مدیریت سبد سرمایه‌گذاری در صنعت پالایشگاهی: بررسی شرایط با بازدهی مثبت و منفی: رویکرد Asymmetric TVP-VAR

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دکتری اقتصادی، دانشکده اقتصاد و علوم اداری، دانشگاه فردوسی مشهد

2 دکتری مدیریت استراتژیک، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس

3 گروه اقتصاد، دانشکده علوم اقتصادی و اداری، دانشگاه قم.

چکیده

صنعت پالایشگاهی یکی از مهمترین صنایع بورس اوراق بهادار تهران است که نوسانات در قیمت جهانی نفت بر رفتار سهم‌های موجود در آن اثرات قابل توجهی دارد. این اثرات به گونه‌ای است که ارتباط بین هر سهم با دیگری را نیز تحت تاثیر قرار می‌دهد. لذا، به جهت عدم امکان بررسی همه سهم‌های موجود در بازار سهام، تشکیل پرتفوی بهینه از صنایع مختلف نیازمند شناسایی سهم پیشرو در این صنعت است. به این منظور در این مطالعه با استفاده از داده‌های روزانه در بازه 31/05/1402-08/08/1395 و با استفاده از روش Asymmetric TVP-VAR ارتباط بین سهم‌های پالایشگاهی در سه حالت بازدهی مثبت، بازدهی منفی و حالت عمومی بررسی شده است. نتایج این مطالعه بیانگر آن است که بین ارتباط در بازدهی منفی و مثبت عدم تقارن برقرار است و شدت ارتباط در بازدهی مثبت بیشتر است. همچنین، سهم‌های شبنا، شبریز در بازدهی منفی و شبندر در بازدهی مثبت سهم‌های پیشرو هستند.

کلیدواژه‌ها

عنوان مقاله [English]

Portfolio Management in the Refining Industry: Investigating Conditions with Positive and Negative Returns: An Asymmetric TVP-VAR Approach

نویسندگان [English]

  • Soheil Rudari 1
  • Esmail Jalili 2
  • Vahid Omidi 3
1 Ph.d. in Economics, Department of Economics and Administrative Sciences. Ferdowsi University, Mashhad, Iran
2 Ph.d. in Strategic Management, Department of Management and Economics, Tarbiat-Modares University, Tehran, Iran
3 Department of Economics and administrative sciences, Qom University.
چکیده [English]

The refining industry is one of the most important industries in the Tehran Stock Exchange, and it has a significant impact on the behavior of the existing shares in it due to fluctuations in global oil prices. These effects are in such a way that they also affect the relationship between each share and the others. Therefore, in order to address the impossibility of examining all the shares available in the stock market, the formation of an optimal portfolio of various industries requires the identification of leading shares in this industry. To this end, in this study, using daily data in the period from August 30, 2016, to May 21, 2023, and employing the Asymmetric TVP-VAR method, the relationship between refining industry shares in three states of positive returns, negative returns, and general returns has been examined. The results of this study indicate that there is an asymmetrical relationship between negative and positive returns, with a stronger relationship observed in positive returns. Additionally, Shabna, Shabriz in negative returns, and Shebandar in positive returns are the leading shares in the refining industry.

کلیدواژه‌ها [English]

  • Positive Return
  • Negative Return
  • Burse
  • Asymmetric TVP-VAR

مراجع

  1. Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., & Oliyide, J. (2022). Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies. Resources Policy, 78, 102877.
  2. Ahmed, A, Huo, R (2021), Volatility transmissions across international oil market, commodity futures and stock markets: Empirical evidence from China, Energy Economics, 93,1-14.
  3. Alshater, M. M., Alqaralleh, H., & El Khoury, R. (2023). Dynamic asymmetric connectedness in technological sectors. The Journal of Economic Asymmetries, 27, e00287.
  4. Antonakakis, N., Chatziantoniou, I., and Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4):84.
  5. Argha, L., Mowlaei, M., Khezri, M. (2020). Investigating Impact of the Selected Domestic and Foreign Assets Returns on Stock Price Index Returns in Iran: An Approach from DCC-FIAPARCH Model. Quarterly Journal of Applied Theories of Economics, 6(4), 251-274. (in persian)
  6. Aroury, M.E.H. Lahiani, A. &khuong Nguyan D. (2015). World gold prices and stock returns in China: Insights for hedging and diversification strategies. Economic Modeling, 44, 273-282.
  7. Cao, G., & Xie, W. (2022). Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: Evidence from TVP-VAR based connectedness approach. Finance Research Letters, 49, 103070.
  8. Cheng, S., Deng, M., Liang, R., & Cao, Y. (2023). Asymmetric volatility spillover among global oil, gold, and Chinese sectors in the presence of major emergencies. Resources Policy, 82, 103579.
  9. Dadmehr, M., Rahnama Roodposhti, F., Nikoumaram, H., & Fallah Shams, M. F. (2021). Investigating the Effects of Contagion Between Monetary and Financial Markets of Iran. Journal of Economics and Modeling, 12(2), 123-166. (in persian)
  10. Frankel, J. A. (1992). Monetary and portfolio-balance models of exchange rate determination. In International economic policies and their theoretical foundations (pp. 793-832). Academic Press.
  11. Gkillas, K., Vortelinos, D. I., & Suleman, T. (2018). Asymmetries in the African financial markets. Journal of Multinational Financial Management, 45, 72-87.
  12. Hoseini, A., jahangiri, K., Heydari, H., & Ghaemi asl, M. (2019). Study of Shock and Volatility Spillovers among Selected Indices of the Tehran Stock Exchange Using Asymmetric BEKK-GARCH Model. Journal of Applied Economics Studies in Iran, 8(29), 123-155. (in persian)
  13. Karami, S., & Rastegar, M. A. (2018). Estimation of Return and Volatilities Spillover between Different Industries of Tehran Stocks’ Exchange. Financial Engineering and Portfolio Management, 9(35), 323-342. (in persian)
  14. Karolyi, G. A. (1995). A multivariate GARCH model of international transmissions of stock returns and volatility: The case of the United States and Canada. Journal of Business & Economic Statistics, 13(1), 11-25.
  15. Koop, G., Pesaran, M. H., and Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1):119–147.
  16. Li, X., Li, B., Wei, G., Bai, L., Wei, Y., & Liang, C. (2021). Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US. Resources Policy, 73, 102166.
  17. Liew, P. X., Lim, K. P., & Goh, K. L. (2022). The dynamics and determinants of liquidity connectedness across financial asset markets. International Review of Economics & Finance, 77, 341-358.
  18. Mohseni, H., & Botshekan, M. H. (2020). Investigating Conditional correlation among Industries in the Capital Market. Scientific Journal of Budget and Finance Strategic Research, 1(1), 75-91. (in persian)
  19. Mohajeri, P., & Taleblou, R. (2022). Investigating the Dynamics of Volatility Spillovers across Sectors’ Returns Utilizing a Time-Varying Parameter Vector Autoregressive Connectedness Approach; Evidence from Iranian Stock Market. Journal of Economic Research (Tahghighat- E- Eghtesadi), 57(2), 321-356. (in persian)
  20. Pesaran, H. H. and Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1):17–29.
  21. Rehman, M. U., Vo, X. V., Ko, H. U., Ahmad, N., & Kang, S. H. (2023). Quantile connectedness between Chinese stock and commodity futures markets. Research in International Business and Finance, 64, 101810.
  22. Reboredo, J. C., Ugolini, A., & Hernandez, J. A. (2021). Dynamic spillovers and network structure among commodity, currency, and stock markets. Resources Policy, 74, 102266.
  23. Saiti, B., & Masih, M. (2016). The co-movement of selective conventional and Islamic stock indices: is there any impact on shariah compliant equity investment in China? International Journal of Economics and Financial Issues, 6(4), 1895-1905.
  24. Taleblou, R., & Mohajeri, P. (2021). Modeling the Transmission of Volatility in the Iranian Stock Market Space-State Nonlinear Approach. Journal of Economic Research (Tahghighat- E- Eghtesadi), 55(4), 963-990. (in persian)
  25. Yunus, N. (2020). Time-varying linkages among gold, stocks, bonds and real estate. The Quarterly Review of Economics and Finance, 77, 165-185.
چشم انداز مدیریت مالی
دوره 13، شماره 43
1402
صفحه 133-154

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