Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods
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Stella Karagianni
A growing body of literature concentrates on the linear dependence between stock returns and inflation. Although the recent empirical evidence suggested the presence of complexities, to our knowledge only a few works have investigated the existence of a potential nonlinear stock returns-inflation relationship. In order to study in more depth the dynamic attributes of this puzzle, we suggest a quite different framework where the primary goal is to explore the association between their underlying dynamics. Through the use of the Recurrence Quantification Analysis (Webber and Zbilut (1994)), the test for structural breaks of Bai and Perron (1998) and the test for nonlinear causality of Diks and Panchenko (2006), we find evidence in favour of negative nonlinear linkages between the inherent dynamics of inflation and stock returns. The presence of nonlinearity reinforces uncertainty. As long as inter-dependences are complex and nonlinear, small perturbations in fundamentals can lead to unexpected propagations within the financial system.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- Contemporaneous-Threshold Smooth Transition GARCH Models
- Filtering Time Series with Penalized Splines
- Real-Time Optimal Monetary Policy with Undistinguishable Model Parameters and Shock Processes Uncertainty
- Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods
- Alternative Estimators of Long-Range Dependence
- Nonparametric Testing for Linearity in Cointegrated Error-Correction Models
Articles in the same Issue
- Article
- Contemporaneous-Threshold Smooth Transition GARCH Models
- Filtering Time Series with Penalized Splines
- Real-Time Optimal Monetary Policy with Undistinguishable Model Parameters and Shock Processes Uncertainty
- Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods
- Alternative Estimators of Long-Range Dependence
- Nonparametric Testing for Linearity in Cointegrated Error-Correction Models
