We propose a new type of ubiquitous decision support system that is powered by a General Bayesian Network (GBN). Because complicated decision support problems are plagued by complexities when interpreting causal relationships among decision variables, GBNs have shown excellent decision support competence because of their flexible structure, which allows them to extract appropriate and robust ca...

In this paper we formulate and test a number of hypotheses regarding insurer participation and volume decisions in derivatives markets. Several specific hypotheses are supported by our analysis. We find evidence consistent with the idea that insurers are motivated to use financial derivatives to hedge the costs of financial distress, interest rate, liquidity, and exchange rate risks. We also fi...

The concept of dependence among variables in a Bayesian belief network is well understood, but what does it mean in an influence diagram where some of those variables are decisions? There are three quite different answers to this question that take the familiar concepts for uncertain variables and extend them to decisions. First is responsiveness, whether the choice for a decision affects anoth...