Araştırma Makalesi
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Volatility Spillovers Between Financial Asset and Commodity Prices: Evidence from Türkiye

Yıl 2024, Cilt: 5 Sayı: 2, 219 - 234, 31.12.2024
https://doi.org/10.62001/gsijses.1566592

Öz

This study examines volatility spillover effects among key commodities, the USD/TRY exchange rate, and the Borsa Istanbul (XU100) using CCC-GARCH and DCC-GARCH models to overcome ARCH model limitations. Analyzing daily data from 2010 to 2023, the results reveal significant short-term volatility clustering, especially influenced by recent price shocks. Long-term spillovers are notable, with persistent volatility connections indicated by high GARCH terms. Correlation analysis shows moderate positive correlations between Gold and Silver with XU100, while Crude Oil and Natural Gas exhibit weak correlations, suggesting limited short-term spillovers. A significant negative correlation exists between USD_TRY and XU100, highlighting the complex relationship between currency and stock market volatility. Overall, short-term spillovers are weak, but long-term relationships show strong persistence, especially regarding USD_TRY and Natural Gas. These findings stress the importance of nuanced volatility-based trading strategies during market turbulence and suggest that fund managers should consider investor behavior and biases when building portfolios.

Kaynakça

  • Abdul Kamal, M., Qayyum, U., Khan, S. & Ngozi Adeleye, B. (2022). Who is trading well with China? A gravity and constant market share analysis of exports of Pakistan and ASEAN in the Chinese market. Journal of Asian and African Studies, 57(6), 1089-1108.
  • Aitken, M., Almeida, N., Harris, F.H.D. & McInish, T.H. (2008) Financial analysts and price discovery. Accounting & Finance, 48(1), 1–24
  • Antonakakis, N. (2012). Exchange return co-movements and volatility spillovers before and after the introduction of Euro. Journal of International Financial Markets, Institutions and Money, 22(5), 1091-1109.
  • Aziz, T. & Hussain, A. (2021). Volatility spillovers of gold prices, oil prices, and economic policy uncertainty on the stock market of Pakistan. Global Business and Economics Review, 24(4), 344–359.
  • Bicondylar-Bheenick, E., Brooks, R., Chi, W. & Do, H.X. (2018). Volatility spillover between the US, Chinese and Australian stock markets. Australian Journal of Management, 43(2), 263–285.
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
  • Bollerslev, T. & Zhou, H. (2006). Volatility puzzles: a simple framework for gauging return-volatility regressions. Journal of Econometrics, 131(1-2), 123-150.
  • Bollerslev, T., Chou, R.Y. & Kroner, K.F. (1992). ARCH modelling in finance: A review of the theory and empirical evidence. Journal of Econometrics, 52(1–2), 5–59.
  • Bollerslev, T., Engle, R.F. & Woodredge, J.M. (1988). A capital asset pricing model with time-varying covariances. Journal of Political Economy, 96(1), 116–131.
  • Booth, G.G., So, R.W. & Tse, Y. (1999). Price discovery in the German equity index derivatives markets. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 19(6), 619–643.
  • Bouri, E.I. (2013). Correlation and volatility of the MENA equity markets in turbulent periods, and portfolio implications. Economics Bulletin, 33(2), 1575–1593.
  • Cevik, E.I., Dibooglu, S., Abdallah, A.A. & Al-Eisa, E.A. (2021). Oil prices, stock market returns, and volatility spillovers: Evidence from Saudi Arabia. International Economics and Economic Policy, 18(1), 157–175.
  • Choi, K. & Hammoudeh, S. (2010). Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment. Energy policy, 38(8), 4388-4399.
  • Dey, S. & Sampath, A. (2020). Returns, volatility and spillover–A paradigm shift in India?. The North American Journal of Economics and Finance, 52, 101–110 https://doiorg/101016/jnajef2019101110
  • Dickey, D.A. & Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431.
  • Dornbusch, R. & Fischer, S. (1980). Exchange rates and the current account. The American economic review, 70(5), 960-971.
  • Ebrahim, S.K. (2000). Volatility transmission between foreign exchange and money markets. Bank of Canada Working Paper, No: 2000-16. bankofcanadaca/2000/08/working-paper-2000-16/
  • Ederington, L.H. & Lee, J.H. (1993). How markets process information: News releases and volatility. The Journal of Finance, 48(4), 1161–1191.
  • Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350.
  • Engle, R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the econometric society, 987-1007.
  • Fedorova, E. & Saleem, K. (2009). Volatility spillovers between stock and currency markets: Evidence from emerging Eastern Europe. [Paper presentation] 22nd Australasian Finance and Banking Conference, https://ssrn com/abstract=1460645.
  • Francis, J., Lafond, R., Olsson, P. & Schipper, K. (2007). Information uncertainty and post‐earnings‐announcement‐drift. Journal of Business Finance & Accounting, 34(3‐4), 403-433.
  • Gahlot, R. (2019). An analytical study on effect of FIIs & DIIs on Indian stock market. Journal of Transnational Management, 24(2), 67–82.
  • Ghosh, S. (2014). Volatility spillover in the foreign exchange market: The Indian Experience. Macroeconomics and Finance in Emerging Market Economies, 7(1), 175–194.
  • Grobys, K., Ruotsalainen, J. & Äijö, J. (2018). Risk-managed industry momentum and momentum crashes. Quantitative Finance, 18(10), 1715-1733.
  • Jarungkitkul, W. & Sukcharoensin, S. (2016). Benchmarking the competitiveness of the ASEAN 5 equity markets: An application of Porter’s diamond model. Benchmarking: An International Journal, 23(5), 1312–1340.
  • Jebran, K., & Iqbal, A. (2016). Dynamics of volatility spillover between stock market and foreign exchange market: Evidence from Asian Countries. Financial Innovation, 2(1), 1–20.
  • Joshi, P. (2011). Return and volatility spill-overs among Asian stock markets. SAGE Open, 1(1) https://doiorg/101177/2158244011413474
  • Kanas, A. (2000). Volatility spillovers between stock returns and exchange rate changes: International evidence. Journal of business finance & accounting, 27(3‐4), 447-467.
  • Kang, S.H. & Yoon, S.M. (2013). Modeling and forecasting the volatility of petroleum futures prices. Energy Economics, 36, 354-362.
  • Oberholzer, N. & von Boetticher, S.T. (2015). Volatility spill-over between the JSE/FTSE indices and the South African Rand. Procedia Economics and Finance, 24, 501-510.
  • Okpara, G.C. & Odionye, J.C. (2012). The direction of volatility spillover between stock prices and exchange rate: evidence from Nigeria. Elixir Finance, 42, 6410-6414.
  • Toparlı, E.A, Çatık, A.N. & Balcılar, M. (2019). The impact of oil prices on the stock returns in Turkey: A TVP-VAR approach. Physica A: Statistical Mechanics and its Applications, 535(C).
  • Yang, M.J. & Liu, M.Y. (2012). The forecasting power of the volatility index in emerging markets: Evidence from the Taiwan stock market. International Journal of Economics and Finance, 4(2), 217-231.
  • Yang, S.Y. & Doong, S.C. (2004). Price and volatility spillovers between stock prices and exchange rates: empirical evidence from the G-7 countries. International Journal of Business and Economics, 3(2), 139.

Finansal Varlık ve Emtia Fiyatları Arasındaki Oynaklık Yayılımları: Türkiye'den Bulgular

Yıl 2024, Cilt: 5 Sayı: 2, 219 - 234, 31.12.2024
https://doi.org/10.62001/gsijses.1566592

Öz

Bu çalışma, ARCH modeli sınırlamalarını aşmak için CCC-GARCH ve DCC-GARCH modellerini kullanarak, temel emtialar olan USD_TRY döviz kuru ve Borsa İstanbul (XU100) arasındaki oynaklık yayılma etkilerini incelemektedir. 2010-2023 yılları arasındaki günlük verileri analiz eden sonuçlar, özellikle son fiyat şoklarından etkilenen önemli kısa vadeli oynaklık kümelenmesini ortaya koymaktadır. Uzun vadeli yayılmalar dikkat çekicidir ve yüksek GARCH terimleri ile gösterilen kalıcı oynaklık bağlantıları vardır. Korelasyon analizi, Altın ve Gümüş ile XU100 arasında orta düzeyde pozitif korelasyonlar gösterirken, Ham Petrol ve Doğal Gaz zayıf korelasyonlar sergilemektedir ve bu da sınırlı kısa vadeli yayılmaları düşündürmektedir. USD_TRY ile XU100 arasında önemli bir negatif korelasyon bulunmaktadır ve bu, döviz kuru ile borsa oynaklığı arasındaki karmaşık ilişkiyi vurgulamaktadır. Genel olarak, kısa vadeli yayılmalar zayıf görünse de uzun vadeli ilişkiler, özellikle USD_TRY ve Doğal Gaz ile ilgili olarak güçlü bir kalıcılık göstermektedir. Bu bulgular, piyasa dalgalanmaları sırasında oynaklık temelli işlem stratejilerinin önemini vurgulamakta ve fon yöneticilerinin portföy oluştururken yatırımcı davranışlarını ve önyargılarını dikkate almaları gerektiğini ortaya koymaktadır.

Kaynakça

  • Abdul Kamal, M., Qayyum, U., Khan, S. & Ngozi Adeleye, B. (2022). Who is trading well with China? A gravity and constant market share analysis of exports of Pakistan and ASEAN in the Chinese market. Journal of Asian and African Studies, 57(6), 1089-1108.
  • Aitken, M., Almeida, N., Harris, F.H.D. & McInish, T.H. (2008) Financial analysts and price discovery. Accounting & Finance, 48(1), 1–24
  • Antonakakis, N. (2012). Exchange return co-movements and volatility spillovers before and after the introduction of Euro. Journal of International Financial Markets, Institutions and Money, 22(5), 1091-1109.
  • Aziz, T. & Hussain, A. (2021). Volatility spillovers of gold prices, oil prices, and economic policy uncertainty on the stock market of Pakistan. Global Business and Economics Review, 24(4), 344–359.
  • Bicondylar-Bheenick, E., Brooks, R., Chi, W. & Do, H.X. (2018). Volatility spillover between the US, Chinese and Australian stock markets. Australian Journal of Management, 43(2), 263–285.
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
  • Bollerslev, T. & Zhou, H. (2006). Volatility puzzles: a simple framework for gauging return-volatility regressions. Journal of Econometrics, 131(1-2), 123-150.
  • Bollerslev, T., Chou, R.Y. & Kroner, K.F. (1992). ARCH modelling in finance: A review of the theory and empirical evidence. Journal of Econometrics, 52(1–2), 5–59.
  • Bollerslev, T., Engle, R.F. & Woodredge, J.M. (1988). A capital asset pricing model with time-varying covariances. Journal of Political Economy, 96(1), 116–131.
  • Booth, G.G., So, R.W. & Tse, Y. (1999). Price discovery in the German equity index derivatives markets. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 19(6), 619–643.
  • Bouri, E.I. (2013). Correlation and volatility of the MENA equity markets in turbulent periods, and portfolio implications. Economics Bulletin, 33(2), 1575–1593.
  • Cevik, E.I., Dibooglu, S., Abdallah, A.A. & Al-Eisa, E.A. (2021). Oil prices, stock market returns, and volatility spillovers: Evidence from Saudi Arabia. International Economics and Economic Policy, 18(1), 157–175.
  • Choi, K. & Hammoudeh, S. (2010). Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment. Energy policy, 38(8), 4388-4399.
  • Dey, S. & Sampath, A. (2020). Returns, volatility and spillover–A paradigm shift in India?. The North American Journal of Economics and Finance, 52, 101–110 https://doiorg/101016/jnajef2019101110
  • Dickey, D.A. & Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427–431.
  • Dornbusch, R. & Fischer, S. (1980). Exchange rates and the current account. The American economic review, 70(5), 960-971.
  • Ebrahim, S.K. (2000). Volatility transmission between foreign exchange and money markets. Bank of Canada Working Paper, No: 2000-16. bankofcanadaca/2000/08/working-paper-2000-16/
  • Ederington, L.H. & Lee, J.H. (1993). How markets process information: News releases and volatility. The Journal of Finance, 48(4), 1161–1191.
  • Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350.
  • Engle, R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the econometric society, 987-1007.
  • Fedorova, E. & Saleem, K. (2009). Volatility spillovers between stock and currency markets: Evidence from emerging Eastern Europe. [Paper presentation] 22nd Australasian Finance and Banking Conference, https://ssrn com/abstract=1460645.
  • Francis, J., Lafond, R., Olsson, P. & Schipper, K. (2007). Information uncertainty and post‐earnings‐announcement‐drift. Journal of Business Finance & Accounting, 34(3‐4), 403-433.
  • Gahlot, R. (2019). An analytical study on effect of FIIs & DIIs on Indian stock market. Journal of Transnational Management, 24(2), 67–82.
  • Ghosh, S. (2014). Volatility spillover in the foreign exchange market: The Indian Experience. Macroeconomics and Finance in Emerging Market Economies, 7(1), 175–194.
  • Grobys, K., Ruotsalainen, J. & Äijö, J. (2018). Risk-managed industry momentum and momentum crashes. Quantitative Finance, 18(10), 1715-1733.
  • Jarungkitkul, W. & Sukcharoensin, S. (2016). Benchmarking the competitiveness of the ASEAN 5 equity markets: An application of Porter’s diamond model. Benchmarking: An International Journal, 23(5), 1312–1340.
  • Jebran, K., & Iqbal, A. (2016). Dynamics of volatility spillover between stock market and foreign exchange market: Evidence from Asian Countries. Financial Innovation, 2(1), 1–20.
  • Joshi, P. (2011). Return and volatility spill-overs among Asian stock markets. SAGE Open, 1(1) https://doiorg/101177/2158244011413474
  • Kanas, A. (2000). Volatility spillovers between stock returns and exchange rate changes: International evidence. Journal of business finance & accounting, 27(3‐4), 447-467.
  • Kang, S.H. & Yoon, S.M. (2013). Modeling and forecasting the volatility of petroleum futures prices. Energy Economics, 36, 354-362.
  • Oberholzer, N. & von Boetticher, S.T. (2015). Volatility spill-over between the JSE/FTSE indices and the South African Rand. Procedia Economics and Finance, 24, 501-510.
  • Okpara, G.C. & Odionye, J.C. (2012). The direction of volatility spillover between stock prices and exchange rate: evidence from Nigeria. Elixir Finance, 42, 6410-6414.
  • Toparlı, E.A, Çatık, A.N. & Balcılar, M. (2019). The impact of oil prices on the stock returns in Turkey: A TVP-VAR approach. Physica A: Statistical Mechanics and its Applications, 535(C).
  • Yang, M.J. & Liu, M.Y. (2012). The forecasting power of the volatility index in emerging markets: Evidence from the Taiwan stock market. International Journal of Economics and Finance, 4(2), 217-231.
  • Yang, S.Y. & Doong, S.C. (2004). Price and volatility spillovers between stock prices and exchange rates: empirical evidence from the G-7 countries. International Journal of Business and Economics, 3(2), 139.
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mikro İktisat (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Emmanuel Dweh Togba

Mert Ural 0000-0003-3252-846X

Yayımlanma Tarihi 31 Aralık 2024
Gönderilme Tarihi 14 Ekim 2024
Kabul Tarihi 16 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 5 Sayı: 2

Kaynak Göster

APA Togba, E. D., & Ural, M. (2024). Volatility Spillovers Between Financial Asset and Commodity Prices: Evidence from Türkiye. Uluslararası Sosyal Ve Ekonomik Çalışmalar Dergisi, 5(2), 219-234. https://doi.org/10.62001/gsijses.1566592