MSCI-İslami Endekslerin Getiri Dağılımı: 2008 Küresel Krizi İle COVİD-19 Salgınının Karşılaştırılması

Öz

İslami borsa endeksleri farklı kriterlere göre derlendikleri için geleneksel borsalardan ayrı fiyat dinamiklerine sahip olması beklenir. Bu çalışmada gelişmiş ve gelişmekte olan ülke MSCI-Islami borsa endekslerinin 2008 ve COVID-19 kriz dönemlerindeki getiri özellikleri ARMA-GARCH modelleri ile araştırılmıştır. Çalışmanın bulguları MSCI-İslami endekslerin getirilerinin birçok finans teorisinde esas kabul edilen normal dağılıma uymadığını göstermektedir. ABD doları cinsinden ölçülen getirilerde risk primi istatistiksel olarak anlamlı bulunmaz iken, tüm borsalarda oynaklığın kalıcı olduğu ampirik olarak kanıtlanmıştır. Borsalarda asimetrik oynaklık daha çok 2008 krizinde gözlemlenmiştir. Sadece Japonya borsasının getirilerinin incelenen her iki kriz döneminde öngörülebilir olduğu çalışmada rapor edilmiştir. Genel olarak MSCI-İslami borsa endeksleri kendi aralarında farklı getiri özelliklerine sahip olsalar da büyük çapta fiyat değişimlerinin ve spekülatif işlemlerin tüm borsalarda sıklıkla yaşandığı göze çarpmıştır.

Anahtar Kelimeler

• Getiri Dağılımı
• Tematik Endeksler
• Finansal Krizler

MSCI-Islamic Indices Return Distribution : A Comparison Of 2008 Global Crisis and the COVID-19 Epidemic

Abstract

Islamic stock market indices are compiled according to different criteria, so they have expected to have different price dynamics from traditional stock markets. The study investigates the return characteristics of developed and developing country MSCI-Islamic stock market indices during the 2008 and COVID-19 crisis periods by using ARMA-GARCH models. The findings of the study show that the returns of MSCI-Islamic indices do not comply with the normal distribution, which is considered essential in many finance theories. While the risk premium is not statistically significant for returns denominated in US dollars, it has been empirically proven that volatility is permanent in all stock markets. Asymmetric volatility in stock markets was mostly observed in the 2008 crisis. It was reported that only the returns of the Japanese stock market were predictable in both crisis periods. Although MSCI-Islamic stock market indices generally have different return characteristics among themselves, it has been noted that Large-Scale Price Changes and speculative transactions are frequently experienced in all stock markets.

Keywords

• Return Distribution
• Thematic Indexes
• Financial Crises

Kaynakça

1. Abdullahi, S. I. (2021). Islamic equities and COVID-19 pandemic: measuring Islamic stock indices correlation and volatility in period of crisis. Islamic Economic Studies, 29(1), 50-66.
2. Adu, G., Alagidede, P., ve Karimu, A. (2015). Stock return distribution in the BRICS. Review of Development Finance, 5(2), 98-109.
3. Ankudinov, A., Ibragimov, R., ve Lebedev, O. (2017). Heavy tails and asymmetry of returns in the Russian stock market. Emerging Markets Review, 32, 200-219.
4. Aparicio, F. M., ve Estrada, J. (2001). Empirical distributions of stock returns: European securities markets, 1990-95. The European Journal of Finance, 7(1), 1-21.
5. Bahar, S., ve Altay, E. (2022). Borsa İstanbul’da Gürültüye Dayalı İşlem: Egarch-M Modeli İle Getiri Oranları Üzerindeki Gürültü Etkisinin Ölçümesi. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 40(4), 721-741.
6. Beck, T., Demirgüç-Kunt, A., ve Merrouche, O. (2013). Islamic vs. conventional banking: Business model, efficiency and stability. Journal of Banking ve finance, 37(2), 433-447.
7. Bessembinder, H. (2018). Do stocks outperform treasury bills?. Journal of financial economics, 129(3), 440-457. Brooks, C., ve Persand, G. (2003). The effect of asymmetries on stock index return value‐at‐risk estimates. The Journal of Risk Finance, 4(2), 29-42.
8. Brooks, C. (2008). Introductory Econometrics for Finance. Cambridge university press.

9. Cao, H. H., Coval, J. D., ve Hirshleifer, D. (2002). Sidelined investors, trading-generated news, and security returns. The Review of Financial Studies, 15(2), 615-648.
10. Carnero, M. A., León, A., ve Ñíguez, T. M. (2023). Skewness in energy returns: estimation, testing and implications for tail risk. The Quarterly Review of Economics and Finance. (90).178-189
11. Chen, H. C., ve Yeh, C. W. (2021). Global financial crisis and COVID-19: Industrial reactions. Finance Research Letters, 42, 101940.
12. Chión, S. J., ve Veliz C, C. N. (2008). On the normality of stock return distributions: Latin American markets, 2000-2007. Journal of CENTRUM Cathedra, 1(2), 90-108.
13. Chowdhury, A. R. (1994). Statistical properties of daily returns from the Dhaka stock exchange. The Bangladesh Development Studies, 22(4), 61-76.
14. Christensen, B. J., Nielsen, M. Ø., ve Zhu, J. (2015). The impact of financial crises on the risk–return tradeoff and the leverage effect. Economic Modelling, 49, 407-418.
15. Conrad, J., Dittmar, R. F., ve Ghysels, E. (2013). Ex ante skewness and expected stock returns. The Journal of Finance, 68(1), 85-124.
16. Corhay, A., ve Rad, A. T. (1994). Statistical properties of daily returns: Evidence from European stock markets. Journal of Business Finance ve Accounting, 21(2), 271-282.
17. Corlu, C. G., Meterelliyoz, M., ve Tinic, M. (2016). Empirical distributions of daily equity index returns: A comparison. Expert systems with applications, 54, 170-192.
18. De Santis, G., ve İmrohoroğlu, S. (1997). Stock returns and volatility in emerging financial markets. Journal of International Money and Finance, 4(16), 561-579..
19. Dravid, A. R. (1987). A note on the behavior of stock returns around ex-dates of stock distributions. The Journal of Finance, 42(1), 163-168.
20. Drożdż, S., Forczek, M., Kwapień, J., Oświe, P., ve Rak, R. (2007). Stock market return distributions: From past to present. Physica A: Statistical Mechanics and its Applications, 383(1), 59-64.
21. Eom, C., Kaizoji, T., ve Scalas, E. (2019). Fat tails in financial return distributions revisited: Evidence from the Korean stock market. Physica A: Statistical Mechanics and its Applications, 526, 121055.
22. Fama, E. F. (1965). The behavior of stock-market prices. The journal of Business, 38(1), 34-105.
23. Haroon, O., Ali, M., Khan, A., Khattak, M. A., ve Rizvi, S. A. R. (2021). Financial market risks during the COVID-19 pandemic. Emerging Markets Finance and Trade, 57(8), 2407-2414.
24. Harvey, C. R., ve Siddique, A. (2000). Conditional skewness in asset pricing tests. The Journal of Finance, 55(3), 1263-1295.
25. Hasan, M. B., Hassan, M. K., Rashid, M. M., ve Alhenawi, Y. (2021). Are safe haven assets really safe during the 2008 global financial crisis and COVID-19 pandemic?. Global Finance Journal, 50, 100668.
26. Hassan, K., Hoque, A., Gasbarro, D., & Wong, W. K. (2023). Are Islamic stocks immune from financial crises? Evidence from contagion tests. International Review of Economics & Finance, 86, 919-948.
27. Hutson, E., Kearney, C., ve Lynch, M. (2008). Volume and skewness in international equity markets. Journal of Banking ve Finance, 32(7), 1255-1268.
28. Kamath, R. R., Chakornpipat, R., & Chatrath, A. (1998). Return distributions and the day-of-the-week effects in the stock exchange of Thailand. Journal of Economics and Finance, 22(2-3), 97-107.
29. Koutmos, G., Negakis, C., ve Theodossiou, P. (1993). Stochastic behaviour of the Athens stock exchange. Applied Financial Economics, 3(2), 119-126.
30. Lanne, M., ve Pentti, S. (2007). Modeling conditional skewness in stock returns. The European Journal of Finance, 13(8), 691-704.
31. Lobão, J. (2024). Efficiency and price clustering in Islamic stocks: evidence from three Asian countries. Journal of Islamic Accounting and Business Research, 15(1), 136-152.
32. Longin, F. M. (1996). The asymptotic distribution of extreme stock market returns. Journal of Business, 383-408. Lukács, P. (2002). Stock return distribution and market capitalisation. Hungarian Statistical Review, 80(SN7), 138-148.
33. McMillen, M. J. (2006). Islamic capital markets: developments and issues. Capital Markets Law Journal, 1(2), 136-172.
34. MSCI (2023), MSCI Islamic Index Series Methodology, www.msci.com/ MSCI_Islamic_Index_Series_Methodology_20230126.pdf . (Erişim Tarihi: 05. 07. 2023).
35. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370.
36. Pekár, J., ve Pčolár, M. (2022). Empirical distribution of daily stock returns of selected developing and emerging markets with application to financial risk management. Central European Journal of Operations Research, 30(2), 699-731.
37. Rehman, M. U., Ahmad, N., Shahzad, S. J. H., ve Vo, X. V. (2022). Dependence dynamics of stock markets during COVID-19. Emerging Markets Review, 51, 100894.
38. Salisu, A. A., ve Shaik, M. (2022). Islamic Stock indices and COVID-19 pandemic. International Review of Economics ve Finance, 80, 282-293.
39. Shamsuddin, A. (2014). Are Dow Jones Islamic equity indices exposed to interest rate risk?. Economic Modelling, 39, 273-281.
40. Siegel, J. J. (2021). Stocks for the long run: The definitive guide to financial market returns ve long-term investment strategies. McGraw-Hill Education.
41. Singleton, J. C., ve Wingender, J. (1986). Skewness persistence in common stock returns. Journal of Financial and Quantitative Analysis, 21(3), 335-341.
42. SP Global Raporu (2022). Islamic Finance Outlook. https://www.spglobal.com/ratings/en/research/pdf-articles/islamic-finance-outlook-2022-28102022v1.pdf
43. Yu, Y., Guo, S., ve Chang, X. (2022). Oil prices volatility and economic performance during COVID-19 and financial crises of 2007–2008. Resources policy, 75, 102531.