Nonlinearity and Nonlinear Econometric Models in Finance

Financial Econometrics

  1. Ruey S. Tsay PhD

Published Online: 15 DEC 2012

DOI: 10.1002/9781118182635.efm0065

Encyclopedia of Financial Models

Encyclopedia of Financial Models

How to Cite

Tsay, R. S. 2012. Nonlinearity and Nonlinear Econometric Models in Finance. Encyclopedia of Financial Models. .

Author Information

  1. H.G.B. Alexander Professor of Econometrics and Statistics, University of Chicago Booth School of Business

Publication History

  1. Published Online: 15 DEC 2012


Many financial and economic data exhibit nonlinear characteristics. Prices of commodities such as crude oil often rise quickly but decline slowly. The monthly U.S. unemployment rate exhibits sharp increases followed by slow decreases. To model these characteristics in a satisfactory manner, one must employ nonlinear econometric models or use nonparametric statistical methods. For most applications, it suffices to employ simple nonlinear models. For example, the quarterly growth rate of the U.S. gross domestic product can be adequately described by the Markov switching or threshold autoregressive models. These models typically classify the state of the U.S. economy into two categories corresponding roughly to expansion and contraction.


  • BDS Test;
  • F Test;
  • Kernel Smoothing;
  • Local Linear Regression;
  • Markov Switching Model;
  • Neural Network;
  • Nonlienarity Test;
  • Nonparametric Method;
  • RESET Test;
  • Threshold Autoregressive Model;
  • Threshold Test