Journals / Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2025 / Sayı: 72

Dynamic linkages between gold, bitcoin, currency basket and BIST100 in Türkiye: DCC-GARCH R2 decomposition and portfolio strategies

Türkiye’de altın, bitcoin, sepet kur ve BİST100 arasındaki dinamik ilişkiler: DCC-GARCH R² ayrıştırması ve portföy stratejileri

Deniz Sevinç(ANADOLU ÜNİVERSİTESİ)0000-0002-6223-9450
Pages
39–49
Publication Date
2025-12-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results indicate that modern strategies offer the highest Sharpe ratios, whereas traditional approaches appear more suitable for risk-averse investors.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study investigates the dynamic relationships between gram gold, Bitcoin (BTC/TRY), a currency basket (50% USD/TRY + 50% EUR/TRY), and the BIST100 index within the Turkish financial market.
📊
Key Findings & Data:Using daily data from 2018 to 2024, the analysis employs the R² decomposed connectedness method based on the DCC-GARCH model.
💡
Conclusion & Impact:The results indicate that modern strategies offer the highest Sharpe ratios, whereas traditional approaches appear more suitable for risk-averse investors.
🔬Design:Modeling & Simulation
📍Scope:2018 Verileri
⚙️Variables:dinamik bağlantılar · DCC-GARCH · R2 bağlantı ölçümü

Abstract

This study investigates the dynamic relationships between gram gold, Bitcoin (BTC/TRY), a currency basket (50% USD/TRY + 50% EUR/TRY), and the BIST100 index within the Turkish financial market. Using daily data from 2018 to 2024, the analysis employs the R² decomposed connectedness method based on the DCC-GARCH model. This approach enables the time-varying assessment of cross-market interactions and the identification of significant contagion effects, particularly during periods of crisis and high volatility. The results reveal strong positive connectedness among gold, Bitcoin, and the currency basket, while the BIST100 index exhibits weak and negative correlations with these assets. This highlights the importance of diversification rather than holding equities alone. Moreover, dynamic portfolios with minimal risk were constructed based on the connectedness findings, and their performance was evaluated using hedging effectiveness metrics. The results indicate that modern strategies offer the highest Sharpe ratios, whereas traditional approaches appear more suitable for risk-averse investors. Overall, the study underscores the importance of incorporating dependency dynamics into portfolio diversification decisions and contributes to systemic risk monitoring from a policy perspective.

Özet

Bu çalışma, Türkiye finans piyasasında gram altın, Bitcoin, sepet kur (%50 USD/TRY + %50 EUR/TRY) ve BİST100 endeksi arasındaki dinamik bağlantıları incelemekte ve yatırımcılar için risk azaltıcı portföy stratejileri önermektedir. Araştırmada 2018–2024 dönemine ait günlük veriler kullanılarak DCC-GARCH modeline dayalı R2 ayrıştırılmış bağımlılık yöntemi uygulanmıştır. Bu yöntem sayesinde piyasalar arası etkileşimler zamana bağlı olarak analiz edilmiş, özellikle kriz ve yüksek volatilite dönemlerinde önemli yayılma etkileri gözlemlenmiştir. Altın, sepet kur ve Bitcoin arasında güçlü pozitif bağlılık bulunurken, BİST100 ile bu varlıklar arasında negatif ve zayıf korelasyonlar tespit edilmiştir. Bu durum, pay senetlerine tek başına yatırım yapmak yerine çeşitlendirmenin önemini göstermektedir. Ayrıca, bağımlılık bulgularına dayalı olarak minimum risk taşıyan dinamik portföyler oluşturulmuş; bu portföylerin etkinliği riskten korunma etkinliği ölçütleriyle değerlendirilmiştir. Sonuçlar modern stratejilerin en yüksek Sharpe oranlarına sahip olduğunu sunarken, geleneksel stratejilerin riskten kaçınan yatırımcılar için daha uygun olduğunu göstermektedir. Çalışma, yatırımcıların portföy çeşitlendirmesinde bağımlılık dinamiklerini dikkate almalarının önemini vurgularken, politika yapıcılar için de sistemik riskin izlenmesine katkı sağlamaktadır.

🔖

Cite This Article

Sevinç, D. (2025). Dynamic linkages between gold, bitcoin, currency basket and BIST100 in Türkiye: DCC-GARCH R2 decomposition and portfolio strategies. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Sayı: 72, 39–49. https://doi.org/10.18070/erciyesiibd.1692319

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (60)

  1. Akca, K., & Ozturk, S. S. (2016). The Effect of 2008 Crisis on the Volatility Spillovers among Six Major Markets. International Review of Finance, 16(1), 169-178. https://doi.org/10.1111/IRFI.12071
  2. Anadolu Ajansı. (2024). Türkiye’de her 5 kişiden biri kripto yatırımcısı. https://www.aa.com.tr/tr/ekonomi/turkiyede-her-5-kisiden-biri-kripto-yatirimcisi/3416905
  3. Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2021). The impact of Euro through time: Exchange rate dynamics under different regimes. International Journal of Finance & Economics, 26(1), 1375-1408. https://doi.org/10.1002/IJFE.1854
  4. Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2020). Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness. Energy Economics, 91, 104762. https://doi.org/10.1016/J.ENECO.2020.104762
  5. Arık, E. (2025). A Cointegration Relationship Between Cryptocurrencies and Financial Instruments Under Structural Breaks. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 46, 201-216. https://doi.org/10.18092/ULIKIDINCE.1538837
  6. Baur, D. G., & 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. https://doi.org/10.1111/J.1540-6288.2010.00244.X
  7. Baur, D. G., & McDermott, T. K. (2010). Is gold a safe haven? International evidence. Journal of Banking & Finance, 34(8), 1886-1898. https://doi.org/10.1016/J.JBANKFIN.2009.12.008
  8. Baur, D. G., & Smales, L. A. (2020). Hedging geopolitical risk with precious metals. Journal of Banking & Finance, 117, 105823. https://doi.org/10.1016/J.JBANKFIN.2020.105823
  9. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
  10. Bouri, E., Das, M., Gupta, R., & Roubaud, D. (2018). Spillovers between Bitcoin and other assets during bear and bull markets. Applied Economics, 50(55), 5935-5949. https://doi.org/10.1080/00036846.2018.1488075;SUBPAGE:STRING:FULL
  11. Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier? Finance Research Letters, 20, 192-198. https://doi.org/10.1016/J.FRL.2016.09.025
  12. Broadstock, D. C., Chatziantoniou, I., & Gabauer, D. (2022). Minimum Connectedness Portfolios and the Market for Green Bonds: Advocating Socially Responsible Investment (SRI) Activity. Içinde C. Floros & I. Chatziantoniou (Ed.), Applications in Energy Finance (ss. 217-253). Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-92957-2_9
  13. Butler, D., & Sevgili, C. (2022). Turkey’s inflation hits new 24-year high beyond 80%. Reuters. https://www.reuters.com/world/middle-east/turkeys-inflation-touches-new-24-year-high-802-2022-09-05/
  14. Capie, F., Mills, T. C., & Wood, G. (2005). Gold as a hedge against the dollar. Journal of International Financial Markets, Institutions and Money, 15(4), 343-352. https://doi.org/10.1016/J.INTFIN.2004.07.002
  15. Cheah, E. T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32-36. https://doi.org/10.1016/J.ECONLET.2015.02.029
  16. Christoffersen, P. (1998). Evaluating Interval Forecasts. International Economic Review, 39(4), 862. https://doi.org/10.2307/2527341
  17. Christoffersen, P., Errunza, V., Jacobs, K., & Jin, X. (2014). Correlation dynamics and international diversification benefits. International Journal of Forecasting, 30(3), 807-824. https://doi.org/10.1016/J.IJFORECAST.2014.01.001
  18. Christoffersen, P., Hahn, J., & Inoue, A. (2001). Testing and comparing Value-at-Risk measures. Journal of Empirical Finance, 8(3), 325-342. https://doi.org/10.1016/S0927-5398(01)00025-1
  19. Christoffersen, P., & Pelletier, D. (2004). Backtesting Value-at-Risk: A Duration-Based Approach. Journal of Financial Econometrics, 2, 84-108. https://papers.ssrn.com/abstract=821715
  20. Cingoz, F., & Kendirli, S. (2019). Altın Fiyatları, Döviz Kuru ve Borsa İstanbul Arasındaki İlişki. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 4(4), 545-554. https://doi.org/10.29106/FESA.649254
  21. Cocca, T., Gabauer, D., & Pomberger, S. (2024). Clean energy market connectedness and investment strategies: New evidence from DCC-GARCH R2 decomposed connectedness measures. Energy Economics, 136, 107680. https://doi.org/10.1016/J.ENECO.2024.107680
  22. Çam, S. (2024). An Analysis of The Long-Term Asymmetric Relationship Between Gold Prices, Exchange Rates, Yields of Government Bond, and The BIST100 Index. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 33(1), 297-310. https://doi.org/10.35379/CUSOSBIL.1371599
  23. Çikrikçi, M., & Özyeşil, M. (2018). Is Bitcoin Becoming An Alternative Investment Option For Turkey? A Comparative Investigation Through The Non-Linear Time Series Analysis. Research Journal of Business and Management, 5(4), 250-261. https://doi.org/10.17261/PRESSACADEMIA.2018.1009
  24. Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/J.IJFORECAST.2011.02.006
  25. Ederington, L. H. (1979). The Hedging Performance of the New Futures Markets. The Journal of Finance, 34(1), 157. https://doi.org/10.2307/2327150
  26. Engle, R. (2002). Dynamic Conditional Correlation. Journal of Business & Economic Statistics, 20(3), 339-350. https://doi.org/10.1198/073500102288618487
  27. Engle, R. F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric Reviews, 5(1), 1-50. https://doi.org/10.1080/07474938608800095
  28. Engle, R. F., Ng, V. K., Hsieh, D., Kaul, G., Kodres, L., Kon, S., Narayanan, M. P., Schwert, B., Seguin, P., Stambaugh, R., & Stulz, R. (1993). Measuring and Testing the Impact of News on Volatility. The Journal of Finance, 48(5), 1749-1778. https://doi.org/10.1111/J.1540-6261.1993.TB05127.X
  29. Erdaş, M. L., & Çağlar, A. E. (2018). Analysis of the relationships between Bitcoin and exchange rate, commodities and global indexes by asymmetric causality test. Eastern Journal of European Studies, 9(2), 27-45. www.ejes.uaic.ro
  30. Fisher, T. J., & Gallagher, C. M. (2012). New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing. Journal of the American Statistical Association, 107(498), 777-787. https://doi.org/10.1080/01621459.2012.688465
  31. Gabauer, D., Chatziantoniou, I., & Stenfors, A. (2023). Model-free connectedness measures. Finance Research Letters, 54, 103804. https://doi.org/10.1016/J.FRL.2023.103804
  32. Genizi, A. (1993). Decomposition of R2 In Multiple Regression With Correlated Regressors. Statistica Sinica, 3(2), 407-420. https://www.jstor.org/stable/24304966?seq=1
  33. Giudici, P., & Abu-Hashish, I. (2019). What determines bitcoin exchange prices? A network VAR approach. Finance Research Letters, 28, 309-318. https://doi.org/10.1016/J.FRL.2018.05.013
  34. Giudici, P., Leach, T., & Pagnottoni, P. (2022). Libra or Librae? Basket based stablecoins to mitigate foreign exchange volatility spillovers. Finance Research Letters, 44, 102054. https://doi.org/10.1016/J.FRL.2021.102054
  35. Glosten, L. R., Jagannathan, R., Runkle, D. E., Breen, W., Hansen, L., Hess, P., Hsieh, D., Judson, R., Kocher-Lakota, N., Mcdonald, R., Nelson, D., & Siegel, D. (1993). On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. https://doi.org/10.1111/J.1540-6261.1993.TB05128.X
  36. Henriques, I., & Sadorsky, P. (2018). Can Bitcoin Replace Gold in an Investment Portfolio? Journal of Risk and Financial Management 2018, Vol. 11, Page 48, 11(3), 48. https://doi.org/10.3390/JRFM11030048
  37. Higgins, M. L., & Bera, A. K. (1992). A Class of Nonlinear Arch Models. International Economic Review, 33(1), 137. https://doi.org/10.2307/2526988
  38. Hung, N. T. (2022). Asymmetric connectedness among S&P 500, crude oil, gold and Bitcoin. Managerial Finance, 48(4), 587-610. https://doi.org/10.1108/MF-08-2021-0355/FULL/PDF
  39. İlarslan, K. (2017). Altın Fiyatları ile Borsa Endeksi Arasında Eş Bütünleşme ve Nedensellik İlişkisi. Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi, 4(6), 114-125. https://dergipark.org.tr/tr/pub/asead/issue/52672/694272
  40. Kayral, İ. E., & Tandoğan, N. Ş. (2020). BİST100, Döviz Kurları ve Altının Getiri ve Volatilitesinde COVID-19 Etkisi. Gaziantep Üniversitesi Sosyal Bilimler Dergisi, 19(COVID-19 Special Issue), 687-701. https://doi.org/10.21547/JSS.786384
  41. Kılıç, E., & Uçaktürk, M. (2020). ALTERNATİF YATIRIM ARAÇLARININ MENKUL KIYMETLER BORSASI İLE ETKİLEŞİMİ. Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 21, 499-518. https://doi.org/10.29029/BUSBED.735972
  42. Klein, T., Pham Thu, H., & Walther, T. (2018). Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis, 59, 105-116. https://doi.org/10.1016/J.IRFA.2018.07.010
  43. Kristoufek, L. (2015). What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis. PLOS ONE, 10(4), e0123923. https://doi.org/10.1371/JOURNAL.PONE.0123923
  44. Kroner, K. F., & Ng, V. K. (1998). Modeling Asymmetric Comovements of Asset Returns. The Review of Financial Studies, 11(4), 817-844. https://doi.org/10.1093/RFS/11.4.817
  45. Lamine, A., Jeribi, A., & Fakhfakh, T. (2024). Spillovers between cryptocurrencies, gold and stock markets: implication for hedging strategies and portfolio diversification under the COVID-19 pandemic. Journal of Economics, Finance and Administrative Science, 29(57), 21-41. https://doi.org/10.1108/JEFAS-09-2021-0173/FULL/PDF
  46. Li, W. (2021). COVID-19 and asymmetric volatility spillovers across global stock markets. The North American Journal of Economics and Finance, 58, 101474. https://doi.org/10.1016/j.najef.2021.101474
  47. Longin, F., & Solnik, B. (2001). Extreme correlation of international equity markets. Journal of Finance, 56(2), 649-676. https://doi.org/10.1111/0022-1082.00340;PAGEGROUP:STRING:PUBLICATION
  48. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91. https://doi.org/10.2307/2975974
  49. Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. https://www.jstor.org/stable/2938260
  50. Schwert, G. W. (1990). Stock Volatility and the Crash of ’87. The Review of Financial Studies, 3(1), 77-102. https://doi.org/10.1093/RFS/3.1.77
  51. Serttaş, F. Ö. (2022). Altın ve Kripto Paraların BİST100 Endeksi için Hedge ve Güvenli Liman Özellikleri: Covid-19 Salgını Etkileri. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24(2), 622-635. https://doi.org/10.26745/AHBVUIBFD.1110109
  52. Sharpe, W. F. (1994). The Sharpe Ratio. The Journal of Portfolio Management, 21(1), 49-58. https://doi.org/10.3905/JPM.1994.409501
  53. Singh, M., & Mattackal, P. (2023). Cryptoverse: Digital coins lure inflation-weary Argentines and Turks. Reuters. https://www.reuters.com/technology/cryptoverse-digital-coins-lure-inflation-weary-argentines-turks-2023-05-02/
  54. Şeker, K., & Akpolat, A. G. (2025). Dynamic Stochastic Volatility Spillover Between Bitcoin and Precious Metals. Uluslararası Ekonomi İşletme ve Politika Dergisi, 9(1), 53-72. https://doi.org/10.29216/UEIP.1596577
  55. 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
  56. Tokat, H. A. (2013). Altın, Döviz ve Hisse Senedi Piyasalarında Oynaklık Etkileşimi Mekanizmasının Analizi. İstanbul Üniversitesi Siyasal Bilgiler Fakültesi Dergisi, 48, 151-162. https://dergipark.org.tr/tr/pub/iusiyasal/issue/630/6414
  57. Wang, G. J., Xie, C., Wen, D., & Zhao, L. (2019). When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin. Finance Research Letters, 31, 489-497. https://doi.org/10.1016/J.FRL.2018.12.028
  58. Yu, J., Shang, Y., & Li, X. (2021). Dependence and Risk Spillover among Hedging Assets: Evidence from Bitcoin, Gold, and USD. Discrete Dynamics in Nature and Society, 2021(1), 2010705. https://doi.org/10.1155/2021/2010705
  59. Zakoian, J. M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. https://doi.org/10.1016/0165-1889(94)90039-6
  60. Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. https://www.jstor.org/stable/2938260