Journal ArticleDOI
Chaotic dynamics: theory and applications to economics, by Alfredo Medio in collaboration with Giampaolo Gallo. Pp 344. £35. 1993. ISBN 0-521-39488-0; (Accompanying Disk ISBN 0-521-42107-1. £30 MSDOS or Apple Mac). (Cambridge University Press)
TLDR
This book introduces chaos and economics in a continuous-time model of inventory business cycles and applications to Economics, and discusses the role of software in this transformation.Abstract:
Preface Part I. Theory: 1. General introduction: chaos and economics 2. Basic mathematical concepts 3. A user's guide 4. Surfaces of sections and Poincare maps 5. Spectral analysis 6. Lyapunov characteristic exponents 7. Dimensions 8. Symbolic dynamics 9. Transition to chaos: theoretical predictive criteria 10. Analysis of experimental signals: some theoretical problems Part II. Applications to Economics: 11. Discrete and continuous chaos 12. Cycles and chaos in overlapping generations models with production 13. Chaos in a continuous-time model of inventory business cycles 14. Analysis of experimental signals Part III. Software: 15. DMC manual 16. MODEL 17. EVAL 18. PLOT 19. STAT 20. FILES 21. UTIL 22. OPTS 23. QUIT 24. Internal menu commands 25. DMC internal compiler.read more
Citations
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Book Chapter
Non-linearity and the environment
R. Degli Agosti,Hubert Greppin +1 more
TL;DR: In this article, the authors introduce the nonspecialised reader to the field of nonlinear dynamics and its relation to environmental problems and use a very simple logistic model, which can be easily simulated even on hand-calculators or spreadsheet-like software's.
Labour Productivity and the Chaotic Economic Growth Model: G7
TL;DR: In this paper, the authors provide a relatively simple chaotic economic growth model that is capable of generating stable equilibria, cycles, or chaos, which is used to prove that erratic and chaotic fluctuations can indeed arise in completely deterministic models.
Book ChapterDOI
Theoretical Background: A New Theoretical Framework for Financial Planning with the Case of Life Insurance Demand—Dynamic Ecological Systemic Framework
TL;DR: In this paper, a conceptual and theoretical framework for understanding the behavioral demand for financial planning, specifically for life insurance, is introduced. And the basic background theories of this new framework are introduced and explained.
Journal ArticleDOI
Simultaneity and non‐linear variability in financial markets: simulation and forecasting
TL;DR: In this article, a model is specified in which both the exchange rate itself and the residuals exhibit simultaneity, while the residual depends on other residuals, and the model is then simulated using embedding noise from a t-distribution.
References
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Book ChapterDOI
Chapter 23 Heterogeneous Agent Models in Economics and Finance
TL;DR: A survey of dynamic heterogeneous agent models (HAMs) in economics and finance can be found in this paper, where the authors focus on simple models that are tractable by analytic methods in combination with computational tools.
MonographDOI
Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems
TL;DR: In this paper, the nonlinear cobweb model with heterogeneous expectations was proposed and empirically validated in a laboratory experiment, and an asset pricing model was proposed with heterogenous beliefs.
Book
Time-Series Analysis and Cyclostratigraphy: Examining Stratigraphic Records of Environmental Cycles
TL;DR: This work Constructing time series in cyclostratigraphy with a focus on environmental cycles recorded stratigraphically and additional methods of time-series analysis.
CapitalLabor Substitution and Competitive Nonlinear Endogenous Business Cycles
TL;DR: In this article, simple geometrical methods were developed to study local indeterminacy, bifurcations and stochastic (sunspot) equilibria near a steady state, in nonlinear two dimensional economic models.
Journal ArticleDOI
Testing for non-linear structure in an artificial financial market
TL;DR: In this paper, the authors present a stochastic simulation model of a prototype financial market, which is populated by both noise traders and fundamentalist speculators, and explore the behavior of the model when testing for the presence of chaos or non-linearity in the simulated data.