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Estimating rational stock-market bubbles with sequential Monte Carlo methods

Benedikt Rotermann and Bernd Wilfling

No 4015, CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster

Abstract: In the context of the present-value stock-price model, we propose a new rational parametric bubble specification that is able to generate periodically recurring and stochastically deflating trajectories. Our bubble model is empirically more plausible than its predecessor variants and has neatly interpretable parameters. We transform our entire stock-price-bubble framework into a nonlinear state-space form and implement a fully-fledged estimation framework, based on sequential Monte Carlo methods. This particle-filtering approach, originally from the engineering literature, enables us (a) to obtain accurate parameter estimates, and (b) to reveal the (unobservable) trajectories of arbitrary rational bubble specifications. We fit our new bubble process to artificial and real-world data and demonstrate the use of parameter estimates to compare important characteristics of historical bubbles which emerged in different stock markets.

Keywords: Present-value model; rational bubble; nonlinear state-space model; particle-filter estimation; EM algorithm (search for similar items in EconPapers)
JEL-codes: C15 C32 C58 G10 G12 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2015-05
New Economics Papers: this item is included in nep-ecm, nep-fmk and nep-ore
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