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How to implement the Bootstrap in Static or Stable Dynamic Regression Models

van Giersbergen, Noud P.A.; Kiviet, Jan F. - 2001

power problems, whereas the remaining two areadequate and in fact equivalent. The equivalence between the two valid …

Persistent link: https://www.econbiz.de/10010324912

Why Frequency Matters for Unit Root Testing

Boswijk, H. Peter; Klaassen, Franc - 2005

It is generally believed that for the power of unit root tests, only the time span and not the observation frequency … methods will yield power gains in the presence of fat tails and persistent volatility clustering, and the strength of these … features (and hence the power gains) increases with the observation frequency. This is illustrated using both Monte Carlo …

Persistent link: https://www.econbiz.de/10010325590

Spot Variance Path Estimation and its Application to High Frequency Jump Testing

Bos, Charles S.; Janus, Pawel; Koopman, Siem Jan - 2009

This paper considers spot variance path estimation from datasets of intraday high frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used...

Persistent link: https://www.econbiz.de/10010325674

Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails

Diks, Cees; Panchenko, Valentyn; van Dijk, Dick - 2008

We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. By construction, existing scoring rules based on weighted...

Persistent link: https://www.econbiz.de/10010326053

GARCH Models for Daily Stock Returns: Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts

Ardia, David; Hoogerheide, Lennart - 2013

We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the...

Persistent link: https://www.econbiz.de/10010326343

Information Theoretic Optimality of Observation Driven Time Series Models

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

We investigate the information theoretic optimality properties of the score function of the predictive likelihood as a device to update parameters in observation driven time-varying parameter models. The results provide a new theoretical justification for the class of generalized autoregressive...

Persistent link: https://www.econbiz.de/10010377213

Testing for Parameter Instability in Competing Modeling Frameworks

Calvori, Francesco; Creal, Drew; Koopman, Siem Jan; … - 2014

parameter dynamics. The new test has higher and more stable power against alternatives with frequent regime switches or with non …

Persistent link: https://www.econbiz.de/10010377214

A New Bootstrap Test for the Validity of a Set of Marginal Models for Multiple Dependent Time Series: An Application to Risk Analysis

Ardia, David; Gatarek, Lukasz; Hoogerheide, Lennart F. - 2014

method can have higher power than a test for a univariate time series, especially for short time series. Therefore our test …

Persistent link: https://www.econbiz.de/10010377229

Maximum Likelihood Estimation for Generalized Autoregressive Score Models

Blasques, Francisco; Koopman, Siem Jan; Lucas, Andre - 2014

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series models driven by the score function of the predictive likelihood. This class of nonlinear dynamic models includes both new and existing observation driven time series models....

Persistent link: https://www.econbiz.de/10010377233

Maximum Likelihood Estimation for Correctly Specified Generalized Autoregressive Score Models: Feedback Effects, Contraction Conditions and Asymptotic Properties

Blasques, Francisco; Koopman, Siem Jan; Lucas, and André - 2014

The strong consistency and asymptotic normality of the maximum likelihood estimator in observation-driven models usually requires the study of the model both as a filter for the time-varying parameter and as a data generating process (DGP) for observed data. The probabilistic properties of the...

Persistent link: https://www.econbiz.de/10010491303