The New Basel Accord and the Nature of Risk: A Game Theoretic Perspective

Basel II changes risk management in banks strongly. Internal rating procedures would lead one to expect that banks are changing over to active risk control. But, if risk management is no longer a simple "game against nature", if all agents involved are active players then a shift from a non-strategic model setting (measuring event risk stochastically) to a more general strategic model setting (measuring behavioral risk adequately) comes true. Knowing that a game is any situation in which the players make strategic decisions – i.e., decisions that take into account each other's actions and responses – game theory is a useful set of tools for better understanding different risk settings. Embedded in a short history of the Basel Accord in this article we introduce some basic ideas of game theory in the context of rating procedures in accordance with Basel II. As well, some insight is given how game theory works. Here, the primary value of game theory stems from its focus on behavioral risk: risk when all agents are presumed rational, each attempting to anticipate likely actions and reactions by its rivals --New Basel Accord,event risk,behavioral risk,rating,simple game,Nash-equilibrium,game theory

Nutritional characterization of gluten free non-traditional pasta

When a food is formulated, its characterization is important from the chemical and biochemical point of view; even more whennon-traditional raw materials are used. Noodles were made with cassava starch and corn flour (4:1), milk, egg, salt and xanthangum. The chemical composition of the pasta was determined and the total and resistant starch content was quantified. Thehydrolysis rate of the starch was measured at different times, from which the hydrolysis index and, subsequently, the predictiveglycemic index was calculated. The chemical composition of the noodles showed its high content of total fibers. From thedigestibility tests, high values were obtained for proteins (93%), and average values for the starch (52%). The results of the starchhydrolysis kinetics showed a higher proportion of slowly digestible starch with a low glycemic index (46%). Analyzed noodles arewithin the dietary guidelines that suggest a diet with high total dietary fiber content and low glycemic index.Fil: Milde, Laura Beatríz. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Chigal, Paola Soledad. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Chiola Zayas, Maria Ofelia. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales; Argentin

Scaling law and critical exponent for alpha_0 at the 3D Anderson transition

We use high-precision, large system-size wave function data to analyse the scaling properties of the multifractal spectra around the disorder-induced three-dimensional Anderson transition in order to extract the critical exponents of the transition. Using a previously suggested scaling law, we find that the critical exponent is significantly larger than suggested by previous results. We speculate that this discrepancy is due to the use of an oversimplified scaling relation

A Strategic Approach to Financial Options

To explain the strategic dimension in pricing options, it will be helpful to go back to the heart of the idea behind the concept of an option: options open up the possibility to postpone current decisions to a future point of time. Because of this flexibility additional information and new experiences can be taken into consideration. There are advantages and benefits resulting from this flexibility. The value of the option with the probabilities of the states of nature occurring. These probabilities will turn out the strategic decision variables of a new player as explained in the paper. --Financial Option,Real Option,Option Premium Game

ADaPTION: Toolbox and Benchmark for Training Convolutional Neural Networks with Reduced Numerical Precision Weights and Activation

Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) are useful for many practical tasks in machine learning. Synaptic weights, as well as neuron activation functions within the deep network are typically stored with high-precision formats, e.g. 32 bit floating point. However, since storage capacity is limited and each memory access consumes power, both storage capacity and memory access are two crucial factors in these networks. Here we present a method and present the ADaPTION toolbox to extend the popular deep learning library Caffe to support training of deep CNNs with reduced numerical precision of weights and activations using fixed point notation. ADaPTION includes tools to measure the dynamic range of weights and activations. Using the ADaPTION tools, we quantized several CNNs including VGG16 down to 16-bit weights and activations with only 0.8% drop in Top-1 accuracy. The quantization, especially of the activations, leads to increase of up to 50% of sparsity especially in early and intermediate layers, which we exploit to skip multiplications with zero, thus performing faster and computationally cheaper inference.Comment: 10 pages, 5 figure

The Anderson model of localization: a challenge for modern eigenvalue methods

We present a comparative study of the application of modern eigenvalue algorithms to an eigenvalue problem arising in quantum physics, namely, the computation of a few interior eigenvalues and their associated eigenvectors for the large, sparse, real, symmetric, and indefinite matrices of the Anderson model of localization. We compare the Lanczos algorithm in the 1987 implementation of Cullum and Willoughby with the implicitly restarted Arnoldi method coupled with polynomial and several shift-and-invert convergence accelerators as well as with a sparse hybrid tridiagonalization method. We demonstrate that for our problem the Lanczos implementation is faster and more memory efficient than the other approaches. This seemingly innocuous problem presents a major challenge for all modern eigenvalue algorithms.Comment: 16 LaTeX pages with 3 figures include