Investigating the Relationship between Oil Prices and Stock Markets in Oil Exporting and Importing Countries by Using Quantile Regression

Subject Areas : Computational economics

Abouzar Gandomkar ¹ , Seyyed Nematollah Mousavi ² , Abbas Aminifard ³

1 - PhD Candidate, Department of Economics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.
2 - Seyyed Nematollah Mousavi Associate Professor, Department of Economics, Marodasht Branch, Islamic Azad University, Marvdasht, Iran.
3 - Assistant Professor, Department of Economics, Shiraz Branch, Islamic Azad University, Shiraz, Iran.

Received: 2023-11-27 Accepted : 2024-03-05 Published : 2024-03-17

Keywords: Oil price, , , , , Stock market, , , , , Quantile regression, , , , , Oil exporting and importing countries.,

Abstract :

Extended Abstract Considering the great importance of exchange rate fluctuations in various sectors of the macro economy, the issue of exchange rate fluctuations and its control has always been discussed in the framework of currency regimes in most countries. Considering that in recent decades, the managed floating system is one of the systems of interest in the world's economies, therefore, the level of involvement in this market and its measurement has played a very important role and has attracted the attention of model makers and economists. In oil-exporting countries, because the economy of these countries is dependent on oil, currency fluctuations and the level of intervention of the monetary authority in these countries are always very important. Most of these studies have identified and explained the paths and quantitative estimation of the effect of oil price on the macroeconomics of countries separately, and very few studies have examined the indirect channels of the effect of oil price shocks on the economy of countries. The point that this study emphasizes is that there is a relationship between oil prices and stock markets in oil importing and exporting countries, which has been neglected in many studies. Purpose In this study, the relationship between oil prices and stock markets in major oil-exporting countries (Russia, Norway, Canada, Iran) and oil-importing countries (USA, India, Japan) has been investigated. For this purpose, quantile regression and weekly data from January 2010 to June 2022 have been used. Methodology Different phenomena in the science of statistics appear in the form of random variables and it will be possible to investigate these phenomena by determining their distribution. In this regard, there are various statistical measures, each of which provides researchers with different information from the random variable distribution. Quantile or quantile regression is a statistical method for estimating and inferring conditional quantile functions. As linear and classical regression methods are based on minimizing the sum of squared errors and can estimate a model for conditional mean functions, quantile regression methods provide a mechanism for estimating models for the conditional mean function and a wide range of other conditional quantile functions. Quantile regression is able to provide a more complete statistical analysis of random relationships between variables. While standard regression methods show how the value of a dependent variable reacts to the change of an explanatory variable; Quantile regression shows the predicted changes for the entire distribution of the dependent variable and is used for the separate effects of the explanatory variable at different points of the distribution of the dependent variable. Of course, it should be acknowledged that one of the shortcomings of standard OLS regression is that the obtained estimate is a number that is used to summarize the relationship between the dependent variable and each of the independent variables. Findings Knowing the common movement between oil and stock markets is of great importance for investors and policy makers. In this context, there is a lot of empirical literature that shows the complexity of oil price dynamics and stock indices and then the relationship between them. In this study, using the quantile regression method, the relationship between oil price and stock index in oil exporting and importing countries in the period of 2010-2022 has been investigated. The results of the study showed that the price of oil has a positive and significant effect on the stock index in Russia, Norway, Canada, America and India in all deciles and the first 4 deciles in the Japanese stock index. Also, the price of oil has had a positive and significant effect on the stock index in Iran in 6 deciles (first 5 deciles, seventh deciles), and in the last two deciles. Also, by examining the R2adj statistic, it can be said that in all the investigated stock exchanges, except for Russia and Iran, 50 to 70% of the stock index changes are explained by the oil price, which shows the importance of the oil price on the stock index in these countries. In other words, the stock value can be considered equal to the sum of the discount of the future liquidity flows, and since these flows are directly affected by macroeconomic events, therefore, these flows can easily be affected by negative impulses. In addition, oil price volatility also has significant effects on stock market returns. The three categories of capital, manpower and oil can be considered as the most important factors that are used in the production of most goods, therefore, changes or fluctuations in each of these three factors will affect the cash flow. Conclusion Depending on whether they are oil importers or exporters, countries have different effects on oil price changes. According to the opinion of many economists, the price increase will bring a decrease in economic growth as well as an increase in inflation for the economy of oil importing countries. But if the oil importing countries have a strong and suitable economic structure, these fluctuations will have a less destructive effect on their economic conditions. In oil exporting countries, it is expected, of course, that the increase in the price of oil will increase their income, which will lead to an increase in their liquidity in the future, which will have a direct and positive impact on the capital market and the stock index. Now, if these incomes are used to buy domestic products, this increase in income leads to an increase in production and economic growth, and consequently to an increase in investment, which leads to an increase in stock prices. Therefore, according to oil price fluctuations in recent years, investors and policymakers should consider market conditions in their decisions based on modeling the relationship between oil and stock markets. Also, considering the changes that will happen over time in relation to the price of oil and the stock market, investors and policy makers should pay attention to this dynamic behavior of stock markets.