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Using a bootstrap method to choose the sample fraction in tail index estimation

Daníelsson, Jón; Haan, Laurens de; Peng, L.; Vries, … - 1997

We use a subsample bootstrap method to get a consistent estimate of the asymptotically optimal choice of the …

Persistent link: https://www.econbiz.de/10010232860

On the ambiguous consequences of omitting variables

De Luca, Giuseppe; Magnus, Jan R.; Peracchi, Franco - 2015

-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than … in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias …

Persistent link: https://www.econbiz.de/10010532602

A bootstrap-based method to achieve optimality in estimating the extreme-value index

Haan, Laurens de; Peng, Liang; Pereira, T. Themido - 1997

Estimators of the extreme-value index are based on a set of upper order statistics. We present an adaptivemethod to choose the number of order statistics involved in an optimal way, balancing variance and biascomponents. Recently this has been achieved for the similar but somewhat less involved...

Persistent link: https://www.econbiz.de/10010342310

Optimal confidence intervals for the tail index and high quantiles

Pinto, Ana P. Ferreira; Vries, Casper G. de - 2004

, but then a bias term with unknown sign has to be estimated. We provide an estimator for this sign and the full programme …. Simulation results are also presented.It is weIl known that extreme value parameter estimators which balance the asymptotic bias …

Persistent link: https://www.econbiz.de/10011338009

Bias correction in the dynamic panel data model with a nonscalar disturbance covariance matrix

Bun, Maurice J. G. - 2001

Approximation formulae are developed for the bias of ordinary andgeneralized Least Squares Dummy Variable (LSDV … proper modelling of thedisturbance covariance structure is indispensable. The biasapproximations are used to construct bias … plausible long-run effects are obtained by the biascorrected estimators. Moreover, bias correction can be substantialunderlining …

Persistent link: https://www.econbiz.de/10011313930

Tail behavior of credit loss distributions for general latent factor models

Lucas, André; Klaassen, Pieter; Spreij, Peter; … - 2001

Using a limiting approach to portfolio credit risk, we obtain analyticexpressions for the tail behavior of the distribution of credit losses. We showthat in many cases of practical interest the distribution of these losses haspolynomial ('fat') rather than exponential ('thin') tails. Our...

Persistent link: https://www.econbiz.de/10011316891

Measuring biases in expectation formation

Peters, Florian; Kucinskas, Simas - 2018

We develop a general framework for measuring biases in expectation formation. The method is based on the insight that biases can be inferred from the response of forecast errors to past news. Empirically, biases are measured by flexibly estimating the impulse response function of forecast...

Persistent link: https://www.econbiz.de/10011869992

On distributions of ratios

Broda, Simon A.; Kan, Raymond - 2013

A large number of exact inferential procedures in statistics and econometrics involve the sampling distribution of ratios of random variables. If the denominator variable is positive, then tail probabilities of the ratio can be expressed as those of a suitably defined difference of random...

Persistent link: https://www.econbiz.de/10010227300

A hybrid joint moment ratio test for financial time series

Groenendijk, Patrick A.; Lucas, André; Vries, Casper G. de - 1998

We advocate the use of absolute moment ratio statistics in conjunctionwith standard variance ratio statistics in order to disentangle lineardependence, non-linear dependence, and leptokurtosis in financial timeseries. Both statistics are computed for multiple return horizonssimultaneously, and...

Persistent link: https://www.econbiz.de/10011299968

Kernel-smoothed conditional quantiles of correlated bivariate discrete data

Gooijer, Jan G. de; Yuan, Ao - 2011

results show excellent estimation accuracy in terms of bias, mean squared error, and confidence interval coverage. Typically …

Persistent link: https://www.econbiz.de/10011382707