Market participants might be more concerned about the risks of unscrupulous traders moving the market against them through gaming or abusive trading, but sudden shifts in trading patterns caused by more benign activity can be equally costly. However, the risks of being caught out by the unexpected can be lessened by a firm grasp of market microstructures, the factors that can influence a stock’s trading performance and the most common reasons behind deviations from the norm.
Trading anomalies can take many forms, including both unexplained swings in stock prices or traded volumes and sudden changes in the pace at which stock values and volumes go up and down. A stock that usually trades heavily in an exchange’s opening auction and is quiet for the rest of the day could, for no apparent reason, switch to heavy trading at the close.
One need only look at the period of high volatility in stock markets worldwide following the collapse of US investment bank Lehman Brothers last year for examples of extreme price and velocity shifts that tested traders’ skills to the limit. Executions turned sour in a matter of minutes, leading some traders to stay out of the market, unless absolutely necessary, rather than risk getting their fingers burned.
The challenge, therefore, is to keep an eye out for tell-tale signs and act swiftly when the need arises.
“I remember a period in 2007 when trading activity spiked in a group of small-cap stocks that usually only traded £1m a day, pushing the stock price up. This sent out ‘buy’ signals to the market, creating a snowball effect and pushing the stocks even higher,” recalls one broker.
“If a trader had left a buy order running in a VWAP algorithm throughout the day for one of the small-cap stocks, he would have ended up with a very poor execution.”
Anomalous stock behaviour often starts with unexpected news, such as a sharp dip in profits or an unforeseen takeover bid, but modern electronic trading tools can both initiate and exaggerate anomalies. A router using sub-standard data, for example, could behave unexpectedly, and aggressive algorithms can sometimes make an anomaly worse by chasing a price up or down.
Quantitative models can also lead to anomalies. The August 2007 example quoted above was caused by a switch from value to growth stocks by a large and influential group of quantitative funds.
The financial markets can simply be prone to volatility at particular periods in time, such as the ‘triple witching hour’ phenomenon – the last trading hour on the third Friday of March, June, September and December, when the contracts for stock index futures, stock index options and stock options all expire and traders scramble to offset their positions.
Traders looking to protect themselves from anomalous market activity need to offset inherent trading risks with accurate data and a thorough knowledge of the market’s workings, according to Miranda Mizen, principal at research and consulting firm TABB Group.
“Everybody needs to understand how this market works now because it has changed dramatically,” says Mizen. “The more you understand the market, the more you can anticipate or interpret market movements.”
And whether or not a trader gets caught out by a market anomaly, effective communication with clients or portfolio managers is also a must. “If an anomaly affects the average price over the day or in the open or close, it is not threatening if you can understand and explain it,” says Mizen. “If you don’t understand it then it may interfere with what you think is best execution or how you are gauging your trading activity.”
Click here to vote in this month’s market surveillance poll.