By Irene Aldridge
Many high-profile long-term investors have publicly expressed their frustration with the tactics of some high frequency traders (HFTs). While much of the criticism leveled against high-frequency traders does not hold water (research has shown that HFTs drive down transaction costs incurred by all investors, for example), certain tactics should give investors pause. This article gives a brief overview of the HFT activity that pundits describe as troublesome and the actions investors can take to immunize their trading. I am scheduled to offer a detailed examination of these HFT activities, means to prevent it and approaches to minimize their impact in my new course specifically designed for investors in NYC on September 22 and 23.
One such HFT strategy is “pinging” or “phishing.” Both terms refer to the process of identifying when a trade of a reasonable size is about to be executed in the markets, and placing a similar, smaller order in the same direction as the order placed by the investor. The practice anticipates the changes in supply and demand that are about to occur following the execution of the investor’s order, and carries the HFT through to a positive short-term return. The mere action of HFTs placing the order causes enough supply-demand imbalance to raise the price of the investor’s trade, lowering its profitability. Little information, however, has been widely available to pinpoint the true impact of these tactics on the markets and how investors can guard against them. The research that I have been publishing shows the investor examples of high-frequency strategies.
One of the commonly prescribed solutions to the problem of order detection is order shredding: splitting up the order into small chunks and sending them to the exchanges in a randomized fashion. Unfortunately, many commonly available algorithms do a poor job at hiding the larger order, and can be easily reverse-engineered to reveal the intentions of the long-term trader. Furthermore, many long term investors use such algorithms without giving a second thought to their efficiency.
For example, the well-known and much used Time-Weighted Average Price algorithm (TWAP) breaks down an order into smaller orders of equal size spaced at equal time intervals within the pre-determined period of time. An investor with the off-the-shelf charting software can observe the equally-spaced trading “blips” of even volume and infer that a large trade sliced using TWAP is going through. Other shredding algorithms require increasingly sophisticated detection tools, yet just a few can truly conceal the large traders’ intentions.
To select the best order execution algorithm, investors need to understand the objectives and the tools at the disposal of HFTs. Co-existing with high-frequency traders can involve making use of their own tools.