An out-of-sample test for nonlinearity in financial time series: An empirical application
AbstractThis paper employs a local information, nearest neighbour forecasting methodology to test for evidence of nonlinearity in financial time series. Evidence from well-known data generating process are provided and compared with returns from the Athens stock exchange given the in-sample evidence of nonlinear dynamics that has appeared in the literature. Nearest neighbour forecasts fail to produce more accurate forecasts from a simple AR model. This does not substantiate the presence of in-sample nonlinearity in the series.
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Bibliographic InfoPaper provided by Department of Economics, University of Macedonia in its series Discussion Paper Series with number 2010_08.
Date of creation: Jun 2010
Date of revision: Jun 2010
nearest neighbour; nonlinearity;
Other versions of this item:
- Theodore Panagiotidis, 2010. "An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application," Computational Economics, Society for Computational Economics, vol. 36(2), pages 121-132, August.
- Theodore Panagiotidis, 2010. "An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application," Working Paper Series 20_10, The Rimini Centre for Economic Analysis.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-06-18 (All new papers)
- NEP-ECM-2010-06-18 (Econometrics)
- NEP-ETS-2010-06-18 (Econometric Time Series)
- NEP-FOR-2010-06-18 (Forecasting)
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