Complex Evolutionary Systems in Behavioral Finance

Hommes, Cars; Wagener, Florian

doi:10.1016/b978-012374258-2.50008-7

Cited by 94 publications

(38 citation statements)

References 133 publications

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“…Based on the perception that models with representative agents frequently failed to predict or even to explain market behavior, researchers increasingly depart from the underlying assumption of rational expectations. Motivated by the seminal survey study of Taylor and Allen (1992), the introduction of heterogenous expectations has proven to be a powerful tool to replicate properties of trading behavior in financial markets (Hommes, 2009;Hommes and Wagener, 2009;Westerhoff, 2009). The bulk of heterogeneous expectation approaches introduces a nonlinear law of motion governing agents' switching between otherwise linear forecasting techniques (Brock and Hommes, 1997;De Grauwe and Grimaldi, 2006;Lux, 1998;Westerhoff, 2003).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear expectations in speculative markets – Evidence from the ECB survey of professional forecasters

Reitz

Rülke

Stadtmann

2012

Journal of Economic Dynamics and Control

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in Nonlinear Expectations in Speculative Markets -Evidence from the ECB Survey of Professional ForecastStefan Reitz, Jan-Christoph Rülke and Georg Stadtmann Abstract: Chartist and fundamentalist models have proven to be capable of replicating stylized facts on speculative markets. In general, this is achieved by specifying nonlinear interactions of otherwise linear asset price expectations of the respective trader groups. This paper investigates whether or not regressive and extrapolative expectations themselves exhibit significant nonlinear dynamics. The empirical results are based on a new data set from the European Central Bank Survey of Professional Forecasters on oil price expectations. In particular, we find that forecasters form destabilizing expectations in the neighborhood of the fundamental value, whereas expectations tend to be stabilizing in the presence of substantial oil price misalignment. June 2011 Abstract Chartist and fundamentalist models have proven to be capable of replicating stylized facts on speculative markets. In general, this is achieved by specifying nonlinear interactions of otherwise linear asset price expectations of the respective trader groups. This paper investigates whether or not regressive and extrapolative expectations themselves exhibit significant nonlinear dynamics. The empirical results are based on a new data set from the European Central Bank Survey of Professional Forecasters on oil price expectations. In particular, we find that forecasters form destabilizing expectations in the neighborhood of the fundamental value, whereas expectations tend to be stabilizing in the presence of substantial oil price misalignment.JEL classification: F31, D84, C33

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Section: Introductionmentioning

confidence: 99%

Nonlinear expectations in speculative markets – Evidence from the ECB survey of professional forecasters

Reitz

Rülke

Stadtmann

2012

Journal of Economic Dynamics and Control

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“…Summarizing the discussion, our continuous-time model generalizes the workhorse of mathematical finance (15). In contrast to the standard model, the evolutionary stock market model derives endogenous asset prices from the market interaction of heterogenous investors.…”

Section: Continuous-time Evolutionary Modelmentioning

confidence: 99%

“…Models with myopic investors, in which the planning horizon and frequency of trade coincide, share this property; see e.g. Brock, Hommes and Wagener [5], Chiarella, Dieci and Gardini [7] and the references in the surveys by Chiarella, Dieci and He [8] and Hommes and Wagener [15].…”

Section: Introductionmentioning

confidence: 99%

“…The existence of continuous-time limits for other discrete-time agentbased finance models with finitely many traders (see the surveys by Chiarella, Dieci and He [8] and Hommes and Wagener [15]), by-and-large, is an open problem. One exception is the paper by Buchmann and Weber [6] who derive the continuous-time limit of a betting market modelà la Kelly [16].…”

Section: Introductionmentioning

confidence: 99%

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From discrete to continuous time evolutionary finance models

Palczewski

Sc̣henk-Hoppé

2010

Journal of Economic Dynamics and Control

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This paper aims to open a new avenue for research in continuous-time financial market models with endogenous prices and heterogenous investors. To this end we introduce a discrete-time evolutionary stock market model that accommodates time periods of arbitrary length. The dynamics is timeconsistent and allows the comparison of paths with different frequency of trade. The main result in this paper is the derivation of the limit model as the length of the time period tends to zero. The resulting model in continuous time generalizes the workhorse model of mathematical finance by introducing asset prices that are driven by the market interaction of investors following self-financing trading strategies. Our approach also offers a numerical scheme for the simulation of the continuous-time model that satisfies constraints such as market clearing at every time step. An illustration is provided.

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“…Agent-based models in which investors are myopic mean-variance optimizers typically have one risky and one risk-free asset (Hommes andWagener, 2009, andChiarella, Dieci andHe, 2009). The risky asset pays a random (i.i.d.)…”

Section: Introductionmentioning

confidence: 99%

Local stability analysis of a stochastic evolutionary financial market model with a risk-free asset

2011

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This paper introduces and analyzes an evolutionary model of a financial marketwith a risk-free asset. Focus is on the study of local stability of the wealth dynamics through the application of recent results on the linearization and stability of random dynamical systems (Evstigneev et al. Proc Am Math Soc 139:1061-1072. Conditions are derived for the linearization of the model at an equilibrium state which ensure local convergence of sample paths to this equilibrium. The paper also shows that the concept of local stability is closely related to the notion of evolutionary stability. A locally evolutionarily stable investmentstrategy in the evolutionary model with a risk-free asset is derived, extending previousresearch. The method illustrated here is applicable for the analysis of manifold economic and financial dynamic models involving randomness. Conditions are derived for the linearization of the model at an equilibrium state which ensure local convergence of sample paths to this equilibrium. The paper also shows that concept of local stability is closely related to the notion of evolutionary stability. A locally evolutionarily stable investment strategy in the evolutionary model with a risk-free asset is derived, extending previous research. Our analysis can serve as an illustration of a mathematically correct approach to the study of local stability in stochastic systems. The method will be useful in the study of other economic and financial dynamic models involving randomness.JEL classification: G11, G12.

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Complex Evolutionary Systems in Behavioral Finance

Cited by 94 publications

References 133 publications

Nonlinear expectations in speculative markets – Evidence from the ECB survey of professional forecasters

Nonlinear expectations in speculative markets – Evidence from the ECB survey of professional forecasters

From discrete to continuous time evolutionary finance models

Local stability analysis of a stochastic evolutionary financial market model with a risk-free asset

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