DEMONS is an audiovisual performance exploring confirmation bias in algorithmic trading. It replays the Black Monday of October 19, 1987, the first stock market crash in which algorithmic trading was implicated.
On that day, responding to a set of strange and seemingly unconnected events unfolding at the time of market opening, the computers of institutional investors on the New York Stock Exchange automatically executed a number of trades in order to protect the values of their portfolios against volatile market conditions.
As algorithms followed a logic dictated by the technical analysis of each others' trading patterns, a domino effect was triggered. Large sums of money were lost as the communications systems of the New York Stock Exchange became overwhelmed by the amount of trading orders submitted by the algorithms, "demons of our own design" in the words of a Wall Street risk manager.
- 2019 (release)
- Flash DemonsMILLE PLATEAUXAudiovisual genealogy of financial algorithmic collapse, limited editon USB
- 2018 (live)
- Radical NetworksSPEKTRUM, berlin
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- (talk)
- IMPAKT FestivalHET HUIS, utrechtDiscussing sonic experimentation with algorithms and financial speculation
DEMONS is an audiovisual performance exploring confirmation bias in algorithmic trading. It replays the Black Monday of October 19, 1987, the first stock market crash in which algorithmic trading was implicated.
On that day, responding to a set of strange and seemingly unconnected events unfolding at the time of market opening, the computers of institutional
investors on the New York Stock Exchange automatically executed a number of trades in order to protect the values of their portfolios against volatile market conditions.
As algorithms followed a logic dictated by the technical analysis of each others' trading patterns, a domino effect was triggered. Large sums of money were lost as the communications systems of the New
York Stock Exchange became overwhelmed by the amount of trading orders submitted by the algorithms, "demons of our own design" in the words of a Wall Street risk manager.
