In this paper we study Markov Decision Process (MDP) problems with the restriction that at decision epochs only a finite number of given Markovian decision rules may be applied. The elements of the finite set of allowed decision rules should be mixed to improve the performance. The set of...

We estimate a model of natural default probabilities conditional on credit ratings and macroeconomic drivers. The output is an issuer-specific expected default rate at variable horizons, which can be combined to form an expected default rate for a given portfolio of rated credits. This permits...

The authors apply a Hidden Markov Model to identify regimes of shifting inflation and then employ an attribution technique based on the Mahalanobis distance to identify the economic variables that determine the trajectory of inflation. Their analysis enables policymakers to focus on the most...

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

Interbank borrowing and lending may induce systemic risk into financial markets. A simple model of this is to assume that log-monetary reserves are coupled, and that banks can also borrow/lend from/to a central bank. When all banks optimize their cost of borrowing and lending, this leads to a...

In this paper, we investigate the impact of the accident reporting strategy of drivers, within a Bonus-Malus system. We exhibit the induced modification of the corresponding class level transition matrix and derive the optimal reporting strategy for rational drivers. The hunger for bonuses...