Evolutionary Computation in Economics and Finance: A Bibliography

Chen, Shu‐Heng; Kuo, Tzu-Wen

doi:10.1007/978-3-7908-1784-3_22

Cited by 42 publications

(29 citation statements)

References 137 publications

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“…(Chen and Wang, 2003). All of these techniques have been applied to modeling agents in the economic literature; see Chen (2002a), Chen (2002b), and Brenner (2006) for a glossary of them.…”

Section: Discussionmentioning

confidence: 99%

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

Chen

Tai

2006

Comput Econ

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Abstract. Agent-based Methodology (ABM) is becoming indispensable for the interdisciplinary study of social and economic complex adaptive systems. The essence of ABM lies in the notion of autonomous agents whose behavior may evolve endogenously and can generate and mimic the corresponding complex system dynamics that the ABM is studying. Over the past decade, many Computational Intelligence (CI) methods have been applied to the design of autonomous agents, in particular, their adaptive schemes. This design issue is non-trivial since the chosen adaptive schemes usually have a profound impact on the generated system dynamics. Robert Lucas, one of the most influential modern economic theorists, has suggested using laboratories with human agents, also known as Experimental Economics, to help solve the selection issue. While this is a promising approach, laboratories used in the current experimental economics are not computationally equipped to meet the demands of the selection task. This paper attempts to materialize Lucas' suggestion by establishing a laboratory where human subjects are equipped with the computational power that satisfies the computational equivalence condition.

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“…(Chen and Wang, 2003). All of these techniques have been applied to modeling agents in the economic literature; see Chen (2002a), Chen (2002b), and Brenner (2006) for a glossary of them.…”

Section: Discussionmentioning

confidence: 99%

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

Chen

Tai

2006

Comput Econ

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“…See Poli et al (2010) for a review of the state of the art in GP. Chen and Kuo (2002) classified the literature on the application of evolutionary computation to economics and finance. Most evolutionary computing in economics has been implemented in finance (Goldberg, 1989).…”

Section: Evolutionary Computationmentioning

confidence: 99%

A new approach for the quantification of qualitative measures of economic expectations

2016

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In this study a new approach to quantify qualitative survey data about the direction of change is presented. We propose a data-driven procedure based on evolutionary computation that avoids making any assumption about agents' expectations. The research focuses on experts' expectations about the state of the economy from the World Economic Survey in twenty eight countries of the Organisation for Economic Co-operation and Development. The proposed method is used to transform qualitative responses into estimates of economic growth. In a first experiment, we combine agents' expectations about the future to construct a leading indicator of economic activity. In a second experiment, agents' judgements about the present are combined to generate a coincident indicator. Then, we use index tracking to derive the optimal combination of weights for both indicators that best replicates the evolution of economic activity in each country. Finally, we compute several accuracy measures to assess the performance of these estimates in tracking economic growth. The different results across countries have led us to use multidimensional scaling analysis in order to group all economies in four clusters according to their performance. We obtain the best results for Belgium, Norway, Austria, Lithuania, Japan and the United Kingdom.

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“…Most economic applications of evolutionary computing are in finance (Chen and Kuo, 2002;Fogel, 2006;Goldberg, 1989). GAs have been used to predict the financial failure of firms (Acosta-González and Fernández, 2014), to explain the 2008 financial crisis (Acosta-González et al, 2012), to model exchange rates (Lawrenz and Westerhoff, 2003), to evaluate the convergence to the rational expectations equilibrium (Maschek, 2010), to optimize the signals generated by technical trading tools (Thinyane and Millin, 2011), to forecast stock price trends in Taiwan (Wei, 2013), etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Let the Data Do the Talking: Empirical Modelling of Survey-Based Expectations by Means of Genetic Programming

2017

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Evolutionary Computation in Economics and Finance: A Bibliography

Cited by 42 publications

References 137 publications

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach

A new approach for the quantification of qualitative measures of economic expectations

Let the Data Do the Talking: Empirical Modelling of Survey-Based Expectations by Means of Genetic Programming

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