Autocorrelation in an unobservable global trend: Does it help to forecast market returns?
In this paper, we empirically test the dependence of the Russian stock market on the world stock market, world oil prices and Russian political and economic news during the period 2001–2010. We find that oil prices are not significant after 2006, and the Japan stock index is significant over the whole period, since it is the nearest market index in terms of closing time to the Russian stock index. We find that political news like the Yukos arrests or news on the Georgian war have a short-term impact, since there are many other shocks. These factors confirm the structural instability of the Russian financial market.
This paper examines the dynamic beta of Russian companies within the framework of the market model. The closing weekly prices of 29 Russian stocks, six Russian sector indices and the MICEX Index as a market index during the period from January 2009 to June 2015 are used to estimate time-varying beta using various econometric techniques. According to the results for the analyzed period, semiparametric regressions are confirmed to be the most effective model. As regards the forecast period, multivariate GARCH models surprisingly outperform all the other methods. An analysis of beta dynamics shows that most of time-varying betas are non-stationary.
In this paper we consider the behavior of Kalman Filter state estimates in the case of distribution with heavy tails .The simulated linear state space models with Gaussian measurement noises were used. Gaussian noises in state equation are replaced by components with alpha-stable distribution with different parameters alpha and beta. We consider the case when "all parameters are known" and two methods of parameters estimation are compared: the maximum likelihood estimator (MLE) and the expectation- maximization algorithm (EM). It was shown that in cases of large deviation from Gaussian distribution the total error of states estimation rises dramatically. We conjecture that it can be explained by underestimation of the state equation noises covariance matrix that can be taken into account through the EM parameters estimation and ignored in the case of ML estimation.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.