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Synopsis
Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties, in a unified and coherent framework. This book contributes to this literature by collecting a set of carefully evaluated contributions that are grouped amongst two topics in financial economics. The first three papers refer to macro-finance issues for real economy, including the elasticity of factor substitution (ES) in the Cobb-Douglas production function, the effects of government public spending components, and quantitative easing, monetary policy and economics. The last three contributions focus on cryptocurrency and stock market predictability. All arguments are central ingredients in the current economic discussion and their importance has only been further emphasized by the COVID-19 crisis.
"synopsis" may belong to another edition of this title.
- PublisherMdpi AG
- Publication date2020
- ISBN 10 3039437852
- ISBN 13 9783039437856
- BindingHardcover
- LanguageEnglish
- Number of pages146
- EditorBernardi Mauro, Grassi Stefano, Ravazzolo Francesco
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