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The forecasting performance of Cartesian ARIMA search and a vector‐valued state space model

Ralf Östermark (Department of Business Administration, Abo Akademi University, Henriksgatan, Finland)

Kybernetes

ISSN: 0368-492X

Article publication date: 1 February 2000

Abstract

The performance of Aoki’s state space algorithm and the Cartesian ARIMA search algorithm (CARlMA) of Östermark and Höglund is compared. The analysis is carried out on a set of stock prices on the Helsinki (Finland) and Stockholm (Sweden) Stock Exchanges. Demonstrates that the Finnish and Swedish stock markets differ in predictability of stock prices. With Finnish stock data, Aoki’s state space algorithm outperforms the subset of MAPE minimizing forecasts. In contrast, with Swedish stock data, ARIMA‐models of a fairly simple structure outperform Aoki’s algorithm. The stock markets are seen to differ in complexity of time series models as well as in predictability of individual asset prices.

Keywords

Citation

Östermark, R. (2000), "The forecasting performance of Cartesian ARIMA search and a vector‐valued state space model", Kybernetes, Vol. 29 No. 1, pp. 83-104. https://doi.org/10.1108/03684920010308862

Publisher

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MCB UP Ltd

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