اثر چندک بر چندک تلاطم قیمت نفت بر بازدهی بازار سهام تهران

Purpose: Capital markets are considered one of the strong levers in the economy of countries, which act to accelerate the process of industrial development (especially in developing countries). By providing the possibility of medium-term and long-term securities transactions, these markets, on the one hand, provide the necessary facilities and resources to the applicants. On the other hand, they provide a suitable yield for the suppliers of these resources. Stock index is one of the important components in people's investment decisions and it is always in the center of attention of investment institutions. In oil-exporting countries, one of the most important factors affecting the efficiency of the capital market is oil price changes. For this reason, many researchers studied the effects of oil prices on stock market returns. Considering the wide impact of oil price volatility on various sectors of the economy of oil exporting countries, it is very important to evaluate the effectiveness of policies aimed at reducing the negative economic effects of oil price volatility on the stock market and subsequently, analyzing the behavior of investor Therefore, investors need to know exactly the type and extent of the effect of oil price fluctuation on the stock market and they are trying to identify the industries that are more quickly and affected by these fluctuations. Therefore, it is necessary to investigate the influence of the stock market on oil price fluctuations. Investigating this relationship can be beneficial in capital market risk management on the one hand, and on the other hand, it can help policymakers in regulating the capital market. Therefore, it is necessary to investigate the influence of the stock market on oil price fluctuations. Investigating this relationship can be beneficial in capital market risk management on the one hand, and on the other hand, it can help policymakers in regulating the capital market. In this research, using the quantile-by-quantile approach, we search and identify the asymmetric effect of oil price volatility on Tehran's stock market returns. This method enables us to analyze the asymmetric effects of oil price fluctuations in different situations of the stock market.



Methodology: The quantile-on-quantile approach is the method used in this research to identify the asymmetric effect of oil price volatility on Tehran's stock market returns. This method enables us to analyze the asymmetric effects of oil price fluctuations in different situations of the stock market. The data used in this research includes daily oil price data and the total stock market index in the period 2009:4-2024:1 and includes 2076 observations that were extracted from the Tehran Stock Exchange website and the Federal Reserve website. In this research, Eviews 12 and MATLAB software were used for data analysis. According to the variance heterogeneity test results, the existence of ARCH effects was confirmed. Therefore, the best GARCH model was chosen to estimate the conditional variance of the oil price. Then, in the final quantile-by-quantile model, the conditional variance of the oil price was used as oil price volatility.

Finding and Discussion: The results show that the alpha coefficient is changing during different quantiles of oil price volatility and stock market returns. For example, around medium to high quantiles of oil price volatility, regardless of the stock market return quantiles, an upward page is observed. This upward increase in α indicates that a relatively large fluctuation in oil prices, regardless of the state of the stock market, has a larger origin. Also, the width from the origin when there is a small fluctuation in the price of oil and the stock market is booming is negative and large in terms of absolute value. In other words, in the high quantiles of the stock market, stock returns strongly react to changes in the low quantiles of τ. For the beta slope, in general, the average of β coefficients is close to zero (-0.09), which indicates that it seems that oil price volatility does not affect stock market returns. However, in different quantiles of stock market returns and oil price volatility, there are regions where β has values opposite to zero. When the stock market is booming; a small fluctuation in oil prices has a positive effect on stock market returns. Conversely, a large volatility in oil prices has a large negative effect on stock market returns. Another point is that the largest β coefficients in terms of absolute value are related to situations where the stock market is in a state of strong prosperity. In general, the values of beta coefficients - regardless of oil price volatility quotients - increase with the increase of stock market return quotients (moving from a state of severe recession to a state of severe prosperity).

Conclusion and Policy Implications: The results of the quantile-on-quantile model show that the relationship between oil price volatility and stock market returns can depend on the size of oil price volatility and the state of the stock market. For example, in high quantiles of the stock market returns, in a state of strong market boom, the impact of oil price volatility on the stock market is greater. Also, this impact, both in terms of direction and absolute value; is different so that a small (big) oil price fluctuation has a big positive (negative) effect on Tehran's stock market return. According to the results of this research, the effect of oil price volatility on stock market returns is completely dependent on the market situation. In general, the slope values in each of the oil price turbulence quantiles; by moving from a state of severe recession to a state of severe prosperity, the stock market increases. By using the quantile-on-quantile model, it becomes possible to estimate the relationship between oil price volatility and Tehran's stock market return in terms of market size and condition, so that investors can determine the optimal combination of asset portfolios and policymakers and economic planners for policy. The limitations of this research are the absence of some data related to the oil variable on daily data (due to deference in holidays)