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Econometrics 2017, 5(4), 47; https://doi.org/10.3390/econometrics5040047

Bayesian Analysis of Bubbles in Asset Prices

1
and
2,*
1
Finance Department, ESSEC Business School, Paris-Singapore, Cergy-Pontoise 95021, CEDEX, France
2
School of Economics and Lee Kong Chian School of Business, Singapore Management University, 90 Stamford Road, Singapore 178903, Singapore
*
Author to whom correspondence should be addressed.
Academic Editors: Federico Bandi, Alex Maynard, Hyungsik Roger Moon and Benoit Perron
Received: 14 July 2017 / Revised: 11 September 2017 / Accepted: 11 September 2017 / Published: 23 October 2017
(This article belongs to the Special Issue Celebrated Econometricians: Peter Phillips)
View Full-Text   |   Download PDF [394 KB, uploaded 23 October 2017]   |  

Abstract

We develop a new model where the dynamic structure of the asset price, after the fundamental value is removed, is subject to two different regimes. One regime reflects the normal period where the asset price divided by the dividend is assumed to follow a mean-reverting process around a stochastic long run mean. The second regime reflects the bubble period with explosive behavior. Stochastic switches between two regimes and non-constant probabilities of exit from the bubble regime are both allowed. A Bayesian learning approach is employed to jointly estimate the latent states and the model parameters in real time. An important feature of our Bayesian method is that we are able to deal with parameter uncertainty and at the same time, to learn about the states and the parameters sequentially, allowing for real time model analysis. This feature is particularly useful for market surveillance. Analysis using simulated data reveals that our method has good power properties for detecting bubbles. Empirical analysis using price-dividend ratios of S&P500 highlights the advantages of our method. View Full-Text
Keywords: parameter learning; markov switching; MCMC; real time bubble detection parameter learning; markov switching; MCMC; real time bubble detection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Fulop, A.; Yu, J. Bayesian Analysis of Bubbles in Asset Prices. Econometrics 2017, 5, 47.

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