Société Générale’s SG
U.S. Machine Learning
Long Short Equity
Index was up 2.3%.This year the
Aberdeen Standard
AI fund trailed the
benchmark of
global stocks by
5 percentage points.The MSCI ACWI Index.Fig. 1 Run {ABAIZAU LX Equity COMP <GO>} to use the Comparative Returns function to track
the performance of Aberdeen Standard’s Artificial Intelligence Global Equity Fund.Galouchko covers European stocks for Bloomberg News in London.over the end of the bull market as trade tensions and an inverted
yield curve flash warning signs for global growth. But they’re afraid
to exit too early and miss out on late-cycle returns.
Yet swings in investor sentiment are hard for machines to
navigate, too. “If the market becomes unpredictable, it’s always
more challenging for AI,” says Anand Rao, global artificial intelli-
gence lead at consulting firm PwC. “This time around, there are
different forces acting. But [the collapse of the credit market
bubble in] 2007 was also very different, and so was [the end of
the dot-com bubble in] 2000. With more data and more history,
AI funds will get better.”
So far, machines seem befuddled by these markets. After
outperforming the Hedge Fund Research HFRX Equity Hedge Index
in four of the last five years, Société Générale SA’s long-short U.S.
stock index based on a machine-learning model has been lagging
this year, with a return of less than half that of HFRX. The
Eurekahedge Artificial Intelligence Hedge Fund Index, which tracks
hedge funds that use machine learning, has also underperformed
in 2019: Its gain of 2.3% through Aug. 31 trailed the 6.9% return for
the broader HFRX Index.
“This year has been challenging for AI funds. It’s probably the
first time in the history of the U.S. that you have a president tweeting
these kinds of things,” says Nicky Indradi, an analyst at Eurekahedge.
“If you give AI funds more time to better understand the technology
they’re using, I’m optimistic that they’ll be able to perform well.”
ONE OF THE SOCGEN INDEX’S creators, Andrew Lapthorne, says
the robot’s strength is in feature recognition: picking biotech
stocks that have a better chance of outperforming, for example.
But he also warns that the strategy needs time to develop before
it can be offered to a larger number of clients—about $39 million
of assets currently track SocGen’s machine-learning strategies.
In addition, he says double-digit returns are unrealistic.
Nobel Prize-winning economist Robert Shiller is also tem-
pered on AI’s prospects. “I think we still need human oversight,”
Shiller says in a London interview. “AI can really mess up when
reacting to text because a word may have a new meaning or there
could be a typo—we would recognize it as a typo, but the machine
might not.”
Still, Boyan Filev, co-head of quantitative equity at Aberdeen
Standard, says the advantage of utilizing machine learning to
manage a portfolio is that it adapts to the market and improves
over time. The fund’s underperformance, he contends, is mainly
the result of challenging markets and changing behavior of
so-called equity factors, which have led to losses at many quant
funds in 2019. “Our fund was positioned more defensively at the
start of the year in line with the bear market of the end of 2018.
However, the sharp reversal of equity markets this year hasn’t
been particularly helpful,” Filev says. “A more stable and
slower-evolving environment is more beneficial to our product.
Very sharp reversals in market directions are very hard to position
against in the short term.”
Filev expects the fund to adapt to conditions, he says. It just
hasn’t done so yet.<GO> INSIDE THE TERMINAL 37