As January draws to a close and New Year’s resolutions start to fade, one wonders what will become of those earnest commitments we made to understand crowding better. We cared because the losses made by so many hedge funds in the last quarter of 2018 were attributed to deleveraging rather than to market beta. Deleveraging is a complex phenomenon which metes out punishment to innocent Market Neutral Funds, while beta is a just a cardinal sin. If you don’t want losses from beta, don’t buy Funds that take that risk. If you don’t want to lose money from deleveraging, that’s a problem. Is it the unavoidable consequence of a world with too much capital in an outsized hedge fund industry? Is it that there is less alpha with bigger tail risk than ever before? Is it time to give up with hedge funds altogether? We’d better think hard about this crowding question.
There are acres of research on everything these days, but on this subject it still doesn’t feel very advanced: the data really is difficult. But at least part of the answer may lie on the surface and not down some academic rabbit hole. Sure, groups of positions and strategies can easily become crowded, impoverished and risky. There are ways of picking this up, and there are things you can do about it (like get out of them quickly): we can see the flows, count the positions and watch the ratio of the reward to the risk collapse.
But should this sort of localized crowding be taken for a half-convincing prophecy for the end of alpha? Excess positioning and its opposite have driven markets for centuries. Whether it is risk management, loss aversion, animal spirits or the madness of the age, prices have always been driven by herds. It is to this that financial markets owe their undimmed and extraordinary ability to appear simultaneously wildly inefficient and exquisitely cunning. (Whether that’s more fascinating than it is frustrating may depend on how long you’ve been around.) In December, the whole world – strategists and managers alike, seemed to think the equity markets were too low for the economic conditions. Too low, one might darkly observe, because they had all sold them: positioning had fallen to long-term lows. On January 2, 2019, Apple warned on earnings, markets went down some more and then, rapidly fulfilling everyone’s central expectation, rallied hard… but with no one on board.
Ah, yes, beta you might say is a true mystery, but alpha? Well, in similar vein, we were told in early 2018 by many hedge fund managers that equity markets were stretched – not just overvalued at the index level, but dangerously extended within the market. Segments of the market (Software, Biotech) traded on optimistic multiples of earnings (or multiples of revenue where earnings were non-existent), while others (Autos, Industrials, Banks) plumbed the depths of valuation not seen since the financial crisis. Company X is pricing in a deep recession and Company Y is priced for perfection, and this contradiction represents potential opportunity.
G. H. Hardy described proof by contradiction as ‘one of a mathematician’s finest weapons.’ Well, in 2018 this weapon backfired. For the first nine months of 2018 the Valuation discrepancy widened. This was not simply a value trap – in many cases the announced earnings for the ‘cheap’ stocks were better than the ‘expensive’ stocks – but still the discrepancy widened. Most credible measures of the Valuation factor suggest that a portfolio holding 100% of the cheapest securities (by P/E) long and 100% of the most expensive securities short would have lost something like 10% over the whole of 20181. Given that some hedge funds and Alternative Risk Premia strategies run Value exposures in the range of 200-300% long and short, then it is not surprising to see the size of losses from these strategies.
The Value trade became crowded due to the shape of the opportunity and the volume of capital allocated to Market Neutral strategies. The Momentum trade (chasing the high PE market leaders ever higher) was also crowded, as Momentum trades historically tend to be. One can lead to the other. The more money chases the Momentum trade, then the more the Value opportunity increases and the more correlated with each other the books holding that exposure become.
When a trade is genuinely attractive, and all the smart money in the market identifies it as such, the inevitable upshot is crowding but the judgements are independent and it dissipates when it works. The crowding is benign: it makes markets behave efficiently. A malign crowding might systematically replicate positions that are held by other participants (some types of price momentum trading for example). This strengthens when it works and it amplifies market gyrations. The “alpha is dead” type hypothesis requires that these benign and malign crowdings should perfectly offset one another over innumerable timeframes and dimensions. Is there some invisible hand that regulates this infinitely complex process? We don’t buy it.
And therein lays the difficulty of simply explaining last year’s returns through crowding. Maybe the hedge fund losses seen in the fourth quarter were attributable to deleveraging of both Value and Momentum factors over that particular time period. And maybe, as the dust settles we are left with a serious dent in the momentum factor as high growth stocks are now trading below their peaks from a few months ago. Investors have a recent reminder that these securities can halve as well as double in price. But the wash-out from Value leaves the spread between expensive and cheap yet wider. This isn’t efficient pricing: it’s the opposite. And it’s not crowded on any measure that we can find.
The pick-up in volatility seen in the fourth quarter, twinned with tighter financial conditions leave traditional assets (as we have said ad infinitum in previous editions) at levels which may not augur well for beta returns for years to come. But the potential alpha opportunity – currently in the value factor, is in our view alive and kicking.
Hedge funds started 2019 with mixed performance. On the whole, anything with positive risk-asset exposure benefited from the bounce in equities and credit, whereas trend following strategies generally were whipsawed from the snap-back after the equity market drawdown in December. The early part of the market rally was also rather indiscriminate, meaning that factor models struggled to add alpha despite a reduction of overall volatility, but alpha-generation generally improved through the latter part of the month despite the market rally softening.
Equity Long-Short returns were generally positive, supported primarily by beta exposure to a rallying market. Many managers had, however, reduced net and gross exposure in the fourth quarter, and as such participated less in the market bounce than they would have hoped. After the initial bounce, returns to alpha started to strengthen through the month, which may suggest that managers were redeploying risk from the lower levels seen towards the end of December.
Returns to Market Neutral strategies in Asia (and in particular Japan) seem to have been the best performers during the month from an alpha perspective. In the more quantitative equity strategies, the picture is more mixed. Fundamental strategies performed positively, generally helped by a return to the Value factor, whereas more Technical strategies struggled to add value.
Equity managers are increasingly bearish for the outlook on earnings in 2019 and feel that while the rally has given managers the opportunity to increase gross exposure levels, there is less enthusiasm to increase net exposure until a clearer macroeconomic picture emerges. In particular, managers are trying to avoid thematic bets in favour of stock-specific opportunities within sectors.
January also saw a rebound in the credit markets alongside other risk assets with US high yield posting one of its best starts to the year. Leveraged loans also improved in January despite outflows continuing, albeit at a slower pace compared to December. Improved market sentiment resulted in a pickup in high yield primary market activity after no US high yield issuance in December. Performance in US high yield was noteworthy across the rating spectrum with all sectors posting positive returns for the month. Energy and Healthcare were among the best performers.
Corporate Credit managers largely performed positively in January with Distressed managers outperforming, driven by a notable upward repricing of several reorg equities that had seen steep sell-offs in the previous few months. GSE preferreds and Puerto Rico muni bonds were also positive contributors for several managers on ongoing favourable news flow. US financial preferreds, after suffering markdowns over the previous few months, also saw a robust month.
Performance was mixed in Structured Credit with relatively stable pricing across most sectors, which lagged the rally in corporate credit. Carry and some mark-to-market gains were offset by corporate credit and equity hedges, which had helped in the previous few months.
In Merger Arbitrage, portfolio risk was lower during the month as mergers completed at year end and managers await recycling capital into new merger transactions. During the month of January, a pharmaceutical company completed its acquisition of a biotechnology company and rolled out of managers’ portfolios. While the US Government shut down caused delays in regulatory approvals of merger deals and other corporate events, global M&A volume picked up from the December’s declining volume. Softer catalyst Event strategies are generally net long equities, and as such benefited from the rising equity markets during the month.
Managed Futures managers suffered another disappointing month, with losses driven by snap-backs in Equities, Commodities and FX. The equity loss is the easiest understood, as markets had been trending downwards for much of the fourth quarter, leading to positioning being materially net short coming into 2019 and losing money into the rally. Oil followed a similar trajectory, also leading to losses. Managers tend to use a covariance matrix to avoid duplicating exposures, and as such the losses in equities were perhaps smaller than might have been expected given the shape of the market, but Oil losses more than offset any benefit from smaller equity positioning. The losses in FX were led by the euro weakness versus the dollar.
Discretionary Macro managers had a mixed month, with mean reversion trades working better than trend following strategies. Fixed Income markets were generally range-bound and failed to contribute meaningfully to return, whereas FX and Commodity strategies were more significant contributors.
1Source: J.P. Morgan, As of January 8, 2019.