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Editorial: Journal of economic behavior and organization: special issue on heterogeneous interacting agents in financial markets
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Testing for Nonlinearity in an Artificial Financial Market
No full textWe present a stochastic simulation model of a prototype financial market. The model covers a number of endogeneous interactions between economic agents: agents may change their mood with respect to the future price development under the influence of other traders’ obeserved behaviour and they may switch between strategies (chartist or fundamentalist) according to observed differences in profits. The particular behavioural variant adopted by an agent also determines her decision to enter on the long or short side of the market. Short-run imbalances between demand and supply lead to price adjustments by a market maker or auctioneer in the usual Walrasian manner. Our interest in this paper is in exploring the behaviour of our model when testing for the presence of chaos or non-linearity in the simulated data. First, attempts to determine the fractal dimension of the underlying process gave unsatisfactory results in that we experienced a lack of convergence of the estimate. Explicit tests for non-linearity and dependence (The BDS and Kaplan tests) also give very unstable results in that we can find both acceptance and strong rejection of IIDness in different realisations of our model. All in all, this behaviour is very similar to experience collected with empirical data and our results may point towards an explanation of why robustness of inference in this area is low. Estimating GARCH models, we also find that most of the nonlinearity is contained in second moments
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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