The Flash Crash: A New Deconstruction

Eric M. Aldrich

University of California, Santa Cruz

Joseph Grundfest

Stanford University Law School

Gregory Laughlin

University of California, Santa Cruz

January 25, 2016

Abstract:

On May 6, 2010, in the span of a mere four and half minutes, the Dow Jones Industrial Average lost approximately 1,000 points. In the following fifteen minutes it recovered essentially all of its losses. This “Flash Crash” occurred in the absence of fundamental news that could explain the observed price pattern and is generally viewed as the result of endogenous factors related to the complexity of modern equity market trading. We present the first analysis of the entire order book at millisecond granularity, and not just of executed transactions, in an effort to explore the causes of the Flash Crash. We also examine information flows as reflected in a variety of data feeds provided to market participants during the Flash Crash. While assertions relating to causation of the Flash Crash must be accompanied by significant disclaimers, we suggest that it is highly unlikely that, as alleged by the United States Government, Navinder Sarao’s spoofing orders, even if illegal, could have caused the Flash Crash, or that the crash was a foreseeable consequence of his spoofing activity. Instead, we find that the explanation offered by the joint CFTC-SEC Staff Report, which relies on prevailing market conditions combined with the introduction of a large equity sell order implemented in a particularly dislocating manner, is consistent with the data. We offer a simulation model that formalizes the process by which large sell orders of the sort observed in the CFTC-SEC Staff Report, combined with prevailing market conditions, could generate a Flash Crash in the absence of fundamental information. Our research also documents the emergence of heretofore unobserved anomalies in market data feeds that correlate very closely with the initiation of and recovery from the Flash Crash. Our analysis of these data feed anomalies is ongoing as we attempt to discern whether they were a symptom of the rapid trading that accompanied the Flash Crash or whether they were causal in the sense that they rationally contributed to traders’ decisions to withdraw liquidity and then restore it after the anomalies were resolved.

The Flash Crash: A New Deconstruction – Introduction

The “Flash Crash” of May 6, 2010, is unique in the history of American equity markets. In the span of a mere four and a half minutes, from 2:41 p.m. to 2:45:28 p.m., “the broad markets plummeted … 5-6% to reach intraday lows of 9-10%” below the markets opening price while volumes in US equity, equity derivatives, and equity futures markets spiked (CFTC and SEC, 2010b, p.9). During this period, the Dow Jones Industrial Average “suffered the greatest one hour decline in its history,” losing about 1,000 points. (Fox et al., 2015, pp.36-37). In the subsequent fifteen minutes “broad market indices recovered while … many individual securities and ETFs experienced extreme price fluctuations and traded in a disorderly fashion.” (CFTC and SEC, 2010b, p.9) “Accenture, for instance, fell from trading at $39.98 at 2:46 to one cent at 2:49 only to return to $39.51 by 2:50. Apple, on the other hand, at one moment traded for almost $100,000 per share.” (Fox et al., 2015, p.37). By 3:00 p.m., “prices of most individual securities significantly recovered and trading resumed in a more orderly fashion.” (CFTC and SEC, 2010b, p.9)

An observer measuring the day’s activity by simply examining opening and closing prices would be oblivious to the chaos that prevailed for a short period in the late afternoon. There would be no indication that hundreds of billions of dollars of equity market capitalization had vanished and then quickly reappeared, or that this perturbation occurred in the absence of any fundamental news that could explain such a rapid and transitory change in market valuations. The Flash Crash is thus generally viewed as an endogenous event whose dynamics are attributed to the complexity of modern equity market microstructure.

Flash Crash

This large, precipitous, and transitory price decline generated significant concern among legislators, regulators, and the investing public. The staffs of the Commodity Futures Trading Commission (CFTC) and the Securities and Exchange Commission (SEC) have attributed the event to unsettled market conditions early in the day, combined with a massive, aggressive E-mini S&P 500 futures sell order initiated by a large mutual fund complex, later identified as Waddell & Reed (CFTC and SEC, 2010b).

More recently, the CFTC and United States Department of Justice (DoJ) expanded the list of causal factors by alleging that Navinder Sarao, a London-based equity futures trader, engaged in illegal “spoofing” activity that materially contributed to the Flash Crash (CFTC v. Sarao, 2015a,b; USA v. Sarao, 2015b,a). In separate criminal and civil proceedings, Sarao is accused of manipulating prices in the near-month E-mini S&P 500 futures contract by consistently layering the sell side of the order book with large quantities of orders at non-marketable prices, with no intention of allowing the orders to be filled in the event of price shifts. Analyses by experts on behalf of the CFTC and DoJ suggest that large order book imbalances at deep, non-marketable prices have significant effects on subsequent prices (USA v. Sarao, 2015b,a). Commentators, however, are skeptical that the actions of a relatively small trader, such as Sarao, could generate such outsized consequences (Pirrong, 2015; Clearfield and Weatherall, 2015). Indeed, if Sarao’s relatively small-scale trading could in fact generate the large-scale effects asserted by the government, modern equity market structures could be viewed as alarmingly fragile.

Flash Crash

The Flash Crash raises difficult, policy-relevant questions of causation. As is the case with most market events, the circumstances of the Flash Crash cannot be replicated. Analysts lack access to the specifications of the automated trading algorithms that were active in the markets prior to and during the crash, and cannot replicate the strategies implemented by human traders active during the relevant period. These limitations are compounded by significant identification issues attributable to complex market interactions and to the simultaneous presence of multiple potentially interactive causal factors. In this environment, correlation is easily confused for causation.

Flash Crash

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