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Hisse Senedi Getirileri, Bitcoin Getirileri ve Riskten Kaçınma Arasındaki İlişki: Çok Değişkenli Bir GARCH Modelinden Kanıtlar

Yıl 2021, Cilt: 29 Sayı: 47, 107 - 118, 25.01.2021
https://doi.org/10.17233/sosyoekonomi.2021.01.05

Öz

Bu çalışma, çok değişkenli bir GARCH modeli kullanarak ABD Dow Jones Borsasında işlem gören hisse senedi getirileri, Bitcoin getirileri ve bunların belirsizlikleri arasındaki ilişkileri araştırmaktadır. Özellikle, yüksek ve düşük olmak üzere farklı risk iştahının ve getirilerde belirsizliğin yüksek olduğu dönemlerde Bitcoin ve ABD hisse senedi getirilerinin verdiği tepkileri karşılaştırmaktadır. Sonuçlar, Bitcoin getirisinin riskten kaçınılan veya yüksek belirsizliğin olduğu dönemlerde hisse senedi gibi tepki verdiğini, ancak iki getiri arasındaki ilişkinin sürdürülebilir olmadığını göstermektedir. Öte yandan, ABD borsa yatırımcıları tüm örneklem dönemi boyunca riskten kaçınma davranışını gösterirken, Bitcoin yatırımcıları aynı davranışı göstermemektedir.

Kaynakça

  • Baeck, C. & M. Elbeck (2015), “Bitcoins as an investment or speculative vehicle? A firstlook”, Appl. Econom. Lett., (22), 30-34.
  • Bekaert, G. & E. Engstrom & N.R. Xu (2017), “The time variation in risk appetite and uncertainty”, Columbia Business School Research Paper No. 17-108, Available at SSRN: <https://ssrn.com/abstract=3069078>, 23.08.2019.
  • Bollerslev, T. (1990), “Modelling the coherence in short-run nominal exchange rates: A multivariate generalized arch model”, The Rev. of Econom. and Statistics, 72(3), 498-505.
  • Bouri, E. & P. Molnár & G. Azzi & D. Roubaud & L.I. Hagfors (2017a), “On the hedge and safe haven properties of Bitcoin: is it really more than a diversifier?”, Finance Res. Lett., (20), 192-198.
  • Bouri, E. & R. Gupta & A.K. Tiwari & D. Roubaud (2017b), “Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions”, Finance Res. Lett., (23), 87-95.
  • Brière, M. & K. Oosterlinck & A. Szafarz (2015), “Virtual currency, tangible return: Portfolio diversification with Bitcoin”, J. Asset Manag., 16(6), 365-373.
  • Cheah, E.-T. & J. Fry (2015), “Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin”, Econom. Lett., (130), 32-36.
  • Cheung, A. & E. Roca & J.-J. Su (2015), “Crypto-currency bubbles: An application of the Phillips-Shi-Yu (2013) methodology on Mt.Gox Bitcoin prices”, Appl. Econom., (47), 2348-2358.
  • Ciaian, P. & M. Rajcaniova & D.A. Kancs (2016), “The economics of Bitcoin price formation”, Appl. Econ., 48(19), 1799-1815.
  • Dwyer, G.P. (2014), “The economics of Bitcoin and similar private digital currencies”, J. Financ. Stab., (17), 81-91.
  • Dyhrberg, A.H. (2016a), “Bitcoin, gold and the dollar - a GARCH volatility analysis”, Finance Res. Lett., (16), 85-92.
  • Dyhrberg, A.H. (2016b), “Hedging capabilities of Bitcoin. Is it the virtual gold?”, Finance Res. Lett., (16), 139-144.
  • Fry, J. & E.-T. Cheah (2016), “Negative bubbles and shocks in cryptocurrency Markets”, Int. Rev. Financ. Anal., (47), 343-352.
  • ING International Survey (2019), <https://think.ing.com/uploads/reports/IIS_New_Tech_Cryptocurrencies_report_18092019.pdf>, 23.08.2019.
  • Katsiampa, P. (2017), “Volatility estimation for Bitcoin: A comparison of GARCH Models”, Econom. Lett., (158), 3-6.
  • Nadarajah, S. & J. Chu (2017), “On the inefficiency of Bitcoin”, Econom. Lett., (150), 6-9.
  • Tiwari, A.K. & R.K. Jana & D. Das & D. Doubaud (2018), “Informational efficiency of Bitcoin”, Econom. Lett., (163), 106-109.
  • Urquhart, A. (2016), “The inefficiency of Bitcoin”, Econom. Lett., (148), 80-82.
  • Urquhart, A. (2017), “Price clustering in Bitcoin”, Econom. Lett., (159) (Suppl. C), 145-148.
  • Wall Street Journal (14/5/2018), Steve Eisman of ‘The Big Short’ bashes cryptocurrency: ‘I don’t see the purpose of it’, Retrieved from: <https://www.wsj.com/articles/steve-eisman-of-the-big-short-bashes-cryptocurrency-i-dont-see-the-purpose-of-it-1526292273>, 23.08.2019.
  • Wall Street Journal (9/1/2018), Jamie Dimon: I ‘regret’ calling Bitcoin a fraud, Retrieved from: <https://www.wsj.com/video/jamie-dimon-i-regret-calling-Bitcoin-a-fraud/A633471B-A251-440E-A959-B72CEFC01E99.html>, 23.08.2019.

The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model

Yıl 2021, Cilt: 29 Sayı: 47, 107 - 118, 25.01.2021
https://doi.org/10.17233/sosyoekonomi.2021.01.05

Öz

This study explores the relationship between the U.S. stock returns, Bitcoin returns and their uncertainties by using a multivariate GARCH model. Specifically, the study compares the reactions of Bitcoin and stock market returns in the presence of global uncertainties and changes in risk appetites. The results show that even though reactions of Bitcoin and stock returns are similar for some highly volatile or risk averse periods, the association between the two returns is not sustainable. Moreover, the U.S. stock market investors are found to be risk averse throughout the entire sample period while Bitcoin investors are not.

Kaynakça

  • Baeck, C. & M. Elbeck (2015), “Bitcoins as an investment or speculative vehicle? A firstlook”, Appl. Econom. Lett., (22), 30-34.
  • Bekaert, G. & E. Engstrom & N.R. Xu (2017), “The time variation in risk appetite and uncertainty”, Columbia Business School Research Paper No. 17-108, Available at SSRN: <https://ssrn.com/abstract=3069078>, 23.08.2019.
  • Bollerslev, T. (1990), “Modelling the coherence in short-run nominal exchange rates: A multivariate generalized arch model”, The Rev. of Econom. and Statistics, 72(3), 498-505.
  • Bouri, E. & P. Molnár & G. Azzi & D. Roubaud & L.I. Hagfors (2017a), “On the hedge and safe haven properties of Bitcoin: is it really more than a diversifier?”, Finance Res. Lett., (20), 192-198.
  • Bouri, E. & R. Gupta & A.K. Tiwari & D. Roubaud (2017b), “Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions”, Finance Res. Lett., (23), 87-95.
  • Brière, M. & K. Oosterlinck & A. Szafarz (2015), “Virtual currency, tangible return: Portfolio diversification with Bitcoin”, J. Asset Manag., 16(6), 365-373.
  • Cheah, E.-T. & J. Fry (2015), “Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin”, Econom. Lett., (130), 32-36.
  • Cheung, A. & E. Roca & J.-J. Su (2015), “Crypto-currency bubbles: An application of the Phillips-Shi-Yu (2013) methodology on Mt.Gox Bitcoin prices”, Appl. Econom., (47), 2348-2358.
  • Ciaian, P. & M. Rajcaniova & D.A. Kancs (2016), “The economics of Bitcoin price formation”, Appl. Econ., 48(19), 1799-1815.
  • Dwyer, G.P. (2014), “The economics of Bitcoin and similar private digital currencies”, J. Financ. Stab., (17), 81-91.
  • Dyhrberg, A.H. (2016a), “Bitcoin, gold and the dollar - a GARCH volatility analysis”, Finance Res. Lett., (16), 85-92.
  • Dyhrberg, A.H. (2016b), “Hedging capabilities of Bitcoin. Is it the virtual gold?”, Finance Res. Lett., (16), 139-144.
  • Fry, J. & E.-T. Cheah (2016), “Negative bubbles and shocks in cryptocurrency Markets”, Int. Rev. Financ. Anal., (47), 343-352.
  • ING International Survey (2019), <https://think.ing.com/uploads/reports/IIS_New_Tech_Cryptocurrencies_report_18092019.pdf>, 23.08.2019.
  • Katsiampa, P. (2017), “Volatility estimation for Bitcoin: A comparison of GARCH Models”, Econom. Lett., (158), 3-6.
  • Nadarajah, S. & J. Chu (2017), “On the inefficiency of Bitcoin”, Econom. Lett., (150), 6-9.
  • Tiwari, A.K. & R.K. Jana & D. Das & D. Doubaud (2018), “Informational efficiency of Bitcoin”, Econom. Lett., (163), 106-109.
  • Urquhart, A. (2016), “The inefficiency of Bitcoin”, Econom. Lett., (148), 80-82.
  • Urquhart, A. (2017), “Price clustering in Bitcoin”, Econom. Lett., (159) (Suppl. C), 145-148.
  • Wall Street Journal (14/5/2018), Steve Eisman of ‘The Big Short’ bashes cryptocurrency: ‘I don’t see the purpose of it’, Retrieved from: <https://www.wsj.com/articles/steve-eisman-of-the-big-short-bashes-cryptocurrency-i-dont-see-the-purpose-of-it-1526292273>, 23.08.2019.
  • Wall Street Journal (9/1/2018), Jamie Dimon: I ‘regret’ calling Bitcoin a fraud, Retrieved from: <https://www.wsj.com/video/jamie-dimon-i-regret-calling-Bitcoin-a-fraud/A633471B-A251-440E-A959-B72CEFC01E99.html>, 23.08.2019.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Ayşen Sivrikaya 0000-0003-2199-3593

Perihan İren Bu kişi benim 0000-0002-5631-4135

Tolga Umay 0000-0003-0263-2258

Yayımlanma Tarihi 25 Ocak 2021
Gönderilme Tarihi 14 Mayıs 2020
Yayımlandığı Sayı Yıl 2021 Cilt: 29 Sayı: 47

Kaynak Göster

APA Sivrikaya, A., İren, P., & Umay, T. (2021). The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model. Sosyoekonomi, 29(47), 107-118. https://doi.org/10.17233/sosyoekonomi.2021.01.05
AMA Sivrikaya A, İren P, Umay T. The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model. Sosyoekonomi. Ocak 2021;29(47):107-118. doi:10.17233/sosyoekonomi.2021.01.05
Chicago Sivrikaya, Ayşen, Perihan İren, ve Tolga Umay. “The Relationship Between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model”. Sosyoekonomi 29, sy. 47 (Ocak 2021): 107-18. https://doi.org/10.17233/sosyoekonomi.2021.01.05.
EndNote Sivrikaya A, İren P, Umay T (01 Ocak 2021) The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model. Sosyoekonomi 29 47 107–118.
IEEE A. Sivrikaya, P. İren, ve T. Umay, “The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model”, Sosyoekonomi, c. 29, sy. 47, ss. 107–118, 2021, doi: 10.17233/sosyoekonomi.2021.01.05.
ISNAD Sivrikaya, Ayşen vd. “The Relationship Between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model”. Sosyoekonomi 29/47 (Ocak 2021), 107-118. https://doi.org/10.17233/sosyoekonomi.2021.01.05.
JAMA Sivrikaya A, İren P, Umay T. The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model. Sosyoekonomi. 2021;29:107–118.
MLA Sivrikaya, Ayşen vd. “The Relationship Between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model”. Sosyoekonomi, c. 29, sy. 47, 2021, ss. 107-18, doi:10.17233/sosyoekonomi.2021.01.05.
Vancouver Sivrikaya A, İren P, Umay T. The Relationship between Stock Returns, Bitcoin Returns, and Risk Aversion: Evidence from a Multivariate GARCH Model. Sosyoekonomi. 2021;29(47):107-18.