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The Effect of Model-Selection Uncertainty on Autoregressive Models Estimates

Azzam, Islam - 2011

Model-selection uncertainty corresponds to the uncertainty about the true lag order of the autoregressive process that should be picked. This paper shows that all model-selection criteria perform poorly in small samples. Model-selection uncertainty adds to the bias and variability in the...

Persistent link: https://www.econbiz.de/10014178863

Robust and Practical Estimation for Measures of Tail Risk

Homescu, Cristian - 2014

We describe characteristics of various risk measures (Value-at-Risk, Expected Shortfall, etc.) that are used to analyze … and quantify the tail risk exposure, and discuss their relative strengths and weaknesses. Emphasis is placed on presenting … and comparing methodologies to compute and backtest estimates for these risk measures, from a practical perspective. We …

Persistent link: https://www.econbiz.de/10013053188

Decomposing portfolio value-at-risk : a general analysis

Hallerbach, Winfried G. - 1999 - This rev.: May 10, 1999

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the … Garman [1996a, 1997a] under the assumption that returns are drawnfrom a multivariate normal distribution. For many portfolios … to cause seriousdistortions in VaR calculations, one has to resort to either alternative distribution specifications …

Persistent link: https://www.econbiz.de/10011301159

Assessment of Uncertainty in High Frequency Data : The Observed Asymptotic Variance

Mykland, Per A. - 2016

The availability of high frequency financial data has generated a series of estimators based on intra-day data, improving the quality of large areas of financial econometrics. However, estimating the standard error of these estimators is often challenging. The root of the problem is that...

Persistent link: https://www.econbiz.de/10013006101

Using Proxy Variables to Control for Unobservables When Estimating Productivity : A Sensitivity Analysis

Ornaghi, Carmine; Van Beveren, Ilke - 2012

The use of proxy variables to control for unobservables when estimating a production function has become increasingly popular in empirical works in recent years. The present paper aims to contribute to this literature in three important ways. First, we provide a structured review of the...

Persistent link: https://www.econbiz.de/10014174156

Scaled and Adjusted Restricted Tests in Multi Sample Analysis of Moment Structures

Satorra, Albert - 2001

moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the …

Persistent link: https://www.econbiz.de/10014179647

Semiparametric Robust Estimation of Truncated and Censored Regression Models

Cizek, Pavel - 2008

Many estimation methods of truncated and censored regression models such as the maximum likelihood and symmetrically censored least squares (SCLS) are sensitive to outliers and data contamination as we document. Therefore, we propose a semiparametric general trimmed estimator (GTE) of truncated...

Persistent link: https://www.econbiz.de/10014047660

Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models

Drost, Feike C.; Akker, Ramon van den; Werker, Bas J. M. - 2008

evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of … autoregression coefficients and a probability distribution on the nonnegative integers, called an immigration or innovation … distribution. Traditionally, parametric models are considered where the innovation distribution is assumed to belong to a …

Persistent link: https://www.econbiz.de/10014050438

Splines for Financial Volatility

Audrino, Francesco; Buhlmann, Peter - 2007

We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...

Persistent link: https://www.econbiz.de/10014051065

Application of the Scaling Functions to Nonparametric Regression

Manole, Daniel Sorin - 2007

For estimating regression function we can use many proceedings. In this paper, we have chosen to apply scaling functions to the estimation of regression functions. When one knows many bivariate date with the values of two variables, in the goal to express a correlation between the two variables...

Persistent link: https://www.econbiz.de/10014051848