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We present a selective survey of modern nonlinear modeling techniques relevant to the field of applied financial econometrics. We first established the usefulness of nonlinear modeling of financial time series and its relevance for forecasting by means of Sims's (1984) definition. Then, we describe specific univariate and multivariate nonlinear models that can be classified either as stochastic or as deterministically chaotic. We also provide several novel numerical applications of these modelsdoi:10.20381/ruor-929 fatcat:qfxmzt5j3zewjo3bw4flj6cbs4