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Decarbonising YFYS benchmarks (without failing the test)
The composition of Your Future Your Super (YFYS) benchmarks has been cause for much consternation from the superannuation industry, with funds taking issue with everything from alternatives being measured against 50/50 equities/bonds to a fixed income benchmark that disincentivises the use of inflation-linked bonds. But they’re particularly bad at ESG, forcing funds to replicate the performance of benchmarks with a high carbon intensity or face existential consequences.
But Realindex head of investments David Walsh (top left) and senior quantitative analyst Andrew Sinclair (top right) have found that significant carbon reductions can be achieved – with relatively low tracking error – by reallocating within pollutive sectors rather than away from them completely.
“Within the higher carbon sectors like utilities, materials and energy, the dispersion in carbon intensity numbers is high; one can achieve very significant reductions just by reallocating from high intensity names to low intensity name,” says Sinclair. “As an illustration, we found that in most sectors, one needs to exclude less than 10 per cent of the sector to get a 30 per cent reduction in carbon intensity for that sector… That illustrates the skew – a few of the firms contribute a large part of carbon intensity.”
Realindex’s research found that for global portfolios a 40 per cent reduction in carbon intensity relative to the MSCI ACWI ex-AU would only have generated a tracking error of 10 basis points across the whole backtest period (December 2008 to June 2022). In Australia, the tracking error impact is substantially higher; decreasing carbon intensity by 30 per cent adds about 50 basis points of tracking error. There was “almost always” a return improvement from reducing carbon intensity in the backtest period, though that “cannot necessarily be extrapolated into the future”.
“If Your Future Your Super benchmarking processes are going to be strictly maintained then low tracking error matters,” Walsh says. “One of the things that YFYS doesn’t do is address that ESG issues are becoming more and more important – net zero being near the front of those. So if you want to have those two conflicting objectives, how do you go about building a portfolio to that effect?”
“Do you take a benchmark that is ESG sensitive, and live with the tracking error of that benchmark against the existing one? Or do you take the existing benchmark and try to manage your tracking error against that by reducing carbon? So it addresses the issue that YFYS doesn’t look at ESG closely, or at all, by showing that you can maintain low tracking error against that and meet your YFYS risk requirements while reducing carbon intensity.”
Elsewhere, the Realindex team have been using natural language processing and a modified version of the Gunning fog index – a readability test that estimates the years of formal education an individual needs to understand a text – to study the transparency of speech from management on earnings calls; mainly whether they use short sentences and clear language or long, rambling answers that “go on and on and don’t get to the point”.
“It’s a sign of how transparent they want to be with shareholders, and it’s arguably a form of governance signal in whether management are being clear in trying to answer questions or whether they’re trying to sidestep potential problems… It captures an element of human nature – when we don’t want to say things, we beat around the bush,” Sinclair says. “What we find, on balance, is that there’s a tendency for answers to be longer and use more complex language in aggregate. They can just be stonewalling, but that tends not to be the nature of these dialogues.”
The start of an earnings call is where most of the management obfuscation can occur; if they blabber on, that’s “a negative signal, or average”. During analyst Q&A, it’s weighted more towards the positive or negative tone of the words being used.
“We think this is a really interesting and important part of research for us because traditionally, systematic managers tend not to be able to capture return forecasts associated with E, S or G issues,” Walsh says. “It’s been a hard place for them to go. And we’re finding that our insights are getting better and better, and that gives us an edge in what we think is a really rich area to explore and improve.”
