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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

By combining two alternative formulations of a test statistic with two alternative resamplingschemes we obtain four different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and power problems, whereas the remaining two areadequate...

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

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

Specification Testing in Hawkes Models

Gresnigt, Francine; Kole, Erik; Franses, Philip Hans - 2015

We propose various specification tests for Hawkes models based on the Lagrange Multiplier (LM) principle. Hawkes models can be used to model the occurrence of extreme events in financial markets. Our specific testing focus is on extending a univariate model to a multivariate model, that is, we...

Persistent link: https://www.econbiz.de/10011403545

Spurious Regression, Cointegration, and Near Cointegration: A Unifying Approach

Haldrup, Niels; Jansson, Michael - 1999

This paper introduces a representation of an integrated vectortime series in which the coefficient of multiple correlation computed fromthe long-run covariance matrix of the innovation sequences is a primitiveparameter of the model. Based on this representation, a notion of nearcointegration is...

Persistent link: https://www.econbiz.de/10010324535

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 matters. In this paper we show that the observation frequency does matter when the high-frequency data display fat tails and volatility clustering, as is typically the case for...

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

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

Conditional score residuals and diagnostic analysis of serial dependence in time series models

Blasques, F.; Gorgi, P.; Koopman, Siem Jan - 2021

. These residuals offer reliable and powerful diagnostic tools for testing residual autocorrelation. Furthermore, they can be … employed in models of which it is not clear how to define residuals. The asymptotic properties of the empirical autocorrelation … testing residual autocorrelation, when compared to squared GARCH residuals. We finally show how a diagnostic analysis can be …

Persistent link: https://www.econbiz.de/10012797256

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

exploits any autocorrelation in the likelihood scores under the alternative. We compare the test's performance with that of …

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

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