Add to ORKGThe Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting problem -- model, parameters, latent states -- is able to be quantified explicitly, and factored into the forecast distribution via the process of integration or averaging. Allied with the elegance of the method, Bayesian forecasting is now underpinned by the burgeoning field of Bayesian computation, which enables Bayesian forecasts to be produced for virtually any problem, no matter how large, or complex. The current state of play in Bayesian forecasting in economics and finance is the subject of this review. The aim is to provide the reader with an overview of modern a...
A complete theory for evaluating forecasts has not been worked out to this date. Many studies on for...
Mean forecasts from professional surveys are often found to outperform most individual responses. Ho...
markdownabstract__Abstract__ Knowing the history of your topic of interest is important: It teach...
The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forec...
The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forec...
Contemporary Bayesian forecasting methods draw on foundations in subjective probability and preferen...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
This paper starts with a brief description of the introduction of the likelihood approach in econome...
This paper starts with a brief description of the introduction of the likelihood approach in econome...
This paper starts with a brief description of the introduction of the likelihood approach in econome...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
It is well known that a Bayesian's probability forecast for the future observations should form a pr...
After a brief description of the first Bayesian steps into econometrics in the 1960s and early 70s, ...
In the last 30 years, whilst there has been an explosion in our ability to make quantative predictio...
__Abstract__ This paper starts with a brief description of the introduction of the likelihood app...
A complete theory for evaluating forecasts has not been worked out to this date. Many studies on for...
Mean forecasts from professional surveys are often found to outperform most individual responses. Ho...
markdownabstract__Abstract__ Knowing the history of your topic of interest is important: It teach...
The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forec...
The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forec...
Contemporary Bayesian forecasting methods draw on foundations in subjective probability and preferen...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
This paper starts with a brief description of the introduction of the likelihood approach in econome...
This paper starts with a brief description of the introduction of the likelihood approach in econome...
This paper starts with a brief description of the introduction of the likelihood approach in econome...
Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach...
It is well known that a Bayesian's probability forecast for the future observations should form a pr...
After a brief description of the first Bayesian steps into econometrics in the 1960s and early 70s, ...
In the last 30 years, whilst there has been an explosion in our ability to make quantative predictio...
__Abstract__ This paper starts with a brief description of the introduction of the likelihood app...
A complete theory for evaluating forecasts has not been worked out to this date. Many studies on for...
Mean forecasts from professional surveys are often found to outperform most individual responses. Ho...
markdownabstract__Abstract__ Knowing the history of your topic of interest is important: It teach...