34 résultats
pour « probability »
"This paper introduces and fully characterizes the novel class of quasi-logconvex measures of risk, to stand on equal footing with the rich class of quasi-convex measures of risk."
"The possibilities of a Keynesian-Knightian synthesis as a way forward are considered by comparing these signposts. It is argued that, although there is some common ground between Knight and Keynes, there are fundamental differences particularly associated with Keynes’s concept of weight of argument."
"... we study two optimisation settings for an insurance company, under the constraint that the terminal surplus at a deterministic and finite time T follows a normal distribution with a given mean and a given variance."
"... we find the difference in decision-makers’ probability assessments between operational and non-operational risk factors is greater when assessing a proximate rather than a remote target. We contribute to the accounting literature by demonstrating how spatial distance affects probability judgments."
"Experimental results over synthetic and real problems confirm the advantages of this inference approach in its ability to accurately recover the original noise and signal matrices, as well as the achieved performance improvement in comparison to other state of art MTGP approaches."
"Using regret bounds from Online Convex Optimization, we obtain rigorous guarantees on the asymptotic power of the tests for a wide range of alternative hypotheses. Our results allow for bounded and unbounded data distributions, assuming that a sub-ψ tail bound is satisfied."
"We ... present a simple sufficient condition for monotone comparative statics of changes in risk under risk aversion."
"We... apply two stochastic orders to some classic decision problems in economics and finance including a portfolio problem, two insurance problems, and four management decision problems and present a simple sufficient condition for monotone comparative statics of changes in risk under risk aversion."
"The growing sophistication of insurance pricing, particularly for property-casualty insurance and reinsurance risk, has created a proliferation of approaches used in practice. Even within firms, pricing methodologies can vary from line to line, ranging from simplistic expected loss ratio targets to sophisticated return on capital models and even more sophisticated probability transform methods."
" In order to quantify resilience uncertainty across the network resolutions (from macro-scale network statistics to individual node dynamics), we propose an arbitrary polynomial chaos (aPC) expansion method to identify the probability of a node in losing its resilience and how the different model parameters contribute to this risk on a single node."