Management of Regional Imbalances in the Russian Mortgage Market Using the Principal Components Method

The article is devoted to the topic of sustainable development of mortgage instruments in the context of pronounced imbalances in regional development. The analysis was carried out on the example of 85 regional markets of Russia, heterogeneous in terms of the degree of development of mortgage mechanisms in their own territories.

Design and Validation of a Scale of Attitudes Towards Academic Feedback (SAAF)

Feedback is a type of formative evaluation linked to student learning and academic achievement. However, it is not known how students perceive this process since there are no instruments to measure attitudes towards feedback. The objective of this work was to develop and validate an attitude scale towards academic feedback through an Exploratory Factor Analysis (EFA), using the principal components method and an internal consistency analysis using Cronbach's Alpha. The sample consisted of 274 students from 2015, 2016, and 2017 cohorts of pedagogy careers from five Chilean universities. The results showed the consolidation of the instrument and its final conformation in four components (Negative experience towards feedback, Effectiveness of feedback, Feedback as an opportunity, and Resistance towards feedback) with a total of 15 items, which allow measuring the students' attitude towards this written formative evaluation.

ОЦІНЮВАННЯ РИЗИКУ ВИКОРИСТАННЯ БАНКІВ З МЕТОЮ ЛЕГАЛІЗАЦІЇ КРИМІНАЛЬНИХ ДОХОДІВ НА ОСНОВІ ГРАВІТАЦІЙНОГО МОДЕЛЮВАННЯ

The article is stressed on a method for assessing the risk of using banks for money laundering based on gravity modeling. Stimulatory factors are reduced to a comparable form by applying relative normalization. The priority of factors is determined using the principal components method. It is determined an integration indicator of a quantitative assessment of a country's rating concerning the characteristics of determining the level of money laundering risk by using Minkowski's metrics. It is built an economic-mathematical model for estimating the risk of money laundering based on the equation of the law of gravitational gravity and gravitational force in social phenomena. It is proved the expediency of application of the developed methodology in the decision of actual questions connected with reduction of risks for the country from the side of money laundering which serves as a basis for perfection of economic policy standards of the state concerning the strengthening of national economic security.

Corporate Bankruptcy Prediction Using the Principal Components Method

A huge number of articles and papers devoted to the study of bankruptcy prediction problems. Solving the problem of predictive ability many difficulties arise from the processing of data ending with the choice of models and algorithms. Efficiency is formed on the basis of three key aspects, such as tools, data quality and algorithms, formed based on the correct formulation of the problem. This research raises the problem of predicting the probability of bankruptcy using the method of neural network modeling. The paper proposes an effective prediction algorithm, in comparison with conventional parametric methods and is able to correctly classify on average more than 94% of observations in the sample of Russian small, medium and large businesses. Also during the research, the issue of data processing was touched upon. By the principal components method of neural networks, factors affecting the bankruptcy and key turning points that could lead to destabilization of the company’s normal operations were discovered. Increasing the accuracy of the forecast can be achieved by using more sophisticated algorithms, which are hybrid models.

Clustering of objects with poorly formalizable features based on a neural network in the form of Kohonen layers

Analysis of profiles of minors in social networks shows that teenagers indicate in them information that increases the level of their social desirability. Such information often does not correspond to the real behavior of the teenager. For a full analysis of the level of deviance of a minor need tools covering the full range of indicators. In contrast to the usual approach to clustering objects based on their Association in groups by the criterion of the minimum distance in multidimensional space when clustering features it is advisable to take into account their proximity to the methods of obtaining information and methods of processing of this information by the inspector for minors. In the first phase of the study is the clustering of signs of deviation, the second the determination of the weighting factors of indicator of the degree of deviance within each group of signs, the third uses the method of cluster-hierarchical approach to forming integral indicator of assessment of deviant behavior of minors. The indicator has a considerable flexibility of the correlation between groups of symptoms and partial characteristics through the introduction of appropriate sets of weighting coefficients. The conclusion is made about the preference of methods based on clustering of objects in the two-dimensional space of targets or accounts of the principal components method, as well as the need for additional analysis of the graphical picture of the relative location of objects. From the comparison of different approaches: 1) clustering on the basis of the generalized indicator of quality and the sign of reverse deviance, 2) clustering on two accounts of the principal components method; 3) clustering on all signs of examination, the following conclusions can be drawn. All methods properly allocate the objects to clusters. However, when you save the main totals (highlighting the best and worst features), the results are slightly different. This is due to the different volume and forms of presentation of the source information. The program assigns numbers of active neurons (clusters) arbitrarily, so in order to arrange the cluster numbers by some feature (for example, the quality of objects), you need to use additional graphical information. From a practical point of view, the first two methods are preferred, based on clustering objects in two-dimensional space, the method of principal components and the analysis of the graphical picture of the mutual location of objects.