In the context of globalization and liberalization of financial markets, the mutual relations between the national stock markets become more relevant. Herewith decisions depend, and they were made regarding to the global diversification of the investment portfolio. The research aims to study the nature (asymmetries and powers) of the mutual relationships of the Russian stock market with foreign stock markets. To achieve this goal, I have researched the parameters of the copula functions of the joint distribution of returns of indexes of the Russian and foreign stock markets and assessed the quality of approximation of functions of the joint distribution of the copula functions under study. To meet these challenges, I consider the model of mixed copulas (which is a function of making the transition from private distributions of random variables to their joint distribution). An estimation of the parameters using the mixed copulas is performed by the method of pseudo-maximum likelihood. The private functions of distribution of returns of stock markets are set empirically. The study confirmed the changeable nature of the relationship of the Russian stock market with foreign stock markets of developed and developing countries. From January 2000 to May 2008, the relationship of the Russian stock market with most of the foreign stock markets has seen a left-handed bias. The period from June 2008 to December 2010 is characterized by increased tightness of the relationship in both “tails” of the joint distribution of returns of stock markets. The third period (January 2011 to March 2014) was characterized by the predominance of right-handed asymmetry in the Russian stock market relationship with the majority of the foreign stock markets. Mixed copulas in most cases have shown a better approximation to the function of the joint distribution of returns pairs of stock markets compared to simple copulas. The results suggest that mixed copula functions are more efficient modeling of the relationship of the stock markets with regard to the simple copulas. Mixed copulas may be applied when assessing the risks of investing in foreign stock, as well as to determine the optimal hedge ratio while hedging currency risks.
This paper presents empirical evidence of the effect of behavioral factors on corporate decisions relative to capital structure. Using panel data on public Russian companies, the authors prove that optimism and overconfidence contribute to debt resources accumulation by distorting managers’ view concerning probability distribution and risks. In this connection, the extension of the list of traditional factors influencing the choice of financial resources by behavioral ones is reasonable.
The research is devoted to the informal employment. The informal employment is complicated and heterogeneous phenomenon that should be considered from all sides. In this paper the factors associated with individual characteristics of the employees and they jobs, which could determine the probability of choosing the informal employment sector, are examined. The empirical model is estimated on a representative sample for Russia (RLMS-HSE) for 2012 year using probit model. In the paper only the main job of the individual is considered.
Importance In the proposed article the diagnostics of the financial state of SMEs is considered Objectives Building and improving solvency diagnostic models and forecasting bankruptcy risk of the SMEs
Methods Using econometric tools a series of logit models are designed and evaluated. The factors (indicators) that are included in the estimated models, was selected consider the following information: frequency of mention of the authors of Russian and foreign methods of risk assessment of bankruptcy, the availability of data, the ability to qualitatively describe the main components of the company's financial condition, informativeness, and others, as well as a set of economic-statistical methods. There are, for example, the algorithms of factor analysis, stepwise selection methods, VIF-factor analysis, and others. Classification characteristics of the models tested in the "training set", taking into account the area under the ROC-curve analysis and error types I and II
Results Consideration industry classification SME objects (and the "sector-specific" structure of balance sheet), development and inclusion (in the models) the parameters that characterize the enterprise resource planning (including estimation of technological efficiency by stochastic frontier analysis), improve the quality of models. The constructed models have good classification properties and predictive power
Conclusions and Relevance Using the proposed models for the diagnosis of the SMEs allows to identify the "problem" enterprise and to diagnose the probability of their bankruptcy, it would be useful for business owner, for creditors of the company and its external counterparties, for the judicial in deciding about the opening of bankruptcy proceedings
This paper investigates the household consumption behavior in Russia. The model assumes that household consumption can be described by the Euler equation. Using panel data on household from 2002 to 2011, we obtained the estimates of the elasticity of intertemporal substitution, which are different for lenders or borrowers.
Theme. Neural network forecasting in the film business. Goal. The article is devoted to application of economic-mathematical modeling in the field of film industry, in particular – to predict revenue and profit from distribution of future films, the identification of factors influencing the commercial success of the film business. Methodology. The basis of economic-mathematical model is a neural network trained on known historical data about the rental of movies, including 20 of the input parameters describing the production costs of the film, its duration, the characteristics of the Director, actors, characteristics of the plot of the film, country-made, genre, etc. Results. RMS relative error of the model was 13.8%, the coefficient of determination of 0.86. Model capabilities are demonstrated in the films: "the Da Vinci Code", "Star wars." Computer experiments were performed by the method of "freezing": using neural networks was carried out computations for the virtual change of the input parameters of the model, for example – the budget of the film, while the other input parameters remained unchanged. It turned out that the virtual increase in the budget of the films has a different effect on the predicted box office films, as well as on the profit margin. In the first case, the virtual increase in the budget leads to a significant increase in projected box office and profit, whereas in the second case, cash collections from a certain point ceases to increase, and profit growth is slowing down and even observed her fall. Different effects on the success of the movie business and other settings of the films. On the basis of computer experiments offered a number of recommendations that could contribute to increased box office receipts of the investigated films. Conclusions. The value of this study is that the created economic-mathematical model can be used for optimization of costs and selection of parameters when planning new movies. It allows you to make forecasts of box office receipts and profits from the rental of newly created films, as well as to investigate the influence of various parameters on the commercial result of the film business.
Importance The global financial crisis disturbed the former trends of the global financial system, without leaving any opportunity for their recovery. The new system configuration is not evident yet, however some components of its post-crisis order are already identifiable. The article identifies and analyzes such components that allow outlining the financial system of the future. Objectives The research reveals the main post-crisis trends in the development of the global financial system, traces these trends in key structural components, i.e. markets, tools, infrastructure, regulatory practices, and determines areas for their further development. Methods The research is based on methods of comparative, empirical and statistical analyses. Results The crisis increased the uncertainty in each component of the global financial system due to internal and external causes, with new areas of activities, operations, and risks emerging. This engenders an array of challenges for financial regulators, which have to find solutions and tackle the loss of confidence. Conclusions and Relevance Having analyzed the key factors and components of the post-crisis development of the global financial system, we conclude on the existing global challenges, which shape not only the global financial system, but also the Russian one. The article may appear interesting for researchers who analyze and forecast the development of global financial markets, and issues of their regulation (mega-regulation).
Importance Economies of the former CIS countries demonstrate disparity in economic development. Thus, it is possible to secure investment in restructuring the national economy only if conditions are relatively better than in the countries vying for foreign capital. Objectives The research pursues building an economic and mathematical model reflecting how direct foreign investment influences economic growth in Russia, Ukraine, and Kazakhstan. Methods The research has been conducted using Stata 13.0. applications. Conclusions and Relevance Foreign direct investment influences economic growth through such factors as gross domestic product, interest rate, average pay, foreign exchange rate, consumer price index, political stability.