships and a new interest rate environment.

He also doubts that growth will continue as it has in recent years. Global equity has led returns at CalSTRS for the last three years in a row, most recently returning 16.4 per cent.

“[Global equity] doesn’t do that year-in year-out. If we have reached the point where valuations are high and we hit pause, it wouldn’t surprise me.”

A new interest rate environment means interest rates are more likely to be higher going forward than they have been in the last decade. This flags opportunities in private credit and infrastructure, which will also become more interesting in an inflationary environment stoked by deficit spending.

“A lot of what we are doing is finding out where the environment is providing the best opportunities in a different world,” he says.

Still, he is hesitant to call an inflection point in real estate where the increase in interest rates and the lingering impact of the pandemic continues to hit hard. But in a reflection that the market might finally be “closer to the bottom” he notices that for the first time investors are beginning to deploy more capital back into debt portions and write equity cheques.

The 8.5 per cent net return for the fiscal year ending June 30 contributes to strong long-term five-year (9.4 per cent) 10-year (8.1 per cent) 20-year (7.4 per cent) and 30-year (7.8 per cent) numbers.

“It’s important to remember that one year is a mile in a marathon,” concludes Chan.

Scott Chan will be speaking at Top1000funds.com’s Fiduciary Investors Symposium on campus at Stanford University from September 16-18. For the program and more information click here.