Robot Traders Need Clarity, They Cannot Keep Up With President Trump

Robot Traders Need Clarity, They Cannot Keep Up With President Trump

$DIA, $SPY, $QQQ, $RUTX, $VXX

FLASH: “Machines are only as smart as their human programmers”

Hedge fund investors learned that the hard way last year when data-crunching computers that invest $220-B based on historical price trends did worse than most human managers.

The losses were so bad that investors pulled billions of dollars out of an investment strategy that for years was seen as a great way to protect portfolios from Southside risks.

Turns out the algorithms behind so-called trend-following quants are rather primitive and suffer from many of the same weaknesses a mortal brain might.

They struggle to react fast enough to the unforeseen side effects of ending a decade of central bank stimulus, and even get baffled by President Trump.

“The models can’t move as fast as the tweets,” said Brooks Ritchey, senior managing director at Franklin Templeton’s K2 Advisors unit who oversees $3.6-B and has exited all but one of the trend-following quants it used to invest in.

A lot has changed since systematic trend-following quants, known in the industry as Commodity Trading Advisors or CTAs, won a big following after gliding through the Y 2008 global financial crisis.

Around them, the community of quantitative investors (computers designed and encoded to identify trades and execute them) expanded exponentially and their algorithms grew more sophisticated.

“It is a strategy which in its pure terms is really probably obsolete now.”

Robotic traders now manage about $1 out of every $3 held in the world’s $3-T hedge fund industry, including models that use inputs like company’s profitability, trends in volatility or shifts in economic cycles to make trading decisions. Many are handing investors big returns and are lauded for preventing human emotion from clouding trading judgment.

But trend followers keep it simple, identifying when to enter and exit trades by back testing price trends against decades of data.

When the algorithm determines it is probable for a market to rise, automatic buy orders are placed for futures or derivatives contracts in anything from stocks and bonds to commodities and currency forwards. Alternatively, if the price forecast looks grim, positions are taken in short futures, betting assets will fall.

Problem is this, they are not very good at responding to surprises, and there have been plenty when central banks removing support from markets can trigger abrupt spikes in volatility or a 280-character Tweet from President Trump can exacerbate or lessen tensions with China or other economic powers. Now, the speed of markets these days can easily confound the historical price trends at the heart of the approach.

“It’s a strategy which in its pure terms is really probably obsolete,” said Robert Frey, PhD, whose has been working in quantitative investing since it was still in its nascent stages of development in the early 1990’s.

Dr.Frey has a doctorate in applied mathematics and statistics, previously worked with Jim Simons at Renaissance Technologies LLC as it grew into the world’s biggest quant-focused hedge fund, now with about $58-B in assets. He started his own company, FQS Capital Partners, in New York in Y 2009 to invest in quants, and has gradually moved away from trend followers.

The turn against CTAs comes 10 years after they rose to fame for rewarding investors with average returns of 21% in Y 2008. Seeing them as a way to guard their portfolios against unforeseen shocks, institutional investors piled in, sending assets soaring to $270-B into the 10 years to Y 2017, according to the data

The strategy has not really delivered.

Between Y’s 2008 and 2018, Societe Generale’s main trend-following index made only 3.7%, compared with an average gain of 62% for hedge funds and a more than 3Xing in the S&P 500, including dividends.

It was the dive in February 2018 that exposed the limitations of CTAs. It happened unexpectedly after a rally in January, only for markets to bounce back days later.

Unlike high-frequency traders that can get in and out of trades in milliseconds, CTAs are typically programmed to change holdings slowly, over several days or even months.

By the time they had adjusted for the falling trend, CTAs were getting burned on the way up. Their net asset value slumped 9% in February, the worst drop in 15 years, and took another 4% hammering during the market downturn in October.

Part of the problem, according to critics, is too much money now chases the same trends, undermining what traders call ‘alpha’ the outperformance possible relative to a benchmark.

CTAs need clarity, not randomness, as the models are designed for a non-crazy-headline environment. Even the discretionary managers are having trouble keeping up.

So, the Key is tune in and pay attention the human way, Donald Trump does not Compute!

Have a terrific week.

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Paul Ebeling

Paul A. Ebeling, polymath, excels in diverse fields of knowledge. Pattern Recognition Analyst in Equities, Commodities and Foreign Exchange and author of “The Red Roadmaster’s Technical Report” on the US Major Market Indices™, a highly regarded, weekly financial market letter, he is also a philosopher, issuing insights on a wide range of subjects to a following of over 250,000 cohorts. An international audience of opinion makers, business leaders, and global organizations recognizes Ebeling as an expert.

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