Testing for Regime Switching

Cho, Jin Seo; White, Halbert

doi:10.1111/j.1468-0262.2007.00809.x

Cited by 121 publications

(151 citation statements)

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“…9 Note that standard asymptotics may not apply here because certain parameters are not identi…ed under the null hypothesis (Andrews, 1993;Andrews and Ploberger, 1994). Similar problems arise for instance when one tests GARCH models (Andrews, 2001) or regime switching models (Cho and White, 2007). However, the di¤erence between our likelihoods is so large that the inference from standard asymptotics is unlikely to be overturned.…”

Section: Maximum Likelihood Estimation On Returns and Rvmentioning

confidence: 93%

The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation

Christoffersen¹,

Feunou²,

Jacobs³

et al. 2014

J. Financ. Quant. Anal.

108

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Many studies have documented that daily realized volatility estimates based on intraday returns provide volatility forecasts that are superior to forecasts constructed from daily returns only. We investigate whether these forecasting improvements translate into economic value added. To do so we develop a new class of affine discrete-time option valuation models that use daily returns as well as realized volatility. We derive convenient closed-form option valuation formulas and we assess the option valuation properties using S&P500 return and option data. We find that realized volatility reduces the pricing errors of the benchmark model significantly across moneyness, maturity and volatility levels. JEL classification: G13 Bank classification: Asset pricing; Econometric and statistical methods RésuméDe nombreuses études ont montré que les estimations de la volatilité réalisée quotidienne qui se fondent sur les rendements intrajournaliers permettent d'aboutir à des prévisions de la volatilité plus justes que les projections faites uniquement à partir des rendements quotidiens. Les auteurs cherchent à déterminer si une telle amélioration prévisionnelle se traduit par une plus-value économique. À cette fin, ils construisent une nouvelle classe de modèles affines en temps discret d'évaluation des options qui font appel aux rendements quotidiens et également à la volatilité réalisée. Ils déduisent des formules analytiques des prix d'options et comparent, à l'aide de données sur les rendements et options liés à l'indice S&P500, les propriétés des modèles à l'étude. Ils constatent que la volatilité réalisée réduit de manière significative les erreurs d'évaluation du modèle de référence pour tous les degrés de parité, échéances et niveaux de volatilité examinés.

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Section: Maximum Likelihood Estimation On Returns and Rvmentioning

confidence: 93%

The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation

Christoffersen¹,

Feunou²,

Jacobs³

et al. 2014

J. Financ. Quant. Anal.

108

View full text Add to dashboard Cite

show abstract

“…which were also considered in Cho and White (2007). Observe that the statistics in (11)- (14) can only be non-negative and are each likely to be larger in value under the alternative hypothesis.…”

Section: Mixture Modelmentioning

confidence: 99%

Identification-robust moment-based tests for Markov switching in autoregressive models

Dufour

Luger

2017

Econometric Reviews

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“…See, for example, Liu and Shao (2003), Dacunha-Castelle and Gassiat (1999), Azaïs, Gassiat, and Mercadier (2006), Chernoff and Lander (1995), Chen, Chen, and Kalbfleisch (2004) and others. Pointwise asymptotic distribution of LR statistic under a fixed null hypothesis for finite mixture models and closely related regime switching models have also been studied in econometrics; see, e.g., Cho and White (2007).…”

Section: Motivation Examples and Literaturementioning

confidence: 99%

Likelihood inference in some finite mixture models

Chen¹,

Ponomareva²,

Tamer³

2013

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Parametric mixture models are commonly used in applied work, especially empirical economics, where these models are often employed to learn for example about the proportions of various types in a given population. This paper examines the inference question on the proportions (mixing probability) in a simple mixture model in the presence of nuisance parameters when sample size is large. It is well known that likelihood inference in mixture models is complicated due to 1) lack of point identification, and 2) parameters (for example, mixing probabilities) whose true value may lie on the boundary of the parameter space. These issues cause the profiled likelihood ratio (PLR) statistic to admit asymptotic limits that differ discontinuously depending on how the true density of the data approaches the regions of singularities where there is lack of point identification. This lack of uniformity in the asymptotic distribution suggests that confidence intervals based on pointwise asymptotic approximations might lead to faulty inferences. This paper examines this problem in details in a finite mixture model and provides possible fixes based on the parametric bootstrap. We examine the performance of this parametric bootstrap in Monte Carlo experiments and apply it to data from Beauty Contest experiments. We also examine small sample inferences and projection methods. Terms of use: Documents in

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Testing for Regime Switching

Cited by 121 publications

References 50 publications

The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation

The Economic Value of Realized Volatility: Using High-Frequency Returns for Option Valuation

Identification-robust moment-based tests for Markov switching in autoregressive models

Likelihood inference in some finite mixture models

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