Forecasting the Nikkei Spot Index with Fractional Cointegration
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.
Asian Studies | Econometrics | Finance
Journal of Forecasting
TSE, Yiu Kuen and Lien, Donald.
Forecasting the Nikkei Spot Index with Fractional Cointegration. (1999). Journal of Forecasting. 18, (4), 259-273. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/261
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