When bubbles burst: econometric tests based on structural breaks

Breitung, Jörg; Kruse, Robinson

doi:10.1007/s00362-012-0497-3

Cited by 21 publications

(8 citation statements)

References 15 publications

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“…Other break testing procedures such as Chow tests, model selection, and CUSUM tests have also been applied for dating bubbles (see for example, for a detailed review in this regard Homm andBreitung, 2012, andKruse, 2013). Balcilar et al (2015), on the other hand relies on long-memory test with breaks to identify housing bubbles in the US over the annual period of 1831-2013.…”

Section: Literature Reviewmentioning

confidence: 99%

Periodically collapsing bubbles in the South African stock market

Balcılar

Gupta

Jooste

et al. 2016

Research in International Business and Finance

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Abstract:This paper studies the existence and timing of bubbles in South Africa's stock market. An empirical model of bubble formation is tested against three competing models of asset price returns that rule out the existence of bubbles. The model controls for nonlinearities inherent in asset price returns by allowing for the existence of multiple regimes. The bubble model fits the data better than the competing models and suggests that the formation and existence of periodically collapsing bubbles are a reality.

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Section: Literature Reviewmentioning

confidence: 99%

Periodically collapsing bubbles in the South African stock market

Balcılar

Gupta

Jooste

et al. 2016

Research in International Business and Finance

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“…Homm and Breitung (2012) evaluate various econometric testing methods, amongst which is the technique developed in Phillips et al (2011), and they rank order their empirical performance using Monte Carlo methods. Breitung and Kruse (2013) build on these results to propose monitoring procedures. In this paper I add a new and simple test for a bubble to the analyst's toolkit.…”

Section: Introductionmentioning

confidence: 98%

A simple test for a bubble based on growth and acceleration

Franses

2016

Computational Statistics & Data Analysis

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“…Such a break could be either the start of a bubble, i.e. a transition from a random walk to a mildly explosive regime (Phillips et al, 2011;Phillips et al, 2013a;Homm and Breitung, 2012) or vice versa its end (Breitung and Kruse, 2013;Breitung, 2014). Both methods rely on the type of indirect stationarity tests initiated by Diba and Grossman (1988) and Hamilton and Whiteman (1985).…”

Section: Introductionmentioning

confidence: 98%