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Tanya Araújo

Publications and source records attributed to Tanya Araújo.

24 records · Page 2Linked to original sources

Agent Based Models and Opinion Dynamics as Markov Chains

This paper introduces a Markov chain approach that allows a rigorous analysis of agent based opinion dynamics as well as other related agent based models (ABM). By viewing the ABM dynamics as a micro description of the process, we show how the corresponding macro description is obtained by a projection construction. Then, well known conditions for lumpability make it possible to establish the cases where the macro model is still Markov. In this case we obtain a complete picture of the dynamics including the transient stage, the most interesting phase in applications. For such a purpose a crucial role is played by the type of probability distribution used to implement the stochastic part of the model which defines the updating rule and governs the dynamics. In addition, we show how restrictions in communication leading to the co-existence of different opinions follow from the emergence of new absorbing states. We describe our analysis in detail with some specific models of opinion dynamics. Generalizations concerning different opinion representations as well as opinion models with other interaction mechanisms are also discussed. We find that our method may be an attractive alternative to mean-field approaches and that this approach provides new perspectives on the modeling of opinion exchange dynamics, and more generally of other ABM.

nlin.AO↗

On the Empirical Relevance of the Transient in Opinion Models

While the number and variety of models to explain opinion exchange dynamics is huge, attempts to justify the model results using empirical data are relatively rare. As linking to real data is essential for establishing model credibility, this Letter develops a empirical confirmation experiment by which an opinion model is related to real election data. The model is based on a representation of opinions as a vector of $k$ bits. Individuals interact according to the principle that similarity leads to interaction and interaction leads to still more similarity. In the comparison to real data we concentrate on the transient opinion profiles that form during the dynamic process. An artificial election procedure is introduced which allows to relate transient opinion configurations to the electoral performance of candidates for which data is available. The election procedure based on the well--established principle of proximity voting is repeatedly performed during the transient period and remarkable statistical agreement with the empirical data is observed.

physics.soc-ph↗

Hiking the hypercube: producers and consumers

We study the dynamics of co-evolution of producers and customers described by bit-strings representing individual traits. Individual ''size-like'' properties are controlled by binary encounters which outcome depends upon a recognition process. Depending upon the parameter set-up, mutual selection of producers and customers results in different types of attractors, either an exclusive niches regime or a competition regime.

q-fin.GN↗

The Geometry of Crashes - A Measure of the Dynamics of Stock Market Crises

This paper investigates the dynamics of stocks in the S&P500 index for the last 30 years. Using a stochastic geometry technique, we investigate the evolution of the market space and define a new measure for that purpose, which is a robust index of the dynamics of the market structure and provides information on the intensity and the sectoral impact of the crises. With this measure, we analyze the effects of some extreme phenomena on the geometry of the market. Nine crashes between 1987 and 2001 are compared by looking at the way they modify the shape of the manifold that describes the S&P500 market space. These crises are identified as (a) structural, (b) general and (c) local.

physics.soc-ph↗

Complex Behavior of Stock Markets: Processes of Synchronization and Desynchronization during Crises

This paper investigates the dynamics of in the S&P500 index from daily returns for the last 30 years. Using a stochastic geometry technique, each S&P500 yearly batch of data is embedded in a subspace that can be accurately described by a reduced number of dimensions. Such feature is understood as empirical evidence for the presence of a certain amount of structure in the market. As part of the inquiry into the structure of the market we investigate changes in its volume and shape, and we define new measures for that purpose. Having these measures defined in the space of stocks we analyze the effects of some extreme phenomena on the geometry of the market. We discuss the hypothesis that collective behavior in period of crises reinforces the structure of correlations between stocks, but that it also may have an opposite effect on clustering by similar economic sectors. Comparing the crises of 1987 and 2001, we discuss why the expansion of the ellipsoid describing the geometry of the distances in the market, which occurs in the latter period, is not homogeneous through sectors. The conclusions from this research identify some of the changes in the structure of the market over the last 30 years.

cond-mat.stat-mech↗

Reconstructing an economic space from a market metric

Using a metric related to the returns correlation, a method is proposed to reconstruct an economic space from the market data. A reduced subspace, associated to the systematic structure of the market, is identified and its dimension related to the number of terms in factor models. Example were worked out involving sets of companies from the DJIA and S&P500 indexes. Having a metric defined in the space of companies, network topology coefficients may be used to extract further information from the data. A notion of "continuous clustering" is defined and empirically related to the occurrence of market shocks.

cond-mat.stat-mech↗