Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/20354
Author(s): | Moreira, A. Martins, L. F. |
Date: | 2020 |
Title: | A new mechanism for anticipating price exuberance |
Volume: | 65 |
Pages: | 199 - 221 |
ISSN: | 1059-0560 |
DOI (Digital Object Identifier): | 10.1016/j.iref.2019.10.006 |
Keywords: | Speculative bubbles Asset pricing Non-stationarity Adaptive learning Dynamic models |
Abstract: | It is very important for investors, market regulators, and policy makers to possess a trustworthy ex-ante tool capable of anticipating price exuberance events. This paper proposes a new statistical mechanism to predict speculative bubbles by inferring a significant probability of exuberance at least one step ahead of a bubble peak period. Contrary to other approaches, we combine asset pricing modeling and non-stationarity statistical analysis and use both in the context of adaptive learning to build a dynamic model specification. Monte Carlo simulations show that the ex-ante prediction is improved enormously by adding the estimated abnormal returns into the model. In some cases our mechanism predicts 100% of the last bubbles of the sample up to five periods before the peak. Furthermore, the mechanism is able to successfully anticipate the technological bubble observed in the 1990’s by estimating a probability greater than 90%, one month before the bubble peak. Thus, this new mechanism provides an advantage for investors interested in performing a very profitable “bubble surfing” strategy and for market regulators whose responsibility is to maintain market efficiency. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Files in This Item:
File | Description | Size | Format | |
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1-s2.0-S1059056019303016-main.pdf | Versão Editora | 2,19 MB | Adobe PDF | View/Open |
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