TY - JOUR
AU1 - Ralf Östermark
AB - 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.
TI - The forecasting performance of Cartesian ARIMA search and a vector‐valued state space model
JF - Kybernetes
DO - 10.1108/03684920010308862
DA - 2000-02-01
UR - https://www.deepdyve.com/lp/emerald-publishing/the-forecasting-performance-of-cartesian-arima-search-and-a-vector-p2A975yaLF
SP - 83
EP - 104
VL - 29
IS - 1
DP - DeepDyve
ER -