In 2016 the BlackRock ASF Sterling Currency Hedging Fund
lost over 43 percent and was rated by Morningstar as the
worst-performing actively managed fund. The Financial Times
asked BlackRock for a comment on the funds performance
and was told, Given the steep fall in sterling last year,
the 2016 fund return was in line with both performance
expectations and the benchmark. In conjunction with our
clients other holdings, the fund achieved the aim of
neutralizing currency exposure across their
BlackRock deserves some credit: At least it had the
fortitude to give an inventive explanation for its
In general, when active managers are requested to justify
their persistent underperformance, they seem to be reading off
a common list of excuses, including cheap leverage, low
volatility, algorithmic trading, passive investing, ETFs,
increased correlation of asset classes or factors, and
Certainly, investing is hard. Producing alpha is incredibly
difficult. But the fact that active managers blame their
struggles on exogenous circumstance reveals not only their
hubris but also the weakness of their investment processes.
Lets take one excuse crowding which
according to a Morgan Stanley survey is the most common excuse
for poor performance cited by hedge fund managers.
In one way this alibi makes sense. Walls of money have
poured into active strategies to the point where it is
difficult to generate meaningfully differentiated returns. We
all know size is the enemy of performance. But we should not be
so easily duped.
First, individual active managers could self-remedy the
crowding problem by following Nancy Reagans advice:
Just say no. They could choose to put investment
excellence ahead of asset gathering.
But more fundamentally, crowding and all other
excuses is a derivative phenomenon.
Crowding is caused not by the increase in assets under
management but rather by sloth. Managers do not work hard
Im not talking about long hours or high conviction.
These are merely overt expressions of tenacity. No, I mean they
settle for the status quo, which is the very cause of their
My conversations with asset owners reveal a consensus view:
Our industry is mired in an intellectual malaise. Not some
operational cabal, but a Stepford wiveslike conformity.
Active managers are, by and large, a homogeneous group: men and
women of a certain age, who studied similar subjects at
university, went to the same business schools, and earned CFAs.
Their professional careers tend to follow similar paths, and
their personal lives have situated them in similar milieus.
These sociological factors produce a uniformity of thought,
a groupthink manifested most clearly in the commonality of the
data and methods used to make investment decisions. The
propaganda of modern financial theory leads active managers to
largely see price, economic, and financial information as the
totality of available and acceptable data sources, and linear
multifactor models and mean-variance optimization as the
exclusive methodologies to extract investable insights from
If managers are going to gain the informational edge
necessary to generate alpha, they will have to move beyond the
artificial constraints of their current data and methods.
Fortunately for active managers and Im not sure
they deserve such good fortune a Cambrian explosion of
new data and new methods is occurring in this, their darkest
hour. Because of innovative technological developments,
thousands of nontraditional, unstructured numerical, text,
speech, and visual data sets are available in the public
domain. Before active managers sneer that the public aspect of
these data sets nullifies their benefits, recognize that (i)
the number, type, and kind of these data sets are enormous and
constantly expanding, especially as a result of the exponential
growth of the Internet of Things; and (ii) according to MIT
Technology Review senior editor Antonio Regalado, only about .5
percent of this nontraditional data is ever analyzed.
And to this point of analysis, concomitant with the
explosion of data there have been revolutionary developments in
computational methods. Machine learning and deep learning
models have been (and continue to be) developed and
successfully applied to draw valuable commercial insights from
nontraditional data in other verticals.
So back to my claim of sloth as active managers
original sin. These new data and methods are fully available to
active managers. Admittedly, it will take great effort to
overcome the substantial barriers to accessing and
incorporating them into investment processes, and this work
would be undertaken with no certainty that these new data and
methods would provide the desired edge. Most fundamentally, as
Jordi Visser, CIO of Weiss Multi-Strategy Advisers, told me,
it will require active managers to realize that what they
think they know no longer matters. And this realization
demands a transformation of managers deeply inculcated
But let us admit that we have reached a nadir in active
management. Managers must undertake whatever hard work is
necessary to develop and deploy their skill. Whining is no
longer an option. They either adapt or die.