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Korku Endeksi Etkisinde İslami ve Konvansiyonel Pay Piyasa Endeksleri Arasındaki İlişki: Türkiye Örneği

Yıl 2023, Cilt: 8 Sayı: 2, 196 - 208, 30.12.2023

Öz

Bu çalışma Türkiye örneği üzerinde piyasalardaki korkunun derecesini ölçen VIX endeksinin konvansiyonel ve İslami pay piyasaları üzerindeki etkisini analiz etmektedir. Çalışma aynı zamanda her iki piyasanın (Konvansiyonel ve İslami) birbirleriyle ilişkisini de nedensellik çerçevesinde ortaya koymaktadır. Çalışma değerlendirmeye konu değişkenler arasındaki nedensellik ilişkisini Toda-Yamamoto prosedürünü Fourier fonksiyonu ile zenginleştiren kümülatif frekanslı bir nedensellik testi kullanarak (Fourier Toda-Yamamoto-FTY) analiz etmektedir. Bu çalışmanın amacı gerek iki pay grubu arasındaki nedensellik ilişkisini gerekse bu piyasalar üzerinde VIX endeksinin etkisini ortaya koyarak bir taraftan literatüre katkıda bulunmak diğer taraftan gelişen İslami piyasaların Türkiye pazarında da güçlenmesi adına yatırımcı kararlarına ışık tutmaktır. 2019/Ocak-2023/Mayıs dönemini kapsayan verilerle yapılan analizlerde VIX endeksinin konvansiyonel ve İslami pay piyasaları üzerinde tek taraflı nedensellik ilişkisi ile etkili olduğu ve aynı zamanda her iki piyasa arasında karşılıklı nedensellik ilişkisinin olduğu görülmüştür.

Kaynakça

  • AAOIFI (2015a). Accounting Auditing and Governance Standards. Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI). https://aaoifi.com/standard/accounting-standards/?lang=en
  • AAOIFI (2015b). Faizsiz Finans Standartları (1. bs). Türkiye Katılım Bankaları Birliği.
  • Adam, N. L., & Bakar, N. A. (2014). Shariah Screening Process in Malaysia. Procedia-Social and Behavioral Sciences, 121, 113-123. https://doi.org/10.1016/j.sbspro.2014.01.1113
  • Adam, N., Sidek, N. Z. M., & Sharif, A. (2022). The impact of global economic policy uncertainty and volatility on stock markets: Evidence from islamic countries. Asian Economic and Financial Review, 12(1), 15-28. https://doi.org/10.18488/5002.v12i1.4400
  • Ahmed, W. M. (2019). Islamic And Conventional Equity Markets: Two Sides of The Same Coin, or Not? The Quarterly Review of Economics and Finance, 72, 191-205. https://doi.org/10.1016/j.qref.2018.12.010
  • Ajmi, A. N., Hammoudeh, S., Nguyen, D. K., & Sarafrazi, S. (2014). How strong are the causal relationships between Islamic stock markets and conventional financial systems? Evidence from linear and nonlinear tests. Journal of International Financial Markets, Institutions and Money, 28, 213-227. https://doi.org/10.1016/j.intfin.2013.11.004
  • Alexakis, C., Pappas, V., & Tsikouras, A. (2015). Long Run asymmetric relationships between Islamic and conventional equity indices (Economics Working Paper Series 2015/002). Lancaster University Management School.
  • Arslan, C. (2022). Dünya’da ve Türkiye’de İslami Endeksler: Katılım 30 Endeksi ile BIST 100 Endeksi Arasındaki Nedensellik İlişkisinin Ampirik Analizi [Yüksek Lisans Tezi]. Karabük Üniversitesi.
  • Badshah, I., Bekiros, S., Lucey, B. M., & Uddin, G. S. (2018). Asymmetric linkages among the fear index and emerging market volatility indices. Emerging Markets Review, 37, 17-31. https://doi.org/10.1016/j.ememar.2018.03.002
  • Baykut, E., & Çonkar, K. (2020). BIST-30 ve KATLM-30 Endeksleri Arasındaki İlişkinin Değerlendirilmesi. Muhasebe ve Finans İncelemeleri Dergisi, 3(2), 163-174. https://doi.org/10.32951/mufider.780774
  • BIST. (2023). Katılım Endeksleri. Borsa İstanbul. https://borsaistanbul.com/tr/sayfa/6842/bist-katilim-endeksleri
  • Billio, M., Donadelli, M., Paradiso, A., & Riedel, M. (2017). Which market integration measure? Journal of Banking & Finance, 76, 150-174. https://doi.org/10.1016/j.jbankfin.2016.12.002
  • Bonaparte, Y., Chatrath, A., & Christie-David, R. (2023). S&P volatility, VIX, and asymptotic volatility estimates. Finance Research Letters, 51, 103392. https://doi.org/10.1016/j.frl.2022.103392
  • Bozoklu, S., Yilanci, V., & Gorus, M. S. (2020). Persistence in per capita energy consumption: A fractional integration approach with a Fourier function. Energy economics, 91, 104926. https://doi.org/10.1016/j.eneco.2020.104926
  • Buğan, M. F. (2016). İslami Hisse Senedi Endeksleri. İçinde S. Erdoğan, A. Gedikli, & D. Ç. Yıldırım (Ed.), İslam Ekonomisi ve Finansı (1. bs, ss. 249-271). Umuttepe Yayınları.
  • Cagliesi, G., & Guidi, F. (2021). A three-tiered nested analytical approach to financial integration: The case of emerging and frontier equity markets. International Review of Financial Analysis, 74, 101698. https://doi.org/10.1016/j.irfa.2021.101698
  • Cevik, E. I., & Bugan, M. F. (2018). Regime-Dependent Relation Between Islamic and Conventional Financial Markets. Borsa Istanbul Review, 18(2), 114-121. https://doi.org/10.1016/j.bir.2017.11.001
  • Chazi, A., Samet, A., & Azad, A. S. (2023). Volatility And Correlation of Islamic and Conventional Indices During Crises. Global Finance Journal, 55, 100800. https://doi.org/10.1016/j.gfj.2022.100800
  • Dania, A., & Malhotra, D. K. (2013). An Empirical Examination of the Dynamic Linkages of Faith-Based Socially Responsible Investing. The Journal of Wealth Management, 16(1), 65-79. https://doi.org/10.3905/jwm.2013.16.1.065
  • Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. The Annals of Statistics, 1-26.
  • Efron, B. (1992). Breakthroughs in Statistics. İçinde S. Kotz & N. L. Johnson (Ed.), Bootstrap Methods: Another Look at the Jackknife (ss. 569-593). Springer. https://doi.org/10.1007/978-1-4612-4380-9_41
  • Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics & Econometrics, 20(4), 399-419. https://doi.org/doi.org/10.1515/snde-2014-0101
  • Enders, W., & Lee, J. (2012). The flexible Fourier form and Dickey–Fuller type unit root tests. Economics Letters, 117(1), 196-199. https://doi.org/doi.org/10.1016/j.econlet.2012.04.081
  • Erdoğan, S., Gedikli, A., & Çevik, E. İ. (2019). Türkiye’de Döviz Kurları ile Katılım Endeksi Arasındaki İlişki. 1-8.
  • Fernandes, M., Medeiros, M. C., & Scharth, M. (2014). Modeling and predicting the CBOE market volatility index. Journal of Banking & Finance, 40, 1-10. https://doi.org/10.1016/j.jbankfin.2013.11.004
  • Fleming, J., Ostdiek, B., & Whaley, R. E. (1995). Predicting stock market volatility: A new measure. The Journal of Futures Markets (1986-1998), 15(3), 265-302. https://doi.org/10.1002/fut.3990150303
  • Giot, P. (2005). Relationships between implied volatility indices and stock index returns. Journal of Portfolio Management, 31(3), 92-100.
  • Girard, E. C., & Hassan, M. K. (2008). Is There a Cost to Faith-Based Investing: Evidence from FTSE Islamic Indices. The journal of Investing, 17(4), 112-121. https://doi.org/10.3905/JOI.2008.17.4.112
  • Gkillas, K., Tsagkanos, A., & Vortelinos, D. I. (2019). Integration and risk contagion in financial crises: Evidence from international stock markets. Journal of Business Research, 104, 350-365. https://doi.org/10.1016/j.jbusres.2019.07.031
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, 37(2), 424-438. https://doi.org/doi.org/10.2307/1912791
  • Hakim, S., & Rashidian, M. (2002). Risk And Return of Islamic Stock Market Indexes. 9th Economic Research Forum Annual Conference in Sharjah, UAE, 26-28.
  • Hammoudeh, S., Mensi, W., Reboredo, J. C., & Nguyen, D. K. (2014). Dynamic Dependence of The Global Islamic Equity Index with Global Conventional Equity Market Indices and Risk Factors. Pacific-Basin Finance Journal, 30, 189-206. https://doi.org/10.1016/j.pacfin.2014.10.001
  • Hasan, M. B., Mahi, M., Hassan, M. K., & Bhuiyan, A. B. (2021). Impact Of COVID-19 Pandemic on Stock Markets: Conventional Vs. Islamic Indices Using Wavelet-Based Multi-Timescales Analysis. The North American Journal of Economics and Finance, 58, 101504. https://doi.org/10.1016/j.najef.2021.101504
  • Hasan, M. B., Rashid, M. M., Shafiullah, M., & Sarker, T. (2022). How Resilient Are Islamic Financial Markets During The COVID-19 Pandemic? Pacific-Basin Finance Journal, 74, 101817. https://doi.org/10.1016/j.pacfin.2022.101817
  • Henda, E. A., & Taher, H. (2017). Are There Causal Relationships Between Islamic Versus Conventional Equity Indices? International Evidence. Studies in Business and Economics, 12(1), 40-60. https://doi.org/10.1515/sbe-2017-0004
  • İçellioğlu, C. Ş. (2018). Sermaye Piyasalarında İslami Endeksler ve Geleneksel Endeksler Arasındaki İlişkiler: Katılım 30 Endeksi ve BİST 100 Endeksi. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 19(2), 132-144.
  • İskenderoglu, Ö., & Akdag, S. (2020). Comparison of the effect of VIX fear index on stock exchange indices of developed and developing countries: The G20 case. South East European Journal of Economics and Business, 15(1), 105-121. https://doi.org/10.2478/jeb-2020-0009
  • Jawadi, F., Jawadi, N., & Idi Cheffou, A. (2020). Wavelet Analysis of The Conventional and Islamic Stock Market Relationship Ten Years After the Global Financial Crisis. Applied Economics Letters, 27(6), 466-472. https://doi.org/10.1080/13504851.2019.1631438
  • Kambouroudis, D. S., & McMillan, D. G. (2016). Does VIX or volume improve GARCH volatility forecasts? Applied Economics, 48(13), 1210-1228. https://doi.org/10.1080/00036846.2015.1096004
  • Karakuş, T. F., & Vural, G. (2022). Katılım Endeksi ile Faiz Oranı, Döviz Kuru ve BIST100 Endeksi Arasındaki İlişkinin İncelenmesi. International Journal of Commerce, Industry and Entrepreneurship Studies (UTISGAD), 2(1), 63-75.
  • Karim, M. M., Kawsar, N. H., Ariff, M., & Masih, M. (2022). Does implied volatility (or fear index) affect Islamic stock returns and conventional stock returns differently? Wavelet-based granger-causality, asymmetric quantile regression and NARDL approaches. Journal of International Financial Markets, Institutions and Money, 77, 101532. https://doi.org/10.1016/j.intfin.2022.101532
  • Kazak, H. (2022). İslami Bankacılık Konvansiyonel Bankacılık Üzerinde Etkili mi? Türkiye Örneği Üzerinden Bir Nedensellik Analizi. Ekonomi Politika ve Finans Araştırmaları Dergisi, 7(4), 982-998. https://doi.org/10.30784/epfad.1196986
  • Koç, Y. D., Çelik, S., & Acar, B. (2018). Katılım 30 Endeksi ile Vadeli-30 Endeksi Arasındaki Nedensellik İlişkisi. 1957-1960.
  • Kose, M. A., Prasad, E. S., & Terrones, M. E. (2006). How do trade and financial integration affect the relationship between growth and volatility? Journal of International Economics, 69(1), 176-202. https://doi.org/10.1016/j.jinteco.2005.05.009
  • Kozyra, J., & Lento, C. (2011). Using VIX data to enhance technical trading signals. Applied Economics Letters, 18(14), 1367-1370. https://doi.org/10.1080/13504851.2010.537623
  • Li, L. (2022). The dynamic interrelations of oil-equity implied volatility indexes under low and high volatility-of-volatility risk. Energy Economics, 105, 105756. https://doi.org/10.1016/j.eneco.2021.105756
  • Ma, S. (2022). Growth effects of economic integration: New evidence from the Belt and Road Initiative. Economic Analysis and Policy, 73, 753-767. https://doi.org/10.1016/j.eap.2022.01.004
  • Majdoub, J., Mansour, W., & Jouini, J. (2016). Market Integration Between Conventional and Islamic Stock Prices. The North American Journal of Economics and Finance, 37, 436-457. https://doi.org/10.1016/j.najef.2016.03.004
  • Mencía, J., & Sentana, E. (2013). Valuation of VIX derivatives. Journal of Financial Economics, 108(2), 367-391. https://doi.org/10.1016/j.jfineco.2012.12.003
  • Mensi, W., Rehman, M. U., Maitra, D., Al-Yahyaee, K. H., & Vo, X. V. (2022). Frequency Spillovers and Portfolio Risk Implications Between Sukuk, Islamic Stock and Emerging Stock Markets. The Quarterly Review of Economics and Finance. https://doi.org/10.1016/j.qref.2022.10.012
  • Nazlioglu, S., Gormus, A., & Soytas, U. (2019). Oil Prices and Monetary Policy in Emerging Markets: Structural Shifts in Causal Linkages. Emerging Markets Finance and Trade, 55(1), 105-117. https://doi.org/10.1080/1540496X.2018.1434072
  • Nazlioglu, S., Gormus, N. A., & Soytas, U. (2016). Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis. Energy economics, 60, 168-175. https://doi.org/doi.org/10.1016/j.eneco.2016.09.009
  • Okka, O., & Kazak, H. (2021). İslami Finansal Yönetim-Sistem ve Uygulama (Konvansiyonel Finansla Mukayeseli) (2. bs). Nobel Akademik Yayıncılık.
  • Ögel, S., & Fındık, M. (2020). Farkli Kitalarda Yer Alan Borsa Endekslerinin Vix (Korku) Endeksi İle İlişkisi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(1), 127-140. https://doi.org/0.33707/akuiibfd.715793
  • Özhan, E., Özbey, F., & Kandır, S. (2023). VIX korku endeksi ile seçilmiş varlık getirileri arasındaki ilişkilerin araştırılması. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(2), 297-308. https://doi.org/10.25287/ohuiibf.1148874
  • Pazarcı, Ş., Kar, A., KILIÇ, E., & UMUT, A. (2022). Türkiye’de Borsa, Döviz Kuru, CDS Primi ve VIX Endeksi İlişkisinin Ampirik Analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 24(3), 1090-1103.
  • Pesaran, M. H., & Pick, A. (2007). Econometric issues in the analysis of contagion. Journal of Economic Dynamics and Control, 31(4), 1245-1277. https://doi.org/10.1016/j.jedc.2006.03.008
  • Refinitiv. (2022). Islamic Finance Development Report 2022: Embracing Change [Islamic Finance Development Report]. LSEG (London Stock Exchange Group). https://www.refinitiv.com/en/products/eikon-trading-software/islamic-finance/islamic-finance-database
  • Sarıtaş, H., & Nazlıoğlu, E. H. (2019). Korku endeksi, hisse senedi piyasası ve döviz kuru ilişkisi: Türkiye için ampirik bir analiz. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(4), 542-551. https://doi.org/10.25287/ohuiibf.538592
  • Shahzad, S. J. H., Ferrer, R., Ballester, L., & Umar, Z. (2017). Risk Transmission Between Islamic and Conventional Stock Markets: A Return and Volatility Spillover Analysis. International Review of Financial Analysis, 52, 9-26. https://doi.org/10.1016/j.irfa.2017.04.005
  • Shima, H., & Nakayama, T. (2010). Higher Mathematics for Physics and Engineering. Springer Berlin Heidelberg.
  • Smolo, E., Jahangir, R., Nagayev, R., & Aysan, A. F. (2023). Performances of Leading Islamic Finance Markets Prior to and During the Covid-19 Pandemic. Heliyon, e12870. https://doi.org/10.1016/j.heliyon.2023.e12870
  • TKBB. (2023). Katılım Finans İlkelerine Uygun Faaliyet Gösteren Şirketlerin Belirlenmesinde Esas Alınacak Rehber (13.07. 2023 Tarihli Güncel Hali). TKBB. https://tkbbdanismakurulu.org.tr/uploads/rehberler/Kat%C4%B1l%C4%B1m-Finans-ilkelerine-Uygun-Faaliyet-Go%CC%88steren-Sirketlerin-Belirlenmesinde-Esas-Al%C4%B1nacak-Rehberin-13.07.2023-Tarihli-Guncel-Hali.pdf
  • Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66(1-2), 225-250. https://doi.org/doi.org/10.1016/0304-4076(94)01616-8
  • Tolstov, G. P., & Silverman, R. A. (1976). Fourier Series. Dover Publications.
  • Tunçel, M. B., & Gürsoy, S. (2020). Korku Endeksi (VIX), Bitcoin Fiyatları ve BİST100 Endeksi Arasındaki Nedensellik İlişkisi Üzerine Ampirik Bir Uygulama. Elektronik Sosyal Bilimler Dergisi, 19(76), 1999-2011. https://doi.org/10.17755/esosder.712702
  • Uçar, G., & Kandemir, T. (2022). BIST 50 ve KATILIM 30 Endeksleri Arasındaki Eşbütünleşme ve Nedensellik İlişkilerinin Değerlendirilmesi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 7(3), 417-432. https://doi.org/10.29106/fesa.1129607
  • Ülev, S., & Özdemir, M. (2015). Katılım Endeksi ile Piyasa Faiz Oranları Arasındaki Nedensellik İlişkisi. Islamic Banking, 47-54.
  • Whaley, R. E. (2000). The investor fear gauge: Explication of the CBOE VIX. İçinde Journal of Portfolio Management (C. 26, Sayı 3, ss. 12-17). https://doi.org/10.3905/jpm.2000.319728
  • Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105. https://doi.org/10.3905/JPM.2009.35.3.098
  • Yıldırım, H. H., & Sakarya, Ş. (2019). BİST 30 ve Katılım 30 Endeksi Volatilitelerinin Karşılaştırılması. Muhasebe ve Finans İncelemeleri Dergisi, 2(2), 167-174. https://doi.org/10.32951/mufider.603460
  • Zapata, H. O., & Rambaldi, A. N. (1997). Monte Carlo evidence on cointegration and causation. Oxford Bulletin of Economics and statistics, 59(2), 285-298. https://doi.org/doi.org/10.1111/1468-0084.00065
  • Zhu, S., Liu, Q., Wang, Y., Wei, Y., & Wei, G. (2019). Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement? Physica A: Statistical Mechanics and its Applications, 536, 122567. https://doi.org/10.1016/j.physa.2019.122567

The Relationship Between Islamic and Conventional Equity Market Indices under the Fear Index Effect: The Case of Türkiye

Yıl 2023, Cilt: 8 Sayı: 2, 196 - 208, 30.12.2023

Öz

This study analyses the impact of the VIX index, which measures the degree of fear in the markets, on conventional and Islamic equity markets in Turkiye. The study also analyses the relationship between the two markets (Conventional-Islamic) in terms of causality. The study analyses the causality relationship between the variables under consideration using a cumulative frequency causality test that augments the Toda-Yamamoto procedure with the Fourier function (Fourier Toda-Yamamoto-FTY). The objective of this study is to enhance the existing body of knowledge by elucidating the causal relationship between distinct categories of stocks and the impact exerted by the VIX index on these financial markets. Furthermore, it aims to offer valuable insights into investor decision-making processes, ultimately striving to strengthen the emerging Islamic markets within the Turkiye market. In the analyses conducted with the data covering the 2019/January-2023/May period, it was observed that the VIX index was effective on conventional and Islamic equity markets with a unilateral causality relationship. At the same time, it is determined that there is a mutual causality relationship between both markets.

Kaynakça

  • AAOIFI (2015a). Accounting Auditing and Governance Standards. Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI). https://aaoifi.com/standard/accounting-standards/?lang=en
  • AAOIFI (2015b). Faizsiz Finans Standartları (1. bs). Türkiye Katılım Bankaları Birliği.
  • Adam, N. L., & Bakar, N. A. (2014). Shariah Screening Process in Malaysia. Procedia-Social and Behavioral Sciences, 121, 113-123. https://doi.org/10.1016/j.sbspro.2014.01.1113
  • Adam, N., Sidek, N. Z. M., & Sharif, A. (2022). The impact of global economic policy uncertainty and volatility on stock markets: Evidence from islamic countries. Asian Economic and Financial Review, 12(1), 15-28. https://doi.org/10.18488/5002.v12i1.4400
  • Ahmed, W. M. (2019). Islamic And Conventional Equity Markets: Two Sides of The Same Coin, or Not? The Quarterly Review of Economics and Finance, 72, 191-205. https://doi.org/10.1016/j.qref.2018.12.010
  • Ajmi, A. N., Hammoudeh, S., Nguyen, D. K., & Sarafrazi, S. (2014). How strong are the causal relationships between Islamic stock markets and conventional financial systems? Evidence from linear and nonlinear tests. Journal of International Financial Markets, Institutions and Money, 28, 213-227. https://doi.org/10.1016/j.intfin.2013.11.004
  • Alexakis, C., Pappas, V., & Tsikouras, A. (2015). Long Run asymmetric relationships between Islamic and conventional equity indices (Economics Working Paper Series 2015/002). Lancaster University Management School.
  • Arslan, C. (2022). Dünya’da ve Türkiye’de İslami Endeksler: Katılım 30 Endeksi ile BIST 100 Endeksi Arasındaki Nedensellik İlişkisinin Ampirik Analizi [Yüksek Lisans Tezi]. Karabük Üniversitesi.
  • Badshah, I., Bekiros, S., Lucey, B. M., & Uddin, G. S. (2018). Asymmetric linkages among the fear index and emerging market volatility indices. Emerging Markets Review, 37, 17-31. https://doi.org/10.1016/j.ememar.2018.03.002
  • Baykut, E., & Çonkar, K. (2020). BIST-30 ve KATLM-30 Endeksleri Arasındaki İlişkinin Değerlendirilmesi. Muhasebe ve Finans İncelemeleri Dergisi, 3(2), 163-174. https://doi.org/10.32951/mufider.780774
  • BIST. (2023). Katılım Endeksleri. Borsa İstanbul. https://borsaistanbul.com/tr/sayfa/6842/bist-katilim-endeksleri
  • Billio, M., Donadelli, M., Paradiso, A., & Riedel, M. (2017). Which market integration measure? Journal of Banking & Finance, 76, 150-174. https://doi.org/10.1016/j.jbankfin.2016.12.002
  • Bonaparte, Y., Chatrath, A., & Christie-David, R. (2023). S&P volatility, VIX, and asymptotic volatility estimates. Finance Research Letters, 51, 103392. https://doi.org/10.1016/j.frl.2022.103392
  • Bozoklu, S., Yilanci, V., & Gorus, M. S. (2020). Persistence in per capita energy consumption: A fractional integration approach with a Fourier function. Energy economics, 91, 104926. https://doi.org/10.1016/j.eneco.2020.104926
  • Buğan, M. F. (2016). İslami Hisse Senedi Endeksleri. İçinde S. Erdoğan, A. Gedikli, & D. Ç. Yıldırım (Ed.), İslam Ekonomisi ve Finansı (1. bs, ss. 249-271). Umuttepe Yayınları.
  • Cagliesi, G., & Guidi, F. (2021). A three-tiered nested analytical approach to financial integration: The case of emerging and frontier equity markets. International Review of Financial Analysis, 74, 101698. https://doi.org/10.1016/j.irfa.2021.101698
  • Cevik, E. I., & Bugan, M. F. (2018). Regime-Dependent Relation Between Islamic and Conventional Financial Markets. Borsa Istanbul Review, 18(2), 114-121. https://doi.org/10.1016/j.bir.2017.11.001
  • Chazi, A., Samet, A., & Azad, A. S. (2023). Volatility And Correlation of Islamic and Conventional Indices During Crises. Global Finance Journal, 55, 100800. https://doi.org/10.1016/j.gfj.2022.100800
  • Dania, A., & Malhotra, D. K. (2013). An Empirical Examination of the Dynamic Linkages of Faith-Based Socially Responsible Investing. The Journal of Wealth Management, 16(1), 65-79. https://doi.org/10.3905/jwm.2013.16.1.065
  • Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. The Annals of Statistics, 1-26.
  • Efron, B. (1992). Breakthroughs in Statistics. İçinde S. Kotz & N. L. Johnson (Ed.), Bootstrap Methods: Another Look at the Jackknife (ss. 569-593). Springer. https://doi.org/10.1007/978-1-4612-4380-9_41
  • Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics & Econometrics, 20(4), 399-419. https://doi.org/doi.org/10.1515/snde-2014-0101
  • Enders, W., & Lee, J. (2012). The flexible Fourier form and Dickey–Fuller type unit root tests. Economics Letters, 117(1), 196-199. https://doi.org/doi.org/10.1016/j.econlet.2012.04.081
  • Erdoğan, S., Gedikli, A., & Çevik, E. İ. (2019). Türkiye’de Döviz Kurları ile Katılım Endeksi Arasındaki İlişki. 1-8.
  • Fernandes, M., Medeiros, M. C., & Scharth, M. (2014). Modeling and predicting the CBOE market volatility index. Journal of Banking & Finance, 40, 1-10. https://doi.org/10.1016/j.jbankfin.2013.11.004
  • Fleming, J., Ostdiek, B., & Whaley, R. E. (1995). Predicting stock market volatility: A new measure. The Journal of Futures Markets (1986-1998), 15(3), 265-302. https://doi.org/10.1002/fut.3990150303
  • Giot, P. (2005). Relationships between implied volatility indices and stock index returns. Journal of Portfolio Management, 31(3), 92-100.
  • Girard, E. C., & Hassan, M. K. (2008). Is There a Cost to Faith-Based Investing: Evidence from FTSE Islamic Indices. The journal of Investing, 17(4), 112-121. https://doi.org/10.3905/JOI.2008.17.4.112
  • Gkillas, K., Tsagkanos, A., & Vortelinos, D. I. (2019). Integration and risk contagion in financial crises: Evidence from international stock markets. Journal of Business Research, 104, 350-365. https://doi.org/10.1016/j.jbusres.2019.07.031
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, 37(2), 424-438. https://doi.org/doi.org/10.2307/1912791
  • Hakim, S., & Rashidian, M. (2002). Risk And Return of Islamic Stock Market Indexes. 9th Economic Research Forum Annual Conference in Sharjah, UAE, 26-28.
  • Hammoudeh, S., Mensi, W., Reboredo, J. C., & Nguyen, D. K. (2014). Dynamic Dependence of The Global Islamic Equity Index with Global Conventional Equity Market Indices and Risk Factors. Pacific-Basin Finance Journal, 30, 189-206. https://doi.org/10.1016/j.pacfin.2014.10.001
  • Hasan, M. B., Mahi, M., Hassan, M. K., & Bhuiyan, A. B. (2021). Impact Of COVID-19 Pandemic on Stock Markets: Conventional Vs. Islamic Indices Using Wavelet-Based Multi-Timescales Analysis. The North American Journal of Economics and Finance, 58, 101504. https://doi.org/10.1016/j.najef.2021.101504
  • Hasan, M. B., Rashid, M. M., Shafiullah, M., & Sarker, T. (2022). How Resilient Are Islamic Financial Markets During The COVID-19 Pandemic? Pacific-Basin Finance Journal, 74, 101817. https://doi.org/10.1016/j.pacfin.2022.101817
  • Henda, E. A., & Taher, H. (2017). Are There Causal Relationships Between Islamic Versus Conventional Equity Indices? International Evidence. Studies in Business and Economics, 12(1), 40-60. https://doi.org/10.1515/sbe-2017-0004
  • İçellioğlu, C. Ş. (2018). Sermaye Piyasalarında İslami Endeksler ve Geleneksel Endeksler Arasındaki İlişkiler: Katılım 30 Endeksi ve BİST 100 Endeksi. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 19(2), 132-144.
  • İskenderoglu, Ö., & Akdag, S. (2020). Comparison of the effect of VIX fear index on stock exchange indices of developed and developing countries: The G20 case. South East European Journal of Economics and Business, 15(1), 105-121. https://doi.org/10.2478/jeb-2020-0009
  • Jawadi, F., Jawadi, N., & Idi Cheffou, A. (2020). Wavelet Analysis of The Conventional and Islamic Stock Market Relationship Ten Years After the Global Financial Crisis. Applied Economics Letters, 27(6), 466-472. https://doi.org/10.1080/13504851.2019.1631438
  • Kambouroudis, D. S., & McMillan, D. G. (2016). Does VIX or volume improve GARCH volatility forecasts? Applied Economics, 48(13), 1210-1228. https://doi.org/10.1080/00036846.2015.1096004
  • Karakuş, T. F., & Vural, G. (2022). Katılım Endeksi ile Faiz Oranı, Döviz Kuru ve BIST100 Endeksi Arasındaki İlişkinin İncelenmesi. International Journal of Commerce, Industry and Entrepreneurship Studies (UTISGAD), 2(1), 63-75.
  • Karim, M. M., Kawsar, N. H., Ariff, M., & Masih, M. (2022). Does implied volatility (or fear index) affect Islamic stock returns and conventional stock returns differently? Wavelet-based granger-causality, asymmetric quantile regression and NARDL approaches. Journal of International Financial Markets, Institutions and Money, 77, 101532. https://doi.org/10.1016/j.intfin.2022.101532
  • Kazak, H. (2022). İslami Bankacılık Konvansiyonel Bankacılık Üzerinde Etkili mi? Türkiye Örneği Üzerinden Bir Nedensellik Analizi. Ekonomi Politika ve Finans Araştırmaları Dergisi, 7(4), 982-998. https://doi.org/10.30784/epfad.1196986
  • Koç, Y. D., Çelik, S., & Acar, B. (2018). Katılım 30 Endeksi ile Vadeli-30 Endeksi Arasındaki Nedensellik İlişkisi. 1957-1960.
  • Kose, M. A., Prasad, E. S., & Terrones, M. E. (2006). How do trade and financial integration affect the relationship between growth and volatility? Journal of International Economics, 69(1), 176-202. https://doi.org/10.1016/j.jinteco.2005.05.009
  • Kozyra, J., & Lento, C. (2011). Using VIX data to enhance technical trading signals. Applied Economics Letters, 18(14), 1367-1370. https://doi.org/10.1080/13504851.2010.537623
  • Li, L. (2022). The dynamic interrelations of oil-equity implied volatility indexes under low and high volatility-of-volatility risk. Energy Economics, 105, 105756. https://doi.org/10.1016/j.eneco.2021.105756
  • Ma, S. (2022). Growth effects of economic integration: New evidence from the Belt and Road Initiative. Economic Analysis and Policy, 73, 753-767. https://doi.org/10.1016/j.eap.2022.01.004
  • Majdoub, J., Mansour, W., & Jouini, J. (2016). Market Integration Between Conventional and Islamic Stock Prices. The North American Journal of Economics and Finance, 37, 436-457. https://doi.org/10.1016/j.najef.2016.03.004
  • Mencía, J., & Sentana, E. (2013). Valuation of VIX derivatives. Journal of Financial Economics, 108(2), 367-391. https://doi.org/10.1016/j.jfineco.2012.12.003
  • Mensi, W., Rehman, M. U., Maitra, D., Al-Yahyaee, K. H., & Vo, X. V. (2022). Frequency Spillovers and Portfolio Risk Implications Between Sukuk, Islamic Stock and Emerging Stock Markets. The Quarterly Review of Economics and Finance. https://doi.org/10.1016/j.qref.2022.10.012
  • Nazlioglu, S., Gormus, A., & Soytas, U. (2019). Oil Prices and Monetary Policy in Emerging Markets: Structural Shifts in Causal Linkages. Emerging Markets Finance and Trade, 55(1), 105-117. https://doi.org/10.1080/1540496X.2018.1434072
  • Nazlioglu, S., Gormus, N. A., & Soytas, U. (2016). Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis. Energy economics, 60, 168-175. https://doi.org/doi.org/10.1016/j.eneco.2016.09.009
  • Okka, O., & Kazak, H. (2021). İslami Finansal Yönetim-Sistem ve Uygulama (Konvansiyonel Finansla Mukayeseli) (2. bs). Nobel Akademik Yayıncılık.
  • Ögel, S., & Fındık, M. (2020). Farkli Kitalarda Yer Alan Borsa Endekslerinin Vix (Korku) Endeksi İle İlişkisi. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(1), 127-140. https://doi.org/0.33707/akuiibfd.715793
  • Özhan, E., Özbey, F., & Kandır, S. (2023). VIX korku endeksi ile seçilmiş varlık getirileri arasındaki ilişkilerin araştırılması. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(2), 297-308. https://doi.org/10.25287/ohuiibf.1148874
  • Pazarcı, Ş., Kar, A., KILIÇ, E., & UMUT, A. (2022). Türkiye’de Borsa, Döviz Kuru, CDS Primi ve VIX Endeksi İlişkisinin Ampirik Analizi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 24(3), 1090-1103.
  • Pesaran, M. H., & Pick, A. (2007). Econometric issues in the analysis of contagion. Journal of Economic Dynamics and Control, 31(4), 1245-1277. https://doi.org/10.1016/j.jedc.2006.03.008
  • Refinitiv. (2022). Islamic Finance Development Report 2022: Embracing Change [Islamic Finance Development Report]. LSEG (London Stock Exchange Group). https://www.refinitiv.com/en/products/eikon-trading-software/islamic-finance/islamic-finance-database
  • Sarıtaş, H., & Nazlıoğlu, E. H. (2019). Korku endeksi, hisse senedi piyasası ve döviz kuru ilişkisi: Türkiye için ampirik bir analiz. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 12(4), 542-551. https://doi.org/10.25287/ohuiibf.538592
  • Shahzad, S. J. H., Ferrer, R., Ballester, L., & Umar, Z. (2017). Risk Transmission Between Islamic and Conventional Stock Markets: A Return and Volatility Spillover Analysis. International Review of Financial Analysis, 52, 9-26. https://doi.org/10.1016/j.irfa.2017.04.005
  • Shima, H., & Nakayama, T. (2010). Higher Mathematics for Physics and Engineering. Springer Berlin Heidelberg.
  • Smolo, E., Jahangir, R., Nagayev, R., & Aysan, A. F. (2023). Performances of Leading Islamic Finance Markets Prior to and During the Covid-19 Pandemic. Heliyon, e12870. https://doi.org/10.1016/j.heliyon.2023.e12870
  • TKBB. (2023). Katılım Finans İlkelerine Uygun Faaliyet Gösteren Şirketlerin Belirlenmesinde Esas Alınacak Rehber (13.07. 2023 Tarihli Güncel Hali). TKBB. https://tkbbdanismakurulu.org.tr/uploads/rehberler/Kat%C4%B1l%C4%B1m-Finans-ilkelerine-Uygun-Faaliyet-Go%CC%88steren-Sirketlerin-Belirlenmesinde-Esas-Al%C4%B1nacak-Rehberin-13.07.2023-Tarihli-Guncel-Hali.pdf
  • Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66(1-2), 225-250. https://doi.org/doi.org/10.1016/0304-4076(94)01616-8
  • Tolstov, G. P., & Silverman, R. A. (1976). Fourier Series. Dover Publications.
  • Tunçel, M. B., & Gürsoy, S. (2020). Korku Endeksi (VIX), Bitcoin Fiyatları ve BİST100 Endeksi Arasındaki Nedensellik İlişkisi Üzerine Ampirik Bir Uygulama. Elektronik Sosyal Bilimler Dergisi, 19(76), 1999-2011. https://doi.org/10.17755/esosder.712702
  • Uçar, G., & Kandemir, T. (2022). BIST 50 ve KATILIM 30 Endeksleri Arasındaki Eşbütünleşme ve Nedensellik İlişkilerinin Değerlendirilmesi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 7(3), 417-432. https://doi.org/10.29106/fesa.1129607
  • Ülev, S., & Özdemir, M. (2015). Katılım Endeksi ile Piyasa Faiz Oranları Arasındaki Nedensellik İlişkisi. Islamic Banking, 47-54.
  • Whaley, R. E. (2000). The investor fear gauge: Explication of the CBOE VIX. İçinde Journal of Portfolio Management (C. 26, Sayı 3, ss. 12-17). https://doi.org/10.3905/jpm.2000.319728
  • Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105. https://doi.org/10.3905/JPM.2009.35.3.098
  • Yıldırım, H. H., & Sakarya, Ş. (2019). BİST 30 ve Katılım 30 Endeksi Volatilitelerinin Karşılaştırılması. Muhasebe ve Finans İncelemeleri Dergisi, 2(2), 167-174. https://doi.org/10.32951/mufider.603460
  • Zapata, H. O., & Rambaldi, A. N. (1997). Monte Carlo evidence on cointegration and causation. Oxford Bulletin of Economics and statistics, 59(2), 285-298. https://doi.org/doi.org/10.1111/1468-0084.00065
  • Zhu, S., Liu, Q., Wang, Y., Wei, Y., & Wei, G. (2019). Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement? Physica A: Statistical Mechanics and its Applications, 536, 122567. https://doi.org/10.1016/j.physa.2019.122567

Ayrıntılar

Birincil Dil Türkçe
Konular Finansal Ekonometri, Finansal Piyasalar ve Kurumlar
Bölüm Araştırma Makalesi
Yazarlar

Hasan KAZAK 0000-0003-0699-5371

Erken Görünüm Tarihi 17 Ekim 2023
Yayımlanma Tarihi 30 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 8 Sayı: 2

Kaynak Göster

APA KAZAK, H. (2023). Korku Endeksi Etkisinde İslami ve Konvansiyonel Pay Piyasa Endeksleri Arasındaki İlişki: Türkiye Örneği. JOEEP: Journal of Emerging Economies and Policy, 8(2), 196-208.

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