The Capital Asset Pricing Model (CAPM) has dominated finance theory for over thirty years; it suggests that the market beta alone is sufficient to explain stock returns. However evidence shows that the cross-section of stock returns cannot be described solely by the one-factor CAPM. Therefore,...

Bayesian model averaging attempts to combine parameter estimation and model uncertainty in one coherent framework. The choice of prior is then critical. Within an explicit framework of ignorance we define a ‘suitable' prior as one which leads to a continuous and suitable analog to the pretest...

Using well-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between frequentist and Bayesian estimation. No significant difference is found between the qualities of the forecasts of the whole density, whereas the Bayesian approach...

French Abstract: Modele factoriel gaussien modélisant les prix d'électricité en France. Modélisation, calibration et valorisation des options vanillas sur forward. Ce document traite aussi la dessaisonalisation des prix et le calcul des facteurs avec maximum de vraisemblance.La calibration...

In many macroeconomic applications, impulse responses and their (bootstrap) confidence intervals are constructed by estimating a VAR model in levels - thus ignoring uncertainty regarding the true (unknown) cointegration rank. While it is well known that using a wrong cointegration rank leads to...

Models continue to increase their already broad use across industry as well as their sophistication. Worldwide regulation oblige financial institutions to manage and address model risk with the same severity as any other type of risk, e.g. Federal Reserve (SR 11-7) (2011), which besides defines...

Many areas of the natural and social sciences involve complex systems that link together multiple sectors. Integrated assessment models (IAMs) are approaches that integrate knowledge from two or more domains into a single framework, and these are particularly important for climate change. One of...

Building on the Shanken (1992) estimator, we develop a new methodology for estimating and testing beta-pricing models when a large number of assets N is available but the number of time-series observations is small. We show empirically that our large N framework can change substantially common...

This paper describes the econometric models used by the Banco de España to monitor consumer price inflation and forecast its future trends. The strategy followed heavily relies on the results from a set of econometric models, supplemented by expert judgment. We consider three different types of...

When constructing unconditional point forecasts, both direct- and iterated-multistep (DMS and IMS) approaches are common. However, in the context of producing conditional forecasts, IMS approaches based on vector autoregressions (VAR) are far more common than simpler DMS models. This is despite...