Nonparametric specification tests for conditional duration models

Fernandes, Marcelo; Grammig, Joachim

doi:10.1016/j.jeconom.2004.06.003

Cited by 85 publications

(71 citation statements)

References 65 publications

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“…When the null is rejected because of an incorrectly assumed density function, the t and J-statistics will be significant, but they will not display any specific dynamic patterns. Finally, when the rejection comes from violations of both dependence and the density function, it will be desirable to combine our omnibus tests with tests that are powerful against violations of the null in a single direction, e.g., Escanciano (2008), Fernandes and Grammig (2005), and Hong (1996).…”

Section: Proposition 1 Letpmentioning

confidence: 99%

“…There are other parametric and nonparametric tests, like those in Engle and Russell (1998), Fernandes and Grammig (2005), and Meitz and Terasvirta (2006), among others, that focus on a single hypothesis, either dynamic specification or density functional form. Thus, by focusing on a test with the same joint hypothesis we will be able to provide a fair comparison.…”

Section: Comparison Of the Autocontour Tests With Hong And Li's Testsmentioning

confidence: 99%

“…There are numerous parametric and nonparametric tests for density functional form, most of which assume iid observations as a starting point as in Andrews (1997), or independence as in Fernandes and Grammig (2005). On the other hand, there are several diagnostic checks that do not explicitly consider the density functional form.…”

Section: Introductionmentioning

confidence: 99%

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Autocontours: Dynamic Specification Testing

González‐Rivera

Senyuz

Yoldaş

2011

Journal of Business & Economic Statistics

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We propose a new battery of dynamic specification tests for the joint hypothesis of iid-ness and density function based on the fundamental properties of independent random variables with identical distributions. We introduce a device-the autocontour-whose shape is very sensitive to departures from the null in either direction, thus providing superior power. The tests are parametric with asymptotic t and chi-squared limiting distributions and standard convergence rates. They do not require a transformation of the original data or a Kolmogorov style assessment of goodness-of-fit, explicitly account for parameter uncertainty, and have superior finite sample properties. An application to autoregressive conditional duration (ACD) models for trade durations shows that the difficulty with the assumed densities lies on the probability assigned to very small durations. Supplemental materials for this article are available online.

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Section: Proposition 1 Letpmentioning

confidence: 99%

Section: Comparison Of the Autocontour Tests With Hong And Li's Testsmentioning

confidence: 99%

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Autocontours: Dynamic Specification Testing

González‐Rivera

Senyuz

Yoldaş

2011

Journal of Business & Economic Statistics

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“…Developing a novel formal test for H 0 of a hypergeometric pole situation is beyond the scope of this paper. Though, we conjecture that using the results in Fernandes and Grammig (2005) for specification testing in the simple density case, the corresponding asymptotic distribution of the centered test statistic nb 2 D(x) + α x could be derived. However, as calculations are quite involved and should be complemented with a valid bootstrap approximation scheme for finite samples, we leave this for future research and a paper on its own.…”

Section: Choice Of Estimators For Different Density Shapes Near Zeromentioning

confidence: 99%

Nonparametric kernel density estimation near the boundary

Malec

Schienle

2014

Computational Statistics & Data Analysis

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Standard fixed symmetric kernel type density estimators are known to encounter problems for positive random variables with a large probability mass close to zero. We show that in such settings, alternatives of asymmetric gamma kernel estimators are superior but also differ in asymptotic and finite sample performance conditional on the shape of the density near zero and the exact form of the chosen kernel. We therefore suggest a refined version of the gamma kernel with an additional tuning parameter according to the shape of the density close to the boundary. We also provide a data-driven method for the appropriate choice of the modified gamma kernel estimator. In an extensive simulation study we compare the performance of this refined estimator to standard gamma kernel estimates and standard boundary corrected and adjusted fixed kernels. We find that the finite sample performance of the proposed new estimator is superior in all settings. Two empirical applications based on high-frequency stock trading volumes and realized volatility forecasts demonstrate the usefulness of the proposed methodology in practice.

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“…Dufour and Engle (2000) and Bauwens, Giot, Grammig, and Veredas (2004) evaluate the model's goodness-of-fit based on the evaluation of density forecasts using the probability integral transform as proposed by Diebold, Gunther, and Tay (1998). A nonparametric test against distributional misspecification is proposed by Fernandes and Grammig (2005) based on the work of Aït-Sahalia (1996).…”

Section: Statistical Inferencementioning

confidence: 99%

Modelling Financial High Frequency Data using Point Processes

Bauwens

Hautsch

2006

SSRN Journal

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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. Terms of use: Documents in AbstractIn this paper, we give an overview of the state-of-the-art in the econometric literature on the modeling of so-called financial point processes. The latter are associated with the random arrival of specific financial trading events, such as transactions, quote updates, limit orders or price changes observable based on financial high-frequency data. After discussing fundamental statistical concepts of point process theory, we review durationbased and intensity-based models of financial point processes. Whereas duration-based approaches are mostly preferable for univariate time series, intensity-based models provide powerful frameworks to model multivariate point processes in continuous time. We illustrate the most important properties of the individual models and discuss major empirical applications.

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Nonparametric specification tests for conditional duration models

Cited by 85 publications

References 65 publications

Autocontours: Dynamic Specification Testing

Autocontours: Dynamic Specification Testing

Nonparametric kernel density estimation near the boundary

Modelling Financial High Frequency Data using Point Processes

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