We introduce a new approach for modelling risk dependence. The methods we describe are applicable to all risk types but are motivated by a need to robustly assess the dependence between operational and other risks such as market and credit.We show through a practical example how the technique...

Historical share prices of selected S&P 500 companies have been accurately approximated by linear functions of the difference between core CPI and subsets of the CPI in the United States. The pricing model describes the evolution of share price along a predetermined trajectory. The selected...

In an environment where economic structures break, variances change, distributions shift, conventional policies weaken and past events tend to reoccur, economic agents have to form expectations over different regimes. This makes the regime-switching dynamic stochastic general equilibrium...

This paper introduces a new modelling framework for energy spot prices based on Lévy semistationary processes. Lévy semistationary processes are special cases of the general class of ambit processes. We provide a detailed analysis of the probabilistic properties of such models and we show how...

This paper proposes a procedure to investigate the nature and persistence of the forces governing the yield curve and to use the extracted information for forecasting purposes. The latent factors of a model of the Nelson-Siegel type are directly linked to the maturity of the yields through the...

State-space models have been increasingly used to study macroeconomic and financial problems. A state-space representation consists of two equations, a measurement equation which links the observed variables to unobserved state variables and a transition equation describing the dynamics of the...

This paper develops a general framework to study how misinterpreting information impacts learning. We consider sequential social learning and passive individual learning settings in which individuals observe signals and the actions of predecessors. Individuals have incorrect, or misspecified...

This paper develops a general framework to study how misinterpreting information impacts learning. Our main result is a simple criterion to characterize long-run beliefs based on the underlying form of misspecification. We present this characterization in the context of social learning, then...

We establish convergence of beliefs and actions in a class of one-dimensional learning settings in which the agent's model is misspecified, she chooses actions endogenously, and the actions affect how she misinterprets information. Our stochastic-approximation-based methods rely on two crucial...

We model inter-temporal ambiguity as the scenario in which a Bayesian learner holds more than one prior distribution over a set of parameters and provide necessary and sufficient condition for ambiguity to fade away because of learning. Our condition applies to most learning environments: iid...