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Forecasting the Nikkei spot index with fractional cointegration

✍ Scribed by Donald Lien; Yiu Kuen Tse


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
168 KB
Volume
18
Category
Article
ISSN
0277-6693

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✦ Synopsis


We investigate the forecast performance of the fractionally integrated error correction model 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. We consider models 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. Our results reinforce the notion that cointegration and fractional cointegration are important for long-horizon prediction.