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Accurate Value-at-Risk Forecasting Based on the (good old) Normal-GARCH Model

Hartz, Christoph; Mittnik, Stefan; Paolella, Marc S. - Institut für Schweizerisches Bankwesen <Zürich> - 2006

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR …

Persistent link: https://www.econbiz.de/10005858360

Transmission of business cycle shocks between the US and the euro area

Fenz, Gerhard; Schneider, Martin - 2008

We analyze the transmission of structural shocks between the US and the euro area within a two-country VAR framework. For that purpose, we simultaneously identify cost-push, demand and monetary policy shocks for both countries using sign restrictions. Our results show that domestic shocks...

Persistent link: https://www.econbiz.de/10013370062

Testing for monotonicity in expected asset returns

Romano, Joseph P.; Wolf, Michael - 2013

Many postulated relations in finance imply that expected asset returns strictly increase in an underlying characteristic. To examine the validity of such a claim, one needs to take the entire range of the characteristic into account, as is done in the recent proposal of Patton and Timmermann...

Persistent link: https://www.econbiz.de/10010316931

Alterntive tests for monotonicity in expected asset returns

Romano, Joseph P.; Wolf, Michael - 2011

Many postulated relations in finance imply that expected asset returns should monotonically increase in a certain characteristic. To examine the validity of such a claim, one typically considers a finite number of return categories, ordered according to the underlying characteristic. A standard...

Persistent link: https://www.econbiz.de/10010316938

A simple two-step method for testing moment inequalities with an application to inference in partially identified models

Romano, Joseph P.; Shaikh, Azeem M.; Wolf, Michael - 2012

This paper considers the problem of testing a finite number of moment inequalities. We propose a two-step approach. In the first step, a confidence region for the moments is constructed. In the second step, this set is used to provide information about which moments are negative. A...

Persistent link: https://www.econbiz.de/10010316942

Some Recent Developments in Predictive Accuracy Testing With Nested Models and (Generic) Nonlinear Alternatives

Corradi, Valentina; Swanson, Norman R. - 2003

Forecasters and applied econometricians are often interested in comparing the predictive accuracy of nested competing models. A leading example of nestedness is when predictive ability is equated with ?out-of-sample Granger causality?. In particular, it is often of interest to assess whether...

Persistent link: https://www.econbiz.de/10010263216

A practical two-step method for testing moment inequalities

Romano, Joseph P.; Shaikh, Azeem M.; Wolf, Michael - 2014

Persistent link: https://www.econbiz.de/10011282464

Consistent pretesting for jumps

Corradi, Valentina; Silvapulle, Mervyn J.; Swanson, … - 2014

If the intensity parameter in a jump diffusion model is identically zero, then parameters characterizing the jump size density cannot be identified. In general, this lack of identification precludes consistent estimation of identified parameters. Hence, it should be standard practice to...

Persistent link: https://www.econbiz.de/10011396835

Poor (wo)man's bootstrap

Honoré, Bo E.; Hu, Luojia - 2015

The bootstrap is a convenient tool for calculating standard errors of the parameters of complicated econometric models …. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible …. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. The …

Persistent link: https://www.econbiz.de/10011460667

Simpler bootstrap estimation of the asymptotic variance of U-statistic based estimators

Honoré, Bo E.; Hu, Luojia - 2015

The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically …, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it … requires repeated re-calculation of the estimator. In Honoré and Hu (2015), we propose a computationally simpler bootstrap …

Persistent link: https://www.econbiz.de/10011460687