An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application
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 nonl...
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| Published in | Computational economics Vol. 36; no. 2; pp. 121 - 132 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Boston
Springer US
01.08.2010
Springer Society for Computational Economics Springer Nature B.V |
| Series | Computational Economics |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0927-7099 1572-9974 |
| DOI | 10.1007/s10614-010-9225-z |
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| Abstract | 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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| AbstractList | 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. Reprinted by permission of Springer 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. [PUBLICATION ABSTRACT] 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. |
| Author | Panagiotidis, Theodore |
| Author_xml | – sequence: 1 givenname: Theodore surname: Panagiotidis fullname: Panagiotidis, Theodore email: tpanag@uom.gr organization: Department of Economics, University of Macedonia |
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| Cites_doi | 10.2307/2289282 10.1016/S0165-1765(99)00156-1 10.1093/biomet/73.2.461 10.1162/108118200569171 10.2307/1392021 10.1080/07474939608800353 10.1016/S0165-1765(98)00019-6 10.1111/j.1467-9892.1983.tb00373.x 10.1002/jae.3950070511 10.1016/0167-2789(89)90074-2 10.1162/003465304774201860 10.1002/jae.3950070510 10.1007/BF01608556 10.2307/1912773 10.1080/01621459.1988.10478639 10.1080/07350015.1998.10524740 10.1007/s10663-008-9100-5 10.1017/S1365100598008049 10.1111/j.2517-6161.1992.tb01884.x |
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| DOI | 10.1007/s10614-010-9225-z |
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| Title | An Out-of-Sample Test for Nonlinearity in Financial Time Series: An Empirical Application |
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