Similar Search Results

Bayesian Nonparametric Calibration and Combination of Predictive Distributions

Bassetti, Federico - 2015

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work of Ranjan and Gneiting (2010) and...

Persistent link: https://www.econbiz.de/10013027970

Bayesian Nonparametric Calibration and Combination of Predictive Distributions

Bassetti, Federico - 2015

Persistent link: https://www.econbiz.de/10013023291

Machine learning for regularized survey forecast combination : partially-egalitarian LASSO and its derivatives

Diebold, Francis X.; Shin, Minchul - In: International journal of forecasting 35 (2019) 4, pp. 1679-1691

Persistent link: https://www.econbiz.de/10012305515

Recovering Statistical Theory in the Context of Model Calibrations

Madan, Dilip B. - 2014

Statistical theory has been relatively absent in the exercise of estimating parameters of an option pricing model from …

Persistent link: https://www.econbiz.de/10013064348

Simulation Optimization Through Regression or Kriging Metamodels

Kleijnen, Jack P. C. - 2017

This chapter surveys two methods for the optimization of real-world systems that are modelled through simulation. These methods use either linear regression metamodels, or Kriging (Gaussian processes). The metamodel type guides the design of the experiment; this design fixes the input...

Persistent link: https://www.econbiz.de/10012956205

Considerations on partially identified regression models

Cerquera, Daniel; Laisney, François; Ullrich, Hannes - 2012

Motivated by Manski and Tamer (2002) and especially their partial identification analysis of the regression model where one covariate is only interval-measured, we offer several contributions. Manski and Tamer (2002) propose two estimation approaches in this context, focussing on general...

Persistent link: https://www.econbiz.de/10009520675

Quantile Regression Under Misspecification, with an Application to the U.S. Wage Structure

Angrist, Joshua D.; Chernozhukov, Victor; … - 2004

Quantile regression (QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fit a linear model for conditional means. An attractive feature of OLS is that it gives the minimum mean square error linear approximation to the conditional expectation function even...

Persistent link: https://www.econbiz.de/10014071862

Construction of uncertainty sets for portfolio selection problems

Wiechers, Christof - 2011

While modern portfolio theory grounds on the trade-off between portfolio return and portfolio variance to determine the … optimal investment decision, postmodern portfolio theory uses downside risk measures instead of the variance. Prominent …. The connections of the solution to robust optimization and decision theory are illustrated. -- Portfolio Optimization …

Persistent link: https://www.econbiz.de/10008939076

Variable selection and functional form uncertainty in cross-country growth regressions

Salimans, Tim - 2011

suggested by new growth theory, while addressing the variable selection problem by means of Bayesian model averaging …. Controlling for variable selection uncertainty, we confirm the evidence in favor of new growth theory presented in several earlier …

Persistent link: https://www.econbiz.de/10011382708

Pricing Bermudan options using regression : optimal rates of convergence for lower estimates

Belomestny, Denis - 2009

The problem of pricing Bermudan options using Monte Carlo and a nonparametric regression is considered. We derive optimal nonasymptotic bounds for a lower biased estimate based on the suboptimal stopping rule constructed using some estimates of continuation values. These estimates may be of...

Persistent link: https://www.econbiz.de/10003828655