Finitary probabilistic methods in econophysics
Econometrics Economics Physics Statistical physics e-böcker
Cambridge University Press
2010
EISBN 9780511777585
Individual and statistical descriptions.
Probability and events.
Finite random variables and stochastic processes.
The Pólya process.
Time evolution and finite Markov chains.
The Ehrenfest-Brillouin model.
Applications to stylized models in economics.
Finitary characterization of the Ewens sampling formula.
The Zipf-Simon-Yule process.
"Econophysics applies the methodology of physics to the study of economics. However, whilst physicists have good understanding of statistical physics, they may be unfamiliar with recent advances in statistical conjectures, including Bayesian and predictive methods. Equally, economists with knowledge of probabilities do not have a background in statistical physics and agent-based models. Proposing a unified view for a dynamic probabilistic approach, this book is useful for advanced undergraduate and graduate students as well as researchers in physics, economics and finance. The book takes a finitary approach to the subject; discussing the essentials of applied probability, and covering finite Markov chain theory and its applications to real systems. Each chapter ends with a summary, suggestions for further reading, and exercises with solutions at the end of the book"--
Probability and events.
Finite random variables and stochastic processes.
The Pólya process.
Time evolution and finite Markov chains.
The Ehrenfest-Brillouin model.
Applications to stylized models in economics.
Finitary characterization of the Ewens sampling formula.
The Zipf-Simon-Yule process.
"Econophysics applies the methodology of physics to the study of economics. However, whilst physicists have good understanding of statistical physics, they may be unfamiliar with recent advances in statistical conjectures, including Bayesian and predictive methods. Equally, economists with knowledge of probabilities do not have a background in statistical physics and agent-based models. Proposing a unified view for a dynamic probabilistic approach, this book is useful for advanced undergraduate and graduate students as well as researchers in physics, economics and finance. The book takes a finitary approach to the subject; discussing the essentials of applied probability, and covering finite Markov chain theory and its applications to real systems. Each chapter ends with a summary, suggestions for further reading, and exercises with solutions at the end of the book"--
