Nonlinear dependence in Finnish stock returns

Past research into the evolution of Finnish stock returns focuses on modeling linear and nonlinear dependence using various ARIMA and GARCH formulations, respectively. This paper extends the extant work by using Grassberger–Procaccia correlation dimensions to explore the nature of the nonlinear dynamics in daily Finnish stock returns during the 1970s and 1980s. Nonlinear behavior in both periods is evident. A simple GARCH model removes the nonlinearity in the first decade and dramatically reduces the nonlinearity in the second period. This supports the notion that Finnish stock returns exhibit nonlinear dependence but that the form of dependence is not chaotic.