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Extreme volatility in the equity markets made August a testing month for both users of execution algorithms and automated trading strategies. Leading players explain the lessons for the future to Chris Hall.

Baptism by Fire

Baptism by Fire When fears of a collapse in the US sub-prime mortgage market quickly led to widespread panic in the financial markets in August, the finger of suspicion was soon pointing at some pretty familiar bogeymen. Hedge fund managers – aided and abetted by heartless, unseeing computerised trading models – were wreaking havoc, spreading contagion and putting granny’s life savings at risk. Within days of BNP Paribas announcing on August 9 the suspension of three hedge funds over their sub-prime exposures, the financial pages were unanimous. ‘Hedge Fund Panic Was Behind Global Stock Markets Collapse’ screamed the UK’s Daily Telegraph, ‘Hedge Funds Prepare For Mass Redemptions’, gloated the Financial Times.

As firms sought to establish and minimise their exposure to credit derivatives, liquidity dried up in the money markets and confidence in equity market valuations wobbled. As figure 1 shows, short-term interest-rate volatility rose persistently from mid-August as the extent of institutions’ credit exposures gradually unraveled, falling away only when the US Federal Open Market Committee lowered its target for the federal funds rate 50 basis points to 4-3/4 per cent on September 18.

In the eyes of some, however, the financial markets would have veered much closer to collapse without recourse to technology-based trading tools to take logical trading decisions amid a period of sustained volatility rarely seen over the past decade. Large investment banks are still counting their losses from their exposure to the US housing market (latest estimates put institutional losses at $60-70 million), but neither banks nor their buy-side clients have been toppled by their use of computerised trading techniques. While, admittedly, some quant-based hedge funds and prop shops might still be nursing their wounds from over-reliance on statistical arbitrage models, buy-side users of execution algorithms may actually look back on August 2007 as a rite of passage from which many emerged more confident and aggressive users of algorithmic trading tools.

Fear, greed and algorithms

It could, however, have been very different. Had there been a repeat of July 7, 2005, when algorithms were ordered to be switched off by the London Stock Exchange in the wake of the London terrorist bombings, the equity markets would have been plunged into chaos, according to Brian Schwieger, Head of EMEA Quantitative Execution Desk, Merrill Lynch. “Following the LSE’s request on 7/7, we saw a significant increase in volatility and spreads as the market lurched down,” says Schwieger. “When the algos were turned off, the traders panicked because they didn’t know how they were going to cope with the volume of orders. What causes volatility is and always has been fear and greed. In contrast, algorithms can take a logical statistical approach to execution. August 2007 has provided a counter-argument to the perceived wisdom that algorithms add to volatility.”

“August 2007 has provided a counter-argument to the perceived wisdom that algorithms add to volatility.”
Brian Schwieger, Merrill Lynch.

The equity markets witnessed a widening of spreads in the region of 20 per cent in mid-August compared to the previous three months, according to Merrill Lynch; far from the conditions many algorithms were designed to operate in. But rather than switching off their algorithms, many users simply changed to more aggressive tools designed specifically to capture liquidity in volatile markets. John Edge, European head of Electronic Client Solutions, JP Morgan, says that a clear understanding of the differences between algorithmic trading tools is crucial to riding out difficult market conditions. “The weight of responsibility must still be on the human trader to take the decision on when, how and with what tool to trade. This means understanding the values of various products, knowing when to change an algorithm, when it’s not performing, and then choosing the right one for the circumstances,” says Edge. Over the summer months, JP Morgan experienced an increase in the percentage of flows directed through its Arid and Aqua strategies. “These algorithms utilise the philosophy of high frequency trading and the demands of an active trader,” says Edge. “Arid and Aqua are adapted from algorithms already used in the fragmented US markets, and have the ability to extract more liquidity than is readily apparent.” ...

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