Nurlan Sailaubekov

Planning company’s activity is a complex process, in which foresight is of great importance. The paper presents a method to predict financial state of a company using available financial data. For the prediction of quantitative indicators of the company currently there are different ways to build predictive models, such as simple and multiple regressions, autoregressive model and others. In this paper, to predict financial indicators of the company we use econometric modeling techniques. Tools to check the time series for the seasonality and stationarity are used in constructing the models. To check the reliability of the analysis techniques applied backtesting. To apply the developed method we used the values of financial indicators of the Kazakh national oil producing company. However, the method can be used for any company despite its size, industry, and so on. Albeit the method proposed is universal one and enables to predict financial state at any company, it has certain shortcomings and should be used along with fun¬damental analysis tools. The method proposed in the paper illustrated adequate results with sufficient accuracy according to the backtesting results. Therefore, based on the results of forecasting the financial state indicators, one can conduct a financial analysis of the expected state in upcoming period and use the derived values for future planning.

The article aims to reveal the university rating by its faculty motivation, which has an impact on human resources development in higher education sector and raises the university competiveness level. To achieve the given goal, the researchers have developed a model for evaluating the university rating on faculty work motivation by assessing implementation of motivational factors in the university, their weight for determining its rating in comparison with the threshold value.
The article examines blocks of motivational factors, such as material-monetary, material- non-monetary and non-material. The authors believe that systemic and timely use of these blocks of motivational factors by the university may increase the lecturers’ professional skills level, quality of the educational program and the academic process itself and contribute to the growth of university competitiveness.
During the research, the lecturers were surveyed by using a structured questionnaire, and a model for assessing the university faculty motivation level has been developed based on the research outcomes. Comparative analysis of the obtained results and the threshold value have been made so that to come up with conclusions on the university
rating. The survey has revealed that the university under study has the B+– class rating, which demonstrates a fairly high result. There have been made recommendations to the given university on achieving the higher-class rating.