پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 25 |
| تعداد شماره‌ها | 938 |
| تعداد مقالات | 7,697 |
| تعداد مشاهده مقاله | 12,622,419 |
| تعداد دریافت فایل اصل مقاله | 8,985,902 |
بررسی اثر سرایتی ریسک سیستمی میان صنایع اصلی در بورس اوراق بهادار تهران: رویکرد شبکه رخداد دنباله‌ای محور | ||
| راهبرد مدیریت مالی | ||
| مقاله 6، دوره 12، شماره 1 - شماره پیاپی 44، فروردین 1403، صفحه 113-138 اصل مقاله (1.9 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22051/jfm.2024.43587.2819 | ||
| نویسنده | ||
| الهام فرزانگان* | ||
| استادیار اقتصاد، گروه علوم اقتصادی و اجتماعی، دانشگاه بوعلی سینا-مجتمع آموزش عالی نهاوند(ویژه دختران)، همدان، ایران | ||
| چکیده | ||
| ریسک سیستمی ثبات بازار مالی را به خطر می‌اندازد، چرا که شکست هر بخش می‌تواند به کل سیستم مالی آسیب برساند. ازاین‌رو اندازه‌گیری دقیق ریسک سیستمی و تجزیه‌وتحلیل مکانیزم انتقال ریسک‌های مالی میان بخش‌‌های مختلف برای محافظت سیستم مالی دربرابر ریسک‌های سیستمی، از اهمیت خاصی برخوردار است. لذا در پژوهش حاضر، یک شبکه رخداد دنباله‌ای محور ساخته می‌شود تا با استفاده از آن اثر سرایتی ریسک سیستمی و وابستگی متقابل ریسک‌های دنباله‌ای میان صنایع در بورس اوراق بهادار تهران بررسی شود. بدین‌منظور، 29صنعت اصلی در بورس اوراق بهادار تهران، متشکل از 196 شرکت فعال، طی دوره زمانی 1397 الی 1401 که دوره‌های استرس مختلفی را پوشش می‌دهد مورد آزمون قرار می‌گیرند. برای اندازه‌گیری پروفایل‌های ریسک، ریزش‌های مورد انتظار شرطی (CoES) محاسبه می‌شود. ماتریس‌های مجاورت زمان متغیر که براساس مشابهت بین پروفایل‌های ریسک هر جفت گره بدست می‌آیند نشان می‌دهند که ارتباط متقابل در شبکه وجود دارد. پروفایل‌های ریسک صنایع به‌طور مثبت همبسته هستند؛ صنعت بانک‌ها و موسسات اعتباری و صنعت بیمه و بازنشستگی هیچ‌گونه نقشی در تنوع‌بخشی ریسک طی رخدادهای دنباله‌ای، ندارند. با محاسبه نمره ریسک سیستمی و استفاده از تکنیک تجزیه ریسک سیستمی، می‌توان نتیجه گرفت که بجز صنایع مالی، سایر صنایع، صنایع مهم سیستمی در شبکه محسوب می‌شوند. نتایج حاصل از مدل رگرسیون کوانتیل شبکه‌ای رخداد دنباله‌ای محور در کوانتیل‌های مختلف، نشان می‌دهد که همه صنایع در انتقال ریسک تحت شرایط حدی بازار، نقش دارند. یافته‌های حاصل از این پژوهش، از اهمیت کاربردی برای مقامات نظارتی جهت اصلاح سیاست‌های مالی و بهبود چارچوب‌های سیاست‌های کلان برخوردار است و نیز برای تصمیم‌گیری سرمایه‌گذاران در تخصیص دارایی‌ها مفید واقع می‌شوند. | ||
| کلیدواژه‌ها | ||
| صنایع؛ ریزش مورد انتظار شرطی؛ ریسک سیستمی؛ تحلیل شبکه‌ای؛ سرایت ریسک | ||
| عنوان مقاله [English] | ||
| Investigating of Systematic Risk Contagion Effect among Industries listed in Tehran Stock Exchange: the Tail Event driven Network | ||
| نویسندگان [English] | ||
| Elham Farzanegan | ||
| Assistant Professor of Economics, Department of Economics and Social Sciences, Nahavand Higher Education Complex, Bu-Ali Sina University, Hamedan, Iran. | ||
| چکیده [English] | ||
| The Tehran Stock Exchange and its industries have contributed to the risk of tail events occurring in recent years, such as the U.S. and European sanctions against Iran and the COVID-19 pandemic. Industries affected by these crises have become more connected. Crisis episodes have raised risk spread within the financial system. Whenever an impulse hits an industry, it is quickly transmitted to other industries through a contagion mechanism, which ultimately causes fluctuations in the whole system. Stress situations suggest that promoting financial stability should be a priority for regulators and academic researchers. For this purpose, analyzing the systemic risk contagion and tail risk interconnectedness among industries is important to enhance the stock market’s safety and design the related macroprudential policies. The stock market plays a vital role in the financial system by allocating resources and facilitating price discovery. However, Tehran Stock Exchange is a completely immature market, which greatly increases the possibility of risk contagion to the entire market. For example, the collapses of stock price bubbles in the Tehran Stock Exchange over the past two decades resulted in huge losses in the net worth of investors and was followed by a recession. The financial turmoil highlights the importance of measuring systemic risk in the stock market. Interconnections among industries in a network imply that a shock in one industry may lead to risk transmission between related industries, causing risk contagion to the entire stock market. Therefore, investigating the risk interrelationships between industries and identifying the systematically linked industries is essential to effectively predict the systemic risks and control risk spread in the stock market. This study analyzes the risk interdependence among the main industries listed on the Tehran Stock Exchange. In particular, the risk contagion effects among industries are analyzed under extreme market conditions. | ||
| کلیدواژه‌ها [English] | ||
| CoES, Industry Sectors, Network Analysis, Risk Contagion, Systemic Risk | ||
|
سایر فایل های مرتبط با مقاله
|
||
| مراجع | ||
|
Acharya, V. V., Pedersen, L. H., Philippon, T., & Richardson, M. (2017). Measuring systemic risk. The Review of Financial Studies, 30(1), 2-47.
Adrian, T., & Brunnermeier, M. K. (2016). CoVaR. The American Economic Review, 106(7), 1705.
Arnold, B., Borio, C., Ellis, L., & Moshirian, F. (2012). Systemic risk, macroprudential policy frameworks, monitoring financial systems and the evolution of capital adequacy. Journal of Banking & Finance, 36(12), 3125-3132.
Acemoglu, D., Carvalho, V. M., Ozdaglar, A., & Tahbaz‐Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977-2016.
Baba Jani, J., Taghavi Fard, M. T., & Ghazali, A. (2018). A framework for measuring and predicting system risk with the conditional value at risk approach. Financial Knowledge of Securities Analysis, 11(39), 15-36. (In Persian)
Brownlees, C., & Engle, R. F. (2017). SRISK: A conditional capital shortfall measure of systemic risk. The Review of Financial Studies, 30(1), 48-79.
Carhart, M. M. (1997). On persistence in mutual fund performance. The Journal of Finance, 52(1), 57-82.
Cavaglia, S., Brightman, C., & Aked, M. (2000). The increasing importance of industry factors. Financial Analysts Journal, 56(5), 41-54.
Chen, C. Y. H., Härdle, W. K., & Okhrin, Y. (2019). Tail event driven networks of SIFIs. Journal of Econometrics, 208(1), 282-298.
Chen, N., & Jin, X. (2020). Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach. The North American Journal of Economics and Finance, 52, 101137.
Diebold, F. X., & Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119-134.
Eivazloo, R., & Rameshg, M. (2019). Measuring systemic risk in the financial institution via dynamic conditional correlation and delta conditional value at risk mode and bank rating. Journal of Asset Management and Financing, 7(4), 1-16. (In Persian)
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
Feng, Y., Wang, G. J., Zhu, Y., & Xie, C. (2023). Systemic risk spillovers and the determinants in the stock markets of the Belt and Road countries. Emerging Markets Review, 55, 101020.
Feng, S., Huang, S., Qi, Y., Liu, X., Sun, Q., & Wen, S. (2018). Network features of sector indexes spillover effects in China: A multi-scale view. Physica A: Statistical Mechanics and its Applications, 496, 461-473.
Gong, X., Xiong, X., & Zhang, W. (2020). Research on systemic risk measurement and spillover effect of financial institutions in China. Management World, 36(8), 65-83.
Härdle, W. K., Wang, W., & Yu, L. (2016). Tenet: Tail-event driven network risk. Journal of Econometrics, 192(2), 499-513.
Hekmati farid, S., Rezazadeh, A., & malek, A. (2018). The Estimation of Systematic Risk in Iranian Financial Sectors (ΔCoVaR Approach). Economic Modelling, 12(43), 99-122. (In Persian)
Hu, L., Gan, Y., & Wen, H. (2023). Do we need to consider multiple inter-bank linkages for systemic risk in China’s banking industry? Analysis based on the multilayer network. Finance Research Letters, 51, 103433.
Kang, S. H., & Lee, J. W. (2019). The network connectedness of volatility spillovers across global futures markets. Physica A: Statistical Mechanics and its Applications, 526, 120756.
Kaufman, G. G., & Scott, K. E. (2003). What is systemic risk, and do bank regulators retard or contribute to it?.The Independent Review, 7(3), 371-391.
Khiabani, N., & Nohammadian Nikpey, E. (2018). Systemic Risk Analysis in Selected Industries of Tehran Stock Exchange: A Multivariate Quantile Regression Approach. Iranian Journal of Economic Research, 23(77), 1-36. (In Persian)
López-Espinosa, G., Moreno, A., Rubia, A., & Valderrama, L. (2012). Short-term wholesale funding and systemic risk: A global CoVaR approach. Journal of Banking & Finance, 36(12), 3150-3162.
Luo, C., Xie, C., Yu, C., & Xu, Y. (2015). Measuring financial market risk contagion using dynamic MRS-Copula models: The case of Chinese and other international stock markets. Economic Modelling, 51, 657-671.
Meharani, A., Najafi Moghadam, A., & Baghani, A. (2021). Estimation value at risk (VAR) and conditional value at risk (CoVaR) at Tehran Stock Exchange by approach to using Fréchet distribution (FD). Financial Engineering and Portfolio Management, 12(46), 449-475. (In Persian)
Namaki, A., Abbasian, E., & Shafiei, E. (2022). Analyzing of Systemic Risk Contributions of Tehran Stock Exchange Companies by Complexity Approach. Financial Management Strategy, 10(1), 91-112. (In Persian)
Ng, S. (2006). Testing cross-section correlation in panel data using spacings. Journal of Business & Economic Statistics, 24(1), 12-23.
Raei, R., Namaki, A., & Askarirad, H. (2023). Decomposition of Systemic Risk and Analysis of the Relationships of Its Dimensions with the Characteristics and Financial Performance of the Banks Listed in Tehran Stock Exchange (TSE). Journal of Asset Management and Financing, 11(1), 1-30. (In Persian)
Roudari, S., & Homayounifar, M. (2021). Investigation of the Effect of Coronavirus Outbreak on Iran Stock Market by Considering Regime Changes. Iranian Journal of Economic Research, 26(87), 195-227. (In Persian)
Sadeghi Shahdani M., Tavakoli H., & Salehi A. (2022). Study of systemic risk in the banking sector of Tehran Stock Exchange: Graph theory approach and ARMA-gjrGARCH-DCC. Quarterly Journal of Economic Research and Policies, 30 (101):307-355. (In Persian)
Shakeri, A., Khosravipour, N., & Jafari, S. M. (2020). Estimation of Systemic Risk of Iranian Banking System Using MES and CoVaR Measures. Financial Management Strategy, 8(4), 235-256. (In Persian)
Tabatabaei. S. J. (2023). Modeling the measurement of volatility connectedness at the time of the Corona outbreak in the structure of the Tehran Stock Exchange industries. Budget and Finance Strategic Research. 3(4). 185-216. (In Persian)
Xu, Q., Yan, H., & Zhao, T. (2022). Contagion effect of systemic risk among industry sectors in China’s stock market. The North American Journal of Economics and Finance, 59, 101576.
Yang, Z., & Wang, S. (2020). Asymmetric contagion of cross-industrial downside risks: New evidence from the regime-switching model. The Journal of World Economy (in Chinese), 43, 28-51.
Zhang, W., Zhuang, X., Wang, J., & Lu, Y. (2020). Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network. The North American Journal of Economics and Finance, 54, 101248.
Zhu, X., Wang, W., Wang, H., & Härdle, W. K. (2019). Network quantile autoregression. Journal of Econometrics, 212(1), 345-358. | ||
|
آمار تعداد مشاهده مقاله: 399 تعداد دریافت فایل اصل مقاله: 304 |
||
