Applications · Social science
Chaos in economics & finance
Hopes of explaining stock-market crashes with deterministic chaos were popular in the 1980s. Decades of statistical testing (BDS, surrogate-data) suggest that pure low-dimensional chaos is rarely the right model, but nonlinear deterministic components are present.
Business cycle models
Nonlinear macroeconomic models (Goodwin, Kaldor-style) admit chaotic regimes. These are useful for thinking about endogenous fluctuations even if they don't predict real GDP.
Tests for deterministic structure
BDS test (Brock-Dechert-Scheinkman, 1996), surrogate-data testing, and correlation-dimension estimates on financial time series. Most find evidence of nonlinearity but not of low-dimensional chaos.
Caveat emptor
Markets are open systems with news, regime shifts, and adaptive participants. Long-term forecasting via chaos models has a poor track record; short-horizon nonlinear forecasting in volatile assets is a more defensible niche.
See also
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