this research applies and compares the market leverage lally method, ibbotson and sinquefield method and siegel method, to present alternative measures for market risk premium (mrp) estimation and test forecasting power of these methods in calculating expected rate of return. the higher level of leverage implies greater risk of investment in a specified stock, so higher return is expected by in...

We develop an approach for automatically learning the optimal feature transformation for a given classification problem. The approach is based on extending the principle of risk minimization (RM), commonly used for learning classifiers, to learning feature transformations that admit classifiers with minimum risk. This allows feature extraction and classification to proceed in a unified framewor...

We analyze the best achievable performance of Bayesian learning under generative models by defining and upper-bounding minimum excess risk (MER): gap between expected loss attainable from data that could be achieved if model realization were known. The definition MER provides a principled way to define different notions uncertainties in learning, including aleatoric uncertainty epistemic uncert...

In this paper, a new approach to risk minimizing vehicle routing and scheduling problem is presented. Forwarding agents or companies have two main concerns for the collection of high-risk commodities like cash or valuable commodities between the central depot and the customers: one; because of the high value of the commodities transported, the risk of ambush and robbery are very high. Two; the ...

the problem of utilizing undesirable (bad) outputs in dea models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. the kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. also, there are some specific features of non-radial data envelopment analysis (dea...