Showing posts with label Cagan model. Show all posts
Showing posts with label Cagan model. Show all posts

Monday, 13 January 2025

Study on Bubbles Solutions of the Cagan Model | Chapter 2 | Bubbles and Behavioral Finance

The purpose of this paper is to study bubbles solutions to the Cagan hyperinflation models under rational expectations. Both the price and exchange rate bubbles are considered. Specifications of the Cagan model under rational expectations will be briefly described, in which the price and exchange rate series are expressed in first-order linear difference equations. The particular and the homogenous solutions to the Cagan model can then be derived. The particular or fundamental solution characterizes a unique dynamic movement of an underlying fundamental process. Several representations of the fundamental solution will be explored. The homogenous or bubble solution is non-unique in a rational expectations framework. Some examples of bubble solution with different dynamic properties are specified. Also, examples of bursting bubble specifications will be illustrated. It is concluded that the problems of multiple solutions make indirect tests more attractive than direct tests for bubble detection. In addition, the general solution, which is just the sum of particular and homogenous solutions, will be discussed. Hence, the bubble paths are characterized as any deviations of the general solution from the fundamental solution when the model is specified correctly.

 

Author(s)details:-

 

Kai-Yin Woo (Associate Professor)
Department of Economics and Finance, Hong Kong Shue Yan University, Hong Kong.

 

Please See the book here :- https://doi.org/10.9734/bpi/mono/978-81-973195-8-7/CH2 

Markov-Switching Cointegration Test for Bubbles during the Interwar European Hyperinflations | Chapter 3 | Bubbles and Behavioral Finance

 

The purpose of this paper is to test for the presence of price and exchange rate bubbles in Cagan's model using data from the interwar European hyperinflations of Germany, Hungary, and Poland. Markov-switching cointegration test would be adopted for the empirical analysis. Then, the regime-shifting behaviour of time series variables is assumed to depend on unobservable states generated by a first-order Markov chain. The probability law that governs the Markov-switching regimes is advantageous in that it is more flexible and allows the data to determine the specific form of nonlinearities that are consistent with the sample information. Inferences about the probabilities of the unobservable states at each point in time can also be made.

 

Author(s)details:-

 

Kai-Yin Woo (Associate Professor)
Department of Economics and Finance, Hong Kong Shue Yan University, Hong Kong.

 

Please See the book here :- https://doi.org/10.9734/bpi/mono/978-81-973195-8-7/CH3