The “Noisy Chaos” Hypothesis
The concept of “noisy chaos” is introduced in this chapter, based on the processes of bifurcation, entropy, and convergence which occur at the heart of the instability in the financial markets and take into account the sensitivities of the financial systems. The key here is to identify and measure indicators that allow us to construct a model that accounts for extreme consensus factors (undisseminated information, correlated investment horizons, and high leverage) in estimating market reversals. Instability is a relatively subjective notion. If we think in calendar time, the system is unstable as the daily fluctuations seem erratic when compared to periods of months and years. But if we think in intrinsic time, it is as if we are looking at the week as a year, the day as a month, and the minutes as days… in doing so, and as markets are “self-affine” then the L-stable process can be found at the day level and the erratic fluctuations will be at the seconds level.