VALUE-AT-RISK IN RANKING CROP INSURANCE ALTERNATIVAES Abstract This study examines the use of conditional value-at-risk (CVaR) as a measure for evaluating risky alternatives. CVaR has been shown to have a number of advantages compared to the more traditionally applied value-at-risk in decision settings that involve choices among truncated revenue distributions. A conceptual presentation illustr...

abstract exchange rate volatility is one of the effective and ambiguous factors in agricultural products export. regarding the importance of agricultural trade, to avoid single-product economy, the main aim of this study is to investigate the impact of exchange rate volatility on the pistachio export of iran during 1338-1386. for this purpose, exchange rate volatility index was estimated using ...

in this paper the conditional location problem is discussed. conditional location problems have a wide range of applications in location science. a new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are compared to those of the previous studies. this algorithm produces much better results than the previous formulations.

Conditional distributions are widely used for practical inference, even when the condition has zero probability (such as setting a continuous variable to an observed value). This popularity contrasts with the scary pitfalls (such as Borel’s paradox) that beset rigorous treatments of conditioning. In general, conditional expectations may arise that do not correspond to any conditional distributi...

This paper presents a parsimonious approach to estimating conditional skewness and kurtosis, as well as conditional variance, in financial log-returns time series. Using a GARCH formulation of the skew t-distribution (Jones and Faddy, 2003), autoregressive relationships are developed for the conditional skewness and conditional kurtosis. A numerical example indicates that allowing for estimates...

We study a generalization of the treatment e¤ect model in which an observed discrete classi…er indicates in which one of a set of counterfactual processes a decision maker is observed. The other observed outcomes are delivered by the particular counterfactual process in which the decision maker is found. Models of the counterfactual processes can be incomplete in the sense that even with knowle...

We study a first-order primal-dual subgradient method to optimize risk-constrained risk-penalized optimization problems, where risk is modeled via the popular conditional value at (CVaR) measure. The algorithm processes independent and identically distributed samples from underlying uncertainty in an online fashion, produces $\eta/\sqrt{K}$-approximately feasible optimal point within $K$ iterat...

We present a new system S for handling uncertainty in a quantified modal logic (first-order modal logic). The system is based on both probability theory and proof theory. The system is derived from Chisholm’s epistemology. We concretize Chisholm’s system by grounding his undefined and primitive (i.e. foundational) concept of reasonableness in probability and proof theory. S can be useful in sys...