Recursive least squares modelling: empirical evidence from the Finnish and Japanese markets

Abstract

Previous evidence suggests that the relationship between different stock markets is unstable over time. In particular, the Finnish and Japanese financial economies are interrelated and exhibit non‐linear behaviour. Presents an approximation of the influence of the Japanese stock market on the Finnish derivatives market by an adaptive recursive least squares (RLS) algorithm. The parameters are allowed to change over time through a discounting factor, thus providing a convenient means for recognizing past information to a specified degree. Following the reasoning of Bera et al. (1992), shows that the RLS algorithm is, theoretically, able to cope with conditional heteroscedasticity. Compares the results with different values on the discount factor and when choosing a suitable value the ARCH‐like effects in the residuals seem to vanish. On the other hand, some new peculiarities in the RLS residuals emerge when ARCH effects are eliminated. The results indicate that the standard RLS algorithm combined with a proper specification of the discount factor could be useful in studying relationships of this kind.

Citation

Höglund, R. and Östermark, R. (1997), "Recursive least squares modelling: empirical evidence from the Finnish and Japanese markets", Kybernetes, Vol. 26 No. 8, pp. 893-907. https://doi.org/10.1108/03684929710182136