Research Article
BibTex RIS Cite

IS BITCOIN MORE THAN A DIVERSIFIER FOR COMMODITIES? RANGE-BASED ANALYSIS VIA cDCC-GARCH

Year 2022, Volume: 7 Issue: 2, 227 - 240, 30.06.2022

Tuğrul Kandemir Halilibrahim Gökgöz

https://doi.org/10.29106/fesa.1092764
Cited By: 2

Abstract

The purpose of this study is to examine the diversifying role of Bitcoin for commodities and its interaction with commodities. Within the scope of the study, the daily data set consisting of Bitcoin, gold, silver, commodity index, crude oil, and energy commodities index variables covering the period 17.09.2014 - 24.11.2021 was transformed into Garman-Klass series, and dynamic conditional correlation models were applied. As a result of the application, it was observed that the most suitable model to test the interaction between Bitcoin and commodities was cDCC-GARCH. The interaction between Bitcoin and commodities (excluding silver) was negative; It has been determined that the interaction between the commodities is positive. The findings show that Bitcoin is a better diversifier for commodities (except silver) than other commodities and acts as a hedge when included in a portfolio of commodities.

Keywords

Bitcoin Cryptocurrency Commodity Portfolio Diversification Safe Haven cDCC-GARCH Volatility Volatility Spillover Garman-Klass

References

  • Aielli, G. P. (2006), Consistent Estimation of Large Scale Dynamic Conditional Correlations, Unpublished paper, University of Florence.
  • Aielli, G. P., (2013). Dynamic conditional correlation: on properties and estimation, Journal of Business & Economic Statistics, 31, 282–299.
  • Alizadeh, S., Brandt, M. W., Diebold, F. X. (2002). Range-based estimation of stochastic volatility models. Journal of Finance, 57, 1047–1091. http://dx.doi.org/10.2139/ssrn.267788.
  • Al-Khazali, O., Bouri, E., & Roubaud, D. (2018). The Impact of Positive and Negative Macroeconomic News Surprises: Gold Versus Bitcoin. Economics Bulletin, 38 (1), 373-382. http://dx.doi.org/10.2139/ssrn.3382828
  • Aslanidis, N., Bariviera, A. F., & Martinez-Ibanez, O. (2019). An Analysis of Cryptocurrencies Conditional Cross Correlations. Finance Research Letters, 31, 130-137. https://doi.org/10.1016/j.frl.2019.04.019
  • Awartani, B., Maghyereh, A. I. (2013). Dynamic Spillovers between Oil and Stock Markets in the Gulf Cooperation Council Countries. Energy Economics, 36, 28–42. https://doi.org/10.1016/j.eneco.2012.11.024
  • Baur, D. K., Dimpfl, T., Kuck, K. (2018). Bitcoin, gold and the US dollar – A replication and extension. Finance Research Letters, 25, 103-110. https://doi.org/10.1016/j.frl.2017.10.012.
  • Baur, D. K., Hong, K., Lee, A. (2015). Bitcoin: Currency or Asset? Hamburg. Kühne Logistics University.
  • Baur, D.G. , Lucey, B.M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financ. Rev. 45, 217–229. https://doi.org/10.1111/j.1540-6288.2010.00244.x.
  • Beneki, C., Koulis, A., Kyriazis, N.A., Papadamou, S. (2019). Investigating volatility transmission and hedging properties between Bitcoin and Ethereum. Res. Int. Bus. Finance 48, 219–227. https://doi.org/10.1016/j.ribaf.2019.01.001.
  • Bhuiyan, R. A., Husain, A., Zhang, C. (2021). A wavelet approach for causal relationship between bitcoin and conventional asset classes. Resources Policy, 71, 101971. https://doi.org/10.1016/j.resourpol.2020.101971.
  • Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroscedasticity. Journal of Econometrics, 31, 307-327.
  • Bouoiyour, J., & Selmi, R. (2015). What Does Bitcoin Look Like? Annals of Economics and Finance, 16 (2), 449-492.
  • 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
  • Bouri, E., Gupta, R., Tiwari, A.K., Roubaud, D. (2017c). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Res. Lett. 23, 87-95. https://doi.org/10.1016/j.frl.2017.02.009.
  • Bouri, E., Jalkh, N., Molnár, P., & Roubaud, D. (2017b). Bitcoin for Energy Commodities before and After the December 2013 Crash: Diversifier, Hedge or Safe Haven? Applied Economics, 49 (50), 5063-5073. SSRN: https://ssrn.com/abstract=2925783
  • Bouri, E., Molnar, P., Azzi , G., Roubaud, D., & Hagfors , L. (2017a). On the Hedge and Safe Haven Properties of Bitcoin: Is it Really more than a Diversifier? Finance Research Letters, 20, 192-198. http://dx.doi.org/10.1016/j.frl.2016.09.025.
  • Bouri, E., Shahzad, S. J., Roubaud, D., Kristoufek, L., & Lucey, B. (2020). Bitcoin, Gold, and Commodities as Safe Havens for Stocks: New Insight through Wavelet Analysis. The Quarterly Review of Economics and Finance, 77, 156-164. https://doi.org/10.1016/j.qref.2020.03.004.
  • Brandt, M. W., Jones, C. S. (2006). Volatility forecasting with RangeBased EGARCH models. Journal of Business and Economic Statistics, 24 (4), 470–486. https://doi.org/10.1198/073500106000000206.
  • Bri`ere, M., Oosterlinck, K., Szafarz, A. (2015). Virtual currency, tangible return: portfolio diversification with Bitcoin. J. Asset Manag. 16, 365–373. http://dx.doi.org/10.2139/ssrn.2324780.
  • Chou, R. Y. (2005). Forecasting financial volatilities with extreme values: the conditional autoregressive range (CARR) model. Journal of Money, Credit and Banking, 37 (3), 561–582. DOI:10.1353/mcb.2005.0027
  • Chou, R. Y. (2006). Modeling the asymmetry of stock movements using price ranges. Advances in Econometrics, 20, 231–258. https://doi.org/10.1016/S0731-9053(05)20009-9.
  • Chou, R. Y. Chou, H., Liu, N. (2010). Range volatility models and their applications in finance. Handbook of Quantitative Finance and Risk Management, 1273-1281, Springer. New York. DOI:10.1007/978-0-387-77117-5_83.
  • Chou, R. Y.,Chou, H., N. Liu. (2015). “Range Volatility: A Review of Models and Empirical Studies.” In Hand-book of Financial Econometrics and Statistics, 2029–2050. New York, NY: Springer.
  • Ciaian, P., Rajcaniova, M., & Kancs, D. A. (2016). The Economics of Bitcoin Price Formation. Applied Economics, 48, 1799-1815. https://doi.org/10.1080/00036846.2015.1109038.
  • Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018). Exploring the Dynamic Relationships between Cryptocurrencies and other Financial Assets. Economics Letters, 165, 28-34. https://doi.org/10.1016/j.econlet.2018.01.004.
  • Das, D., Le Roux, C.L., Jana, R.K., Dutta, A. (2020). Does Bitcoin Hedge Crude Oil Implied Volatility and Structural Shocks? A Comparison with Gold, Commodity and The US Dollar. Finance Research Letters 36, 101335. https://doi.org/10.1016/j.frl.2019.101335
  • Do, A., Powell, R., Yong, J., Singh, A. (2019). Time-varying asymmetric volatility spillover between global markets and China’s A, B and H-shares using EGARCH and DCC-EGARCH models, The North American Journal of Economics and Finance, Vol. 54. https://doi.org/10.1016/j.najef.2019.101096
  • Dyhrberg, A. H. (2016). Bitcoin, Gold and the Dollar – A GARCH Volatility. Finance Research Letters, 16, 85-92. http://dx.doi.org/10.1016/j.frl.2015.10.008.
  • Eisl, A., Gasser, S., Weinmayer, K. (2015). Caveat Emptor: Does Bitcoin Improve Portfolio Diversification? http://dx.doi.org/10.2139/ssrn.2408997.
  • Garman, M. B., & Klass, M. J. (1980). On the Estimation of Security Price Volatilities from Historical Data. The Journal of Business, 53 (1), 67–7.
  • Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2019). Portfolio Diversification with Virtual Currency: Evidence from Bitcoin. International Review of Financial Analysis, 63, 431-437. https://doi.org/10.1016/j.irfa.2018.03.004.
  • Halaburda, H., Gandal, N. (2014). Can we predict the winner in a market with network effects? Competition in cryptocurrency market," in Games 7 (3), 16, NET Institute Working Paper No. 14-17. http://dx.doi.org/10.2139/ssrn.2506463.
  • Jareno, F., de la Gonzalez, M., Tolentino, M., Sierra, K. (2020). Bitcoin and Gold price returns: a quantile regression and NARDL analysis. Resour. Pol. 67, 1–16. https://doi.org/10.1016/j.resourpol.2020.101666.
  • Jiang, S., Li, Y., Luc, Q., Wang, S., Wei, Y. (2022). Volatility communicator or receiver? Investigating volatility spillover mechanisms among Bitcoin and other financial markets. Research in International Business and Finance, 59, 101543. https://doi.org/10.1016/j.ribaf.2021.101543.
  • Klein, T., Thu, H.P., Walther, T. (2018). Bitcoin is not the New Gold – a comparison of volatility, correlation, and portfolio performance. Int. Rev. Financ. Anal. 59, 105–116. https://doi.org/10.1016/j.irfa.2018.07.010.
  • Kurka, J. (2019). Do Cryptocurrencies and Traditional Asset Classes Influence Each Other? Finance Research Letters, 31, 38–4. https://doi.org/10.1016/j.frl.2019.04.018.
  • Li, X., Wang, C. A. (2017). Quantile spillovers and dependence between Bitcoin, equities and strategic commodities. Economic Modelling, 93, 230-258. https://doi.org/10.1016/j.econmod.2020.07.012.
  • Lin, M. Y., An, C. L. (2021). The relationship between Bitcoin and resource commodity futures: Evidence from NARDL approach. Resources Policy, 74, 102383. https://doi.org/10.1016/j.resourpol.2021.102383.
  • Lucey, B., Larkin, C., O’Connor, F. (2014). Gold Markets around the World – Who Spills over What, to Whom, When? Applied Economics Letters, 21 (13), 887–892. https://doi.org/10.1080/13504851.2014.896974.
  • Lyócsa, S. (2014). Growth-Returns Nexus: Evidence from Three Central and Eastern European Countries. Economic Modelling, 42, 343–355. https://doi.org/10.1016/j.econmod.2014.07.023.
  • Mensi, W., Şensoy, A., Aslan, A., & Kang, S. H. (2019). High-Frequency Asymmetric Volatility Connectedness between Bitcoin and Major Precious Metals Markets. North American Journal of Economics & Finance, 50, 1-38. https://doi.org/10.1016/j.najef.2019.101031.
  • Molnar, P. (2016). High-low range in GARCH models of stock return volatility. Applied Economıcs, 48 (51), 4977–4991. http://dx.doi.org/10.1080/00036846.2016.1170929.
  • Molnár, P. 2012. Properties of Range-Based Volatility Estimators. International Review of Financial Analysis 23, 20–29. https://doi.org/10.1016/j.irfa.2011.06.012.
  • Moussa, W., Mgadmi, N., B´ejaoui, A., Regaieg, R. (2021). Resources Policy, 74, 102416. https://doi.org/10.1016/j.resourpol.2021.102416.
  • Okorie, D. I., & Lin, B. (2020). Crude Oil Price and Cryptocurrencies: Evidence of Volatility Connectedness and Hedging Strategy. Energy Economics, 87, art. 104703. https://doi.org/10.1016/j.eneco.2020.10470.
  • Rehman, M., Kang, S. H. (2021). A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets. Global Finance Journal, 49, 100576. https://doi.org/10.1016/j.gfj.2020.100576.
  • Salihoğlu, E., Göv, A. (2021). Dijital Emtia Olarak Bitcoin’e Yatırım Portföyünde Yer Verilmeli mi?: Bitcoin’in Altın, Gümüş ve Petrol Fiyatları ile İlişkisi Üzerine Bir İnceleme. İktisadi İdari ve Siyasal Araştırmalar Dergisi, 6 (16), 538-554. https://doi.org/10.25204/iktisad.970269.
  • Selmi, R., Mensi, W., Hammoudeh, S., Bouoiyour, J. (2018). Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold. Energy Econ. 74, 787–801. https://doi.org/10.1016/j.eneco.2018.07.007.
  • Shahzad, S.J.H., Bouri, E., Roubaud, D., Kristoufek, L., Lucey, B. (2019). Is Bitcoin a better safe-haven investment than Gold and commodities? Int. Rev. Financ. Anal. 63, 322–330. https://doi.org/10.1016/j.irfa.2019.01.002.
  • Symitsi, E., Chalvatzis, K. J. (2019). The economic value of Bitcoin: a portfolio analysis of currencies, Gold, oil and stocks. Res. Int. Bus. Finance 48, 97–110. https://doi.org/10.1016/j.ribaf.2018.12.001.
  • Syuhada, K., Suprijanto, D., Hakim, A. (2021). Comparing gold’s and Bitcoin’s safe-haven roles against energy commodities during the COVID-19 outbreak: A vine copula approach. Finance Research Letters, 102471. https://doi.org/10.1016/j.frl.2021.102471.
  • Taylor, S. J. (1986). Forecasting the Volatility of Currency Exchange Rates. International Journal of Forecasting, 3, 159-170.
  • Trabelsi, N. (2018). Are there any volatility spill-over effects among cryptocurrencies and widely traded asset classes? J. Risk Financ. Manag. 11 (4), 66. https://doi.org/10.3390/jrfm11040066.
  • Tsay, R. S. (2013). Multivariate time series analysis: With R and financial applications. John Wiley & Sons.
  • Urom, C., Abid, I., Guesmi, K., Chevallier, J. (2020). Quantile spillovers and dependence between Bitcoin, equities and strategic commodities. Econ. Modell. 93, 230–258. https://doi.org/10.1016/j.econmod.2020.07.012.
  • Wang, G., Tang, Y., Xie, C., Chen, S. (2019). Is bitcoin a safe haven or a hedging asset? Evidence from China. Journal of Management Science and Engineering, 4, 173-188. https://doi.org/10.1016/j.jmse.2019.09.001.
  • Whelan, K. (2013). How is Bitcoin Different from the Dollar? Forbes, http://www.forbes.com/sites/karlwhelan/2013/11/19/how-is-Bitcoin-different-from-the-dollar
  • Zhang, Y.J., Bouri, E., Gupta, R., Ma, S. J. (2021). Risk spillover between Bitcoin and conventional financial markets: an expectile-based approach. North Am. J. Econ. Finance, 55, 101296. https://doi.org/10.1016/j.najef.2020.101296.

BİTCOİN, EMTİALAR İÇİN ÇEŞİTLENDİRİCİDEN FAZLASI MI? ARALIĞA DAYALI cDCC-GARCH İLE ANALİZİ

Year 2022, Volume: 7 Issue: 2, 227 - 240, 30.06.2022

Tuğrul Kandemir Halilibrahim Gökgöz

https://doi.org/10.29106/fesa.1092764
Cited By: 2

Abstract

Bu çalışmanın amacı Bitcoin’in emtialar için çeşitlendirici rolünün ve emtialarla etkileşiminin incelenmesidir. İnceleme kapsamında Bitcoin, altın, gümüş, emtia endeksi, ham petrol ve enerji emtiaları endeksi değişkenlerinden oluşan 17.09.2014 - 24.11.2021 dönemini kapsayan günlük veri seti Garman-Klass serilerine dönüştürülmüş ve dinamik koşullu korelasyon modelleri uygulanmıştır. Uygulama sonucunda Bitcoin ile emtialar arasındaki etkileşimi test etmek için en uygun modelin cDCC-GARCH olduğu gözlenmiş ve Bitcoin ile emtialar (gümüş hariç) arasındaki etkileşimin negatif yönlü; emtiaların kendi aralarındaki etkileşimin pozitif yönlü olduğu tespit edilmiştir. Bulgular, Bitcoin’in emtialar için (gümüş hariç) diğer emtialara göre daha iyi bir çeşitlendirici olduğunu ve Bitcoin’in emtia bulunduran portföye dahil edildiğinde hedge etme görevi üstlendiğini göstermektedir.

Keywords

Bitcoin Kripto Para Emtia Portföy Çeşitlendirmesi Güvenli Liman cDCC-GARCH Volatilite Volatilite Yayılımı Garman-Klass

References

  • Aielli, G. P. (2006), Consistent Estimation of Large Scale Dynamic Conditional Correlations, Unpublished paper, University of Florence.
  • Aielli, G. P., (2013). Dynamic conditional correlation: on properties and estimation, Journal of Business & Economic Statistics, 31, 282–299.
  • Alizadeh, S., Brandt, M. W., Diebold, F. X. (2002). Range-based estimation of stochastic volatility models. Journal of Finance, 57, 1047–1091. http://dx.doi.org/10.2139/ssrn.267788.
  • Al-Khazali, O., Bouri, E., & Roubaud, D. (2018). The Impact of Positive and Negative Macroeconomic News Surprises: Gold Versus Bitcoin. Economics Bulletin, 38 (1), 373-382. http://dx.doi.org/10.2139/ssrn.3382828
  • Aslanidis, N., Bariviera, A. F., & Martinez-Ibanez, O. (2019). An Analysis of Cryptocurrencies Conditional Cross Correlations. Finance Research Letters, 31, 130-137. https://doi.org/10.1016/j.frl.2019.04.019
  • Awartani, B., Maghyereh, A. I. (2013). Dynamic Spillovers between Oil and Stock Markets in the Gulf Cooperation Council Countries. Energy Economics, 36, 28–42. https://doi.org/10.1016/j.eneco.2012.11.024
  • Baur, D. K., Dimpfl, T., Kuck, K. (2018). Bitcoin, gold and the US dollar – A replication and extension. Finance Research Letters, 25, 103-110. https://doi.org/10.1016/j.frl.2017.10.012.
  • Baur, D. K., Hong, K., Lee, A. (2015). Bitcoin: Currency or Asset? Hamburg. Kühne Logistics University.
  • Baur, D.G. , Lucey, B.M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financ. Rev. 45, 217–229. https://doi.org/10.1111/j.1540-6288.2010.00244.x.
  • Beneki, C., Koulis, A., Kyriazis, N.A., Papadamou, S. (2019). Investigating volatility transmission and hedging properties between Bitcoin and Ethereum. Res. Int. Bus. Finance 48, 219–227. https://doi.org/10.1016/j.ribaf.2019.01.001.
  • Bhuiyan, R. A., Husain, A., Zhang, C. (2021). A wavelet approach for causal relationship between bitcoin and conventional asset classes. Resources Policy, 71, 101971. https://doi.org/10.1016/j.resourpol.2020.101971.
  • Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroscedasticity. Journal of Econometrics, 31, 307-327.
  • Bouoiyour, J., & Selmi, R. (2015). What Does Bitcoin Look Like? Annals of Economics and Finance, 16 (2), 449-492.
  • 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
  • Bouri, E., Gupta, R., Tiwari, A.K., Roubaud, D. (2017c). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Res. Lett. 23, 87-95. https://doi.org/10.1016/j.frl.2017.02.009.
  • Bouri, E., Jalkh, N., Molnár, P., & Roubaud, D. (2017b). Bitcoin for Energy Commodities before and After the December 2013 Crash: Diversifier, Hedge or Safe Haven? Applied Economics, 49 (50), 5063-5073. SSRN: https://ssrn.com/abstract=2925783
  • Bouri, E., Molnar, P., Azzi , G., Roubaud, D., & Hagfors , L. (2017a). On the Hedge and Safe Haven Properties of Bitcoin: Is it Really more than a Diversifier? Finance Research Letters, 20, 192-198. http://dx.doi.org/10.1016/j.frl.2016.09.025.
  • Bouri, E., Shahzad, S. J., Roubaud, D., Kristoufek, L., & Lucey, B. (2020). Bitcoin, Gold, and Commodities as Safe Havens for Stocks: New Insight through Wavelet Analysis. The Quarterly Review of Economics and Finance, 77, 156-164. https://doi.org/10.1016/j.qref.2020.03.004.
  • Brandt, M. W., Jones, C. S. (2006). Volatility forecasting with RangeBased EGARCH models. Journal of Business and Economic Statistics, 24 (4), 470–486. https://doi.org/10.1198/073500106000000206.
  • Bri`ere, M., Oosterlinck, K., Szafarz, A. (2015). Virtual currency, tangible return: portfolio diversification with Bitcoin. J. Asset Manag. 16, 365–373. http://dx.doi.org/10.2139/ssrn.2324780.
  • Chou, R. Y. (2005). Forecasting financial volatilities with extreme values: the conditional autoregressive range (CARR) model. Journal of Money, Credit and Banking, 37 (3), 561–582. DOI:10.1353/mcb.2005.0027
  • Chou, R. Y. (2006). Modeling the asymmetry of stock movements using price ranges. Advances in Econometrics, 20, 231–258. https://doi.org/10.1016/S0731-9053(05)20009-9.
  • Chou, R. Y. Chou, H., Liu, N. (2010). Range volatility models and their applications in finance. Handbook of Quantitative Finance and Risk Management, 1273-1281, Springer. New York. DOI:10.1007/978-0-387-77117-5_83.
  • Chou, R. Y.,Chou, H., N. Liu. (2015). “Range Volatility: A Review of Models and Empirical Studies.” In Hand-book of Financial Econometrics and Statistics, 2029–2050. New York, NY: Springer.
  • Ciaian, P., Rajcaniova, M., & Kancs, D. A. (2016). The Economics of Bitcoin Price Formation. Applied Economics, 48, 1799-1815. https://doi.org/10.1080/00036846.2015.1109038.
  • Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018). Exploring the Dynamic Relationships between Cryptocurrencies and other Financial Assets. Economics Letters, 165, 28-34. https://doi.org/10.1016/j.econlet.2018.01.004.
  • Das, D., Le Roux, C.L., Jana, R.K., Dutta, A. (2020). Does Bitcoin Hedge Crude Oil Implied Volatility and Structural Shocks? A Comparison with Gold, Commodity and The US Dollar. Finance Research Letters 36, 101335. https://doi.org/10.1016/j.frl.2019.101335
  • Do, A., Powell, R., Yong, J., Singh, A. (2019). Time-varying asymmetric volatility spillover between global markets and China’s A, B and H-shares using EGARCH and DCC-EGARCH models, The North American Journal of Economics and Finance, Vol. 54. https://doi.org/10.1016/j.najef.2019.101096
  • Dyhrberg, A. H. (2016). Bitcoin, Gold and the Dollar – A GARCH Volatility. Finance Research Letters, 16, 85-92. http://dx.doi.org/10.1016/j.frl.2015.10.008.
  • Eisl, A., Gasser, S., Weinmayer, K. (2015). Caveat Emptor: Does Bitcoin Improve Portfolio Diversification? http://dx.doi.org/10.2139/ssrn.2408997.
  • Garman, M. B., & Klass, M. J. (1980). On the Estimation of Security Price Volatilities from Historical Data. The Journal of Business, 53 (1), 67–7.
  • Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2019). Portfolio Diversification with Virtual Currency: Evidence from Bitcoin. International Review of Financial Analysis, 63, 431-437. https://doi.org/10.1016/j.irfa.2018.03.004.
  • Halaburda, H., Gandal, N. (2014). Can we predict the winner in a market with network effects? Competition in cryptocurrency market," in Games 7 (3), 16, NET Institute Working Paper No. 14-17. http://dx.doi.org/10.2139/ssrn.2506463.
  • Jareno, F., de la Gonzalez, M., Tolentino, M., Sierra, K. (2020). Bitcoin and Gold price returns: a quantile regression and NARDL analysis. Resour. Pol. 67, 1–16. https://doi.org/10.1016/j.resourpol.2020.101666.
  • Jiang, S., Li, Y., Luc, Q., Wang, S., Wei, Y. (2022). Volatility communicator or receiver? Investigating volatility spillover mechanisms among Bitcoin and other financial markets. Research in International Business and Finance, 59, 101543. https://doi.org/10.1016/j.ribaf.2021.101543.
  • Klein, T., Thu, H.P., Walther, T. (2018). Bitcoin is not the New Gold – a comparison of volatility, correlation, and portfolio performance. Int. Rev. Financ. Anal. 59, 105–116. https://doi.org/10.1016/j.irfa.2018.07.010.
  • Kurka, J. (2019). Do Cryptocurrencies and Traditional Asset Classes Influence Each Other? Finance Research Letters, 31, 38–4. https://doi.org/10.1016/j.frl.2019.04.018.
  • Li, X., Wang, C. A. (2017). Quantile spillovers and dependence between Bitcoin, equities and strategic commodities. Economic Modelling, 93, 230-258. https://doi.org/10.1016/j.econmod.2020.07.012.
  • Lin, M. Y., An, C. L. (2021). The relationship between Bitcoin and resource commodity futures: Evidence from NARDL approach. Resources Policy, 74, 102383. https://doi.org/10.1016/j.resourpol.2021.102383.
  • Lucey, B., Larkin, C., O’Connor, F. (2014). Gold Markets around the World – Who Spills over What, to Whom, When? Applied Economics Letters, 21 (13), 887–892. https://doi.org/10.1080/13504851.2014.896974.
  • Lyócsa, S. (2014). Growth-Returns Nexus: Evidence from Three Central and Eastern European Countries. Economic Modelling, 42, 343–355. https://doi.org/10.1016/j.econmod.2014.07.023.
  • Mensi, W., Şensoy, A., Aslan, A., & Kang, S. H. (2019). High-Frequency Asymmetric Volatility Connectedness between Bitcoin and Major Precious Metals Markets. North American Journal of Economics & Finance, 50, 1-38. https://doi.org/10.1016/j.najef.2019.101031.
  • Molnar, P. (2016). High-low range in GARCH models of stock return volatility. Applied Economıcs, 48 (51), 4977–4991. http://dx.doi.org/10.1080/00036846.2016.1170929.
  • Molnár, P. 2012. Properties of Range-Based Volatility Estimators. International Review of Financial Analysis 23, 20–29. https://doi.org/10.1016/j.irfa.2011.06.012.
  • Moussa, W., Mgadmi, N., B´ejaoui, A., Regaieg, R. (2021). Resources Policy, 74, 102416. https://doi.org/10.1016/j.resourpol.2021.102416.
  • Okorie, D. I., & Lin, B. (2020). Crude Oil Price and Cryptocurrencies: Evidence of Volatility Connectedness and Hedging Strategy. Energy Economics, 87, art. 104703. https://doi.org/10.1016/j.eneco.2020.10470.
  • Rehman, M., Kang, S. H. (2021). A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets. Global Finance Journal, 49, 100576. https://doi.org/10.1016/j.gfj.2020.100576.
  • Salihoğlu, E., Göv, A. (2021). Dijital Emtia Olarak Bitcoin’e Yatırım Portföyünde Yer Verilmeli mi?: Bitcoin’in Altın, Gümüş ve Petrol Fiyatları ile İlişkisi Üzerine Bir İnceleme. İktisadi İdari ve Siyasal Araştırmalar Dergisi, 6 (16), 538-554. https://doi.org/10.25204/iktisad.970269.
  • Selmi, R., Mensi, W., Hammoudeh, S., Bouoiyour, J. (2018). Is Bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold. Energy Econ. 74, 787–801. https://doi.org/10.1016/j.eneco.2018.07.007.
  • Shahzad, S.J.H., Bouri, E., Roubaud, D., Kristoufek, L., Lucey, B. (2019). Is Bitcoin a better safe-haven investment than Gold and commodities? Int. Rev. Financ. Anal. 63, 322–330. https://doi.org/10.1016/j.irfa.2019.01.002.
  • Symitsi, E., Chalvatzis, K. J. (2019). The economic value of Bitcoin: a portfolio analysis of currencies, Gold, oil and stocks. Res. Int. Bus. Finance 48, 97–110. https://doi.org/10.1016/j.ribaf.2018.12.001.
  • Syuhada, K., Suprijanto, D., Hakim, A. (2021). Comparing gold’s and Bitcoin’s safe-haven roles against energy commodities during the COVID-19 outbreak: A vine copula approach. Finance Research Letters, 102471. https://doi.org/10.1016/j.frl.2021.102471.
  • Taylor, S. J. (1986). Forecasting the Volatility of Currency Exchange Rates. International Journal of Forecasting, 3, 159-170.
  • Trabelsi, N. (2018). Are there any volatility spill-over effects among cryptocurrencies and widely traded asset classes? J. Risk Financ. Manag. 11 (4), 66. https://doi.org/10.3390/jrfm11040066.
  • Tsay, R. S. (2013). Multivariate time series analysis: With R and financial applications. John Wiley & Sons.
  • Urom, C., Abid, I., Guesmi, K., Chevallier, J. (2020). Quantile spillovers and dependence between Bitcoin, equities and strategic commodities. Econ. Modell. 93, 230–258. https://doi.org/10.1016/j.econmod.2020.07.012.
  • Wang, G., Tang, Y., Xie, C., Chen, S. (2019). Is bitcoin a safe haven or a hedging asset? Evidence from China. Journal of Management Science and Engineering, 4, 173-188. https://doi.org/10.1016/j.jmse.2019.09.001.
  • Whelan, K. (2013). How is Bitcoin Different from the Dollar? Forbes, http://www.forbes.com/sites/karlwhelan/2013/11/19/how-is-Bitcoin-different-from-the-dollar
  • Zhang, Y.J., Bouri, E., Gupta, R., Ma, S. J. (2021). Risk spillover between Bitcoin and conventional financial markets: an expectile-based approach. North Am. J. Econ. Finance, 55, 101296. https://doi.org/10.1016/j.najef.2020.101296.
There are 59 citations in total.

Details

Primary Language Turkish
Subjects Economics, Finance, Business Administration
Journal Section Araştırma Makaleleri
Authors

Tuğrul Kandemir 0000-0002-3544-7422

Halilibrahim Gökgöz 0000-0001-8000-9993

Early Pub Date June 30, 2022
Publication Date June 30, 2022
Submission Date March 24, 2022
Acceptance Date May 9, 2022
Published in Issue Year 2022 Volume: 7 Issue: 2

Cite

APA Kandemir, T., & Gökgöz, H. (2022). BİTCOİN, EMTİALAR İÇİN ÇEŞİTLENDİRİCİDEN FAZLASI MI? ARALIĞA DAYALI cDCC-GARCH İLE ANALİZİ. Finans Ekonomi Ve Sosyal Araştırmalar Dergisi, 7(2), 227-240. https://doi.org/10.29106/fesa.1092764

Cited By

Bitcoin’in kriz dönemindeki çeşitlendirici etkisi: G7’den kanıtlar
Muhasebe ve Finansman Dergisi
https://doi.org/10.25095/mufad.1311409
BİTCOİN İLE GELİŞMİŞ VE GELİŞMEKTE OLAN ÜLKELER ARASINDAKİ VOLATİLİTE YAYILIM ETKİSİNİN TVP-VAR İLE ANALİZİ
Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
https://doi.org/10.17065/huniibf.1098448
 Download Cover Image