Nexus between Crude Oil, Exchange Rate and Stock Market Returns: An Empirical Evidence from Indian Context

Crude oil is considered as a major resource of any developing country it may be either Oil importing or exporting countries. The present study examines the relationship between the Exchange rate, Crude oil and Stock market returns. The study analyse the monthly observations from April 1, 2003 to March 31, 2019 with the help of Co integration, Granger causality, Variance Decomposition. The overall findings of the study indicate a significant effect of Crude oil on USD/INR Exchange rate. Theoretically, an oil price shock may be transmitted as the collapse in Crude prices pushes down the domestic price of non-traded products and hence the real Exchange rate and returns from Stock Market.


INTRODUCTION
Crude Oil is seen as a significant resource for the economy. Changes in Oil prices influence all facets of the economy in political, economic and commercial terms, etc. In the last few years, oil has influenced the Indian economy in a number of ways, and the stock market is considered to be one of the main factors that have impacted the economy in recent years. Owing to the rise in crude oil prices, the exchange rate will have an impact and will lead to changes in the macro-economic conditions of the importing countries. Thus, the relationship between the exchange rate and Crude Oil makes it possible to understand the stock market of any country.
Theoretically, changes in Crude Oil price can affect stock market in two different ways. First, if there is an increase in production costs as Crude Oil price increases, the other factor remains the same which will adversely reduce the company's earnings. Second, if only selling price increases due to the increase in Crude Oil price which will result in lower demand for the product and again adversely affect the earnings. So in both scenarios the economy will face various long-term and short-term challenges. The entire scenario depends on one factor being Exchange rate. So the relationship between Crude Oil, Exchange rate and Stock Market will be defiantly arises. Figure 1 indicates the fluctuations occurred in Exchange rate (USD/INR), WTI Crude Oil and Nifty 50. We can clearly elaborate the changes caused due to change in Crude oil leads to change in Exchange rates and Nifty 50 index. That's make this study more important to investigate the relationship between the variables.
Oil price affects economies in various ways, including supply side shock, demand side shock, transfer of wealth from oil importing countries to exporting countries, oil price shocks, change in production structure and decrease in investment Expenditure (Abdalla and Abdelbaki, 2014).In the past literature it has been theoretically explained the interlinkages between Crude Oil This Journal is licensed under a Creative Commons Attribution 4.0 International License and Exchange rate. Which includes (Caprio and Clark, 1981), (Golub, 1983), (Krugman, 1980) Whereas they have attempted to explain that as the price of crude oil increases the value of the dollar decreases so that they share an inverse relationship. The exchange rate and share price shares reverse relationship because it will attract more Foreign Institutional Investors as the domestic currency depreciates, and the demand will rise which will lead to higher share prices and vice versa. Devaluation will help the country export more and import less while in appreciation it exports more and less. Devaluation for the exporting countries and appreciation for the importing countries is therefore always considered better.
It's an important study which will help to understand the dynamic relationship between Exchange rate, Crude Oil and Stock Market. Additionally, India is considered as a developing nation which will continue to grow and prosper in the global economy. Our study is divided into five sections. This includes literature review in second section to find out the gap. Third section deals with Research Methodology and design. Further; Fourth section elaborates the analysis and findings of the results and finally section five concludes the study.

LITERATURE REVIEW
The relationship between Crude Oil, Exchange rate, and Stock prices has always attracted the researcher and academicians from late 90's. (Pogue, 1921) Studied the price index of Oil stocks in USA and concluded that there is a relationship between Crude Oil prices and Stock Market. Whereas (Bjornland, 2008;Constantinos et al., 2010;Constantinos et al., 2010;Ono, 2011) explained the impact on the Stock Market of Oil price shocks. They claimed that it would lead to changes in Macroeconomic variables as Crude Oil fluctuates and contributes to changes in returns of the stock market.
Similarly, (Salma, 2015;Mohamed, 2011;Fatima and Bashir, 2014;Jennings, 2012;Nath and Samanta, 2003;Sahu et al., 2014), The relationship between Crude Oil and Exchange rate is also the major concern among the researchers in twentieth century. There are many articles which have studied the relationship between them and found that there is positive as well as negative relationship among the variables. This studies includes (Kaushik et al., 2014;Adam et al., 2018;Arfaoui and Rejeb, 2017;Sahu et al., 2014;Gocekli, 2015;Beckmann et al., 2017;Qiang et al., 2019;Fratzscher et al., 2014;Hidhayathulla and Mahammad, 2014;Pavlova, 2011;Siddique, 2014;Zhang, 2013). All the study concludes that there is a relationship between the Crude oil and Exchange rate.
Whereas many studies has focused on all the three aspects including Crude Oil, Exchange rate (USD/INR) and Stock Market returns which includes (Rastogi, 2016;Sathyanarayana et al., 2017;Singh and Kapil, 2016;Basher et al., 2010;Najaf and Nazaf, 2016;Poornima and Ganeshwari 2013;Zakaria and Shamsuddin, 2012), Concludes that the exchange rate, Crude Oil and stock-market returns are related.
The present study tries to see in the Indian Context the similar relationship between the variable. The study attempted to examine the dynamic interactions between Crude Oil Prices, USD/INR exchange rates and Nifty Index in Indian economy. Understanding the integration among these variables is of utmost importance as India is heavily dependent on crude oil imports. In 2018 India Source: Authors Computation ranked third in terms of oil imports dollar value worth of $114.5 billion (9.7%) crude oil. A very small portion of the prior literature has been focused on understanding the simultaneity of oil prices, exchange rate, and stock market returns, especially for India alone. It is very crucial to consider the simultaneity of these factors so that investors, portfolio managers and policy makers can make better choices. This paper is a novel attempt to explore the dynamics between WTI crude oil prices, USD / INR exchange rates, and Nifty Index in Indian economy.

MATERIAL AND METHODS
The research aims to analyze the complex relationship between Nifty

Unit Root Test
Before proceeding with any econometric tool, it is crucial to determine the Stationarity of the Variables. In time series we always face a problem of non-stationarity series. When the observations are correlated with its own lags and mean and variance are not constant over the period of time then the variable under study is non stationary. Whereas to transform the series from non-stationary into stationary the difference stationary process is used. The regression equation of the same is as follows:

Granger Causality Test
The Granger Causality test is used to study the causal relationship between variables empirically. It helps to determine whether one series is useful in estimating and forecasting the other series. In the bivariate framework if Y 1 causes Y 2 means the forecast for Y 2 will improve when the lag of Y 1 is taken into consideration.

Johansen Co-integration Test
For investigating the long term relationship between Crude Oil, Stock market returns and Exchange rate. Johansen's co-integration test has been used. In this test we study the co-integrating properties of independent variables with dependent. If the stationary variables having a linear combination and integrated at the same order then these variables are called Co-integrated.

Variance Decomposition or Forecast Error Variance Decomposition (FEVD)
The variance decomposition or Forecast Error Variance Decomposition (FEVD) is used in econometric and multivariate time series analysis. It indicates that the information of each variable contributes to the other variable in auto regression. Determines how much exogenous shocks to the other variables can explain the variances in forecast error of each variable.

ANALYSIS AND DISCUSSION
All variables are non-stationary at the level where the p-value is more than 0.05%. As a result, we conduct the Unit Root Test in the first difference. All the series are stationary at a 1% level of significance at the first difference (Table 1). Since all variables are integrated in the same order we could proceed with the Co-integration to explore the long-term relationship between the Nifty Index, the WTI Crude Oil Prices and the USD/INR Exchange rate.
The results of Granger Causality for Nifty Index, the USD/INR Exchange rate, and WTI Crude oil prices are shown in Table 2.
There is a bi-directional causality among the USD/INR Exchange rate and the Nifty Index, since the p-value is less than 5 per cent. It could be inferred that in the short run, stock market is affected by the USD/INR Exchange rate and vice versa. We could also observe a Bi-directional causal link among Nifty Index and WTI Crude oil prices. However, there exists a unidirectional causality flowing from Crude oil prices to Exchange rates.    Table 3 displays Co-integration test estimates. The test was performed by taking appropriate lag interval as 1 to 2, chosen according to the optimum lag length criterion. The outcome of Co-integration test indicates the absence of cointegrating vectors at 5% significance level. Therefore, the null hypothesis of no Co-integration cannot be rejected at 5% significance level. Thus, no long-term co-integrating relationship exists between these variables. Therefore, in an unrestricted framework, we applied the VAR model to forecast the joint dynamics and causative relationships between the Nifty Index, the USD/INR Exchange rate, and Crude oil prices (Table 4).
In Equation 1, Lag (1) and Lag (2) coefficient of Nifty Index are C (1) and C (2) for which the probability values are 0.000 and 0.007, respectively. Since the associated p-values are <0.05%, it is possible to reject the null hypothesis that Nifty lag (1) and lag (2) are not significant to influence Nifty. Therefore it could be inferred that past values of Nifty Index influence Nifty's monthly closing rates.
Further, in equation two, lag (1) lag (2) coefficient of the Nifty Index is significant. This implies that the Nifty Index has a significant impact on the USD/Rupee Exchange rate. Coefficients associated with lag (1) and lag (2) of USD/INR Exchange rate are significant. This explains that USD/INR Exchange rate is affected by its own past values.
(Lag 1 and Lag 2) coefficient of Nifty Index and (Lag 1 and Lag 2) coefficients of WTI Crude Oil prices are significant in Equation 3. Therefore it states that the Nifty Index and past WTI Crude oil values are useful to understand the WTI Crude oil prices.

CONCLUSION
The study attempted to examine the dynamic interactions between Crude Oil Prices, USD/INR exchange rates and Nifty Index in India. The findings of the Co-integration test indicate that there is no long-term relationship between the variables. The lack of long-term relationships between these variables is consistent with existing literature (Kumar, 2014;Nath and Samanta, 2003;Basher et al., 2010;Adebiyi et al., 2010;Agrawal, 2010;Dhaoui and Khraief, 2014;Huang et al., 1996;Hussin et al., 2012;Imarhiagbe, 2010;Olufisayo, 2014.
The output of the USD/INR exchange rate forecast error variance is significantly explained by the Nifty value, i.e. 16.74%. This indicates that USD/INR exchange rates are guided by the performance of the stock market. The findings of the study show a significant impact of the Nifty Index on the Foreign USD/INR Exchange rate. Over a period of time, SEBI has liberalised the rules to allow for free foreign investor entry and exit. The Growth of the Indian stock market has attracted more and more investors from around the world, which in turn increases the demand for local currency. This Growth in demand, in turn, pushes up the value of the currency.
The overall findings of the study also indicate a significant impact of Crude oil on USD/INR Exchange rate. Theoretically, an oil price shock may be transmitted as the collapse in Crude prices pushes down the domestic price of non-traded products and hence the real exchange rate. Given the lack of literature analysing the integration among oil prices, exchange rate, and stock market returns in India; this paper can motivate further research in this area.