By Satyajit DasLike alchemists seeking to transform base metals into gold, asset managers are constantly seeking perfect formula for investment success.
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 rubric, quant funds now have over $1.5 trillion under management.
Index and quantitative investing account for over half of all equity trading, double level a decade ago.
But, after initial success, theyve produced uneven returns recently a bad run that may well continue.
Arguably, inherent weaknesses of approach are now being exposed.Fancy math cant mask fact that quantitative investing strategies 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.
First of all, quant investing is tainted by hindsight bias belief that understanding past allows future to be predicted.
Given enough time, money and computing power, a strategy predicting high returns can be found and validated using back testing to check its historical performance.
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 what data is or isnt available.
London Business School researchers found over 300 factors that could be used to develop potential strategies, heightening risk of an overfitted model.
There is in addition problem of ergodicity, that is, lack of a truly representative data sample.Its important to remember, too, that financial eras are characterized by specific policies, market structures, instruments and investors.
Unique conditions that shape returns, volatility and correlation may change.
While models create an illusion of sophisticated certainty, they cant capture full range of events that produced a particular outcome and 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 change.Increases in funds under management may create competition that reduces a strategys expected return.
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 science on which theyre supposedly based.
Fund managers can then collect their high fees (standard 2 per cent on assets under management plus an additional 20 per cent of outperformance) on promise of future performance.While there will always be some standouts, its not clear why so many managers can claim 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 themselves.
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)