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An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application

  • Theodore Panagiotidis

    ()

    ( Department Of Economics, University Of Macedonia, Thessaloniki, Greece; The Rimini Centre for Economic Analysis (RCEA), Italy)

This 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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File URL: http://www.rcfea.org/RePEc/pdf/wp20_10.pdf
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Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 20_10.

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Date of creation: Jan 2010
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Handle: RePEc:rim:rimwps:20_10
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  1. Jaditz, Ted & Sayers, Chera L, 1998. "Out-of-Sample Forecast Performance as a Test for Nonlinearity in Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 110-17, January.
  2. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  3. Golan, Amos & Perloff, Jeffrey M., 2002. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2bw559zk, Department of Agricultural & Resource Economics, UC Berkeley.
  4. David Chappell & Theodore Panagiotidis, 2005. "Using the correlation dimension to detect non-linear dynamics: Evidence from the Athens Stock Exchange," Econometrics 0504005, EconWPA.
  5. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1998. "Testing nonlinear forecastability in time series: Theory and evidence from the EMS," Economics Letters, Elsevier, vol. 59(1), pages 49-63, April.
  6. Theodore Panagiotidis, 2010. "Market efficiency and the Euro: the case of the Athens stock exchange," Empirica, Springer, vol. 37(3), pages 237-251, July.
  7. Agnon, Yehuda & Golan, Amos & Shearer, Matthew, 1999. "Nonparametric, nonlinear, short-term forecasting: theory and evidence for nonlinearities in the commodity markets," Economics Letters, Elsevier, vol. 65(3), pages 293-299, December.
  8. Granger Clive W.J., 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-11, September.
  9. LeBaron, Blake, 1992. "Forecast Improvements Using a Volatility Index," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S137-49, Suppl. De.
  10. Mizrach, B, 1992. "Multivariate Nearest-Neighbor Forecasts of EMS Exchange Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S151-63, Suppl. De.
  11. Jaditz Ted & Riddick Leigh A., 2000. "Time-Series Near-Neighbor Regression," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(1), pages 1-11, April.
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