A global optimization heuristic for estimating agent based models

Gilli, Manfred; Winker, Peter

doi:10.1016/s0167-9473(02)00214-1

Cited by 201 publications

(187 citation statements)

References 15 publications

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“…In Figure (2) we show a typical simulated pattern of the price obtained from (16) using the Langevin equation (12) for the change of z and a uniform distribution for ∆ξ = η. In the lower parts we compare the returns calculated from (18) and from the approximation (19).…”

Section: Market Implementationmentioning

confidence: 99%

“…[30,34]), for true multi-agent models parameter estimation and evaluation on the base of empirical data is still largely missing in the pertinent literature. As far as we know the only exception is a recent paper by Gilli and Winker [12], who estimate some of the parameters of Kirman's seminal herding model [17,18]. They introduce a simulated moment approach extracting two key parameters of the model via matching of the empirical kurtosis and the first autocorrelation coefficient of squared returns.…”

Section: Introductionmentioning

confidence: 99%

“…Our traders are also divided into the groups of fundamentalists and noise traders following the legacy of Beja and Goldman [4], as well as many other authors. Like in [12] the interaction among the traders is based on a variant of the herding mechanism introduced by Kirman, but this herding mechanism is embedded into a simpler framework for the market dynamics which allows to derive a closed-form solution for the distribution of returns. The simplicity of this approach also enables us to consider a generalization of the herding mechanism of our model by allowing for asymmetric transition probabilities.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

2005

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The behavioral origins of the stylized facts of financial returns have been addressed in a growing body of agent-based models of financial markets. While the traditional efficient market viewpoint explains all statistical properties of returns by similar features of the news arrival process, the more recent behavioral finance models explain them as imprints of universal patterns of interaction in these markets. In this paper we contribute to this literature by introducing a very simple agent-based model in which the ubiquitous stylized facts (fat tails, volatility clustering) are emergent properties of the interaction among traders. The simplicity of the model allows us to estimate the underlying parameters, since it is possible to derive a closed form solution for the distribution of returns. We show that the tail shape characterizing the fatness of the unconditional distribution of returns can be directly derived from some structural variables that govern the traders' interactions, namely the herding propensity and the autonomous switching tendency.

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Section: Market Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

2005

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“…Not much later, Winker and Gilli (2001) and Gilli and Winker (2003) also for less obvious asset classes, such as oil (ter Ellen and Zwinkels, 2010), housing (Kouwenberg and Zwinkels, 2014), gold (Baur and Glover, 2014), options (Frijns et al, 2010), hedge funds (Schauten et al, 2015), and credit markets (Chiarella et al, 2015).…”

Section: Estimationmentioning

confidence: 99%

“…Winker and Gilli (2001) and Gilli and Winker (2003) in the fundamentalists' behaviour further destabilise the exchange rate. This is in stark contrast to the findings in Manzan and Westerhoff (2007).…”

Section: Foreign Exchange Marketmentioning

confidence: 99%