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

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری علوم اقتصادی، دانشکده اقتصاد، مدیریت و علوم اداری، دانشگاه سمنان، سمنان، ایران

2 استاد گروه اقتصاد، دانشکده اقتصاد، مدیریت و علوم اداری دانشگاه سمنان، سمنان، ایران

چکیده

در این پژوهش اثر تلاطم قیمت نفت بر بازدهی بازار سهام تهران با رویکرد چندک بر چندک برآورد شده است. در این رویکرد وابستگی‌های میان چندک‌های تلاطم قیمت نفت و بازدهی بازار سهام تهران نشان داده شده است. بدین منظور ابتدا با روش ناهمسان واریانس شرطی خودتوضیحی تعمیم یافته، تلاطم قیمت نفت مشخص و سپس با استفاده از رویکرد چندک بر چندک اثر تلاطم قیمت نفت بر بازده بازار سهام تهران برآورد شده است. جامعه آماری، داده‌های مربوط به متغیرهای نفت و شاخص قیمت سهام بازار بورس تهران و نمونه آماری شامل 2076 مشاهده از داده‌های روزانه مربوط به متغیرهای نفت و شاخص قیمت سهام بازار بورس تهران طی دوره زمانی 1388:1 تا 1402:10 می‌باشد. نتایج این پژوهش نشان می‌دهد که اثر تلاطم قیمت نفت بر بازار سهام تهران، در طول چندک‌های مختلف بازده بازار سهام تهران متفاوت می‌باشد. به طوری که، بیشترین اثرگذاری تلاطم قیمت نفت بر بازده بازار سهام تهران مربوط به حالتی است که بازار سهام در وضعیت رونق شدید قرار دارد. در این حالت تلاطم کوچک (بزرگ) قیمت نفت اثر مثبت (منفی) بزرگی بر روی بازده بازار سهام تهران دارد. بر اساس نتایج می‌توان گفت رابطه بین تلاطم قیمت نفت و بازده بازار سهام به مقدار تلاطم قیمت نفت و وضعیت بازار سهام بستگی دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Quantile-on-Quantile Effects of Oil Price Volatility on Tehran Stock Market Return

نویسندگان [English]

  • Asghar Vahedi 1
  • Esmaiel Abounoori 2
1 Ph.D. Student in Economic sciences-Econometrics, Semnan University, Semnan, Iran.
2 Professor of Econometrics & Social Statistics, Department of Economics, Semnan University, Semnan, Iran. .
چکیده [English]

Purpose: Capital markets are considered as strong levers in the economy of countries, serving 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 provide the necessary facilities and resources to the applicants. They also 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 variation. 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, to analyze 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 to identify the industries that are more quickly affected by these fluctuations. Investigating this relationship can be beneficial in capital market risk management. It can also help policymakers regulate the capital market. Therefore, it is necessary to investigate the influence of the stock market on oil price fluctuations. In this research, using the quantile-by-quantile approach, we search and identify the asymmetric effect of oil price volatility on Tehran 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 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 include daily oil price data and the total stock market index in the period of 2009:4-2024:1. They include 2076 observations that were extracted from the Tehran Stock Exchange website and the Federal Reserve website. In this research, the Eviews 12 and MATLAB software packages were used for data analysis. According to the variance heterogeneity test results, the 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 the oil price volatility.
Findings and Discussion: The alpha coefficient varies 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 trend in α indicates that a relatively large fluctuation in oil prices, regardless of the state of the stock market, has a larger origin. Also, when there is a small fluctuation in the price of oil and the stock market is booming, the width from the origin 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 oil price volatility does not seem to 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.
Conclusions 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 a small (big) oil price fluctuation has a big positive (negative) effect on Tehran 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 moves from a state of severe recession to a state of severe prosperity, thus promoting the stock market. The quantile-on-quantile model makes it possible to estimate the relationship between oil price volatility and Tehran stock market return in terms of market size and condition, so that investors can determine the optimal combination of asset portfolios, policymakers, and economic planners for policy. The limitations of this research are the lack of daily data related to the oil variable, which is due to the difference in holidays.

کلیدواژه‌ها [English]

  • Oil price volatility
  • Stock market return
  • Quantile on Quantile Regression
  • Conditional variance
Abounoori, E., Keshavarz Hadad, G., & Mirzaaghanasab, I. (2020).           Estimation of the Volatility Transmissions between the Exchange Rate and the Stock Market Returns in Terms of Individual Industries in Iran. The Journal of Economic Policy, 12(23), 253-278. (In Persian)
Abounouri, E., & Moshrefi, G., (2007). The Effect of Macroeconomic Indicators on the Stock Price Index of the Petrochemical Industry in Iran using the ARDL Model. Economics Research, 6(2): 209-228. (In Persian)
Amin Kharazian, N., Aleemran, R., Baradaran Hasanzadeh, R., & Farhang, A. (2022). Investigating the Relationship between Oil Price and Iran's Stock Market Index with an Emphasis on Political Uncertainty and the Corona Pandemic: Using Wavelet Transform Approach. Economic Modeling, 58(16): 37-49. (In Persian)
Assifuah-Nunoo, E., Junior, P., O. Adam, A., M. & Bossman, A. (2022). Assessing the Safe Haven Properties of Oil in African Stock Markets amid the COVID-19 Pandemic: a Quantile Regression Analysis. Quantitative Finance and Economics6(2): 244-269.
Balcilar, M., Demirer, R., & Hammoudeh, S. (2019). Quantile Relationship between Oil and Stock Returns: Evidence from Emerging and Frontier Stock Markets. Energy Policy134 , Article 110931: 1-14.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3): 307-327.
Elhami, A., H. Shahbazi, N., & Fallah, M. A. (2023). Stock Market Developments in 2019 and its Impact on Economic and National Security. Defense Economics8(27): 77-108. (In Persian)
Engle, R. F. (1982). Autoregressive conditional Heteroscedadticity with Estimates of The variance of UK Inflation. Econometrica, 50 (4): 987-1008.
Fakari Sardhai, B., Sabohi, M., & Shahpuri, A. (2018). The Effects of Changes in the Price of Crude Oil on the Tehran Stock Exchange index: The Use of M-GARCH Approach BEKK. Economic Research, 53(2): 387-407. (In Persian)
Ge, Z. (2023). The Asymmetric Impact of Oil Price Shocks on China Stock Market: Evidence from Quantile-on-Quantile Regression. The Quarterly Review of Economics and Finance89 (2023): 120-125.
Ge, Z., & Sun, Y. (2024). Asymmetric Impact of Oil Price Shocks on Inflation: Evidence from Quantile-on-Quantile Regression. International Review of Financial Analysis. Article 103097.
Hamilton, J. D. (1983). Oil and the Macroeconomy since World War II. Journal of political economy91(2): 228-248.
Hassan, M. K., Alhomaidi, A., & Hasan, M. B. (2022). How do Sectoral Islamic Equity Markets React to Geopolitical Risk, Economic Policy Uncertainty, and Oil Price Shocks? Using Quantile on Quantile Regression Analysis. Economic Policy Uncertainty, and Oil Price Shocks.
Hosseinioun, N. S., Behname, M., & Ebrahimi Salari, T. (2016). Volatility Transmission of the Rate of Returns in Iranian Stock, Gold and Foreign Currency Markets. Iranian Journal of Economic Research, 21(66): 123-150. (In Persian)
Jiang, Y., Tian, G., & Mo, B. (2020). Spillover and Quantile Linkage between Oil Price Shocks and Stock Returns: New Evidence from G7 Countries. Financial Innovation6(1): 1-26.
Jones, C. M., & Kaul, G. (1996). Oil and the Stock Markets. The journal of Finance51(2): 463-491.
Joo, Y. C., & Park, S. Y. (2021). The Impact of Oil Price Volatility on Stock Markets: Evidences from Oil-importing Countries. Energy Economics101: Article 105413.
Khatib Semnani, M., A. Shojaee, M., & Ghiasi Khosroshahi, M. (2014). Investigating the Effect of Crude Oil Price Fluctuations on the Efficiency Index of Tehran Stock Exchange. Financial Economics, 8(29): 90-113. (In Persian)
Kilian, L., & Park, C. (2009). The Impact of Oil Price Shocks on the US Stock Market. International economic review50(4): 1267-1287.
Kling, J. L. (1985). Oil Price Shocks and Stock Market Behavior. The Journal of Portfolio Management12(1): 34-39.
Koenker. R., & Bassett Jr, G. (1978). Regression Quantiles. Econometrica: journal of the Econometric Society, 33-50.
Liu, F., Umair, M., & Gao, J. (2023). Assessing Oil Price Volatility Co-movement with Stock Market Volatility through Quantile Regression approach. Resources Policy81: Article 103375.
Ma, F., Wahab, M. I. M., Huang, D., & Xu, W. (2017). Forecasting the Realized Volatility of the Oil Futures Market: A Regime Switching Approach. Energy Economics67: 136-145.
Mamipour, S., & Feli, A. (2017). The Impact of Oil Price Volatility on Tehran Stock Market at Sector-Level: A Variance Decomposition Approach. Monetary & Financial Economics, 24(13): 205-236. (In Persian)
Mirhashmi Dehnavi, S. M. (2015). The Asymmetric Effect of Oil Price Shock on Stock Market: Evidence from Oil Exporting Countries. Quarterly Journal of Fiscal and Economic Policies, 3(11): 85-108. (In Persian)
Monjazeb, M. R., Matani, M., & Movahedi, F. (2022). Impacts of the Asymmetric Oil Price Volatility on Iranian Stock Returns: A Quantile Approach. Quarterly Journal of Applied Theories of Economics, 9(4): 97-132. (In Persian)
Naeem, M. A., Hasan, M., Arif, M., Balli, F., & Shahzad, S. J. H. (2020). Time and Frequency Domain Quantile Coherence of Emerging Stock Markets with Gold and Oil Prices. Physica A: Statistical Mechanics and Its Applications553: Article 124235.
Panetta, F. (2002). The Stability of the Relation between the Stock Market and Macroeconomic Forces. Economic Notes, 31: 417-450.
Rostami, J., Fatahi, Sh., & Sohaili, K. (2023). Modeling and Estimating the Return of Tehran Stock Exchange using Dynamic Models. Financial Economics, 62(17): 185-216. (In Persian)
Rostami, M., Makiyan, S. N., & Roozegar, R. (2021). Stock Return Volatility using Bayesian Symmetric and Asymmetric GARCH. The Journal of Economic Policy12(24), 171-206. (In Persian)
Sadorsky, P. (1999). Oil Price Shocks and Stock Market Activity. Energy economics21(5): 449-469.
Salehi, A. K., & Hamuleh Alipour, M. (2018). An Investigation the Impact of Crude Oil Price Shocks on Stock Returns of Listed Companies in Tehran Stock Exchange. Accounting and Management vision, 1(3): 69-85. (In Persian)
Samadi, S., Shiranifakhr, Z., & Davarzadeh, M. (2007). Investigating the Influence of World Price of Gold and Oil on the Tehran Stock Exchange index: Modelling and Forecasting. Journal of Quantitative Economics (Quarterly Journal of Economics Review), 4(2): 25-51. (In Persian)
Sharifabadi, A. M., EbrahimZadeh Pezeshki, R., & Abolghasemi, M. (2015). Presenting a New Method to Prioritize Nonfinancial Factors Influencing the Sale of an Entity's Stock by a Combined Approach of Kano and QFD Models: A Case Study of the Stock Market in Yazd. The Journal of Economic Policy7(13), 85-110. (In Persian)
 
Sim, N., & Zhou, H. (2015). Oil Prices, US Stock Return, and the Dependence between their Quantiles. Journal of Banking & Finance55: 1-8.
Taherpoor, J., Mirzaei, H., khodaparast, Y., & Rezai, S. (2020). The Effect of Coronavirus Outbreak on Government Budget in Year 2020. Journal of Iranian Economic Issues, 7(2): 181-221. (In Persian)
Tavakolian, H., Etemadi, S. A., & Tehrani, R. (2016). Volatility Spillover of Brent Oil Price Return on Return of Iran and USA Financial Markets and Related Industries: A MGARCH Approach. Iranian Energy Economics, 6(21): 33-61.
Vahedi, A., Abounoori, E., & Malekzadeh, P. (2024). The Effect of Oil Price Shocks on Iranian Stock Market’s Return using Quantile on Quantile Model. Iranian Energy Economics,46(12), Articles in Press,  (In Persian)
Tchatoka, F. D., Masson, V., & Parry, S. (2019). Linkages between Oil Price Shocks and Stock Returns Revisited. Energy Economics82: 42-61.
Xie, Q., & Tang, G. (2022). Do Market Conditions Interfere with the Transmission of Uncertainty from Oil Market to Stock Market? Evidence from a Modified Quantile-on-Quantile Approach. Energy Economics, 114: Article 106250.