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Evaluates an identification strategy, based on ridge regression, for mutliple‐input models. The corresponding computer algorithm was implemented on a VAX–8800 computer at the Computing Centre at A˚bo Akademi. The evaluation of the ridge‐regression method was carried out by simulations of different transfer‐function noise model structures. The models are essentially the same as those of Edlund, but a far greater number of replications, 1,000, is used in each of the 21 cases tested. Furthermore, uses actually identified and estimated ARIMA models of the residuals in the identification procedure of impulse response weights, unlike Edlund, who used only theoretical noise models in filtering the input and output series. A short discussion of the underlying theory is presented in Part I. The procedures and results of the empirical testing will be published in Part II in Kybernetes, Vol. 22 No. 7, 1993.

Evaluates an identification strategy, based on ridge regression, for multiple‐input models. The models are essentially the same as those of Edlund, but a far greater number of replications, 1,000, is used in each of the 21 cases tested. Furthermore, users actually identified and estimated ARIMA models of the residuals in the identification procedure of impulse response weights, unlike Edlund, who used only theoretical noise models in filtering the input and output series. A short discussion of the underlying theory was presented in Part I, Kybernetes, Vol. 22 No. 4, 1993, pp. 47–53. In Part II the procedures and results of the empirical testing are published together with some concluding remarks.

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.

The power and size of five cointegration tests, the ADF‐, Zˆ_α‐, ECM‐, SW‐, and JJ‐statistics, are evaluated in some large‐scale Monte Carlo simulations, when the underlying system is subjected to regime shifts. Following the suggestion by Gregory and Hansen, selects the minimum value for the shift‐corrected statistics evaluated over a set of tentative break points for the regime shifts. The performance of these statistics is compared to the corresponding ordinary statistics in conditions of regime shifts. The results show that no test uniformly outperforms the others in terms of power in the parameter space we have used.

In this paper we try to assess how a weighted shares index and corresponding futures index respond to a change in the short‐term interest rate. Three methods are applied in analysing the data: an error correction regression method, a state space method and a neural network method. Results indicate presence of cointegration in the data set. A sensitivity analysis of each model was carried out by studying the evolution of the predictions after the studied time period, using deterministic values of the inputs. An analysis of the influence of an interest rate shock yielded interesting results. In the neural network model, again, more complicated response patterns were observed.

This paper aims to explore how organizational actors make reference to history and how they use historical reference purposefully in order to affect strategy‐making.

The paper draws on in‐depth case studies on two Swedish MNCs. Data have been collected through 79 interviews as well as participant observation and archival studies.

Organizational actors purposefully construct and use history in order to establish continuity in strategy processes. The use of historical references legitimizes or delegitimizes specific strategic options.

Two old firms with a clear interest in organizational history have been studied. Future research on additional companies, including young firms and firms with less interest in history, is needed.

The purposeful use of history can be a powerful tool for managers to influence organizational change processes.

Very little research on the use of history in business organizations has so far been done. In an interdisciplinary manner the paper introduces concepts from research in history to management research. Based on two rich case studies the paper contributes by outlining what role different uses of history play in strategic and organizational change.