The Central Banks discuss bank recapitalization arrangements. Markup to capital is needed because the current Basel approach is insensitive to some risks. As the Basel Committee moves from comprehensive risk modelling towards a revised, simplified, standardised approach, where one-two triggers measure risk, banking regulators increase demand for a capital add-on to meet unaccounted risks. The paper suggests the add-on estimates for the joint effect of the concentration and PD-LGD correlation risks leaving other unaccounted ones out-of-scope. The previous studies estimated add-ons for each risk separately. We show their joint impact on capital can be higher up to 5.3 times than the sum of two taken apart. Then previous results do not provide sufficient capital for a bank. We obtain that Basel underestimates the joint risk in 1.9 times on average. We expect that our contribution will be useful at least but not last for specialised lending (e.g. real estate and project finance), where the joint effect of concentration and PD-LGD correlation risks is the most observable.
Изучаются явные двухслойные по времени и симметричные по пространству разностные схемы, построенные посредством аппроксимации 1D баротропных квазигазо/квазигидродинамических систем уравнений. Они линеаризуются на постоянном решении с ненулевой скоростью, и для них выводятся как необходимые, так и достаточные условия $L^2$-диссипативности решений задачи Коши в зависимости от числа Маха. Эти условия различаются между собой не более чем в 2 раза. Результаты существенно развивают известные для линеаризованной схемы Лакса-Вендроффа. Выполняются также численные эксперименты по анализу применимости найденных условий в нелинейной постановке для нескольких схем при различных числах Маха.
As a result of the climate change the situation in Arctic area leads to several important consequences. On the one hand, fossil fuels can be exploited much easier than before. On the other hand, their excavation leads to serious potential threats to fishing by changing natural habitats which in turn creates serious damage to the countries’ economies. Another set of problems arises due to the extension of navigable season for shipping routes. Thus, there are already discussions on how should resources be allocated among countries. In Aleskerov and Victorova (An analysis of potential conflict zones in the Arctic Region, HSE Publishing House, Moscow, 2015) a model was presented analyzing preferences of the countries interested in natural resources and revealing potential conflicts among them. We present several areas allocation models based on different preferences over resources among interested countries. As a result, we constructed several allocations where areas are assigned to countries with respect to the distance or the total interest, or according to the procedure which is counterpart of the Adjusted Winner procedure. We consider this work as an attempt to help decision-making authorities in their complex work on adjusting preferences and conducting negotiations in the Arctic zone. We would like to emphasize that these models can be easily extended to larger number of parameters, to the case when some areas for some reasons should be excluded from consideration, to the case with ‘weighted’ preferences with respect to some parameters. And we strongly believe that such models and evaluations based on them can be helpful for the process of corresponding decision making.
Nowadays, we have seen a growing number of networks where nodes are connected to each other through different types of relationships. This makes identification of their topological structure and key elements both important and problematic. In this paper we propose a novel model for influence assessment in such networks using social choice rules. We evaluate node-to-node influence for each layer of the network and consider the problem of influence estimation as a problem of social choice or multi-criteria decision-making. We present various solutions that allow to aggregate information about node-to-node influence into a single vector representing the ranking of nodes or the ranking of the strongest connections in a network. Our approach takes into account individual attributes of nodes, the possibility of their group influence as well as their indirect connections. The presented model is mostly designed networks where there is no clear dependency among the layers. To present our approach we analyze the global trade food network with respect to three main products in order to identify the most important players in the field of food security.