What could be the underlying causes of this increase in volatility?
There is no doubt that the deteriorating economic environment that began in 2008 has been a factor, as well as the recent U.S. debt downgrade and European sovereign debt issues.
Investors and the financial media, will usually use economic or news events, to rationalize a plausible explanation for why volatility occurred over an entire trading day. However, if volatility is also increasing over periods as small as milliseconds, can the explanation be the same?
Advances in technology are also a contributing factor. Investors are now able to receive information almost instantly, resulting in security prices changes occurring in minutes rather than over days.
In the days before modern technology began to dominate the financial markets, being as close as possible to the action in a trading pit was how investors learned the best information and received superior price execution.
Although technology continues to evolve dramatically, the compulsion to be close to a trading epicenter remains. The introduction of co-location, or proximity hosting, allows trading firms to physically place their computer servers as close as metres away from those of a financial exchange, with the goal of reducing the transmission time required to send electronic trading instructions. Exchanges now offer space in custom-built facilities to reduce the time it takes to execute a trade to a millisecond. The result is that these firms can utilize much faster trading strategies.
Many exchanges in North America, Europe and Asia offer these co-location facilities. The TMX Group, which is the operator of the Toronto Stock Exchange, has a facility with 200 co-location spaces allowing connections to its equities and derivatives platforms simultaneously.
Trades that used to be completed in the trading pits are now completed electronically through matching-engine computer systems. Today’s trade execution is no longer based on single exchange pricing; rather it is routed to any trading platform that offers the best pricing from multiple markets at a specific moment in time.
Technological advances have allowed alternative trading platforms to develop and increase their volumes at the expense of traditional financial exchanges. Examples include:
• Electronic Communication Networks, which are similar to exchanges but are not allowed to list stocks.
• Dark Pools, where trades are matched anonymously.
The combination of improved technology and alternative trading platforms has resulted in the development of new trading strategies, which are generically referred to as “high frequency trading”.
As the name implies, high frequency trading requires the completion of a large number of orders at very fast speeds. These strategies use complex algorithms to analyze multiple markets and then execute electronic orders. Algorithms are designed to trade faster than humans.
It is estimated that 50%-70% of trading volume now comes from high-frequency trading orders.
Most algorithmic trading strategies generally fall into the following categories:
• Execution or volume algorithms, which take large orders and then dissect them into smaller tranches, with the goal of minimizing the impact on the pricing of the securities being traded.
• Statistical algorithms, which search exchanges for profitable pricing anomalies.
• Algorithm detection algorithms, which attempt to find the strategies of algorithms and then profit by executing transactions in advance of the detected algorithm.
Advocates of high frequency trading suggest that these strategies increase exchange volume and enhance the speed of trade execution. While this is true, volume is not liquidity. Liquidity allows investors to buy and sell securities under all market conditions.
The efficiency of high frequency trading has essentially replaced the specialist market-maker system that used to be present on major exchanges. Specialists were required to always provide a market for securities in both good and bad environments. High frequency traders are under no such obligation. They trade only when they believe it is profitable.
Therefore, if over 50%-70% of daily trading volumes are now attributed to high frequency trading strategies that are indifferent to the fundamentals of the securities being traded and do not have an obligation to trade when prices are declining, then the potential for unintended consequences is very real.
An example is the Flash Crash that occurred on May 6 2010, when the Dow Jones Industrial Average declined by 1,010 points or 10.2% in only five minutes. The cause of the crash has been attributed to the execution of a volume algorithm that set off what had previously been thought of as being an unlikely chain of events. Ironically, it was an exchange computer that caught the error and produced a five second trading halt that allowed human traders the time they required to assess the situation and produce an eventual reversal.
Is high frequency trading responsible for the increase in financial market volatility?
While price movements in financial markets are largely unpredictable, there are periods where volatility tends to cluster. This occurs when large price movements tend to bring about other large moves and small moves bring about other small moves, until the trend inexplicably reverses. The flash crash shows that high frequency trading does have the potential to heighten volatility given the right circumstances, however knowing when these circumstances are present can only be detected in hindsight.
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