Research Of Asymmetric Effect Of Exchange Rate On Stock Industry Indices In Russia

In this paper,the influence of currency changes on the stock market prices in the Russian Federation is studied in detail.For the reason that composite data might suffer from aggregation bias as composite data do not reflect how each of the different sectors in Russia is affected by changes in different macroeconomic variables,the composite index was disaggregate by considering the sectoral stock price indices for Russian Federation.Sectorial stock indices are price-weighted by market capitalization indices of the most liquid shares of Russian issuers whose activities are related to the relevant sector of the industry admitted to circulation on the Moscow Stock Exchange and included in the calculation base for the broad market index.Thus,the change in quotations of the sectorial stock index allows us to understand what is happening with the shares of companies of a particular industry at the moment.Analysis of the impact of the exchange rate on sectorial stock indices will identify the sectors most dependent on currency fluctuations,which in the future will allow predicting changes in the values??of indices and quotations of shares of companies in a certain industry,depending on changes in the exchange rate.Thus,the following stock industry indices were considered as explanatory variables in this paper: Russian Trade System composite index,Oil and Gas industry price index,Metal Mining industry index,Finance industry index,Chemistry industry index,Power Engineering industry index,Consumer Goods industry index,Telecommunication industry index,Transport industry index.The analysis assumes the use of monthly data,which is because the data of higher frequency on the macroeconomic variables included in the analyzed model cannot be found.The study period is determined from January 2009 to December of 2018.Based on the analysis of the literature,we can conclude that the exchange rate can have both positive and negative effects on industrial indices.Due to the fact that the stock market is affected by several macroeconomic factors at the same time,it is necessary to establish what factors can be included in the basic model.In order to establish a complete picture of the interaction of the ruble exchange rate on stock index prices,the model included additional macroeconomic variables,which,according to many authors,should have a direct impact on the formation of stock market prices.The factors included in the model were selected through a literature review and empiricalanalysis based on the OLS model.Following variable: United States Dollar Exchange Rate;World Price of Brent Crude Oil;Average Growth of Gross Domestic Product of the Russian Federation per Month;were used to build a complete model suitable for assessing the quantitative impact of exchange rates on the prices of industry indices.Oil prices influence the Russian stock market in two ways: via changing the market cost of oil shares representing a substantial part of the RTS index and via increasing or reducing the external imbalance and supply of money.GDP is one of the fundamental factors influencing the development of the stock market.The impact of GDP on the stock market depends on the business cycle.At the beginning of the cycle,after the recession,GDP has a positive impact on the stock exchange.In the rest of the business cycle,GDP growth is associated with an increase in the profits of enterprises and leads to an increase in the stock market.Too much growth is perceived with caution,because,as history shows,often precedes a recession.Before performing the OLS analysis,it is necessary to make sure that all the data are stationary at same level.Primary data analysis showed that some data are in long-term trend movement,so it is logical to assume that the data become stationary only in the first difference.In such cases applying the classical regression technique to the levels of variables leads to a spurious correlation,especially when the variables involved exhibit consistent trend either upward or downward.Therefore,the Augmented Dickiey-Fuller(ADF)test is employed to determine whether there is a unit root in economic variables used in the study.The test showed that some time series are stationary at I(0),and all the time series are stationary at I(1).For this reason the data series are transformed into rates of change by taking the log differences in each of the series in the form ?()to generate the unanticipated components.After calculatingthe results of the OLS model,it is necessary to verify the reliability of the calculations.Diagnostic tests were conducted to verify the accuracy of the specification of the model.To check the adequacy of the model,standard tests were used,specifically: test for autocorrelation,test for heteroscedasticity,residual normality test.This study adopted Breusch Godfrey Serial Correlation LM Test to test for the presence of serial correlation on the residuals.The null hypothesis of this test indicates the absence of serial correlation.Breusch-Pegan-Godfrey test was used to test for the presence of Heteroscedasticity.OLS estimators of the` regression coefficients are best linearunbiased estimators if the residuals follow the normal distribution with zero mean and constant variance.Jarque-Berra statistics was used to test for normality.The next part of the study analyzed the long-term relationship of the factors included in the model.On the basis of the studied literature,it can be concluded that under the condition that the data are at different levels of stationary researchers cannot use Johnson co-integration model.In this case,the presence of long-term relationships should be checked through the bounds testing approach.Thus,as a test for checking the presence of cointegration was chosen F-Bounds Test.For a more detailed analysis of the short-run and long-run dependence of industry indices on the exchange rate and other macroeconomic variables,the ARDL model was applied.The choice of ARDL approach in this study is based on,its flexibility that it can be appalied when the variables are purely I(0)or purely I(1)or combination of both different order of integration.Also can be applied in studies with small sample size.In the third part of the work NADRL model is used for investigating the effect of appreciation of currency and depreciation of currency separately.Then,using the Wald test,the coefficients of positive and negative deviations in the long and short term were compared,thanks to this,the presence or absence of asymmetry for all industry indices was established.This test is made with the purpose of selecting the correct model for the estimation of both long and short term effects.Finally the CUSUM and CUSUMQ tests were employed to check the stability of the estimated coefficients.In order to check for Autocorrelation among the residuals,the Lagrange Multiplier(LM)test was conducted.In order to check for model misspecification Ramsey's Regression Specification Error Test(RESET)was conducted.Thus,after obtaining the results of the linear and nonlinear model,the evaluation of the significance of the results will be carried out as follows: First is establishing the relationship between the variables in the short term by evaluating the Wald-F test.If the coefficients of the short-term model are significant,then the p-value of the coefficients of the long-term relations will be evaluated.Then the significance of t-statistics of ECT will be checked.Based on the results of these three tests,it will be possible to judge whether or not there is a relationship between the positive and negative changes in the dollar and the prices of the stock market indices in the short and long term.The results of the study show that the impact of the exchange rate is asymmetric in the short term for almost all indices,also,in the long-run,asymmetry is observed in six of the nine cases.According to the results of this study,it can be concluded that the appreciation of the dollar negatively affects both the short-term and long-term prospects.The asymmetric effect in most cases varies in magnitude,which means that investors are not willing to take the risks associated with a weak local currency.Also in this case,the reason for this effect can be the expectation of long-term inflation.Prolonged inflation is associated with falling oil prices,as a consequence of the rise in the cost of export of raw materials and also the unwillingness of Russian entrepreneurs to compensate for the losses associated with the growth of the dollar at the expense of the financial balance of firms.The implication of these results is indubitable,theoretical and practical.This work will serve as a theoretical basis for further research of the Russian market,because the paper fully describes the factors that affect the Russian stock market and industry indices.Also,this work will serve as a theoretical basis for political decision-making,since the stock market is undoubtedly one of the main components of any country.Also the practical implication of this work is very wide.First,this paper presents the results of empirical studies that will serve as a theoretical basis for decision-making related to governance.In the last decade,the Russian Federation has faced a rapid growth of the dollar and a large volatility of the ruble.The Russian economy faced a big problem associated with the weakening of the ruble after the global financial crisis in 2008 and us sanctions in 2014.In these circumstances,it is necessary to clearly understand how the exchange rate affects the economy.To this end,this work has been analyzed in detail the impact of the exchange rate on all industries of the country through the analysis of industry indices.Thus,this work fully reflects the relationship between the exchange rate and industry indices and serves as the basis for political decision-making.