We present an accurate and efficient method for Bayesian forecasting of two financial risk measures, Value-at-Risk and Expected Shortfall, for a given volatility model. We obtain precise forecasts of the tail of the distribution of returns not only for the 10-days-ahead horizon required by the...

We investigate the impacts of in-vehicle activities of commuters in the autonomous car on aggregate travel patterns. We allow for an autonomous car to affect the utility difference between being at home and being in the vehicle differently than the utility difference between being at work and...

We analyse the importance of macroeconomic information, such as industrial production index and oil price, for forecasting daily electricity prices in two of the main European markets, Germany and Italy. We do that by means of mixed-frequency models, introducing a Bayesian approach to reverse...

We study different mixes of private and public supply of roads in a network with bottleneck congestion and heterogeneous users. In our setting, there are two parallel links for one origin and destination pair and two groups of travellers, where the group with higher value of time also has higher...

We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt the widely used blockmodel framework and allow the highdimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors. The...

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...

We introduce a dynamic network model with probabilistic link functions that depend on stochastically time-varying parameters. We adopt the widely used blockmodel framework and allow the high-dimensional vector of link probabilities to be a function of a low-dimensional set of dynamic factors....

Various contributions to the recent literature on congestion pricing have demonstrated that when services at a congestible facility are provided by operators with market power, the case in point often being a few airlines jointly using a congested airport, optimal congestion pricing rules...

This paper presents the R-package MitISEM (mixture of t by importance sampling weighted expectation maximization) which provides an automatic and flexible two-stage method to approximate a non-elliptical target density kernel -- typically a posterior density kernel -- using an adaptive mixture...

This article investigates competition in a market with an emerging technology using a discrete choice model to analyze demand and welfare. We focus on industry structure and investigate the impact of different market structures on demand for the new technology and on welfare. The car market...