Testing the effect of local macroeconomic indicators and global risk factors on the Turkish participation stock market: Evidence from quantile regression approach

Amal Essayem; Şakir Görmüş; Murat Güven

doi:10.5152/TBE.2022.1018360

TR EN

Lokal Makroekonomik Göstergelerin ve Küresel Risk Faktörlerinin Türkiye Katılım Endeksi Üzerindeki Etkisinin Test Edilmesi: Kantil Regresyon Yaklaşımı

Öz

Bu çalışmanın amacı, Mayıs 2011-Nisan 2021 döneminde Türkiye hisse senedi piyasasında lokal makroekonomik göstergelerin ve küresel risk faktörlerinin katılım endeksi üzerindeki etkisini araştırmaktır. Kantil regresyon yaklaşımı kullanarak, lokal makroekonomik göstergelerin ve küresel risk faktörlerinin düşen(bear), normal, yükselen(bull) piyasa koşullarındaki etkisini tespit etmekteyiz. Ampirik sonuçlar, lokal makroekonomik göstergeler arasında para politikasıyla ilgili göstergelerden CPI(SGB)’nin sadece düşüş piyasasında (yükseliş piyasası) KAT30'u etkilediğini gösterirken, CDS tüm kantillerde KAT30'u negatif etkilemektedir. Küresel risk faktörleri söz konusu olduğunda, sonuçlar KAT30'un Q0.75 ve Q0.95 dışındaki tüm kantillerde VIX'ten negatif etkilendiğini göstermektedir. Bu durum, düşüş piyasasında VIX’in KAT30 üzerindeki etkisinin daha güçlü olduğu göstermektedir.. Bununla birlikte, OVX ve MSCI'nin etkisi, üst kantillerde pozitif ve anlamlıdır.

Anahtar Kelimeler

Katılım endeksi , lokal makroekonomik göstergeler , Küresel risk faktörleri , Kantil regresyon , Türkiye borsası

Testing the effect of local macroeconomic indicators and global risk factors on the Turkish participation stock market: Evidence from quantile regression approach

Abstract

The purpose of this paper is to investigate the effect of Local Macroeconomic Indicators (LMI) and Global Risk Factors (GRF) on the participation index in the Turkish stock market from May 2011 to April 2021. Using the quantile regression approach (QR-A), we detect the impact of LMI and GRF across different market conditions: bull, bear and normal. The empirical results demonstrate that, among LMI, monetary policy related indicators CPI (SGB) merely influence KAT30 return at bearish market (bullish market); however, CDS negatively affects KAT30 return across all quantiles. When it comes to global risk factors, results show that KAT30 return is negatively affected by VIX across all quantiles except Q0.75 and Q0.95. This means that the VIX impact on KAT30 return is stronger during the bearish market. Yet, OVX and MSCI positively impact the index’ return across upper quantiles.

Keywords

Global risk factors , local macroeconomic indicators , participation index , quantile regression , Turkish stock market

Kaynakça

AAOIFI. (2015), Shari’ah standards, Kingdom of Bahrain: Dar Alamaiman.
Ahmed, N., & Farooq, O. (2018). Does the degree of Shari’ah compliance affect the volatility? Evidence from the MENA region. Research in International Business and Finance, 45, 150–157.
Al-Khazali, O., Lean, H. H., & Samet, A. (2014). Do Islamic stock indexes outperform conventional stock indexes? A stochastic dominance approach. Pacific Basin Finance Journal, 28, 29–46.
Ali, S., Shahzad, S. J. H., Raza, N., & Al-Yahyaee, K. H. (2018). Stock market efficiency: A comparative analysis of Islamic and conventional stock markets. Physica A: Statistical Mechanics and Its Applications, 503, 139–153.
Aloui, C., Hkiri, B., Lau, C. K. M., & Yarovaya, L. (2016). Investors’ sentiment and US Islamic and conventional indexes nexus: A time–frequency analysis. Finance Research Letters, 19, 54–59.
Arouri, M. E., & Nguyen, D. K. (2010). Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade. Energy Policy, 38(8), 4528–4539.
Arshad, S., Aun, S., & Rizvi, R. (2013). Interactions Between Islamic Stock Indices And Business Cycles : Focusing On Asia Pacific. Australian Journal of Basic and Applied Sciences, 7(9), 1–9.
Bahloul, S., & Ben Amor, N. (2021). A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets. International Journal of Emerging Markets, In Press.
Banerjee, P. S., Doran, J. S., & Peterson, D. R. (2007). Implied volatility and future portfolio returns. Journal of Banking and Finance, 31(10), 3183–3199.
Bekaert, G., & Harvey, C. R. (1995). Time‐Varying World Market Integration. The Journal of Finance, 50(2), 403–444.

Bekaert, G., Harvey, C. R., Lundblad, C. T., & Siegel, S. (2011). What Segments Equity Markets ? The Review of Financial Studies, 24(12), 3841–3890.
Bhaduri, S., & Saraogi, R. (2010). The predictive power of the yield spread in timing the stock market. Emerging Markets Review, 11(3), 261–272.
Brogaard, J., & Detzel, A. (2015). The asset-pricing implications of government economic policy uncertainty. Management Science, 61(1), 3–18.
Camgöz, M., Köse, A., & Seval, B. (2019). Risk and Return Characteristics of Islamic Indices: An Empirical Approach. Istanbul Business Research, 47(2), 124–153.
Chang, B. H., Sharif, A., Aman, A., Suki, N. M., Salman, A., & Khan, S. A. R. (2020). The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach. Resources Policy, 65.
Chau, F., Deesomsak, R., & Wang, J. (2014). Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries. Journal of International Financial Markets, Institutions and Money, 28(1), 1–19.
Christou, C., Cunado, J., Gupta, R., & Hassapis, C. (2017). Economic policy uncertainty and stock returns in PacificRim countries: Evidence based on a Bayesian panel VAR model. Journal of Multinational Financial Management, 40, 92–102.
Çonkir, D., Meriç, E., & Esen, E. (2021). Analysis of the Relationship Between the Fear Index (VIX) and Emerging Markets: A Study on Investor Sentiment (Turkey). Journal Of The Human And Social Science Researces, 10(1), 52–84.
Coronado, M., Corzo, T., & Lazcano, L. (2012). A Case for Europe: The Relationship between Sovereign CDs and Stock Indexes. Frontiers in Finance and Economics, 9(2), 32–63.
Dewandaru, G., Rizvi, S. A. R., Masih, R., Masih, M., & Alhabshi, S. O. (2014). Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis. Economic Systems, 38(4), 553–571.
Dickey, D. A., & Fuller, W. A. (1979), Distribution Of The Estimators For Autoregressive Time Series With A Unit Root, Journal of the American Statistical Society, 75, 427–431.
Donadelli, M. (2015). Asian stock markets, US economic policy uncertainty and US macro-shocks. New Zealand Economic Papers, 49(2), 103–133.
Driesprong, G., Jacobsen, B., & Maat, B. (2008). Striking oil: Another puzzle? Journal of Financial Economics, 89(2), 307–327.
Erdoğan, L., Ceylan, R., & Abdul-Rahman, M. (2021). The Impact of Domestic and GRFon Turkish Stock Market: Evidence from the NARDL Approach. Emerging Markets Finance and Trade, 1–14.
Estrella, A., & Mishkin, F. S. (1998). Predicting U.S. Recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45–56.
Fama, E. F. (1981). Stock Returns, Real Activity, Inflation, and Money. American Economic Association Stock Returns The American Economic Review, 71(4), 545–565.
Fama, E. F. (1990). Stock Returns, Expected Returns, and Real Activity. The Journal of Finance, 45(4), 1089–1108.
Fatima, A., Rashid, A., & Khan, A. (2019). Asymmetric Impact Of Shocks On Islamic Stock Indices: a cross country analysis. Journal of Islamic Marketing, 10(1), 2–86.
Filis, G. (2010). Macro economy, stock market and oil prices: Do meaningful relationships exist among their cyclical fluctuations? Energy Economics, 32(4), 877–886.
Ftiti, Z., & Hadhri, S. (2018). Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? A multi-scale perspective Zied. Pacific-Basin Finance Journal, 53, 40–55.
Fisher, I. (1930). The Theory of Interest. New York: The Macmillan.
Ghorbel, A., Abdelhedi, M., Boujelbene, Y., Ghorbel, A., Abdelhedi, M., & Boujelbene, Y. (2014). Assessing the Impact of Crude Oil Price and Investor Sentiment on Islamic Indices : Subprime Crisis ,Journal Of African Business, 15(1), 13-24.
Giot, P. (2005). Relationships Between Implied Volatility Indexes And Stock Index Returns. Journal of Portfolio Management, 31(3), 92–100.
Guesmi, K., & Nguyen, D. K. (2011). How strong is the global integration of emerging market regions ? An Empirical Assessment. Economic Modelling, 28(6), 2517–2527.
Haddad, H. Ben, Mezghani, I., & Al Dohaiman, M. (2020). Common shocks, common transmission mechanisms and time-varying connectedness among Dow Jones Islamic stock market indices and global risk factors. Economic Systems, 44(2).
Hammoudeh, S., Kim, W. J., & Sarafrazi, S. (2016). Sources of Fluctuations in Islamic, U.S., EU, and Asia Equity Markets: The Roles of Economic Uncertainty, Interest Rates, and Stock Indexes. Emerging Markets Finance and Trade, 52(5), 1195–1209.
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.
Ho, C. S. F., Abd Rahman, N. A., Yusuf, N. H. M., & Zamzamin, Z. (2014). Performance of global Islamic versus conventional share indices: International evidence. Pacific Basin Finance Journal, 28, 110–121.
Jawad, S., Shahzad, H., Mensi, W., & Hammoudeh, S. (2018). Extreme dependence and risk spillovers between oil and Islamic stock markets. Emerging Markets Review, 34, 42–63.
Jawadi, F., Jawadi, N., & Cheffou, A. I. (2018). A Statistical Analysis of Uncertainty for Conventional and Ethical Stock Markets A Statistical Analysis of Uncertainty for Conventional and Ethical Stock Indexes. The Quarterly Review of Economics and Finance, 74, 9–17.
Jouini, J. (2013). Return and volatility interaction between oil prices and stock markets in Saudi Arabia. Journal of Policy Modeling, 35(6), 1124–1144.
Kang, W., Ratti, R. A., & Vespignani, J. (2016). The impact of oil price shocks on the U.S. stock market: A note on the roles of U.S. and non-U.S. oil production. Economics Letters, 145, 176–181.
Kangalli Uyar, S. G., Uyar, U., & Balkan, E. (2021). The role of precious metals in extreme market conditions: evidence from stock markets. Studies in Economics and Finance, 39(1), 63–78.
Koenker, R., & Bassett, G., Jr. (1978). Regression quantiles, Econometrica, 46(1), 33–50.
Koenker, R. (2005). Quantile regression, Cambridge: Cambridge University Press.
Kling, J. L. (1985). Oil price shocks and stock market behavior. J. Portf. Manag, 12, 34–39.
Lean, H. H., & Nguyen, D. K. (2014). Policy uncertainty and performance characteristics of sustainable investments across regions around the global financial crisis. Applied Financial Economics, 24(21), 1367–1373.
Liang, C. C., Troy, C., & Rouyer, E. (2020). and Asian stock prices: Evidence from the asymmetric NARDL model. North American Journal of Economics and Finance, 51.
Lin, B., & Su, T. (2020). The linkages between oil market uncertainty and Islamic stock markets: Evidence from quantile-on-quantile approach. Energy Economics, 88.
Liu, H. Y., & Chen, X. L. (2017). The imported price, inflation and exchange rate pass-through in China. Cogent Economics and Finance, 5(1).
Mezghani, T., & Boujelbène, M. (2018). The contagion e ff ect between the oil market , and the Islamic and conventional stock markets of the GCC country Behavioral explanation. 11(2), 157–181.
Mun, K. C. (2012). The joint response of stock and foreign exchange markets to macroeconomic surprises: Using US and Japanese data. Journal of Banking and Finance, 36(2), 383–394.
Murthy, U., Anthony, P., & Vighnesvaran, R. (2016). Factors Affecting Kuala Lumpur Composite Index (KLCI) Stock return in Malaysia. International Journal of Business and Management, 12(1), 122–132.
Naifar, N. (2016). Do global risk factors and macroeconomic conditions affect global Islamic index dynamics? A quantile regression approach. Quarterly Review of Economics and Finance, 61, 29–39.
Narayan, P. K., & Narayan, S. (2010). Modelling the impact of oil prices on Vietnam’s stock prices. Applied Energy, 87(1), 356–361.
Nazlioglu, S., Hammoudeh, S., & Gupta, R. (2015). Volatility transmission between Islamic and conventional equity markets: evidence from causality-in-variance test. Applied Economics, 47(46), 4996–5011.
Öner, H., İçellioğlu, C., & Öner, S. (2018). Volatilite Endeksi (Vıx) ile Gelişmekte Olan Ülke Hisse Senedi Piyasası Endeksleri Arasındaki Engel-Granger Eş-Bütünleşme ve Granger Nedensellik Analizi. Finansal Araştırmalar ve Çalışmalar Dergisi, 10(18), 110–124.
Paltrinieri, A., Floreani, J., Kappen, J. A., Mitchell, M. C., & Chawla, K. (2019). Islamic, socially responsible, and conventional market comovements: Evidence from stock indices. Thunderbird International Business Review, 61(5), 719–733.
Resnick, B. G., & Shoesmith, G. L. (2002). Using the Yield Curve to Time the Stock Market. Financial Analysts Journal, 58(3), 82–90.
Sadorsky, P. (1999). Oil price shocks and stock market activity. Energy Economics, 21(5), 449–469.
Safiullah, M., & Shamsuddin, A. (2021). Asset pricing factors in Islamic equity returns. International Review of Finance, 21(2), 523–554.
Trabelsi, N., & Naifar, N. (2017). Are Islamic stock indexes exposed to systemic risk? Multivariate GARCH estimation of CoVaR. Research in International Business and Finance, 42, 727–744.
Tursoy, T., & Faisal, F. (2018). The impact of gold and crude oil prices on stock market in Turkey: Empirical evidences from ARDL bounds test and combined cointegration. Resources Policy, 55, 49–54.
Usman, M., Ali, M., Jibran, Q., Amir-ud-din, R., & Akhter, W. (2019). Decoupling hypothesis of Islamic stocks : Evidence from copula CoVaR approach. Borsa Istanbul Review, 19(1), 56–63.
Whaley, R. E. (2009). Understanding the VIX. Journal of Portfolio Management, 35(3), 98–105.
Yarovaya, L., Elsayed, A. H., & Hammoudeh, S. (2021). Determinants of Spillovers between Islamic and Conventional Financial Markets: Exploring the Safe Haven Assets during the COVID-19 Pandemic. Finance Research Letters, In Press.
Zhu, H., Guo, Y., You, W., & Xu, Y. (2016). The heterogeneity dependence between crude oil price changes and industry stock returns in China: Evidence from a quantile regression approach. Energy Economics, 55, 30–41.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Ekonomi

Bölüm

Araştırma Makalesi

Yazarlar

Amal Essayem ^* Bu kişi benim
0000-0002-1565-4037
Türkiye

Şakir Görmüş Bu kişi benim
0000-0002-1857-8682
Türkiye

Murat Güven
0000-0001-5604-4369
Türkiye

Yayımlanma Tarihi

15 Temmuz 2022

Gönderilme Tarihi

3 Kasım 2021

Kabul Tarihi

25 Mart 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 36 Sayı: 3

DOI

https://doi.org/10.5152/TBE.2022.1018360

IZ

https://izlik.org/JA78AC48MR

APA

Essayem, A., Görmüş, Ş., & Güven, M. (2022). Testing the effect of local macroeconomic indicators and global risk factors on the Turkish participation stock market: Evidence from quantile regression approach. Trends in Business and Economics, 36(3), 258-267. https://doi.org/10.5152/TBE.2022.1018360

Cited By

BIST 100 ve Katılım 50 Endekslerinin Döviz Kuru, CDS Risk Primi, CBOE Oynaklık Endeksi (VIX) ve Petrol Fiyatları Arasındaki İlişkinin İncelenmesi

Kahramanmaraş Sütçü İmam Üniversitesi Sosyal Bilimler Dergisi

https://doi.org/10.33437/ksusbd.1400787

DYNAMIC LINKAGES BETWEEN TURKISH ISLAMIC STOCK MARKET AND GLOBAL MACROECONOMIC RISK FACTORS: EVIDENCE FROM DCC-GARCH MODEL

Akademik Hassasiyetler

https://doi.org/10.58884/akademik-hassasiyetler.1590078

Content of this journal is licensed under a Creative Commons Attribution 4.0 International License

29928

Lokal Makroekonomik Göstergelerin ve Küresel Risk Faktörlerinin Türkiye Katılım Endeksi Üzerindeki Etkisinin Test Edilmesi: Kantil Regresyon Yaklaşımı

Öz

Anahtar Kelimeler

Testing the effect of local macroeconomic indicators and global risk factors on the Turkish participation stock market: Evidence from quantile regression approach

Abstract

Keywords

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster

Cited By

BIST 100 ve Katılım 50 Endekslerinin Döviz Kuru, CDS Risk Primi, CBOE Oynaklık Endeksi (VIX) ve Petrol Fiyatları Arasındaki İlişkinin İncelenmesi

DYNAMIC LINKAGES BETWEEN TURKISH ISLAMIC STOCK MARKET AND GLOBAL MACROECONOMIC RISK FACTORS: EVIDENCE FROM DCC-GARCH MODEL