@ARTICLE{26543120_26551189_2010, author = {D. Samoylov}, keywords = {, RTSI drivers, variance decomposition, cointegration, Russian financial crisisvector autoregression}, title = {Factors that Have Influenced the RTSI during the Financial Crisis of 2008–2009 and before it}, journal = {HSE Economic Journal }, year = {2010}, month = {1}, volume = {14}, number = {2}, pages = {244-267}, url = {https://ej.hse.ru/en/2010-14-2/26551189.html}, publisher = {}, abstract = {This article deals with the influence of different factors on the RTSI in the pe riod from March 2007 to August 2009. The period is further subdivided into three subperiods - pre-crisis, high oil prices and time of crisis ones. The stationarity testing, the Granger causality analysis, the analysis of cointegration, the impulse response func tions and the variance decomposition let us get the information on the degree of oil price im pact, the S&P-500 and FTSE-100 stock indices one and the «investors’ fear gauge» index VIX influence on the RTSI. The time series cointegration analysis demonstrates the pres ence of the cointegration relations. The results of the research can be applied in mak ing scenario forecasts based on the middle-run and long-run oil prices.}, annote = {This article deals with the influence of different factors on the RTSI in the pe riod from March 2007 to August 2009. The period is further subdivided into three subperiods - pre-crisis, high oil prices and time of crisis ones. The stationarity testing, the Granger causality analysis, the analysis of cointegration, the impulse response func tions and the variance decomposition let us get the information on the degree of oil price im pact, the S&P-500 and FTSE-100 stock indices one and the «investors’ fear gauge» index VIX influence on the RTSI. The time series cointegration analysis demonstrates the pres ence of the cointegration relations. The results of the research can be applied in mak ing scenario forecasts based on the middle-run and long-run oil prices.} }