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Bayesian demographic modeling and forecasting : an application to U.S. mortality

Reichmuth, Wolfgang H. (contributor); … - 2008

We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U … jointly with the latent variables underlying mortality of all age classes. In contrast to previous models, a similar … forecasts for particular age classes. A structural analysis of the relationship between age-specific mortality and covariates is …

Persistent link: https://www.econbiz.de/10003770767

Modeling and forecasting age-specific mortality : a Bayesian approach

Reichmuth, Wolfgang H. (contributor); … - 2008

We present a new way to model age-specific demographic variables, using the example of age-specific mortality in the … their dynamics jointly with the latent variables underlying mortality of all age classes. In contrast to previous models, a … for particular age classes. A structural analysis of the relationship between age-specific mortality and covariates is …

Persistent link: https://www.econbiz.de/10003770768

Multi-population Mortality Projection : The Augmented Common Factor Model with Structural Breaks

Wang, Pengjie - 2020

Multi-population mortality forecasting has become an increasingly important area in actuarial science and demography …, as a means to avoid long-run divergence in mortality projection. This paper aims to establish a unified state …-space Bayesian framework to model, estimate and forecast mortality rates in a multi-population context. In this regard, we …

Persistent link: https://www.econbiz.de/10012832560

Forecasting with Many Predictors Using Message Passing Algorithms

Korobilis, Dimitris - 2017

Machine learning methods are becoming increasingly popular in economics, due to the increased availability of large datasets. In this paper I evaluate a recently proposed algorithm called Generalized Approximate Message Passing (GAMP), which has been popular in signal processing and compressive...

Persistent link: https://www.econbiz.de/10012955264

Deep Bayesian Estimation of the Rough Path-Dependent Volatility Model for Forecasting Purposes

Parent, Léo - 2023

The rough path-dependent volatility (RPDV) model (Parent 2022) effectively captures key empirical features that are characteristic of volatility dynamics, making it a suitable choice for volatility forecasting. However, its complex structure presents challenges when it comes to estimating the...

Persistent link: https://www.econbiz.de/10014354222

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

Dobrev, Dobrislav - 2011

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

Persistent link: https://www.econbiz.de/10013128339

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

A Non-Linear Forecast Combination Procedure for Binary Outcomes

Lahiri, Kajal - 2015

We develop a non-linear forecast combination rule based on copulas that incorporate the dynamic interaction between individual predictors. This approach is optimal in the sense that the resulting combined forecast produces the highest discriminatory power as measured by the receiver operating...

Persistent link: https://www.econbiz.de/10013028905

WALS Estimation and Forecasting in Factor-Based Dynamic Models with an Application to Armenia

Magnus, J.R. - 2011

Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known BMA and the recently developed WALS. Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using...

Persistent link: https://www.econbiz.de/10013125420

Large vector autoregressions with asymmetric priors

Carriero, Andrea; Clark, Todd E.; Marcellino, Massimiliano - 2015 - This draft: November 2015

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

Persistent link: https://www.econbiz.de/10011389735