INSUBCONTINENT EXCLUSIVE:
By Satyajit DasLike alchemists seeking to transform base metals into gold, asset managers are constantly seeking perfect formula for
In recent years, search has focused on proprietary quantitative strategies, involving rule-based investments
The genre is ill-defined and marketed under different names, including factor investing, risk parity, smart beta and so forth.
Whatever
Index and quantitative investing account for over half of all equity trading, double level a decade ago
essentially rely on pattern recognition: Models look to correlate past periods of superior returns with specific factors including value,
size, volatility, yield, quality and momentum
Once latter are identified, fund managers construct portfolios with specified return and risk parameters consisting of securities that match
those optimal characteristics
Other techniques exploit short-term dislocations between individual prices and comparable securities or broader market, betting that
relationship will eventually revert to normal.
Such approaches have several fundamental weaknesses
Given enough time, money and computing power, a strategy predicting high returns can be found and validated using back testing to check its
But, this heightens risk of overfitting, or adjusting model to suit a specific set of historical conditions
Those may look like a winning recipe, but could turn out to be an historical fluke.
Modelling is also affected by practical matters, such as
London Business School researchers found over 300 factors that could be used to develop potential strategies, heightening risk of an
financial eras are characterized by specific policies, market structures, instruments and investors
Unique conditions that shape returns, volatility and correlation may change
could perform poorly where a paradigm shift occurs
Modern markets may simply be too complex to be modeled accurately.
Quant strategies naturally lack transparency, given that asset managers
are reluctant to disclose too many details and lose their competitive edge
This, however, increases risk of gaming
A low-volatility fund, for instance, might buy illiquid assets whose prices change infrequently, thus giving illusion of stability
Some strategies, such as selling options, might produce a lot of small gains but be vulnerable to large losses if market conditions
Where size of funds increases, strategy could become crowded, making trading difficult and creating unpredictable profits and losses.
At
their most basic level, quant funds are selling hope with a financially catchy name
Investors disillusioned with below-expected returns are switching to low-cost index products
To counter this trend, fund managers have sought to seduce investors with complex and opaque black-box strategies, made credible by rocket
Fund managers can then collect their high fees (standard 2 per cent on assets under management plus an additional 20 per cent of
sustained superior performance
The basic technology, data and expertise is readily available
Logically, anomalies that strategies rely on should dissipate
There is an inherent contradiction in that approach exploits inefficiencies, but requires market efficiency to realign prices to generate
returns.
The reality is that any fund managers possessing a magic investment formula guaranteeing low risk and high returns would have no
incentive to share secret
Successful firms such as Renaissance Technologies LLC have closed some funds to outside investors, preferring to capture returns for
As legendary investor Paul Tudor Jones once noted, if there was a single easy formula to follow, then all investors would already be
rich.
(This column does not necessarily reflect opinion of economictimes.com, Bloomberg and its owners)
