ABSTRACT

The general consensus was that the exchange of enormously large amounts of information in ultra-short bursts of time caused instability in the interactions among multiple systems, which included not only networked computers but also the human traders on the floor. In fact, information events may well be ubiquitous, occurring at all scales, and in any medium through which information is propagated when the volumes of exchange are high and the networks are densely concentrated. Something of the difference of the information event, in which an event produces new information about information itself, also seems to lurk in the new excitement surrounding the advent of Big Data. Benoit Mandelbrot and Nassim Nicholas Taleb’s distinction between “mild and wild randomness” suggests one difference between types of information event. The model entailed features unfamiliar and even disturbing to classical economists: many complex variables, inherently incomplete information and essentially unpredictable, nonlinear effects.