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BERG working paper series

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Has Fulltext

  • no (5)
  • yes (3)

Author

  • Frank Westerhoff (3)
  • Guido Heineck (2)
  • Reiner Franke (2)
  • Björn-Christopher Witte (1)
  • Christoph Wunder (1)
  • Fabio Tramontana (1)
  • Frank H. Westerhoff (1)
  • János Seregi (1)
  • Laura Gardini (1)
  • László Balogh (1)

Document Type

  • Arbeitspapier (7)
  • Buch (Monografie) (1)

Keywords

  • Capital-Asset-Pricing Modell ; Mehragentensystem ; Volabilität ; Online-Publikation (1)
  • Goods market, stock market, heterogeneous speculators, stability analysis, complex dynamics (1)
  • Gütermarkt ; Aktienmarkt ; Börsenspekulation ; Dynamisches Modell ; Online-Publikation (1)
  • Kapitalmarkt ; Künstliche Intelligenz ; Mehragentensystem ; Online-Publikation (1)
  • Structural stochastic volatility; method of simulated moments; autocorrelation pattern; fat tails; bootstrapped p-values (1)
  • financial markets; autocorrelations; artificial intelligence; agent-based modeling (1)

Institute

  • Lehrstuhl für Volkswirtschaftslehre, insbesondere Wirtschaftspolitik (4)
  • Lehrstuhl für Volkswirtschaftslehre, insbesondere Empirische Mikroökonomik (2)
  • Lehrstuhl für Volkswirtschaftslehre, insbesondere Finanzwissenschaft (2)
  • Wissenschaftliches Institut für Hochschulsoftware der Universität Bamberg (ihb) (1)

8 search hits

search hits 1 to 8

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86
Do literacy and numeracy pay off? : on the relationship between basic skills and earnings (2012)
Manfred Antoni Guido Heineck
83
Show/Hide Abstract Why a Simple Herding Model May Generate the Stylized Facts of Daily Returns: Explanation and Estimation (2012)
Reiner Franke Frank Westerhoff
The paper proposes an elementary agent-based asset pricing model that, invoking the two trader types of fundamentalists and chartists, comprises four features: (i) price determination by excess demand; (ii) a herding mechanism that gives rise to a macroscopic adjustment equation for the market fractions of the two groups; (iii) a rush towards fundamentalism when the price misalignment becomes too large; and (iv) a stronger noise component in the demand per chartist trader than in the demand per fundamentalist trader, which implies a structural stochastic volatility in the returns. Combining analytical and numerical methods, the interaction between these elements is studied in the phase plane of the price and a majority index. In addition, the model is estimated by the method of simulated moments, where the choice of the moments reflects the basic stylized facts of the daily returns of a stock market index. A (parametric) bootstrap procedure serves to set up an econometric test to evaluate the model’s goodness-of-fit, which proves to be highly satisfactory. The bootstrap also makes sure that the estimated structural parameters are well identified.
87
The social welfare function of forests in the light of the theory of public goods (2012)
János Seregi Zsuzsanna Lelovics László Balogh
89
The bull and bear market model of Huang and Day: some extensions and new results (2012)
Fabio Tramontana Frank Westerhoff Laura Gardini
84
Show/Hide Abstract Interactions between the real economy and the stock market (2012)
Frank Westerhoff
We develop a simple behavioral macro model to study interactions between the real economy and the stock market. The real economy is represented by a Keynesian goods market approach while the setup for the stock market includes heterogeneous speculators. Using a mixture of analytical and numerical tools we find, for instance, that speculators may create endogenous boom-bust dynamics in the stock market which, by spilling over into the real economy, can cause lasting fluctuations in economic activity. However, fluctuations in economic activity may, by shaping the firms’ fundamental values, also have an impact on the dynamics of the stock market.
88
Agent-based models for economic policy design : two illustrative examples (2012)
Frank H. Westerhoff Reiner Franke
82
Show/Hide Abstract Removing systematic patterns in returns in a financial market model by artificially intelligent traders (2012)
Björn-Christopher Witte
The unpredictability of returns counts as a stylized fact of financial markets. To reproduce this fact, modelers usually implement noise terms − a method with several downsides. Above all, systematic patterns are not eliminated but merely blurred. The present article introduces a model in which systematic patterns are removed endogenously. This is achieved in a reality-oriented way: Intelligent traders are able to identify patterns and exploit them. To identify and predict patterns, a very simple artificial neural network is used. As neural network mimic the cognitive processes of the human brain, this method might be regarded as a quite accurate way of how traders identify patterns and forecast prices in reality. The simulation experiments show that the artificial traders exploit patterns effectively and thereby remove them, which ultimately leads to the unpredictability of prices. Further results relate to the influence of pattern exploiters on market efficiency.
85
Working time preferences, hours mismatch and well-being of couples: Are there spillovers? (2012)
Christoph Wunder Guido Heineck

search hits 1 to 8

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