Thu, Feb 06, 2020 - Page 9 News List

Wars and viruses: Are robots less prone to panic?

Algorithms that read news feeds and make trade decisions at lightning speed might be immune to panic or greed, but their insight is limited to analyzing precedents

By Saikat Chatterjee  /  Reuters, LONDON

Illustration: Mountain People

Widely blamed for volatile “flash crashes” in currencies and equities, high-frequency algorithms might also be why shock global events, including a coronavirus outbreak, seem to have lost their power to spook markets for any length of time.

Whether stocks, bonds, currencies or commodities, asset prices seem less prone to any selloff for very long; the US killing of an Iranian general and Iran’s retaliatory missile attack are among potential catastrophes that triggered violent, but surprisingly short-lived reactions just since the start of this year.

In both cases, knee-jerk yen-buying and selling of equities faded within hours, allowing stocks to scale new record peaks.

Now even as the 2019 novelcoronavirus (2019-nCoV) outbreak in China threatens to throttle economic growth, global stocks are not far off all-time highs.

Certainly, many factors are shaping the resilience, not least central bank money printing and rising global savings, which boosted the value of world stocks by US$25 trillion in the past decade.

Yet it is hard not to link the shift in reaction by financial markets to the rise of automated trading strategies. In the past six years, the share of algo-trading in the US$6.6 trillion-a-day FX market has more than doubled to 27 percent among fund managers, a survey by Greenwich Associates found.

There is some reason to believe algorithms cause volatility, especially when trading thins and the humans overseeing them vanish, for instance during public holidays. That is what likely happened during the Wall Street flash crash of 2010 and dramatic, but fleeting yen moves in January last year.

However, they also offer the advantage of being able to transact at lightning speed at any hour of the day or night, with razor-sharp accuracy and lower overall costs.

Being machines, they are also alien to the common human impulses of fear and greed that tend to take over.

Algorithmic trading is dispassionate, said Scott Wacker, global head of fixed income, currency and commodity e-sales at JPMorgan, one bank at the forefront of the algo revolution.

“As a result, the reaction function in currency markets to even major geopolitical news has considerably shortened, which enables stability to return more quickly,” Wacker said.

In short, when left-field events hit, not only can algorithms scan and react swiftly to news feed, many now can gauge the potential asset price impact. The most sophisticated can be “trained” to learn from the experience before the next shock.

One currency trader familiar with algorithm use said that a machine reading 2019-nCoV cases would typically buy stocks if informed of “500 new cases, 10 deaths.” If it is “3,000 new cases, 200 deaths,” it might sell.

“The point being that as soon as a headline is out, the machine-led market is trading on it,” the trader said, speaking on condition of anonymity.

However, the machines had “vol triggers,” he said, meaning they can stop trading when the market moves beyond specified limits.

First and second-generation programs merely broke down large buy/sell orders into chunks to minimize market impact.

Now algorithms can be hooked up to sophisticated language processing technology to “read and analyze” news feeds, then react accordingly, all in the space of seconds, said Antony Foster, head of G10 FX trading at Nomura.

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