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A Bayesian Approach to Inference on Probabilistic Surveys

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

with the noisy rational expectations hypothesis. We find that in contrast to theory, for horizons close to two years, there … relationship becomes one-to-one, as the theory would predict …

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

A Bayesian Theory of Games : An Analysis of Strategic Interactions with Statistical Decision Theoretic Foundation

Teng, Jimmy - 2012

set of games than current Nash Equilibrium based games theory, including games with inaccurate observations, games with … games analyzed by the current games theory, it generates far lesser equilibriums and normally generates only a unique … equilibrium. It also resolves inconsistencies in equilibrium results by different solution concepts in current games theory …

Persistent link: https://www.econbiz.de/10014172228

Modeling Intertemporal and Contemporal Dependence in Binary TSCS Data : A Bayesian Model with Ar(P) Errors and Non-Nested Clustering

Pang, Xun - 2009

I propose a Bayesian generalized linear multilevel model with pth-order autoregressive errors for modeling unbalanced binary time-series cross-sectional (TSCS) data by considering correlation in both the time and spatial dimensions. By controlling for heterogeneities in the two dimensions and...

Persistent link: https://www.econbiz.de/10013156766

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

Sparse Graphical Vector Autoregression : A Bayesian Approach

Ahelegbey, Daniel Felix - 2019

In high-dimensional vector autoregressive (VAR) models, it is natural to have large number of predictors relative to the number of observations, and a lack of efficiency in estimation and forecasting. In this context, model selection is a difficult issue and standard procedures may often be...

Persistent link: https://www.econbiz.de/10012904383

Bayesian Inference of General Linear Restrictions on the Cointegration Space

Villani, Mattias - 2007

The degree of empirical support of a priori plausible structures on the cointegration vectors has a central role in the analysis of cointegration. Villani (2000) and Strachan and van Dijk (2003) have recently proposed finite sample Bayesian procedures to calculate the posterior probability of...

Persistent link: https://www.econbiz.de/10012730252

Asymptotic properties of Bayesian inference in linear regression with a structural break

Shimizu, Kenichi - 2022

This paper studies large sample properties of a Bayesian approach to inference about slope parameters in linear regression models with a structural break. In contrast to the conventional approach to inference about the slope parameters that does not take into account the uncertainty of the...

Persistent link: https://www.econbiz.de/10013307969

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

In this paper we consider two cases of pairs trading strategies: a conditional statistical arbitrage method and an implicit statistical arbitrage method. We use a simulation-based Bayesian procedure for predicting stable ratios, defined in a cointegration model, of pairs of stock prices. We show...

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

Bayesian Methods

Bauwens, Luc - 2012

Persistent link: https://www.econbiz.de/10013108925

Fast, approximate MCMC for Bayesian analysis of large data sets : a design based approach

Kaeding, Matthias - 2016

We propose a fast approximate Metropolis-Hastings algorithm for large data sets embedded in a design based approach. Here, the loglikelihood ratios involved in the Metropolis-Hastings acceptance step are considered as data. The building block is one single subsample from the complete data set,...

Persistent link: https://www.econbiz.de/10011566817