Quantitative Hedge Funds = Conventional Economics = BS

 

8 September 2010. David Caploe PhD, Chief Political Economist, EconomyWatch.com

And we don’capital t mean “Bachelors of Science” – particularly since most of the people we’re talking about have at least one PhD, if not more.

While the dominance of computers, and the evident correctness of Moore’s Law – at least until this point –

has obviously been a huge benefit to every aspect of mind-based economic hobbies,

it has also brought with it a really evident downside, in two locations above all:

stock trading and standard academic economics – and the two are not unrelated,

especially since every “discipline” began to come under the quantitative impact at about the same time.

In stock trading, the so-called “quantitatives”, or quants, were revered because the brightest minds in finance,

who could outwit Wall Street with their Ph.D.’s and superfast computers.

But following blundering through the financial panic, losing big in 2008 and lagging badly in 2009,

these so-called quantitative investment managers no longer look like geniuses,

and some investors have fallen from love with them.

The combined assets of quantitative funds specializing in United States stocks have plunged to $467 billion,

from $1.2 trillion in 2007, a 61 percent decline,

according to eVestment Alliance, a study firm.

That drop reflects each bad investments and withdrawals by clients.

The assets of a broader universe of quant protect funds have dwindled by about $50 billion.

One in 4 quant hedge funds has closed since 2007, according to Lipper Tass.

“Should you go back to early 2008, when Bear Stearns blew up,

that’s when a lot of quant managers got taken out of the water,”

said Neil Rue, the managing director with Pension Talking to Alliance in Portland, Ore.

“For a lot of, that was the beginning of the end,” he or she added.

Wall Street’s rocket researchers have been written off before.

When the actual hedge fund Long Term Capital Management nearly collapsed in 1998, for instance,

some predicted that quants would never regain their former glory.

But this latest problem is nonetheless a stinging comedown for the wizards of higher finance.

For a generation, managing a quant account — and making millions or perhaps billions for yourself —

seemed to be the important dream in every math as well as physics department.

String theory experts, computer scientists and nuclear physicists

came down from their ivory systems to pursue their prospects on Wall Street.

Along the way, they turned investment management on its head,

even as their critics asserted they deepened market collapses like the panic associated with 2008.

Granted, Wall Street is not about to pull the plug on it’s computers.

To the contrary.

A technical arms race is under way to design financial software

that can outwit and out-trade the most advanced computer systems on the planet.

But the decrease of quant fund assets nonetheless runs against what has already been a powerful trend in finance.

For a change, flesh-and-blood money managers do better than the machines.

Much from the money that is flowing out of quant funds is flowing into funds managed by people, rather than computers.

Terry Dennison, the United States overseer of investment consulting at Mercer,

which advises pension funds and endowments,

said the quants had disappointed numerous big investors.

Despite their high-octane pc models — in fact, because of all of them —

many quant funds failed to protect their investors from losses

when the actual markets came unglued two years ago.

And many managers who jumped into this field during happy times

plugged similar investment criteria to their models.

In other words, the computer systems were making the same bets, and all won or lost in tandem.

“They were all fishing in the same pond,” Mr. Dennison said.

Quant money is still struggling to explain exactly what went wrong.

Some blame personnel changes.

Others complain that nervous clients withdrew so much money therefore quickly

that the funds were forced to sell investments at a loss.

Still others say their models merely failed to predict how the marketplaces would react

to near-catastrophic, once-in-a-lifetime financial events like Black September 2008 and the collapse of Lehman Brothers.

“It’s funny, but when quants do well, they all call themselves brilliant,

but when things don’t proceed well, they whine as well as call it an anomalous market,”

said Theodore Aronson, the quant fund manager in Philly

whose firm’s assets have fallen to $19 billion, from $31 billion in the spring of 2007.

But Mr. Aronson, who has been using quantitative theories to take a position

since he was at Drexel Burnham Lambert in the 1970s,

said investors would eventually come back.

“In the good years, the money rolled in, so I can’t really complain now concerning the cash flow going out,” Mr. Aronson stated.

“If somebody can give me personally proof that this is a horrible way to invest,

then I’m going to get out of it and retire.”

Still, a few of the biggest names in the business are shrinking after years of breakneck development.

During the last 18 months, assets possess fallen at quant funds managed by

Intech Investment Management, a unit of the mutual fund company Janus;

by the large money management company Blackrock;

and by Goldman Sachs Asset Management.

Even quant legends like Jim Simons, the former code cracker who founded Renaissance Technologies, have seen better days.

Mr. Simons was recognized as the King of the Quants

after their in-house fund, Medallion, posted an average return of nearly 39 % a year,

after fees, from 2000 to 2007.

It was an impressive run rivaling some of the greatest feats in investing history.

But since then, traders have pulled money out of two Renaissance funds

that Mr. Simons experienced opened during the quant boom.

After dropping 16 percent in 08 and 5 percent in 2009,

assets in the larger of the two funds have dropped to about $4 billion from $26 billion in 2007.

Ironically enough, that fund is up regarding 6.8 percent this season,

compared with a loss of about 3 % marketwide.

In an effort to woo back investors, some quants are tweaking their computer models.

Others tend to be reworking them altogether.

“I think it’s dangerous right now just because a lot of quants are working on what We call regime-change models,”

or strategies that can shift suddenly with the underlying currents in the market,

said Margaret Stumpp, the main investment officer at Quantitative Administration Associates in Newark.

The firm has $66 billion in assets under management,

and its oldest large-cap fund has had only two down years — 2001 and 2009 — because opening in 1997.

“It’utes tantamount to throwing out the infant with the bathwater if you engage in at wholesale prices changes to your approach,” Ms. Stumpp said.

But many quants, particularly past due arrivals, are hunting for something, something, that will give them a new edge.

Those who fail again might not survive this shakeout.

“What we’re seeing is that not all quants are created equal,”

said Maggie Ralbovsky, a managing director with Wilshire Associates,

which gives investment advice to pension funds and endowments,

according to this post in the New York Times.

And nor, Maggie, are all economists,

especially the ones that disregard the political and historical aspects of economics –

in short, just about all of them.

Now, the reasons for the “quantitative” domination of academic economics

are just about just like for their ubiquity in stock trading:

numbers tend to be impressive, especially when you consider the actual ever-increasing speed and amounts of information

of which even the tiniest computer systems can now make sense.

But numbers account for only so much of what goes on in the real world,

and the most successful stock traders pay just as much attention to emotion

as they do to numbers when trying to figure out how to handle their money.

The most obviously related emotions, of course, are greed –

the desire for more / more / much more –

and fear – what are you going to perform when you start losing or, in the worst case scenario, face the possibilities of losing it ALL.

Which has led a lot of economists to the current weird version of conventional psychology, however –

since that TOO has been mathematized over the last Twenty five years –

that has only re-doubled the fundamental problem:

the unwillingness to deal with politics and background,

the structures that set the actual framework and meaning of action.

So while behavioral economics may be a little improvement over purely mathematical financial aspects,

neither begins to acknowledge there are bigger structures

within which all people have operated all the time, and always will.

Because, of course, there is a definite drawback in recognizing

the reality of politics and history in being able to make sense of economic behavior:

losing the certainty which comes from an allegedly / self-styled / so-called “rigorous” approach.

And it’s obvious this certainty provides emotional security, especially when it comes to money –

which is why “quants” of disciplines stick so militantly for their graphs and equations,

as Margaret Stumpp so simply puts it in the quote just before Maggie’s:

“It’s tantamount to throwing out the baby with the bathwater if you engage in at wholesale prices changes to your approach”

just because something happened that a) you didn’capital t predict or b) even think would ever happen,

although you might think someone with an open thoughts would do exactly that

if their prior work had failed to permit the possibility of precisely the sort of major event that DID occur.

Indeed, her attitude is summed up more generally by people who argue above:

“their designs simply failed to predict how the markets would react to near-catastrophic,

once-in-a-lifetime financial events like Black September and the collapse of Lehman Brothers.”

The problem, of course, is that anyone familiar with history –

or anthropology or sociology or their systematic combination into medianalysis –

knows it is precisely these so-called Or self-styled / alleged “once in a lifetime” events that are what matter,

the times where history turns, after which life – as the quants are finding – is never quite the same.

Obviously, this particular realization is a bit more immediate for traders,

who must deal with the actual realities of life every single day in a way more cloistered academics – particularly those with tenure –

can avoid more often than not, and spent most of their effort in doing just that: engaging in the most intense forms of avoidance and denial.

But the simple fact of the matter is that those “once in a lifetime” events DID happen.

And not only did the actual “quants” in both areas completely fail to predict their possibility,

and create a mockery of those who actually said they could happen,

but we are also just about all STILL dealing, now, two years later,

with merely the IMMEDIATE effects of those events.

Indeed, I would venture to predict,

we are only JUST realizing their medium- and longer-term consequences,

above all, the dreaded moment when the “other shoe” –

namely, those “financial weapons of mass destruction,” the derivatives – begin to fall.

And when that happens, just as with their correlatives in the realm of physics,

there are likely to be both immediate “blast effects” and then longer-term “fallout.”

Once those strike, you can be pretty sure that,

while the quants of both trading and conventional economics

will be sure they can tell us the exact dimensions of the actual mess into which we will have fallen,

it would seem to become wise to take those predictions with a ton of salt as well.

Because it’s pretty unlikely any of them every considered “it would actually come to this.”

 

David Caploe PhD

Editor-in-Chief

EconomyWatch.com

President / acalaha.com