Title

Forecasting the Nikkei Spot Index with Fractional Cointegration

Publication Type

Journal Article

Publication Date

1999

Abstract

The forecast performance of the fractionally integrated error correction model is investigated against several competing models for the prediction of the Nikkei stock average index. The competing models include the martingale model, the vector autoregressive model and the conventional error correction model. Models are considered with and without conditional heteroscedasticity. For forecast horizons of over twenty days, the best forecasting performance is obtained for the model when fractional cointegration is combined with conditional heteroscedasticity. The results reinforce the notion that cointegration and fractional cointegration are important for long-horizon prediction.

Discipline

Asian Studies | Econometrics | Finance

Research Areas

Econometrics

Publication

Journal of Forecasting

Volume

18

Issue

4

First Page

259

Last Page

273

ISSN

0277-6693

Publisher

Wiley

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