Funds News

Quant traders limit risk as losses mount

NEW YORK (Reuters) - Robust returns for a group of powerful hedge funds that thrived for years using sophisticated trading programs may be a thing of the past after a “Black Swan” event hit global markets this year.

A trader works on the floor of the New York Stock Exchange, October 29, 2008. REUTERS/Brendan McDermid

The carnage in financial markets worldwide, what many viewed as a so-called Black Swan event because it was out of the ordinary and had severe repercussions, has scorched returns for most of these funds. That forced them to embrace new models that place less capital at risk and employ little or no leverage.

With the failure of many investment systems that ran on algorithms created by mathematicians-turned-traders, quantitative funds, also known as “quants” are also veering away from models with longer-term horizons. They have instead focused on high-frequency strategies, or very short-term trades that often are executed in seconds.

“It is a confusing time to be running money ... using quantitative approaches where recent events create statistical outcomes so out of step with the past that historical analysis is of limited value,” said the New York-based Roger Ehrenberg, formerly president of DB Advisors and now an active early-stage investor in financial technology and digital media.

“Clearly, a massive deleveraging had taken place and quants are running far less levered strategies than (before).”

Quants had racked up large gains in the past, some as high as 60 percent, not because of any superior stock-picking ability, some analysts say, but due to the high level of leverage they were allowed to take on.

But 2008 is a different story. The typical hedge fund has fallen by nearly 20 percent so far this year, according to Hedge Fund Research. In October, the HFRX Global Hedge Fund Index lost 9.26 percent, almost doubling its year-to-date loss to 19.79 percent.

HFRX’s Quantitative Directional index, the closest measure of systematic traders’ performance, showed a loss of 7.20 percent in October, falling nearly 20 percent this year.

Losses were also compounded by huge redemptions, with the global hedge fund industry losing $100 billion in assets last month, according to an estimate of Eurekahedge Pte.

“Models involving shorts are under turmoil because of the regime change induced by new and ever-changing short-sale regulations,” said Ernest Chan, a quantitative trader who runs a consulting firm in New York which develops statistical models for stocks and futures.

Another negative, he added, was volatility. Quant models work best in more tepid market conditions and this year’s extreme volatility threw a spanner in the works.


Given the surge in volatility, Chan said profit and loss fluctuations have been much higher than usual, prompting deleveraging as a risk-management measure. This, he added, has drained liquidity from the market, and has led to ever higher volatility, creating a vicious cycle.

Still, there are some bright spots in the industry.

Hedge funds using statistical arbitrage have done relatively well, with some delivering as much as 10 percent returns, traders say. Statistical arbitrage refers to mean-reversion strategies involving large numbers of securities -- hundreds to thousands depending on the amount of capital -- with very short holding periods, measured in days or seconds.

Analysts say mean-reversal models, which assume an asset will revert back to its average price over time despite wild market fluctuations, continue to beat momentum strategies in a crisis environment.

“This is not surprising because market returns have completely dominated specific returns and... market returns have been highly mean-reverting lately,” Chan said.

Most quants are also trying to incorporate more risk management inputs to their models, with the default of several U.S. financial institutions drawing attention to the dangers of counterparty risk.

“Outlier data points are the biggest problems for quants because if you account for all potential outliers... and with your trading sizes so small... you can never make a meaningful return,” said Bob Marcellus, president of Richmond Group Fund, a systematic asset manager in Richmond, Virginia.

“You better have a comprehensive handle on your risk systems from the get-go and if you’re caught scrambling, you’re going to have problems with your model.”

In the end, as quants attempt to reverse losses and adjust to lower leverage, analysts say these funds may have to extract value from completely new and untested data and find ways to capture their edge in a frantic environment.

Most participants are also convinced that new quant standards may have to emerge to enable this group of traders to outperform again, as they had in the past.

“Is it new paradigms or new data sets that will lead quants forward to better times? I would bet that it will be a combination of the two,” said Ehrenberg, DB Advisors’ former chief. “And if history is any guide, a handful of quant funds will emerge from the ashes as market beaters for years to come.”