Türkiye’de Borsa ve Makroekonomik Değişkenler Arasındaki Nedensellik İlişkisi: Dalgacık Bağdaşıklığı Analizi ile Yeniden İnceleme

Year 2020, Issue: 56, 229 - 254, 30.08.2020

Remzi Gök

https://doi.org/10.18070/erciyesiibd.666618

Cited By: 2

Abstract

Bu çalışmada makroekonomik değişkenlere ait (Bist100, 2 yıllık devlet tahvil faizi, 5 yıllık CDS, döviz sepeti, gram altın) eşbütünleşme ve nedensellik ilişkisi araştırılmıştır. 2011-01-14 ve 2019-04-30 arası günlük kapanış fiyatları kullanılarak önemli ampirik bulgular elde edilmiştir. Öncelikle, tüm değişkenler birinci farkta durağandır. İkincisi, oluşturulan yirmi modelin on üçünde eşbütünleşme ilişkisi tespit edilmiştir. Üçüncüsü, VECM modeline göre kısa ve uzun dönemli tek ve çift yönlü nedensellik bulgularına rastlanmıştır. Dördüncüsü, dalgacık bağdaşıklığı test sonuçlarına göre Bist100-döviz sepeti ve Bist100-altın fiyatları zıt yönde; tahvil faizleri-döviz sepeti, tahvil faizleri-altın fiyatları ve CDS-altın fiyatları aynı yönde hareket etmektedir. Ayrıca, 16-128 günlük periyotta ve 2013-2017 yılları arasında döviz sepeti, Bist100 endeksini tek yönlü olarak takip etmektedir. Durağan değişkenlerin ele alındığı testte, Bist100 ile CDS arasındaki anlamsız ve altın-döviz sepeti arasındaki iki yönlü hariç olmak üzere, diğer değişkenler arasında tek yönlü varyansta nedensellik ilişkisi bulunmuştur. Bu sonuçlar portföy ve risk yönetimi ve finansal istikrarın sağlanmasına yönelik alınacak kararlar için büyük öneme sahiptir.

Keywords

Dalgacıklar, Hisse, Altın, CDS

Causality Between Stock Market and Macroeconomic Variables in Turkey: New Evidence From Wavelet Coherence Analysis

Abstract

We examine the dependence and causal linkages among selected macroeconomic variables, namely BIST100, bond yields, CDS, currency basket, and gold prices, in Turkey. Using daily data covering the period 2011-01-14 to 2019-04-30, we find the following empirical results. First, all variables are found to be integrated into the first order, namely stationary in first log-difference. Second, our paper detects evidence of significant interdependence in thirteen out of twenty pairs of variables. Third, the findings of the VECM test reveal unidirectional and bidirectional causalities in the short- and long-run. Fourth, the results of wavelet coherence analysis highlight a negative relationship for the pairs of BIST100-currency basket and BIST100-gold prices while positive linkages are observed for the pairs of bond rates-currency basket, bond rates-gold prices, and CDS-gold prices. In addition, the BIST100 index unidirectionally leads currency basket between 16- and 128-day holding periods between 2013-2017 years. Lastly, there exist unidirectional causal linkages among changes in prices for all the pairs of variables, except for BIST100-CDS with noncausality and gold-currency basket with two-way causality. Our findings yield significant implications for portfolio and risk management and financial stability.

Keywords

Wavelets, Stock, Gold, CDS

References

• Akkaya, M. (2017). Türk tahvillerinin CDS primlerini etkileyen içsel faktörlerin analizi [Analysis of internal factors affecting CDS premiums of Turkish treasuries]. Maliye ve Finans Yazıları, 1(107), 130-145.
• Aksoylu, E. and Görmüş, Ş. (2018). Gelişmekte olan ülkelerde ülke riski göstergesi olarak kredi temerrüt swapları: asimetrik nedensellik yöntemi [Credit default swaps as an indicator of sovereign risk in developing countries: asymmetric causality method]. Ekonomik ve Sosyal Araştırmalar Dergisi, 14(1), 15-33.
• Aktug, R. E., Vasconcellos, G. and Bae, Y. (2012). The dynamics of sovereign credit default swap and bond markets: empirical evidence from the 2001 to 2007 period. Applied Economics Letters, 19(3), 251-259.
• Andrieş, A. M., Ihnatov, I. and Tiwari, A. K. (2014). Analyzing time–frequency relationship between interest rate, stock price and exchange rate through continuous wavelet. Economic Modelling, 41, 227-238.
• Arouri, M. E. H., Lahiani, A. and Nguyen, D. K. (2015). World gold prices and stock returns in China: insights for hedging and diversification strategies. Economic Modelling, 44, 273-282.
• Balı, S. and Cinel, M. (2011). Altın fiyatlarının İMKB 100 Endeksi’ne etkisi ve bu etkinin ölçümlenmesi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 25(3-4), 45-63.
• Başarır, Ç. and Keten, M. (2016). Gelişmekte olan ülkelerin CDS primleri ile hisse senetleri ve döviz kurları arasındaki kointegrasyon ilişkisi [A cointegration analysis between CDS premiums, stock indexes and exchange rates in emerging countries]. Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 8(15), 369-380.
• Baur, D. G. and Lucey, B. M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217-229.
• Bhunia, A. (2013). Cointegration and causal relationship among crude price, domestic gold price and financial variables: an evidence of BSE and NSE. Journal of Contemporary Issues in Business Research, 2(1), 1-10.
• Chkili, W. (2016). Dynamic correlations and hedging effectiveness between gold and stock markets: evidence for BRICS countries. Research in International Business and Finance, 38, 22-34.
• Ciner, C., Gurdgiev, C. and Lucey, B. M. (2013). Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates. International Review of Financial Analysis, 29, 202-211.
• Dahir, A. M., Mahat, F., Ab Razak, N. H. and Bany-Ariffin, A. N. (2018). Revisiting the dynamic relationship between exchange rates and stock prices in BRICS countries: A wavelet analysis. Borsa Istanbul Review, 18(2), 101-113.
• Delis, M. D. and Mylonidis, N. (2011). The chicken or the egg? A note on the dynamic interrelation between government bond spreads and credit default swaps. Finance Research Letters, 8(3), 163-170.
• Dornbusch, R. (1976). Expectations and exchange rate dynamics. Journal of Political Economy, 84(6), 1161–1176.
• Dornbusch, R. and Fisher, S. (1980). Exchange rates and the current account. American Economic Review, 70(5), 960-971.
• Elmas, B. and Polat, M. (2014). Altın fiyatlarını etkileyen talep yönlü faktörlerin tespiti: 1988-2013 dönemi [Determination Demand Faktors of Affecting Gold Price: Period 1988-2013]. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 15(1), 171-187.
• Flannery, M. J. and James, C. M. (1984). The effect of interest rate changes on the common stock returns of financial institutions. The Journal of Finance, 39(4), 1141-1153.
• Forte, S. and Pena, J. I. (2009). Credit spreads: An empirical analysis on the informational content of stocks, bonds, and CDS. Journal of Banking & Finance, 33(11), 2013-2025.
• Frankel, J. A. (1984). Tests of Monetary and Portfolio Balance Models of Exchange Rate Determination. John Bilson and Richard Marston (Eds.) eds., In Exchange Rate Theory and Practice, Chicago: University of Chicago Press for NBER, (pp.239-260).
• García, M. M., Valle, C. T. and Marín, J. L. M. (2014). Sovereign bond spreads and credit default swap premia: cointegration and causality. Investment Management and Financial Innovations, 11(2), 47-59.
• Granger, C. W., Huangb, B. N. and Yang, C. W. (2000). A bivariate causality between stock prices and exchange rates: evidence from recent Asian flu. The Quarterly Review of Economics and Finance, 40(3), 337-354.
• Grinsted, A., Moore, J. C. and Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11(5/6), 561-566.
• Gün, M., Kutlu, M. and Karamustafa, O. (2016). Gezi parkı olaylarının Türkiye kredi temerrüt swapları (CDS) üzerine etkisi [The Effects of Gezi Park Protests on Turkey’s Credit Default Swaps (CDS)]. Journal of Business Research Turk, 557-575.
• Hacker, R. S., Karlsson, H. K. and Månsson, K. (2014). An investigation of the causal relations between exchange rates and interest rate differentials using wavelets. International Review of Economics & Finance, 29, 321-329.
• Hafner, C. M. and Herwartz, H. (2006). A Lagrange multiplier test for causality in variance. Economics letters, 93(1), 137-141. Hatemi-J, A. (2008). Tests for cointegration with two unknown regime shifts with an application to financial market integration. Empirical Economics, 35(3), 497-505.
• Ingalhalli, V. and Reddy, Y. V. (2016). A study on dynamic relationship between oil, gold, forex and stock markets in Indian context. Paradigm, 20(1), 83-91.
• Jain, A. and Biswal, P.C. (2016). Dynamic linkages among oil price, gold price, exchange rate, and stock market in India. Resources Policy, 49, 179-185.
• Jarrow, R. A. and Yu, F. (2001). Counterparty risk and the pricing of defaultable securities. The Journal of Finance, 56(5), 1765-1799.
• Kim, K. H. (2003). Dollar exchange rate and stock price: evidence from multivariate cointegration and error correction model. Review of Financial economics, 12(3), 301-313.
• Le, T. and Chang, Y. (2016). Dynamics between strategic commodities and financial variables: evidence from Japan. Resources Policy, 50, 1-9.
• Lee, J. and Strazicich, M. C. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. The Review of Economics and Statistics, 85(4), 1082-1089.
• Longstaff, P. F., Mithal, S. and Neis, E. (2003). The credit-default swap market: is credit protection priced correctly? Working Paper, Anderson School, UCLA, August, 1-31.
• Malhotra, J. and Corelli, A. (2018). The determinants of CDS spreads in multiple industry sectors: a comparison between the US and Europe. Risks, 6(3), 89.
• Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of finance, 29(2), 449-470.
• Norden, L. and Weber, M. (2009). The co‐movement of credit default swap, bond and stock markets: An empirical analysis. European financial management, 15(3), 529-562.
• Özpınar, Ö., Özman, H. and Doru, O. (2018). Kredi temerrüt takası (CDS) ve kur-faiz ilişkisi: Türkiye örneği [Credit Default Swap (CDS) & The Link Between Currency And Interest Rate: Turkey]. Bankacılık ve Sermaye Piyasası Araştırmaları Dergisi, 2(4), 31-45.
• Smith, G. (2001). The price of gold and stock price indices for the United States. The World Gold Council, 8(1), 1-16.
• Şahin, E. E. and Özkan, O. (2018). Kredi temerrüt takası, döviz kuru ve Bist100 Endeksi İlişkisi [Credit Default Swap, Exchange Rates and BİST100 Index Relationship: Cointegration and Causality Analysis]. Hitit Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 11(3), 1939-1945.
• Tiwari, A. K., Bhanja, N., Dar, A. B. and Islam, F. (2015). Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets. Empirical Economics, 48(2), 699-714.
• Tokat, H. A. (2013). Altın, döviz ve hisse senedi piyasalarında oynaklık etkileşimi mekanizmasının analizi [Volatility interaction mechanism among the gold, foreign exchange and equity markets]. İstanbul Üniversitesi Siyasal Bilgiler Fakültesi Dergisi, 48, 151-162.
• Toraman, C., Başarır, Ç. and Bayramoğlu, M. F. (2011). Altın fiyatlarını etkileyen faktörlerin tespiti üzerine: MGARCH modeli ile bir inceleme [Determination of factors affecting the price of gold: a study of MGARCH model]. Uluslararası Alanya İşletme Fakültesi Dergisi, 3(1), 1-20.
• Torrence, C. and Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of Climate, 12(8), 2679-2690.
• Yıldız, A. (2014). BIST100 endeksi ile alternatif yatırım araçlarının ilişkisi [The relationship between Bist100 index and alternative investment instruments]. SDÜ İİBF Dergisi, 19(2), 39-56.
• Zhang, G., Yau, J. and Fung, H. G. (2010). Do credit default swaps predict currency values?. Applied Financial Economics, 20(6), 439-458.
• Živkov, D., Njegiċ, J. and Peċanac, M. (2019). Wavelet analysis of the interdependence between stocks and bonds in the selected East European and Eurasian emerging markets. Ekonomický Časopis (Journal of Economics), 67(2), 175-194.