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A Bayesian Approach to Inference on Probabilistic Surveys

Del Negro, Marco; Casarin, Roberto; Bassetti, Federico - 2022

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

Persistent link: https://www.econbiz.de/10014080529

Sampling Properties of the Bayesian Posterior Mean With an Application to WALS Estimation

De Luca, Giuseppe - 2020

Many statistical and econometric learning methods rely on Bayesian ideas, often applied or reinterpreted in a frequentist setting. Two leading examples are shrinkage estimators and model averaging estimators, such as weighted-average least squares (WALS). In many instances, the accuracy of these...

Persistent link: https://www.econbiz.de/10012839923

Priors, Posterior Odds and Lagrange Multiplier Statistics in Bayesian Analysis of Cointegration

Kleibergen, Frank R.; Paap, Richard - 1998

Using the standard linear model as a base, a unified theory of Bayesian Analysis of Cointegration Models is constructed. This is achieved by defining (natural conjugate priors in the linear model and using the implied priors for the cointegration model

Persistent link: https://www.econbiz.de/10014069432

Skewed logistic distribution for statistical temperature post-processing in mountainous areas

Gebetsberger, Manuel; Stauffer, Reto; Mayr, Georg. J.; … - 2018

Non-homogeneous post-processing is often used to improve the predictive performance of probabilistic ensemble forecasts. A common quantity to develop, test, and demonstrate new methods is the near-surface air temperature frequently assumed to follow a Gaussian response distribution. However,...

Persistent link: https://www.econbiz.de/10011847486

Posterior analysis of econometric models using Monte Carlo integration

Dijk, Herman K. van - 1984

Persistent link: https://www.econbiz.de/10000000631

State correlation and forecasting : a Bayesian approach using unobserved components models

Uzeda, Luis - 2018

Implications for signal extraction from specifying unobserved components (UC) models with correlated or orthogonal innovations have been well investigated. In contrast, the forecasting implications of specifying UC models with different state correlation structures are less well understood. This...

Persistent link: https://www.econbiz.de/10011809478

Decomposing portfolio value-at-risk : a general analysis

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

the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …

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

Exact Moment Simulation Using Random Orthogonal Matrices

Alexander, Carol; Ledermann, Walter; Ledermann, Dan - 2010

methodology is thus termed "ROM simulation''. We discuss certain classes of random orthogonal matrices and show how each class … produces samples with different characteristics. ROM simulation has applications to many problems that are resolved using … illustration, we apply ROM simulation to determine the value-at-risk of a stock portfolio …

Persistent link: https://www.econbiz.de/10014204404

Return and risk of pairs trading using a simulation-based Bayesian procedure for predicting stable ratios of stock prices

Gatarek, Lukasz; Hoogerheide, Lennart; Dijk, Herman K. van - 2014

implicit statistical arbitrage method. We use a simulation-based Bayesian procedure for predicting stable ratios, defined in a …

Persistent link: https://www.econbiz.de/10010259626

Testing the statistical significance of microsimulation results : often easier than you think ; a technical note

Goedemé, Tim; Van den Bosch, Karel; Salanauskaite, Lina; … - 2013

In the microsimulation literature, it is still uncommon to test the statistical significance of results. In this paper we argue that this situation is both undesirable and unnecessary. Provided the parameters used in the microsimulation are exogenous, as is often the case in static...

Persistent link: https://www.econbiz.de/10010201167