VI Международная школа-симпозиум Анализ, Моделирование, Управление, Развитие экономических систем.
In this paper we propose a method for predicting significant multivariate nonstationary time series, ie series, in which changes in the structure, variables, or model coefficients of the variables. Due to the time-dependent processes that give rise to economic indicators, most economic time series falls into the category under consideration. The need to predict rate of capital flight as the subject of investigation, the volume of Russian investment abroad of non-banking corporations, as its major component.
This scientific work is dedicated to applying of two-layer interval weighted graphs in non-stationary time series forecasting and evaluation of market risks. The first layer of the graph, formed with the primary system training, displays potential system fluctuations at the time of system training. Interval vertexes of the second layer of the graph (the superstructure of the first layer) which display the degree of time series modeling error are connected with the first layer by edges. The proposed model has been approved by the 90-day forecast of steel billets. The average forecast error amounts 2,6% (it’s less than the average forecast error of the autoregression models).
The current work is devoted to study of interrelations of the obtained time series by means of econometric and wavelet analysis. At the first stage of this study, econometric analysis was conducted, regression was constructed. In the regression influence of the number of nomads and the amount of resource on the number of plowmen was studied. The coefficient of determination (R2) of the constructed regression turned out to be 0.81, the Durbin-Watson statistics equals to 0.94, which indicates the presence of positive first-order autocorrelation of errors. The next stage is an analysis based on wavelet transforms, which helps to get rid of high-frequency "noise" and interference in considered time series. Within the framework of this paper, the Haar wavelet and the Daubechies 2 tap wavelet were considered (the remaining wavelets give similar results). After the time series had been cleared by the wavelet analysis, regression analysis was applied again. The coefficient of determination of new regressions depending on which wavelet was applied and the interference of what frequency were removed took values in the range from 0.86 to 0.93. The coefficient of determination of new regressions depends on which wavelet was applied and the interference of what frequency were removed. It takes values in the range from 0.86 to 0.93. However, the Durbin-Watson statistics decreased its values and began to take values in the range from 0.01 to 0.46, which still indicates the presence of positive first-order autocorrelation of errors. In the end, we learn that in this situation, the application of wavelet analysis significantly increases the explanatory power of regression, on the other hand, the problem of autocorrelation of errors can not be resolved in this way, in some sense it is only getting worse.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.