The article is dedicated to the method of aggregation of financial analysts’ recommendations in the framework of the evidence theory. This method considered on the example of Russian stock market and the quality of the obtained results was compared with the classical consensus forecast. It is shown that the combination rules, which are widely developed in the theory of evidence, allow aggregating the recommendations of analysts taking into account the historical reliability of information sources, the nature of the taken decisions (pessimism-optimism), the conflict between forecasts and recommendations, etc. In most cases it turned out that, obtained aggregated forecasts are more accurate than consensus forecast.
This paper presents the results of volatility forecasting for indices of the Russian stock market using existing and developed by the authors fuzzy asymmetric GARCH-models. These models consider various switching functions which are taking into account the positive and negative shocks and are built using the tools of fuzzy numbers. Furthermore, in some models there are used switching functions that consider expert macroeconomic information. It was shown that fuzzy asymmetric GARCH-models provide a more accurate prediction of volatility than similar crisp models.
In the problem of aggregation of rankings or preferences of several agents, there is a well-known result that reasonable social ranking is not strategy-proof. In other words, there are some situations when at least one agent can submit insincere ranking and change the final result in a way beneficial to him. We call this situation manipulable and using computer modelling we study 10 majority relation-based collective decision rules and compare them by their degree of manipulability, i.e. by the share of the situation in which manipulation is possible. We found that there is no rule that is best for all possible cases but some rules like Fishburn rule, Minimal undominated set and Uncovered set II are among the least manipulable ones.
We consider explicit two-level three-point in space finite-difference schemes for solving 1D barotropic gas dynamics equations. The schemes are based on special quasi-gasdynamic and quasi-hydrodynamic regularizations of the system. We linearize the schemes on a constant solution and derive the von Neumann type necessary condition and a CFL type criterion (necessary and sufficient condition) for weak conservativeness in $L^2$ for the corresponding initial-value problem on the whole line. The criterion is essentially narrower than the necessary condition and wider than a sufficient one obtained recently in a particular case; moreover, it corresponds most well to numerical results for the original gas dynamics system.
The necessity of comparison of histograms with the help of relationship of type “more or less” arises in many problems of decision-making. There are many approaches to solve this problem. But the histograms can be distorted. Then, we have to find the conditions on the distortions under which the comparison of the two histograms does not change. The solution of this problem is researched in the paper with respect to three popular probabilistic methods of comparison.
We use data on economic, management and political science journals to produce quan- titative estimates of (in)consistency of the evaluations based on six popular bibliometric indicators (impact factor, 5-year impact factor, immediacy index, article influence score, SNIP and SJR). We advocate a new approach to the aggregation of journal rankings. Since the rank aggregation is a multicriteria decision problem, ranking methods from social choice theory may solve it. We apply either a direct ranking method based on the majority rule (the Copeland rule, the Markovian method) or a sorting procedure based on a tournament solution, such as the uncovered set and the minimal externally stable set. We demonstrate that the aggregate rankings reduce the number of contradictions and represent the set of the single-indicator-based rankings better than any of the six rankings themselves.
Modern co-authorship networks contain hidden patterns of researchers interaction and publishing activities. We aim to provide a system for selecting a collaborator for joint research or an expert on a given list of topics. We have improved a recommender system for finding possible collaborator with respect to research interests and predicting quality and quantity of the anticipated publications. Our system is based on a co-authorship network derived from the bibliographic database, as well as content information on research papers obtained from SJR Scimago, staff information and the other features from the open data of researchers profiles. We formulate the recommendation problem as a weighted link prediction within the co-authorship network and evaluate its prediction for strong and weak ties in collaborative communities.
We study stochastic voting models where the candidates are allowed to have any smooth, strictly increasing utility functions that translate vote shares into payoffs. We find that if a strict Nash equilibrium exists in a model with an infinite number of voters, then nearby equilibria should exist for similar large, but finite, electorates. If the votes are independent random events, then equilibria will not depend on the utility functions of the candidates. Our results have implications for existing models of redistributive politics and spatial competition, as the properties of pure-strategy equilibria in such games carry over to equilibria in games with arbitrary candidate preferences. On the other hand, candidate utility functions will matter if the individual voting decisions are correlated. In the presence of aggregate uncertainty, such as changing economic conditions or political scandals, the preferences of parties and candidates with respect to shares of votes will have an effect on political competition.
The Arctic region is one of the most sensitive and vulnerable to climate change. The dramatic melting of Arctic ice has several negative consequences for the whole ecosystem as well as for a way of life of native people but it also creates new opportunities for the region. First, it opens up potential for exploitation of large deposits of natural resources such oil and gas. Second, it shrinks Arctic shipping routes which offer significant economic savings for many countries. These benefits has already attracted many countries, both Arctic and non-Arctic, thus resulting in potential conflict of interests. In our paper we present a mathematical approach to the problem of conflict resolution in the Arctic. First, we propose an approach how the level of interest in each part of the region should be evaluated with respect to main resources - oil, gas, fish and maritime routes. Second, we present several models of areas allocation to resolve the problem of conflict resolution. As a result, we applied several scenarios of areas allocation, evaluated their efficiency based on the total satisfaction level and identified conflict zones in the Arctic.
In this paper we consider the NP-hard 1|rj|ΣTj scheduling problem, suggesting a polynomial algorithm to find its approximate solution with the guaranteed absolute error. The algorithm employs a metric introduced in the parameter space. In addition, we study the possible application of such an approach to other scheduling problems.
A new approach to network decomposition problems (and, hence, to classification problems, presented in network form) is suggested. Opposite to the conventional approach, consisting in construction of one, “the most correct” decomposition (classification), the suggested approach is focused on construction of a family of classifications. Basing on this family, two numerical indices are introduced and calculated. The suggested indices describe the complexity of the initial classification problem as whole. The expedience and applicability of the elaborated approach are illustrated by two well-known and important cases: political voting body and stock market. In both cases the presented results cannot be obtained by other known methods. It confirms the perspectives of the suggested approach.
The concept of anomalous clustering applies to finding individual clusters on a digital geography map supplied with a single feature such as brightness or temperature. An algorithm derived within the individual anomalous cluster framework extends the so-called region growing algorithms. Yet our approach differs in that the algorithm parameter values are not expert-driven but rather derived from the anomalous clustering model. This novel framework successfully applies to the issue of automatically delineating coastal upwelling from Sea Surface Temperature (SST) maps, a natural phenomenon seasonally occurring in coastal waters.
Using network approach, we propose a new method of identifying key food exporters based on the long-range (LRIC) and short-range interaction indices (SRIC). These indices allow to detect several groups of economies with direct as well as indirect influence on the routes of different levels in the food network.
The Basel Committee on Banking Supervision (BCBS) standards are generally accepted by 46 countries in the world (28 jurisdictions). However, these countries differ in terms of details of standards’ implementation, i.e. national discretions take place. In 2012 the Basel Committee launched Regulatory Compliance Assessment Program (RCAP) to assure that all member states operate according to rules at least not softer than the original ones. Standards’ unification across countries results in need for less developed countries to adopt standards faster and in a more stringent form. One may foresee financial instability exacerbation as an outcome of such policy.
That is why paper objective is to demonstrate that standards’ implementation (RCAP) score is an implicit product of country’s macroeconomic and financial system development. For example, higher share of foreign banks and higher unemployment are strongly associated with countries that have regulation significantly different from the Basel original ones (having low compliance scores finally). This is exactly why standards should be differentiated by countries. Key message of the paper is that to promote financial stability regulator should target natural heterogeneity of risk management and risk regulation instead of that appealing artificial homogeneity (of which RCAP is one the examples).
Trading processes is a vital part of human life and any unstable situation results in the change of living conditions of individuals. We study the power of each country in terms of produce trade. Trade relations between countries are represented as a network, where vertices are territories and edges are export flows. As flows of products between participants are heterogeneous we consider various groups of substitute goods (cereals, fish, vegetables). We detect key participants affecting food retail with the use of classical centrality measures. We also perform clustering procedure in order to find communities in networks.
The chapter reviews the argument that mechanism design theory can be enlisted to achieve the same outcome as the best state-contingent contract, even if some states cannot be described ex ante.
We develop a new model of multicriterial decision analysis with a hierarchical criteria structure. The suggested methodology is based on a rigorously defined specification of qualitative and quantitative im- portance of criteria of all levels of the hierarchy, and enables the comparison of decision alternatives for different types of criteria scale.
This paper is devoted to the study of estimation of internal conflict of evidence in the framework of belief functions theory. The decomposition approach, which was proposed early by the author, will be considered with this purpose. The establishment of some properties of this conflict measure is a main result of this paper. In particular, estimates of the upper bound of the internal conflict in the case of categorical evidence and bifocal bodies of evidence are obtained for decomposition with the help of Dempster’s rule and Dubois and Prade’s disjunctive rule.
In this study, we use a sample of 192 listed shipping companies and employ a logit model in order to investigate the determinants of the probability of default. We enhance our analysis by isolating not only the cases of company liquidations but also those cases where companies had to change their legal status due to warning liquidity signals. Our key findings are in line with prior research and moreover we depict a changing trend in the marginal effects of relevant variables, on the probability of default. We further show, through an empirical application, how the obtained results can be used in a managerial decision-making process and in a bank credit underwriting process in order to assess the creditworthiness of a shipping company.