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Bitcoin Enerji Tüketimi Özelinde Bitcoin Öncü Göstergeleri ve Hisse Senedi Piyasaları Ortak Hareket Ediyor Mu? Bitcoin Üreticisi Ülkelerden Kanıtlar

Year 2022, Volume: 13 Issue: 3, 1323 - 1342, 17.10.2022

Abstract

Bu çalışmada Bitcoin enerji tüketimi, Bitcoin fiyat ve Bitcoin hacim değişkenleri arasındaki ilişkinin incelenmesi ve öncü Bitcoin göstergeleriyle en çok Bitcoin üretimi yapan 5 ülkenin hisse senedi piyasalarının ortak hareket edip etmediklerinin araştırılması amaçlanmıştır. Bu bağlamda çalışmada Bitcoin enerji, Bitcoin fiyat, Bitcoin hacim, Amerika Birleşik Devletleri, Çin, Kazakistan, Rusya ve Kanada endeksleri 2011-2022 aylık verileri dikkate alınmıştır. Çalışmada Diebold ve Yılmaz (2012) yayılım endeksi ve zamanla değişen parametreli VAR (TVPVAR) yöntemleri kullanılmıştır. Diebold ve Yılmaz (2012) yayılım endeksi yöntemi sonucunda Bitcoin enerji değişkeninin Bitcoin fiyatına yayılım etkisinin %3.5 olduğu görülmüştür. Bitcoin öncü göstergelerinden incelenen tüm hisse senedi endekslerine yayılım olduğu görülürken en yüksek yayılımın ise Bitcoin fiyatından SP500 endeksine doğru olduğu görülmüştür. Diebold ve Yılmaz (2012) net yayılım endeksi %4.54 olarak hesaplanmıştır. Bununla birlikte kurulan TVPVAR modelinde değişkenlerin 4, 8 ve 12 aylık dönemlerdeki etki tepki fonksiyonları incelenmiştir. TVPVAR modeli etki tepki fonksiyonlarında Bitcoin enerji fiyatlarında 4, 8 ve 12 aylık dönemlerdeki şokların Bitcoin fiyatına benzer şiddetle yayıldığı gözlemlenmiştir. Çalışma sonucunda Bitcoin enerjide yaşanan şokların tüm dönemlerde, fiyat ve hacimde yaşanan şokların ise kısa dönemlerde SP500, Shangai, Kase ve RTSI endekslerinde benzer şiddette yayıldığı gözlemlenmiştir.

References

  • Antonakakis, N., Chatziantoniou, I. ve Gabauer, D. (2019). Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios. Journal of International Financial Markets, Institutions and Money, 1(61), 37-51.
  • Attarzadeh, A. ve Balcilar, M. (2022). On the dynamic return and volatility connectedness of cryptocurrency, crude oil, clean energy, and stock markets: a time-varying analysis, Environmental Science and Pollution Research, 1-12.
  • Aysan, A.F., Demir, E., Gozgor, G. ve Lau, C.K.M. (2019). Effects of the geopolitical risks on Bitcoin returns and volatility. Research in International Business and Finance, 47, 511-518.
  • Baharumshah, A. Z., ve Liew, V.K.S. (2006). Forecasting performance of exponential smooth transition autoregressive exchange rate models. Open economies review, 17(2), 235-251.
  • Baker, S.R., Bloom, N. ve Davis, S.J. (2016). Measuring economic policy uncertainty. The quarterly journal of economics, 131(4), 1593-1636.
  • Baktemur, İ. (2021). Türkiye için işsizliğin doğrusal olmayan zaman serileri ile incelenmesi̇. İçinde: Ekonometrı̇de Güncel Yöntemler ve Uygulamalar (Prof. Dr. Ahmet M. Gökçen’e Armağan), (Ed. Çil, N.) İstanbul: İstanbul Üniversitesi Yayınevi. Doi: http://10.26650/B/SS10.2021.013. Bouri, E., Das, M., Gupta, R. ve Roubaud, D. (2018). Spillovers between Bitcoin and other assets during bear and bull markets, Applied Economics, 50(55), 5935-5949.
  • Bouri, E., Gupta, R., Tiwari, A. K. ve Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87-95.
  • Cambridge Alternative Finance Center (2022). [Çevrim içi: https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/.], Erişim tarihi: 15.07.2022.
  • Conlon, T., Corbet, S. ve McGee, R.J. (2020). Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic, Research in International Business and Finance, 54, 101248.
  • Corbet, S., Lucey, B. M. ve Yarovaya, L. (2019). The financial market effects of cryptocurrency energy usage. Available at SSRN. [Çevrim içi: https://doi.org/10.2139/ssrn.3412194], Erişim tarihi: 15.07.2022.
  • Corbet, S., Lucey, B. ve Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81-88.
  • Dahir, A.M., Mahat, F., Noordin, B.A.A. ve Ab Razak, N.H. (2020). Dynamic connectedness between Bitcoin and equity market information across BRICS countries: Evidence from TVP-VAR connectedness approach, International Journal of Managerial Finance, 16(3), 357-371.
  • Demir, E., Gozgor, G., Lau, C. K.M. ve Vigne, S.A. (2018). Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters, 26, 145-149.
  • Diebold, F. X. ve Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of forecasting, 28(1), 57-66.
  • Fang, L., Bouri, E., Gupta, R. ve Roubaud, D. (2019). Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?. International Review of Financial Analysis, 61, 29-36.
  • Gajardo, G., Kristjanpoller, W.D. ve Minutolo, M. (2018). Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?, Chaos, Solitons & Fractals, 109, 195-205.
  • Gandal, N., Hamrick, J.T., Moore, T. ve Oberman, T. (2018). Price manipulation in the Bitcoin ecosystem. Journal of Monetary Economics, 95, 86-96.
  • Giudici, P. ve Abu-Hashish, I. (2019). What determines bitcoin exchange prices? A network VAR approach. Finance Research Letters, 28, 309-318.
  • Goodell, J.W., McGee, R.J. ve McGroarty, F. (2020). Election uncertainty, economic policy uncertainty and financial market uncertainty: a prediction market analysis. Journal of Banking & Finance, 110, 105684.
  • Guesmi, K., Saadi, S., Abid, I. ve Ftiti, Z. (2019). Portfolio diversification with virtual currency: Evidence from bitcoin. International Review of Financial Analysis, 63, 431-437.
  • Güngör, S. ve Erer, D. (2022). Türkiye’deki gıda fiyatları ile petrol fiyatları ve döviz kuru arasındaki doğrusal olmayan ilişkinin incelenmesi: zamanla-değişen parametreli VAR modelleri. Alanya Akademik Bakış, 6(2), 2481-2498.
  • Hong, H. ve Stein, J.C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of finance, 54(6), 2143-2184.
  • Hu, J. ve Chen, Z. (2016). A unit root test against globally stationary ESTAR models when local condition is non-stationary. Economics Letters, 146, 89-94.
  • Hung, N.T. (2021). Bitcoin & CEE stock markets: fresh evidence from using the DECO-GARCH model & quantile on quantile regression, European Journal of Management & Business Economics, 30(2), 261-280.
  • Hung, N.T. (2022). Asymmetric connectedness among S&P 500, crude oil, gold & Bitcoin, Managerial Finance, 48(4), 587-610.
  • Kapetanios, G., Shin, Y. ve Snell, A. (2003). Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics, 112(2), 359-379.
  • Karabıyık, C. (2020). Türkiye’de borsa, emtia, tahvil ve döviz piyasaları arasındaki etkileşim: yayılım endeksi yaklaşımı. Journal Of Management and Economics Research, 18(4), 265-284.
  • Krause, M. J. ve Tolaymat, T. (2018). Quantification of energy and carbon costs for mining cryptocurrencies. Nature Sustainability, 1(11), 711.
  • Kruse, R. (2011). A new unit root test against ESTAR based on a class of modified statistics. Statistical Papers, 52(1), 71-85.
  • Kwon, J.H. (2020). Tail behavior of Bitcoin, the dollar, gold & the stock market index, Journal of International Financial Markets, Institutions & Money, 67, 101202.
  • Lee, T. H., White, H. ve Granger, C. W. (1993). Testing for neglected nonlinearity in time series models: A comparison of neural network methods and alternative tests. Journal of Econometrics, 56(3), 269-290.
  • Li, J. ve Li, P. (2021). Volatility Spillovers between Bitcoin & Chinese Economic & Financial Markets, Available at SSRN 3997392.
  • Maghyereh, A. ve Abdoh, H. (2020). Tail dependence between Bitcoin & financial assets: Evidence from a quantile cross-spectral approach, International Review of Financial Analysis, 71, 101545.
  • Mensi, W., Rehman, M.U., Maitra, D., Al-Yahyaee, K. H. ve Sensoy, A. (2020). Does bitcoin co-move & share risk with Sukuk & world & regional Islamic stock markets? Evidence using a time-frequency approach, Research in International Business & Finance, 53, 101230.
  • Nakajima, J. (2011). Time-varying parameter VAR model with stochastic volatility: An overview of methodology and empirical applications. Monetary and Economic Studies.
  • Narayan, P. K., Phan, D. H. B., & Sharma, S. S. (2019b). Does Islamic stock sensitivity to oil prices have economic significance?. Pacific-Basin Finance Journal, 53, 497-512.
  • Narayan, P.K. ve Sharma, S.S. (2011). New evidence on oil price and firm returns. Journal of Banking & Finance, 35(12), 3253-3262.
  • Narayan, P.K., Narayan, S., Rahman, R.E. ve Setiawan, I. (2019a). Bitcoin price growth and Indonesia's monetary system. Emerging Markets Review, 38, 364-376.
  • Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72 (3), 2005, 821–852.
  • Roy, R. P. ve Roy, S. S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368-380.
  • Sajeev, K. C. ve Afjal, M. (2022). Contagion effect of cryptocurrency on the securities market: a study of Bitcoin volatility using diagonal BEKK & DCC GARCH models, SN Business & Economics, 2(6), 1-21.
  • Şenol, Z. ve Koç S. (2022). Borsa, faiz, döviz kuru, altın, petrol ve bitcoin arasındaki volatilite yayılımları, Uluslararası İktisadi ve İdari İncelemeler Dergisi, (35), 31-46.
  • Sha, Y. ve Song, W. (2021). Can Bitcoin hedge Belt & Road equity markets?, Finance Research Letters, 42, 102129.
  • Symitsi, E. ve Chalvatzis, K.J. (2018). Return, volatility & shock spillovers of Bitcoin with energy & technology companies, Economics Letters, 170, 127-130.
  • Tiwari, A.K., Raheem, I.D. ve Kang, S.H. (2019). Time-varying dynamic conditional correlation between stock & cryptocurrency markets using the copula-ADCC-EGARCH model, Physica A: Statistical Mechanics & its Applications, 535, 122295.
  • Trabelsi, N. (2018). Are there any volatility spill-over effects among cryptocurrencies & widely traded asset classes?, Journal of Risk & Financial Management, 11(4), 66.
  • Tsay, R. S. (2005). Analysis of financial time series. New York: John Wiley & Sons.
  • Ubilava, D. ve Helmers, C. G. (2013). Forecasting ENSO with a smooth transition autoregressive model. Environmental Modelling & Software, 40, 181-190.
  • Urom, C., Abid, I., Guesmi, K. ve Chevallier, J. (2020). Quantile spillovers & dependence between Bitcoin, equities & strategic commodities, Economic Modelling, 93, 230-258.
  • Urquhart, A. ve Zhang, H. (2019). Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis, 63, 49-57.
  • Ustaoğlu, E. (2022). Return & Volatility Spillover Between Cryptocurrency & Stock Markets: Evidence from Turkey, Muhasebe ve Finansman Dergisi, 93, 117-126.
  • Wang, G.J., Xie, C., Wen, D. ve Zhao, L. (2019). When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin. Finance Research Letters, 31, 489-497.
  • Wang, P., Li, X., Shen, D. ve Zhang, W. (2020). How does economic policy uncertainty affect the bitcoin market? Research in International Business and Finance, 53, 101234.
  • Wu, S., Tong, M., Yang, Z. ve Derbali, A. (2019). Does gold or Bitcoin hedge economic policy uncertainty? Finance Research Letters, 31, 171-178.

Do The Stock Markets and The Leading Indicators of Bitcoin Act Together in The Special of Bitcoin Energy Consumption? The Evidence from Producing Countries of Bitcoin

Year 2022, Volume: 13 Issue: 3, 1323 - 1342, 17.10.2022

Abstract

In this study, it was aimed to examine that the relationship between Bitcoin price, Bitcoin volume and bitcoin energy consumption, and to research leading indicators of Bitcoin and whether the stock markets of the 5 countries that produce the most Bitcoin act together. In this context, 2011-2022 monthly data of Bitcoin energy, Bitcoin price, Bitcoin volume, USA, China, Kazakhstan, Russia, and Canada indexes was regarded in the study. Diebold and Yilmaz (2012) spillover index and time varying parameter VAR (TVPVAR) methodologies were used in the study. In the result of Diebold and Yilmaz (2012) spillover methodology was observed that the spillover effect of the Bitcoin energy variable on the Bitcoin price is 3.5%. While was observed from leading indicators of Bitcoin to all series examined be spillover, the most spillover was observed that be from Bitcoin price to SP500 index. Net spillover index of Diebold and Yilmaz (2012) was calculated that is 4.54%. In addition to this, in the TVPVAR established model was examined the action and the reaction functions in 4, 8 and 12 months periods. In the action-reaction functions of the TVPVAR model, it was observed that the shocks at the 4, 8 and 12-month periods in Bitcoin energy prices spread with a similar intensity to the Bitcoin price. In the result of the study was observed that Bitcoin energy shocks spread to SP500, Shanghai, Kase and RTSI indexes in all periods, the shocks of the price and the volume shocks spread to these indexes in short periods.

References

  • Antonakakis, N., Chatziantoniou, I. ve Gabauer, D. (2019). Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios. Journal of International Financial Markets, Institutions and Money, 1(61), 37-51.
  • Attarzadeh, A. ve Balcilar, M. (2022). On the dynamic return and volatility connectedness of cryptocurrency, crude oil, clean energy, and stock markets: a time-varying analysis, Environmental Science and Pollution Research, 1-12.
  • Aysan, A.F., Demir, E., Gozgor, G. ve Lau, C.K.M. (2019). Effects of the geopolitical risks on Bitcoin returns and volatility. Research in International Business and Finance, 47, 511-518.
  • Baharumshah, A. Z., ve Liew, V.K.S. (2006). Forecasting performance of exponential smooth transition autoregressive exchange rate models. Open economies review, 17(2), 235-251.
  • Baker, S.R., Bloom, N. ve Davis, S.J. (2016). Measuring economic policy uncertainty. The quarterly journal of economics, 131(4), 1593-1636.
  • Baktemur, İ. (2021). Türkiye için işsizliğin doğrusal olmayan zaman serileri ile incelenmesi̇. İçinde: Ekonometrı̇de Güncel Yöntemler ve Uygulamalar (Prof. Dr. Ahmet M. Gökçen’e Armağan), (Ed. Çil, N.) İstanbul: İstanbul Üniversitesi Yayınevi. Doi: http://10.26650/B/SS10.2021.013. Bouri, E., Das, M., Gupta, R. ve Roubaud, D. (2018). Spillovers between Bitcoin and other assets during bear and bull markets, Applied Economics, 50(55), 5935-5949.
  • Bouri, E., Gupta, R., Tiwari, A. K. ve Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87-95.
  • Cambridge Alternative Finance Center (2022). [Çevrim içi: https://www.jbs.cam.ac.uk/faculty-research/centres/alternative-finance/.], Erişim tarihi: 15.07.2022.
  • Conlon, T., Corbet, S. ve McGee, R.J. (2020). Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic, Research in International Business and Finance, 54, 101248.
  • Corbet, S., Lucey, B. M. ve Yarovaya, L. (2019). The financial market effects of cryptocurrency energy usage. Available at SSRN. [Çevrim içi: https://doi.org/10.2139/ssrn.3412194], Erişim tarihi: 15.07.2022.
  • Corbet, S., Lucey, B. ve Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81-88.
  • Dahir, A.M., Mahat, F., Noordin, B.A.A. ve Ab Razak, N.H. (2020). Dynamic connectedness between Bitcoin and equity market information across BRICS countries: Evidence from TVP-VAR connectedness approach, International Journal of Managerial Finance, 16(3), 357-371.
  • Demir, E., Gozgor, G., Lau, C. K.M. ve Vigne, S.A. (2018). Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters, 26, 145-149.
  • Diebold, F. X. ve Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of forecasting, 28(1), 57-66.
  • Fang, L., Bouri, E., Gupta, R. ve Roubaud, D. (2019). Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?. International Review of Financial Analysis, 61, 29-36.
  • Gajardo, G., Kristjanpoller, W.D. ve Minutolo, M. (2018). Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?, Chaos, Solitons & Fractals, 109, 195-205.
  • Gandal, N., Hamrick, J.T., Moore, T. ve Oberman, T. (2018). Price manipulation in the Bitcoin ecosystem. Journal of Monetary Economics, 95, 86-96.
  • Giudici, P. ve Abu-Hashish, I. (2019). What determines bitcoin exchange prices? A network VAR approach. Finance Research Letters, 28, 309-318.
  • Goodell, J.W., McGee, R.J. ve McGroarty, F. (2020). Election uncertainty, economic policy uncertainty and financial market uncertainty: a prediction market analysis. Journal of Banking & Finance, 110, 105684.
  • Guesmi, K., Saadi, S., Abid, I. ve Ftiti, Z. (2019). Portfolio diversification with virtual currency: Evidence from bitcoin. International Review of Financial Analysis, 63, 431-437.
  • Güngör, S. ve Erer, D. (2022). Türkiye’deki gıda fiyatları ile petrol fiyatları ve döviz kuru arasındaki doğrusal olmayan ilişkinin incelenmesi: zamanla-değişen parametreli VAR modelleri. Alanya Akademik Bakış, 6(2), 2481-2498.
  • Hong, H. ve Stein, J.C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of finance, 54(6), 2143-2184.
  • Hu, J. ve Chen, Z. (2016). A unit root test against globally stationary ESTAR models when local condition is non-stationary. Economics Letters, 146, 89-94.
  • Hung, N.T. (2021). Bitcoin & CEE stock markets: fresh evidence from using the DECO-GARCH model & quantile on quantile regression, European Journal of Management & Business Economics, 30(2), 261-280.
  • Hung, N.T. (2022). Asymmetric connectedness among S&P 500, crude oil, gold & Bitcoin, Managerial Finance, 48(4), 587-610.
  • Kapetanios, G., Shin, Y. ve Snell, A. (2003). Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics, 112(2), 359-379.
  • Karabıyık, C. (2020). Türkiye’de borsa, emtia, tahvil ve döviz piyasaları arasındaki etkileşim: yayılım endeksi yaklaşımı. Journal Of Management and Economics Research, 18(4), 265-284.
  • Krause, M. J. ve Tolaymat, T. (2018). Quantification of energy and carbon costs for mining cryptocurrencies. Nature Sustainability, 1(11), 711.
  • Kruse, R. (2011). A new unit root test against ESTAR based on a class of modified statistics. Statistical Papers, 52(1), 71-85.
  • Kwon, J.H. (2020). Tail behavior of Bitcoin, the dollar, gold & the stock market index, Journal of International Financial Markets, Institutions & Money, 67, 101202.
  • Lee, T. H., White, H. ve Granger, C. W. (1993). Testing for neglected nonlinearity in time series models: A comparison of neural network methods and alternative tests. Journal of Econometrics, 56(3), 269-290.
  • Li, J. ve Li, P. (2021). Volatility Spillovers between Bitcoin & Chinese Economic & Financial Markets, Available at SSRN 3997392.
  • Maghyereh, A. ve Abdoh, H. (2020). Tail dependence between Bitcoin & financial assets: Evidence from a quantile cross-spectral approach, International Review of Financial Analysis, 71, 101545.
  • Mensi, W., Rehman, M.U., Maitra, D., Al-Yahyaee, K. H. ve Sensoy, A. (2020). Does bitcoin co-move & share risk with Sukuk & world & regional Islamic stock markets? Evidence using a time-frequency approach, Research in International Business & Finance, 53, 101230.
  • Nakajima, J. (2011). Time-varying parameter VAR model with stochastic volatility: An overview of methodology and empirical applications. Monetary and Economic Studies.
  • Narayan, P. K., Phan, D. H. B., & Sharma, S. S. (2019b). Does Islamic stock sensitivity to oil prices have economic significance?. Pacific-Basin Finance Journal, 53, 497-512.
  • Narayan, P.K. ve Sharma, S.S. (2011). New evidence on oil price and firm returns. Journal of Banking & Finance, 35(12), 3253-3262.
  • Narayan, P.K., Narayan, S., Rahman, R.E. ve Setiawan, I. (2019a). Bitcoin price growth and Indonesia's monetary system. Emerging Markets Review, 38, 364-376.
  • Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72 (3), 2005, 821–852.
  • Roy, R. P. ve Roy, S. S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368-380.
  • Sajeev, K. C. ve Afjal, M. (2022). Contagion effect of cryptocurrency on the securities market: a study of Bitcoin volatility using diagonal BEKK & DCC GARCH models, SN Business & Economics, 2(6), 1-21.
  • Şenol, Z. ve Koç S. (2022). Borsa, faiz, döviz kuru, altın, petrol ve bitcoin arasındaki volatilite yayılımları, Uluslararası İktisadi ve İdari İncelemeler Dergisi, (35), 31-46.
  • Sha, Y. ve Song, W. (2021). Can Bitcoin hedge Belt & Road equity markets?, Finance Research Letters, 42, 102129.
  • Symitsi, E. ve Chalvatzis, K.J. (2018). Return, volatility & shock spillovers of Bitcoin with energy & technology companies, Economics Letters, 170, 127-130.
  • Tiwari, A.K., Raheem, I.D. ve Kang, S.H. (2019). Time-varying dynamic conditional correlation between stock & cryptocurrency markets using the copula-ADCC-EGARCH model, Physica A: Statistical Mechanics & its Applications, 535, 122295.
  • Trabelsi, N. (2018). Are there any volatility spill-over effects among cryptocurrencies & widely traded asset classes?, Journal of Risk & Financial Management, 11(4), 66.
  • Tsay, R. S. (2005). Analysis of financial time series. New York: John Wiley & Sons.
  • Ubilava, D. ve Helmers, C. G. (2013). Forecasting ENSO with a smooth transition autoregressive model. Environmental Modelling & Software, 40, 181-190.
  • Urom, C., Abid, I., Guesmi, K. ve Chevallier, J. (2020). Quantile spillovers & dependence between Bitcoin, equities & strategic commodities, Economic Modelling, 93, 230-258.
  • Urquhart, A. ve Zhang, H. (2019). Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis, 63, 49-57.
  • Ustaoğlu, E. (2022). Return & Volatility Spillover Between Cryptocurrency & Stock Markets: Evidence from Turkey, Muhasebe ve Finansman Dergisi, 93, 117-126.
  • Wang, G.J., Xie, C., Wen, D. ve Zhao, L. (2019). When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin. Finance Research Letters, 31, 489-497.
  • Wang, P., Li, X., Shen, D. ve Zhang, W. (2020). How does economic policy uncertainty affect the bitcoin market? Research in International Business and Finance, 53, 101234.
  • Wu, S., Tong, M., Yang, Z. ve Derbali, A. (2019). Does gold or Bitcoin hedge economic policy uncertainty? Finance Research Letters, 31, 171-178.
There are 54 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Müge Sağlam Bezgin 0000-0001-8674-2707

Selim Güngör 0000-0002-2997-1113

Publication Date October 17, 2022
Submission Date August 19, 2022
Published in Issue Year 2022 Volume: 13 Issue: 3

Cite

APA Sağlam Bezgin, M., & Güngör, S. (2022). Bitcoin Enerji Tüketimi Özelinde Bitcoin Öncü Göstergeleri ve Hisse Senedi Piyasaları Ortak Hareket Ediyor Mu? Bitcoin Üreticisi Ülkelerden Kanıtlar. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 13(3), 1323-1342. https://doi.org/10.36362/gumus.1164266