Co-authored with Steve Krawciw
Most recent routs in the U.S. financial markets have prompted an outpouring of angst. Detractors of high-frequency trading (HFT) were particularly up in arms about the market downturn, which many of them blamed squarely on manipulation by HFT. Much of the debate about the role of HFT in the events of August 2015 crash as well as previous market crashes was largely based on speculation. This article introduces data-driven evidence about the sequence of events on August 24, 2015, a particularly bad Monday when the U.S. equity markets lost over 4% in a single day.
To understand the trading dynamics that led to a precipitous drop in prices on August 24, 2015, we use probabilistic estimates (shown accurate in tests) of aggressive HFT and institutional activity. These estimates, developed by our company, AbleMarkets, are based on our proprietary methodologies for tracking aggressive HFT as well as large institutions, such as pension funds and hedge funds, in the U.S. equities markets. To detect aggressive HFT and institutional flow, we use complicated data-intensive computer programs running on hundreds of servers at any one time. The programs use highly granular market data and apply proprietary data science techniques to extract trading profiles of entities behind observed market orders. Since we are using anonymous market data to develop our conclusions, we do not identify particular institutions behind the trades. For instance, we can say with a high degree of confidence that a particular market order was placed by a high-frequency firm, but do not point to whether the high-frequency trader in question was, for example, employed by Getco or Virtu. Similarly, we can point to orders placed by large institutions, but we do not identify institutions that may include CALPERS or the Harvard University Endowment.
Our company's, AbleMarkets, analysis of trading on August 24, 2015, shows that while there were bursts of aggressive HFT activity during the sell-off, it was the institutional activity, not the HFT activity that led and dominated the sell-off. Specifically, the events have appeared to unfold as follows: institutions would sell particular securities, creating acute selling pressure in the markets. Aggressive HFTs would then step in and sell the market further, but only for a relatively short period of time.
Specifically, on August 24, 2015, aggressive HFT reached 50% by volume in several major stocks throughout the day. However, the proportion of aggressive HFTs alternated between HFT buyers and sellers. For instance, the proportion of aggressive HFT Sellers in the S&P500 ETF (NYSE:SPY) was 62% shortly after the market open. However, proportion of aggressive HFT quickly reversed to spike to 75% in aggressive HFT BUY trades in major U.S. equities, such as MMM, at 9:45 AM that same day. Following that, aggressive HFTs further reversed the buy streak and started selling around 10:20 AM on the same day, with aggressive HFT sellers accounting for 53% in MMM, for example. The dominance of aggressive
HFT sellers continued through 2:21 PM in equities such as V, GS and SPY, staying at about 55% by volume in these securities. Around 2:30 PM, aggressive HFTs became once again more prominent on the buy side of the limit order book, where they stayed until the market close at about 50% of trading volume initiated by market buy orders.
On the same day, August 24, 2015, institutional sellers reached 70% to 90% of trading volume at market open and at Noon in major U.S. equities such as V, GS and MMM. In other words, in stocks like V and GS, institutional sellers started the selloff before HFT sellers by an extensive period of time as well as an extensive volume of trades.
The results of our analysis make sense intuitively when the nature of HFT strategies is taken into account. By definition, HFT is very short-term in its outlook and does not sustain a prolonged sell-off. Instead, HFT strategies alternate buy and sell (long and short) positions throughout the day. While achieving high-frequency reversals of positions throughout the day, aggressive HFTs tend to be balanced in their buy and sell activity: market buy orders quickly follow market sells and vice versa. Aggressive HFTs avoid accumulating large positions, and, as a result, do not tend to be directional on any particular day.
On the other hand, trades of large institutions, such as pension funds, tend to be large (sometimes taking several days to process) and are uni-directional - selling or buying without much alternating. As a result, institutions are capable of impacting the markets much more than do aggressive HFTs.
Steve Krawciw is CEO of AbleMarkets.com. Irene Aldridge is Managing Director of Able Alpha Trading, LTD., and AbleMarkets.com and author of High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems (2nd edition, Wiley, 2013).