Impact оf Political News: Evidence From Russia
The following research is dedicated to the analysis of political events’ impact on price dynamics of Russian stock market financial assets. In recent times, in line with the sharpening of internal and external political clashes, such events significantly affect the country’s financial system. However, this issue is insufficiently considered on Russian market. Constructed econometric GARCH models allowed unambiguously characterizing the impact of political events on return and volatility of financial assets. Moreover, the effects of leverage and clusterization were also assessed. The provided research discloses the impact of political events on the market as a whole as well as on separate industries. It was demonstrated that the obtained results are similar to the ones from other developing markets, however, the particularity of Russian stock market was also revealed. As the obtained results disclose the peculiarities of price formation on Russian market, they will be useful for domestic and foreign investors, operating on Russian stock market, other market participants and specialists in financial science. Analysis of a wider range of political events is a considerable advantage of the present research in comparison with the other papers that cover the Russian market. As a result, the market reaction to such events’ manifestation was studied more thoroughly.
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.
The paper presents an analysis of the stocks traded on MICEX from 2007 to 2011. In order to analyze the data, we construct a market graph model. The vertices of the graph represent stocks; the edges represent strong similarity between considered stocks returns. We suggest using the following way to calculate the similarity measure: we calculate the number of the periods when two considered stocks have the positive return simultaneously. Our results show that the market graph model with the suggested similarity measure can be used to describe the stock market dynamics in an effi- cient and concise manner.
The article is devoted to one of the most popular approaches to forecasting market prices - technical analysis. We investigate the effectiveness of methods of technical analysis on the most liquid stocks of the Russian stock market. Derived conclusions about the overall effectiveness of technical analysis and identifies financial assets for which the use of these methods can achieve the best performance of market making operations.
The aim of this article is to prove the evidence of cross sectional momentum effect in Russian stock market within the variety of momentum strategy design elements and disclosure of the momentum effect nature.
We use a Markov chains models for the analysis of Russian stock market. First problem studied in the paper is the multiperiod portfolio optimization. We show that known approaches applied for the Russian stock market produce the phenomena of non stability and propose a new methods in order to smooth it. The second problem addressed in the paper is a structural changes on the Russian stock market after the financial crisis of 2008.We propose a hidden Markov chains model to analyse a structural changes and apply it for the Russian stock market.
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.