This article investigates the behavior of the Russian government bond yields and its sensitivity to a selected range of macroeconomic, monetary, international and event factors. The analysis concerns both individual and joint, short-term and long-term influence of factors under study, with emphasis to the most informative determinants of yields. In whole the results of the empirical study using monthly data from 2003 to 2009 indicate a major significant role of changes in monetary factors, notably the minimum repo rate and the interbank interest rate, as well as of foreign exchange rate risk factor. Joint influence of theoretical fundamentals, namely inflation and its expectations, exchange rate and money supply growth, explain less than a third of bond yields movements. On the other hand, no importance of GDP and domestic debt growth as well as of external risk factors, such as oil prices, foreign interest rates and changes in international reserves is found. Also the results provide evidence for the fact that most government bond yields respond to certain political and economic events and reflect crisis changes of the market.
An ensemble of classifiers has been built to solve the problem of video image recognition. The paper offers a way to estimate the a posteriori probability of an image belonging to a particular class in the case of an arbitrary distance and nearest neighbor method. The estimation is shown to be equivalent to the optimal naive Bayesian estimate given Kullback-Leibler divergence being used as proximity measure. The block diagram of a video image recognition system is presented. The system features automatic adaptation of the list of images of identical objects which is fed to the committee machine input. The system is tested in face recognition task using popular data bases (FERET, AT&T, Yale) and the results are discussed.