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| Author: | Östermark, R. (et al.) |
| Title: | Nonlinear modelling of the Finnish banking and finance branch index |
| Journal: | European Journal of Finance
2004 : AUG, VOL. 10:4, p. 277-289 |
| Index terms: | Banking Finland Financial models Time series Stock exchanges |
| Freeterms: | Variance-nonlinearity Mean-nonlinearity |
| Language: | eng |
| Abstract: | It is well documented that daily returns of several financial assets cannot be modelled by pure linear processes. In this paper some linear modelling techniques are applied to a Finnish financial time series, the daily Banking and Finance branch index on the Helsinki Stock Exchange. The techniques include a variance-nonlinear model from the ARCH family, a mean-nonlinear model, namely Smooth Transition Autoregression (STAR)-model and a neural network. Linearity is tested by standard autocorrelation tests, LM-tests against the specific nonlinear models and theBDS-test. The study demonstrates that the stock series is both linearly and nonlinearly dependent. Adapting an ARCH eliminates the dependencies most satisfactorily. The ARCH-models and STAR-models were estimated using the SHAZAM-package. |
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