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 InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 36 (2010)
Issue (Month): 2 (August)
Nearest neighbour; Nonlinearity; C22; C53; G10;
Other versions of this item:
- 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.
- Theodore Panagiotidis, 2010. "An out-of-sample test for nonlinearity in financial time series: An empirical application," Discussion Paper Series 2010_08, Department of Economics, University of Macedonia, revised Jun 2010.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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