Asset health prediction is imperative to optimal asset management. Online and offline inspections can provide useful information for predicting asset health. The information from an asset health inspection can be divided into two types. (1) Direct indicators which directly determine failures...

This paper is concerned with the Bayesian estimation and comparison of flexible, high dimensional multivariate time series models with time varying correlations. The model proposed and considered here combines features of the classical factor model with that of the heavy tailed univariate...

Time series resulting from aggregation of several sub-series can be seasonally adjusted directly or indirectly. With model-based seasonal adjustment, the sub-series may also be considered as a multivariate system of series and the analysis may be done jointly. This approach has considerable...

Despite their success and widespread usage in industry and business, ES methods have received little attention from the statistical community. We investigate three types of statistical models that have been found to underpin ES methods. They are ARIMA models, state space models with multiple...

In this dissertation we propose a new model which captures observed features of asset prices. The model reproduces the skewness and fat tails of asset returns by introducing a discretized variance gamma process as the driving innovation process, in addition to a double gamma process to reflect...

Incluye bibliografía ; This article estimates a general credit risk model with both macroeconomic and latent credit factors for Spanish banks during the period 2004-2010. The proposed framework allows to estimate with bank level data both the standard credit risk model of Basel II and...

In dieser Arbeit setzen wir uns mit den Auswirkungen von Risikobeschränkungen auf das optimale Verhalten eines Investors auseinander, welcher versucht, den erwarteten Endnutzen zu einem festgelegten Zeitpunkt zu maximieren. Dazu kann er ein vorgegebenes Anfangsvermögen in einem Markt...