Investors should adopt the standardised fee reporting template for private equity released by the Institutional Limited Partners Association, according to Mike Heale and Andrea Dang from CEM Benchmarking. Their research shows that it is not possible to get complete costs from current statements alone, with important costs buried by GP’s statements. CEM encourages all pension funds to adopt the ILPA fee reporting template by asking all GPs to report in this format.

Private equity is an increasingly important asset class for many pension funds. Private equity holdings of US public funds have doubled from 4 per cent to 8 per cent of total assets over the past 10 years in the CEM database. However, private equity firms have received sharp criticism of late for the lack of transparency and understatement of full costs in investor financial statements. CEM research concluded that less than half of full private costs were reported by pension funds in 2012 and 2013.

To further examine this problem, CEM was commissioned by a group of leading global funds to study how private equity costs are reported to limited partners (LPs). The goals of the research were to estimate the full cost of private equity and its components to determine whether full costs can be obtained using financial statements provided by general partners (GPs).

CEM received 2014 financial statement data for 147 private equity partnerships from 15 client funds. There were 126 direct limited partnerships and 21 fund-of-funds. Total commitments were $455 billion, and total net asset value (NAV) was $238 billion. Vintage years ranged from 2000 to 2014, and primary geographic regions of investment were US at 40 per cent and global at 31 per cent.

CEM concluded from this study that partnership financial statements rarely provide enough consistent and detailed cost information to estimate full costs. As a result, it is not possible to get complete costs from current statements alone.

Size of total PE cost and components

Using a combination of the CEM database and the financial statement review, we estimated the total cost of investing directly in private equity was 380 basis points on a fees-paid basis (management fee basis – typically total commitments during the investment period and invested capital post-commitment period) or 571 basis points based on NAV (partnership’s current value). Fund-of-fund costs were higher due to the additional top-layer manager fees: 173 basis points on a fees-paid basis or 217 basis points on NAV.

160201 - Table 1

Gross management fees accounted for almost half of total private equity cost, while carried interest was about one-third of total private equity cost. Regarding the amount of carried interest, the limited time period of this study introduces potential bias because private equity returns are highly positively correlated with stockmarket returns. However, we would still expect carried interest to be a large portion of total cost over a longer time period.

Findings on financial statement transparency and consistency

CEM found that extracting the appropriate figures from the statements can be very difficult and time-consuming. The format and wording across statements varies and is not standardised. Important cost information is buried in the notes to the statements. These deficiencies, and especially those described below, impede understanding and identification of true costs.

Treatment of management fees

The financial statements perpetuate the industry myth that management fees are reduced by fee offsets (charges to portfolio companies that are shared by the GP and LPs). The table below demonstrates that the actual LP cost is 189 basis points versus the 143 basis points that is typically reported.

160201 - Table 2

Thirty-one per cent of limited partnerships did not even report gross management fees, thereby implying that the net management fee is the only cost that matters. CEM believes reporting net management fees is misleading because the GP receives compensation equal to the gross management fee plus their share of fees eligible for offsets.

Inconsistent reporting of carried interest

Carried interest was usually reported on an accrual basis, although the basis was indeterminate for 21 per cent of statements. Also, carried interest was not reported in the same format across statements. Some partnerships had a separate account balance that tracked carried interest while some statements only had carried interest detail in the notes to financial statements.

Partnership expenses and transaction costs

Partnership expenses include professional, administrative, accounting and other fees. These were higher than expected and varied widely across partnerships, ranging from 5 to 106 basis points. In addition, categories for partnership expenses were vague in some cases with some partnerships reporting only two categories of expenses – professional and other.

Transaction costs were excluded from our analysis because they were identifiable in only 6 per cent of statements. Dutch funds are required to report PE transaction costs. CEM data from Dutch funds in 2014 suggests transaction costs average 32 basis points.

The solution – the new ILPA fee reporting template

The only way to get full private equity costs is by asking the GPs directly. A growing number of LPs are asking GPs to complete bespoke cost templates. Some pension funds are invested in hundreds of partnerships. This is an inefficient and problematic solution for both LPs and GPs.

Fortunately, a good global solution is now at hand. The Institutional Limited Partners Association (ILPA) recently released a new standardised fee reporting template. Several leading pension funds, interested industry firms, and CEM participated in the ILPA working group for this initiative. The template development process featured extensive global consultation and feedback from LPs, GPs, industry associations, and other interested parties.

The template features a lot more than cost information. It includes important management, control, and fiduciary information. For example, it has an interesting section that summarises all “GP and related party compensation”.

The cost information in the template is standardised, detailed, and complete. Six line items contain the cost information needed to report and benchmark total cost and its major components: gross management fees; accrued carried interest; total partnership expenses; and capitalised transaction fees and expenses.

Now it needs to be adopted. CEM encourages all pension funds to adopt the ILPA fee reporting template by asking all GPs to report in this format.

Full cost disclosure has many benefits for LPs:

  • Better decisions – CEM research shows that PE performance is impacted by costs. Higher cost implementation styles, such as fund-of-funds, generate lower returns. A better understanding of true costs will lead to better decisions.
  • Lower costs – understanding full costs can lead to reductions through negotiation with GPs. For example, a larger share of portfolio company fees is now distributed to LPs. Over time, the split has moved from a 0 per cent/100 per cent LP/GP distribution to about 85 per cent/15 per cent
  • Reputation risk – stakeholders are increasingly demanding transparency and evidence that these costs are being managed.
  • Fiduciary duty – LPs investing for others have a fiduciary duty to ensure that costs are reasonable and that correct amounts are paid. The amounts involved are huge.

Standardised full cost disclosure for private equity has arrived. You can find it on the ILPA website.

Carpe diem!

Mike Heale is a partner and Andrea Dang is a senior analyst at CEM Benchmarking.

PGGM has committed to reducing its carbon footprint by 50 per cent, but for many asset classes it doesn’t know what the current carbon footprint is. To fill this gap it has been creating some innovative partnerships, including the data and analysis provider, GeoPhy, which has the carbon footprints of a staggering 60 million properties globally. Amanda White reports on what can be achieved when “real estate meets big data”.

The €182 billion ($280 billion) PGGM has made a commitment to reduce by 50 per cent the carbon footprint of its portfolio by 2020. But to do this it needs to know what its current carbon footprint is.

For some asset classes that is easier than others, and for real estate it means collaborating with new providers to fill the data gap, improve transparency and ultimately develop a model to map real estate.

PGGM was a founder of GRESB, alongside APG and USS, which assesses the sustainability performance of real assets around the globe.

Mathieu Elshout, private real estate investment manager at PGGM, says the fund has been using GRESB to measure the “green” performance of its €10 billion ($15 billion) real estate portfolio for some time. And according to the GRESB ratings, 50 per cent of  PGGM’s private and listed real estate portfolio has a green star.

“We are very happy with that because we have seen an increase in our green star-rated buildings. That is not a goal in itself to invest in green star real estate but we think there is a link between better financial and sustainable performance.”

But the fund also has a new ambition to decrease the carbon footprint of its portfolio by 50 per cent by 2020.

In order to achieve this, PGGM needs more data, so it could not only look at the performance of its existing portfolio, but use carbon footprints as an input for decision making for new investments as well.

“There are other new instruments and standards needed to compare between portfolios and we are talking to other institutional investors to develop common standards and compare data,” Elshout says.

PGGM has teamed up with GeoPhy which maps the quality of the real estate portfolio and, specifically, maps the carbon footprint of buildings.

GeoPhy has data on a staggering 60 million buildings in 49 countries.

Chief executive of GeoPhy, Teun Van Den Dries, was trained as a sustainability engineer and architect and did a lot of traditional carbon footprinting, producing one-by-one reports. This in-field experience was a driving force for the business to seek a more robust method for carbon footprinting. Its business is all about data, and it partners with data suppliers and employs data scientists for analysis.

GeoPhy has data on each building’s year of construction, sustainability labels, refurbishments, size, function and energy usage.

It uses an automated structure, with no manual review, via local data sources: for example, in the UK, the land registry is a data partner in exchange for analysis.

PGGM engaged GeoPhy for portfolio mapping to build an approximation of the portfolio carbon footprint, and handed over its portfolio holdings.

“PGGM has a carbon reduction mandate but it had no baseline to measure that against,” Van den Dries says.

With a baseline in place, PGGM can engage with companies, use it as a tool for reporting and demonstrate progress in its mission to reducing its carbon footprint by 2020.

GeoPhy has now done the analysis for PGGM on every building in its real estate portfolio – about 7.5 million individual buildings – to reveal what their baseline is. PGGM is now reviewing, and decisions can be made on how to reduce it.

Because the analysis is done at such a detailed level, Van Den Dries says it reveals some interesting anomalies that might not be immediately apparent.

“The differences in relative carbon intensity were a surprise,” Van Den Dries says.

“The range of carbon footprints is enormous. For example, look at the two classic peers of the UK-based REITs, British Land and Land Securities. They both have 25 to 30 per cent in London office buildings, then residential in the rest of the country. If you look at carbon footprint, then Land Securities is the front runner, but British Land performs better because Land Securities has about 8 per cent of its portfolio in small, old hotel properties. It is a small exposure but the impact on the portfolio is enormous. It would be more effective to refurbish those hotels,” he says.

For PGGM, the aim of the portfolio mapping is to create a market standard, and it has already asked all its funds managers to use it and report on it.

“This will give them a better sense of how to direct their managers and challenge them,” Van Den Dries says.

PGGM’s Elshout says the baseline gives the manager a tool for engaging with managers and companies to reduce the carbon footprint.

“Via engagement we expect there will be more focus on improving the carbon footprint. If we divest, the building and carbon footprint will still be there,” he says. “We believe financial and sustainability performance are connected, and we are positioning the portfolio such that our belief in that sustainability pays off.”

Analysing smart beta performance and risks is not monkey business. For a better understanding of smart beta strategies it is crucial to analyse their construction principles, performance characteristics and risk-factor exposures, including not only value and small-cap factors, but also a variety of other well-documented risk factors such as momentum, profitability, investment, low risk, and possibly others, writes Felix Goltz, head of applied research at the EDHEC-Risk Institute.

 

In the marketing of smart beta strategies, index providers focus primarily on the ability of these strategies to deliver outperformance over the cap-weighted benchmark. The issue of risk exposure of these indices and performance attribution to well-defined risk factors is rarely addressed by index providers. The existence of so many smart beta strategies coupled with so little information on their sources of performance poses a risk of confusion and overgeneralisations.

There have been claims that smart beta results in value and size tilts, irrespective of the weighting method chosen, that different smart betas produce similar premia, that the added value is the same when the strategy is inverted, and that the performance of smart beta is similar to that of randomly generated portfolios, which are also referred to as “monkey portfolios”. Since the idea that smart beta strategies are as good as random deviations from cap-weighting is at the heart of all the claims above, we collectively refer to these as the “monkey portfolio” argument.

 

Research refutes argument

In recent research, we reported results to a series of straightforward tests of these claims. In order to test the various claims, we distinguished the four main claims made by monkey portfolio proponents: (i) all smart beta strategies lead to similar performance; (ii) all smart beta strategies have unavoidable value and small cap tilts resulting in performance that is similar across strategies; (iii) smart beta strategies are as good as inverse or “upside-down” strategies; and (iv) smart beta performance is due to a rebalancing effect.

Our results were not supportive of the “monkey portfolio” argument. We found that various smart beta strategies displayed pronounced differences in performance characteristics and factor exposures.

We also obtained a reassuring finding that inverting a portfolio strategy does not, in general, lead to the same performance as the original. Moreover, our tests did not support the idea that rebalancing is a main driver of smart beta performance.

Our findings imply that analysing smart beta performance and risks is not monkey business. For a better understanding of smart beta strategies it is crucial to analyse their construction principles, performance characteristics and risk-factor exposures, including not only value and small-cap factors, but also a variety of other well-documented risk factors such as momentum, profitability, investment, low risk, and possibly others.

 

Smart beta strategies

Obviously, whether or not the abovementioned arguments hold may depend heavily on which class of strategies one includes.

While their empirical tests are limited to selected strategies, the authors putting forward the monkey portfolio arguments claim that these results apply to smart beta strategies in general, meaning that an analysis of any choice of smart beta strategies should fulfil their claims.

Our selection of strategies focuses mainly on explicit factor-tilted smart beta strategies, which correspond to indices that providers have launched relatively recently.

In fact, the first generation of smart beta indices usually changed the weighting scheme from market cap-weighting, while paying no attention to explicitly controlling the exposures to systematic risk factors. Such strategies provided implicit tilts to systematic factors. More recently, many providers have launched factor-tilted indices to extract factor premia (explicit factor tilts).

The increasing interest in factor-tilted smart beta indices is also due to the success of factor investing, especially since the Norwegian Oil Fund report by Ang, Goetzmann and Schaefer, which showed that the returns relative to a cap-weighted benchmark of the fund’s actively-managed portfolio can be explained by exposure to a set of well-documented alternative risk factors.

Among possible strategies, we include a broad set of smart beta strategies in our tests. First, we include the popular fundamental-weighted portfolio strategy and the equal-weighted strategy based on broad universe.

Given that many monkey portfolio proponents are also promoters of fundamental-weighted indices, it is interesting to first check whether their general claims apply to the type of smart beta strategy they promote.

Second, we include a variety of strategies that seek explicit exposure to a given risk factor by selecting stocks with desired factor exposures. Such smart beta strategies are being offered as “factor indices” by most major index providers.

We include two different approaches in our tests. First, we include indices which select stocks by factor score and apply a diversification-based weighting scheme (diversified factor indices); and second, we include indices which, in addition to selecting stocks with the highest factor exposure, also use a weighting that favours stocks with desired characteristics (concentrated factor indices).

It should be noted that our set of strategies deliberately differs from the strategies tested in some previous research that does not include explicit factor-tilted strategies in the set of test portfolios.

Our research can thus be understood as a test of whether the claims of monkey portfolio proponents apply only to the specifications of smart beta the authors have selected for their empirical tests, or whether they apply more generally to a broader set of commonly used smart beta strategies. In particular, given the recent interest in explicit factor-tilted strategies, it appears to be relevant to test the extent to which the strong claims of monkey portfolio proponents carry over to such strategies.

 

Insights from testing

While we have not attempted to conduct an exhaustive assessment of the above claims across all possible strategies, our analysis of some commonly employed smart beta strategies suggests that these statements do not hold in general. Our results show that, while some strategies such as fundamental equity indexation may perhaps be mostly driven by a value tilt and may generate similar performance to their upside-down counterpart, many smart beta strategies display exposure to additional factors, as well as pronounced differences in factor exposures across different strategies.

Moreover, and perhaps reassuringly, the inverse of these strategies generates inferior performance.

The differences from the original results underlying the monkey portfolio arguments can be explained by the fact that we consider strategies which explicitly tilt towards a variety of risk factors, while the evidence in favour of monkey portfolio claims had omitted such strategies and instead focused on a particular selection of strategies which may better correspond to such claims.

In particular, if one selects strategies which stay relatively close to equal-weighting, it may not be entirely surprising that the performance of such strategies is extensively driven by value and small-cap exposure, as has been documented for equal-weighted strategies. Moreover, it may not be surprising that strategies which are close to equal weighting can be inverted while maintaining comparable performance benefits.

An important insight from our tests is that one should be careful to not overgeneralise results that have been derived from testing particular strategies.

While the monkey portfolio arguments may apply to particular strategies, they have been invalidated for the explicit factor strategies we chose as our main test portfolios here, and therefore these claims cannot be applied to smart beta strategies in general.

In line with our other rejections of the other aspects of the monkey portfolio argument, we do not find that rebalancing is of great consequence in explaining smart beta performance.

Our findings of important differences across various smart beta strategies imply that care must be taken not to fall into the trap of oversimplification and overgeneralisation.

The differences in factor exposures across smart beta strategies imply that using a particular set of indices corresponds to particular factor selection and factor allocation decisions.

Moreover, the different factor tilts play an important role in shaping the risk–return profile of smart beta strategies. Factor-tilted smart beta strategies perform due to large positive exposure to their respective factors, while their inverted counterparts underperform the originals due to less pronounced or negative exposure to the same factors.

When considering the adoption of smart beta strategies, investors should carefully consider which set of factor exposures is best-aligned with their investment beliefs and objectives. Making a selection from among smart beta strategies is not monkey business after all.

 

Felix Goltz is head of applied research at the EDHEC-Risk Institute, and research director at ERI Scientific Beta

 

The debate about the effect of pay inequality on both the financial and real-world markets is about to get a whole lot hotter this year. And there are a number of concurrent changes underway that mean investors will be armed with information to better gauge the relationship between macroeconomic income inequality, intracompany wage structures and corporate performance.

According to Winnie Byanyima, executive director, Oxfam International, “extreme inequality isn’t just a moral wrong. We know that it hampers economic growth and it threatens the private sector’s bottom line”.

A recent Oxfam report presented at the 2016 World Economic Forum, Having it All and Wanting more, 62 people in the world have the same wealth as the bottom half of the population, and MSCI believes that this magnitude of the disparity and the centralisation of global wealth are hard to overstate.

The Organisation for Economic Co-operation and Development has estimated that the growing inequality has cumulatively shaved off almost nine percentage points from growth of gross domestic products in the UK, Finland and Norway, and between six and seven percentage points in the US, Italy and Sweden between 1990 and 2010.

According to Linda-Eling Lee, global head of research for MSCI’s ESG group, wealth is more concentrated than at any other time in human history, including the Roman times.

“There is the issue of this disparity from a human perspective, but also financially the companies that investors invest in are starting to see the consequence of the unsustainable wage gap,” she says.

Lee says wage stagnation, and inequality, has led to public and policy pressure.

“Companies are not necessarily anticipating a large wage hike,” she says, and both Walmart and McDonald’s have already announced significant pay increases.

But perhaps the biggest change will come from the fact that companies will begin disclosing the chief executive pay ratio – the ratio between CEO pay and median worker salary – in January 2017, as part of new rules dictated by the Dodd-Frank Act in the US.

“The new disclosure may illuminate potential linkages between inequality and long-term economic growth, a particular concern for large institutional investors or ‘universal owners’.

All this means that investors will be armed with information to better gauge the relationship between macroeconomic income inequality, intracompany wage structures and corporate performance,” MSCI says in its report 2016 ESG Trends to Watch.

“This will affect operating costs which will affect earnings and ultimately their share price,” Lee says.

She says that according to MSCI research, companies with the largest pay gap do not show better company results, for example, better margins.

The MSCI research which analysed data from 591 companies from the MSCI ACWI Investable Market Index of the companies that have consistently disclosed some pay information for employees between 2009 and 2014.

“The preliminary analysis indicates that a high corporate pay gap did not achieve the intended cost savings, as indicated by the lack of significant difference in operating profit margins between companies with a high pay gap and a low pay gap. In fact, on average, companies with low pay gaps had higher operating profit margins over 2009 to 2014 than companies with high gaps in pay between their CEOs and average workers. In our data, sectors with the largest pay gaps – consumer discretionary, for instance – are also getting squeezed by wage pressure and likely to face both political and investor pressure on wage structures.”

“In 2016, we may be nearing a tipping point in the ever-widening pay gap as companies start to release pay-ratio data and wage shocks come to a head. As a result, we expect that investor and academic focus could shift from sector- and country-level impacts of income inequality to how intracompany pay structures are linked to economic growth,” the MSCI research shows.

 

In the first of a series of contributed articles exclusively for conexust1f.flywheelstaging.com, global head of investment research at Mercer, Deb Clarke examines the decision making of long-horizon investors, advocating that investors incorporate a broader perspective of risk into their decision making.

As we start 2016 it is always tempting to do the obvious of a review of 2015 and predict what might be expected to happen in 2016. In reality, while the turning of the calendar may identify some new themes it does not necessarily mean ‎your investment strategy needs to change. In fact Mercer would argue that one of the aspects of decision making that long-term pension schemes, endowments or defined contribution plans can exploit is their longer-term time horizon.

So what prevents them from doing so?

There has been much discussion about long-term mandates and how investors and managers might work in partnership to create strategies that deliver a long-term return which better matches investors’ liabilities and objectives.

This may look very different to that of the return profile of any given index.

And perhaps therein lies one of the behavioural pitfalls of decision making and the potential for regret risk.

Having to report to your board why one of your managers returned, say, 6 per cent when the market was up double digits is likely to be a tough ask.

In addition, there are questions around how an investor might evaluate managers if they are mandated to generate a return not linked to an index.

We believe it is possible to succeed with this approach if investors genuinely understand, and by implication “buy into” the manager’s strategy, and agree at the outset on the measures that will be used to monitor the progress of the portfolio on a regular (but not too frequent) basis.

This is likely to align investors and managers more closely and make for a much better-informed discussion about portfolio performance, ultimately leading to good long-term relationships and better long-term performance.

Long-horizon investors generally invest in businesses rather than share prices.

They expect the growth of those businesses over the long term to be rewarded in terms of attractive total return to the investor and may even engage with the company to enhance those returns.

Most investors in this category would focus on companies of high quality with strong brands, large market shares, high barriers to entry, low operational gearing, robust balance sheets, etc., and which therefore have the ability to earn higher rates of return on capital employed, well beyond the market’s short-term time horizon.

The second type of long-horizon investor is quite different. This type of investor buys companies which they expect to grow to a much greater extent than the market currently believes they will.

These companies may already have been identified as high-growth companies by the market but this type of long-term investor believes that the market lacks the imagination or time horizon to understand how fast and for how long the business can actually grow.

In neither case is the monitoring of share prices or portfolio performance against market indices a good way of assessing progress over short time periods because of the prevalence of “noise” in those share price movements.

The combination of clarity around decision making and establishment of a clear set of beliefs is critical to success in investing.

But these are not static concepts, and as the world changes there is a need to adapt. There are many new participants in the stockmarket and changes in the economic and political environment.

This is creating patterns of performance and speed of change that have not been seen before. Does this lead to a need for sharper and quicker decision making?

Arguably it does, but investors need to recognise their own strengths; that is, do they have the capacity and skill to speed up decision making, or should they focus on getting their long-term decisions right and seek to benefit from being a patient investor?

One area where Mercer believes change is required is around the need for investors to incorporate a broader perspective on risk into their decision making.

This broader perspective should include consideration of geopolitical, environmental, social and technological change; but what does that mean in reality?

Geopolitical risk is running at an elevated level and seems likely to continue to do so, and we are seeing the impact at both a geographical level as well as at a sector level – for example, the energy sector.

The pace of technological change is, arguably, accelerating and we now have many industries in which the dynamics have changed beyond most investors’ expectations; for example, the largest “hotel” company, Airbnb, does not own any buildings.

Perhaps this faster pace of technological change and the uprising of the shared economy could lead to the landscape of the market, as we currently know it, changing dramatically over the next 10 years with new companies undermining old hierarchies, consumer behaviours changing and government policies adapting.

The current market environment, while presenting a number of uncertainties, does offer the potential for interesting opportunities.

Mercer believes that in order to take advantage of those opportunities investors may need to operate and think in ways that are different from the past. This will be an exciting period, but all those involved in investing will need to be open-minded about how the world may evolve from here.

 

Renewable energy infrastructure is an immature market and needs an accepted definition of equity risk, according to Jim Barry, global head of Blackrock Infrastructure Investment Group. This lack of a common language means investors need to be very clear on what risk exposure they are looking for and where they “play” in renewable energy.

Speaking at the Fiduciary Investors Symposium in Chicago, Barry said that the debt side, which is newer, is much “safer” because they have a language of risk – which is credit rating.

“I am a person on a mission on definition of equity risk. This is an immature industry as we have no definition. On the debt side you can define what you want and get it. But if you put 20 investors in a room and ask them for a definition of core, you’ll get 20 different definitions – there is no common language.”

As a result investors need to closely examine the risk-factor exposure of potential investors.

“If you buy a wind farm in the US with an investment-grade utility… and it’s an operating asset – that is clearly a core low-end risk. If you buy a platform with development exposure as well as operating assets across multiple jurisdictions … it may be on the spectrum, and that’s private equity risk in renewable power infrastructure.”

Investors need to think very clearly on how they want to play in this space and what equity risk exposure they are looking for.

Investing in renewable power projects is relatively new for many investors compared with investing in more traditional energy and infrastructure.

Five years ago, investments in this area would have been considered niche, but it has grown very quickly.

Now, 20 per cent of the market for infrastructure is in renewable power assets, with growth driven by fundamental secular shifts. And coal is the loser.

“Coal is frankly dead – if you’re taking a 20 to 30-year perspective, it is dead,” Barry says, “and that is driving a response to the other technologies.”

“I’m not saying there isn’t money to be paid in the short term from coal in terms of tactical plays. But there is no new coal being built in the US today because no utility is taking on a 30-year contingent liability on carbon dioxide.”

Blackrock Infrastructure has no coal investments.

Barry says gas is a big winner, particularly in North America where shale gas is increasing. But nuclear is challenged.

“Renewables is a go-to for just a need for power, before we even get to climate,” he said.

Barry says that renewables are all about the resource; it is a fixed-cost asset and something like 70 to 85 per cent over 30 years in the capital cost. So if you get more wind or sun per site you’ll get a cheaper cost of electricity.

He says the US has the cheapest renewables in the world, citing the contract price for wind in the mid-west as somewhere between $0.025–$0.03 per kilowatt hour fixed price for 20 years.

“It’s like power for nothing for utilities,” he says.

But, he warns, these are complex transactions with unique circumstances market by market, with credit risk on the price, and regulatory risk.