Demystification Committee

Flash

May 6, 2010. Against a backdrop of a hung UK parliament, the result of an indecisive General Election, and of street riots in Athens, a consequence of the approval of EU-backed austerity measures aimed at preventing Greece’s default on loan payments, a flash crash inexplicably wipes a trillion dollars from stock markets on the other side of the globe.

Flash is a reenactment of the stock market crash of May 6, 2010. In Flash, historical market trading data from the day and wireless network data collected on May 6, 2018 from the original location and during the same time-span of the original accident (19:32—19:57 GMT) are translated into sound by means of custom software.

As events unfolded on May 6, 2010, and for years after the crash, commentators failingly searched for a meaningful narrative. Half a decade later, a trader is arrested in London and extradited to be prosecuted in the US for manipulating the financial market during that volatile day. Trading with software from his home WiFi and PC, he is accused of inflating the financial market to profit from its chaos, triggering a machinic positive feedback loop with his actions.

The trader used a customised piece of trading software, hacked to enable a trading tactic known as spoofing: the altering of the perceived supply-and-demand of a commodity on the stock market, thus affecting its perceived value. His software quickly placed, modified and cancelled sell and buy orders without executing them. As the value of the commodity changed, the software would autonomously alter its offering, keeping it close to the market value but, crucially, never likely to be taken up by another trader. The software would then execute a portion of the orders at an advantageous price and cancel the rest.

Spoofing capitalises on confirmation bias. In a financial market dominated by algorithms and imbued with noise, the positive feedback loop triggered by the trader’s software was multiplied through the echo chamber of algorithmic decision-making, which feeds on collective trading patterns. The trader knew that the synchronicity of global events and the noise they propagate, amplified by the news network’s affect and speculation on fear, contributed to a volatile market.

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