Welcome to Asset Allocator, FT Specialist's newsletter for wealth managers, fund selectors and DFMs.
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Where credit's due
Corporate bonds and riskier government debt, like equities, are rallying as if the good times are back and an epidemic hasn't shut down the world's second largest economy. Yesterday saw Greek 10-year yields trade below 1 per cent for the first time ever; US corporate bond yields are also at or around record lows.
In Europe, too, credit is in demand. TwentyFour AM inadvertently anticipated both the above records last Friday by highlighting that Greek bank debt was similarly trading at "spectacular" levels. Global corporate and junk bond spreads are also near multi-year lows.
As ever, all such prices can simply be said to be bringing forward future returns - and lowering the chances that corporate credit will be able to give much of a boost to portfolios in future.
Then again, there are always pockets of value. The US energy sector is one such pocket, according to Capital Economics. But there must be questions over whether such bonds might trade at a permanent discount in future, even if commodity prices rebound, thanks to asset managers' emerging ESG priorities.
The forecaster's other potential winner - UK corporate bonds - will be of more use to wealth managers. Specifically, it thinks the opportunity is in domestic high-yield debt, which trades at more of a discount to the US market than UK investment grade issuance.
The idea is that increased clarity over Brexit this year should ultimately help close this gap. Fund selectors who continue to invest heavily in strategic bond funds - they of the sizeable UK high-yield debt weightings - will be watching with interest.
'Quantamental’ is the new phrase on lips this week, courtesy of the FT’s examination of asset managers’ interest in machine learning and the like. The idea is that mining new data sources will help give the active management industry the edge it’s lacked over the past few years.
The first example provided – that of GLG’s managers now working more closely with their quant colleagues at AHL - looks appropriate enough, given how GLG has risen up wealth managers’ radars over the past few years.
Whether that good performance is driven by this kind of collaboration, as opposed to some sensible hires, is another question. Whatever the flaws of star manager culture, many DFMs will still be implicitly backing the latter option. And while there may be some truth in fund firms’ ability to benefit from such processes, discerning an aggregate benefit may be a long time coming. For now, those looking for an active management saviour are arguably better off pinning their hopes on ESG.
Many professional fund selectors will point to their own record of choosing better-than-average performers. But even they don't get it right all the time - and there are factors making it harder for all active managers at the moment.
Market highs are increasingly being driven by just a handful of big stocks; fund managers find it hard to overweight these big beasts. Until that dynamic changes - and there's still plenty of evidence of investors piling in to these names - active management as a whole will remain under the cosh, machine learning or no.
A new benchmark
If the sheer gulf of returns between value and growth serves as an argument for the former style, here’s one for the books. UK value funds have had one of their worst months versus growth investors in 20 years, FTAdviser reports.
As a milestone, it’s one that may well only embolden die hard fans in both the growth and value camps. And for DFMs looking at dedicated value funds it will mean greater thought about which way to lean. Even Schroders’ Nick Kirrage admits it’s “difficult to say” what might prompt a further ascendancy for value, though he ultimately believes in a return to form.
A greater question, perhaps, is how the continued dominance of growth affects the many equity managers who leaned in to value exposure in 2019. With no let-up in the search for relative outperformance, managers could well tilt back and forth according to where the wind blows.