We present new evidence that normal heartbeat series are nonchaotic, nonlinear, and multifractal. In addition to considering the largest Lyapunov exponent and the correlation dimension, the results of the parametric and semiparametric estimation of the long memory parameter (long-range dependence) unambiguously reveal that the underlying process is nonstationary, multifractal, and has strong nonlinearity.

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This article considers the use of the long memory volatility process, FIGARCH, in representing Deutschemark -US dollar spot exchange rate returns for both high and low frequency returns data. The FIGARCH model is found to be the preferred specification for both high frequency and daily returns data, with similar values of the long memory volatility parameter across frequencies, which is indicative of returns being generated by a self similar process. The BDS test for non-linearity is applied to the residuals of the model for the high frequency returns. No evidence is found to suggest that the procedure for filtering the high frequency returns to remove the intraday periodicity has induced any non-linearities in the residuals; and the FIGARCH specification is found to be adequate (JEL C22, F31).

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