Some of the biggest and most established players in the automated fund sector have suffered some of their worst losing streaks since May, with the $16 billion BlueTrend fund operated by Leda Braga, the hedge fund industry’s most respected female manager, posting its worst peak-to-trough performance of 16.9% between May and June. The fund has never suffered a negative calendar year.
Meanwhile, the largest automated fund in the business, Winton Capital, which boasts $29 billion of assets under management, faired better but still suffered consecutive losing months, falling 2.4% in May, 1.75% in June and 0.5% in July. The fund is up 4% year-to-date, a source familiar with the matter says.
Like most of the quant fund sector, BlueTrend and Winton are trend-following strategies, which focus on a technical analysis of market prices rather than the fundamental drivers of the companies, instruments or commodities they participate in.
According to alternative investments data specialist Preqin, automated or algorithmic funds have underperformed the hedge fund universe so far this year by 2.07% to 3.7%. Measured over a longer time frame, the gap widens to 3.69% for automated funds versus 10.22% for the sector as a whole.
Given their systematic nature, and focus on recent historical trends for future trading cues, the trend-followers fell victim to the unexpected downside correlation across markets, and were unable to rebalance their strategies quickly enough to capture the subsequent correction.
Dario Castagna, investment consultant at Morningstar Investment Management in Chicago, says: “Most algorithmic strategies tend to be trend-followers based on recent market returns, volatilities and correlations. They typically don’t fare well when the market changes direction quickly.
“Recently, the most short-term-oriented ones performed the worst because after suffering from the correction, many of them rebalanced and missed the subsequent recovery. Longer-term based ones did better because they did not reduced risk. This is particularly true for the domestic equity-based strategies as the US stock markets are up since the beginning of the correction.”
Trying to understand the drivers of quant fund performance, however, is not for the faint-hearted. Indeed, the secrecy traditionally associated with the hedge fund industry is particularly acute in the automated fund world.
Part of the problem is the finite nature of the data universe employed by most funds as algorithm inputs. Everyone has, more or less, access to the same pricing feeds, post-trade data and market-sensitive corporate information.
With nearly 700 new funds launched since 2010, according to Preqin, the race to rinse competitive advantage from the available data is becoming intense and difficult to win. Moreover, the similarity in strategies, or at least returns, available from these funds becomes more apparent when markets fall and individual fund performances converge to the downside.
A California-based quant fund manager, who claims his fund generated consecutive months of positive performance through the recent turbulence, concedes that trend-followers don’t deal very well with secular shifts, boding ill for their future performance in the face of the gradual winding down of QE – after five years of massive support for asset markets.
“It’s difficult for many quant styles when there’s a regime shift, or when there are lots of exogenous drivers on markets like government interventions,” he says. “Most strategies look to the recent past to predict the near future, and in either a regime change or intervention situation, the recent past is not a particularly good guide to the near future.
“If the market’s perception of fair value has suddenly changed, one can find oneself taking bets that are highly likely to lose as the market continues in its new path.”
Although Winton’s founder David Harding says his strategy is purpose-built to deal with surprises, and his fund beat rival BlueTrend during the summer, the longer-term performance of the sector versus human judgement could be a reason why new launches are slowing down.
With 68 launches in 2013, from a peak of 277 amid the volatility of 2011, what started out as an attractive way to generate uncorrelated returns amid choppy markets appears to be losing its appeal.