Araştırma Makalesi
BibTex RIS Kaynak Göster

Relationship of risk tolerance with brown and green cryptocurrencies: An examination with A-ARDL and NARDL methods for domestic investors

Yıl 2025, Cilt: 27 Sayı: 1, 130 - 153

Öz

The aim of this study is to reveal the relationship between brown and green cryptocurrency prices and domestic investors' risk tolerances. For that purpose, the risk tolerances of domestic individual investors and institutional investors were sorted as independent variables of the study. To examine long-run symmetric and asymmetric relationships of the dependent and independent variables, four different research models were created. The test results showed that the domestic investors’ risk tolerances don’t have a symmetric cointegration relationship with brown and green crypto prices. However, there are asymmetric cointegrations between domestic individual investor risk tolerance both with brown and green cryptocurrency prices and between domestic institutional investor risk tolerance both with brown and green cryptocurrency prices. According to those results, the changes in the brown and green cryptocurrency prices impact domestic investors’ risk tolerances. Stellar and Tron, which are green cryptocurrencies, especially have asymmetric effects on risk tolerance.

Kaynakça

  • Aydoğan, B., Cayirli, O., & Vardar, G. (2024). Impact of Macroeconomics Factors on Cryptocurrency Pricing: Evidence from Bitcoin and Ethereum Markets. Computational Economics, 1-36. https://doi.org/10.1007/s10614-024-10804-0
  • Bajwa, I. A. (2025). Reinvestment intentions in cryptocurrency: Examining the dynamics of risks and investor risk tolerance. Digital Business, 5(1), 100104. https://doi.org/10.1016/j.digbus.2024.100104
  • Benzekri, M.K.& Özütler, H.Ş. (2021). Bitcoin fiyat hareketleri üzerine: ARIMA ile kısa vadeli bir fiyat tahmini. İktisat Politikası Araştırmaları Dergisi, 8(2), 293-309. http://dx.doi.org/10.26650/JEPR.946081
  • Bouri, E., Gupta, R., Lau, M., & Roubaud, D. (2019). Risk aversion and Bitcoin returns in normal, bull, and bear markets (No. 201927).
  • Breusch, T. S. (1978). Testing for autocorrelation in dynamic linear models. Australian Economic Papers, 17, 334-55. http://dx.doi.org/10.1111/j.1467-8454.1978.tb00635.x
  • Dilek, Ş., & Furuncu, Y. (2019). Bitcoin mining and its environmental effects. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 33(1), 91-106.
  • Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar–A-GARCH volatility analysis. Finance Research Letters, 16, 85-92. https://doi.org/10.1016/j.frl.2015.10.008
  • Esparcia, C., Fakhfakh, T., & Jareño, F. (2024). The green, the dirty and the stable: Diversifying equity portfolios by adding tokens of different nature. The North American Journal of Economics and Finance, 69, 102020.
  • Foley, S., Frijns, B., Garel, A., & Roh, T. Y. (2022). Who buys Bitcoin? The cultural determinants of Bitcoin activity. International Review of Financial Analysis, 84, 102385. https://doi.org/10.1016/j.irfa.2022.102385
  • Gemici, E., Gök, R., & Bouri, E. (2023). Predictability of risk appetite in Turkey: Local versus global factors. Emerging Markets Review, 55, 101018. https://doi.org/10.1016/j.ememar.2023.101018
  • Gerrans, P., Abisekaraj, S. B., & Liu, Z. F. (2023). The fear of missing out on cryptocurrency and stock investments: Direct and indirect effects of financial literacy and risk tolerance. Journal of Financial Literacy and Wellbeing, 1(1), 103-137.
  • Goodkind, A. L., Jones, B. A., & Berrens, R. P. (2020). Cryptodamages: Monetary value estimates of the air pollution and human health impacts of cryptocurrency mining. Energy Research & Social Science, 59, 101281. https://doi.org/10.1016/j.erss.2019.101281
  • Göksu, S., & Balkı, A. (2023). ARDL ve NARDL eşbütünleşme analizleri: Adım adım E-views uygulaması. Serüven Yayınevi, Ankara-Türkiye
  • Gurdgiev, C., & O’Loughlin, D. (2020). Herding and anchoring in cryptocurrency markets: Investor reaction to fear and uncertainty. Journal of Behavioral and Experimental Finance, 25, 100271. https://doi.org/10.1016/j.jbef.2020.100271
  • Haq, I. U. (2023). Time‐frequency comovement among green financial assets and cryptocurrency uncertainties. Economic Notes, 52(1), e12216.
  • Hayashi, F., & Routh, A. (2024). Financial Literacy, Risk Tolerance, and Cryptocurrency Ownership in the United States. Federal Reserve Bank of Kansas City Working Paper, (24-03).
  • Kılıç, M., & Altan, İ. M. (2023). Are green cryptocurrencies safe? Investigation of the green and non-green cryptocurrencies. Akademik Yaklaşımlar Dergisi, 14(2), 651-663.
  • Lashkaripour, M. (2023). How carbon is priced in cryptocurrencies. Available at SSRN 4560309.
  • Malladi, R.K., Dheeriya, P.L. (2021) Time series analysis of cryptocurrency returns and volatilities. Journal of Economics and Finance, 45, 75–94. https://doi.org/10.1007/s12197-020-09526-4
  • Meyer, J. H., Friederich, F., Matute, J., & Schwarz, M. (2024). My money—My problem: How fear‐of‐missing‐out appeals can hinder sustainable investment decisions. PsychoLy & Marketing.
  • Naeem, M. A., Nguyen, T. T. H., Karim, S., & Lucey, B. M. (2023). Extreme downside risk transmission between green cryptocurrencies and energy markets: the diversification benefits. Finance Research Letters, 58, 104263. https://doi.org/10.1016/j.frl.2023.104263
  • Ögel, S., & Ögel, İ. Y. (2021). The interaction between perceived risk, attitude, and intention to use: An empirical study on bitcoin as a cryptocurrency. In new challenges for future sustainability and wellbeing (pp. 211-241). Emerald Publishing Limited.
  • Önk.H, & Saygın, O. (2022). Bitcoin, risk iştahı, BIST100 endeksi ilişkisi: Türkiye örneği. International Journal of Disciplines in Economics & Administrative Sciences Studies, 8(42), 419-427. https://doi.org/10.29228/ideas.62987
  • Patel, R., Gubareva, M., & Chishti, M. Z. (2024). Assessing the connectedness between cryptocurrency environment attention index and green cryptos, energy cryptos, and green financial assets. Research in International Business and Finance, 70, 102339. https://doi.org/10.1016/j.ribaf.2024.102339
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
  • Robba, M., Sorgente, A., & Iannello, P. (2024). Disentangling the “crypto fever”: An exploratory study of the psychoLical characteristics of cryptocurrency owners. Current Research in Behavioral Sciences, 6, 100151.
  • Sam, C. Y., McNown, R., & Goh, S. K. (2019). An augmented autoregressive distributed lag bounds test for cointegration. Economic Modelling, 80, 130-141.
  • Sridharan, U., Mansour, F., Ray, L. and Huning, T. (2023). Effect of risk attitude on cryptocurrency adoption for compensation and spending. Journal of Financial Economic Policy, 15(4/5), 337-350. https://doi.org/10.1108/JFEP-04-2023-0099 Syed, A. A., Ahmed, F., Kamal, M. A., Ullah, A., & Ramos-Requena,
  • J. P. (2022). Is there an asymmetric relationship between economic policy uncertainty, cryptocurrencies, and global green bonds? Evidence from the United States of America. Mathematics, 10(5), 720.
  • Tabachnick, B. G., & Fidell, L. S. (2015). Using multivariate statistics. (6.basım). Allyn & Bacon / Pearson Education. 6. Basımdan Çeviri: Mustafa Baloğlu, Nobel Akademik Yayıncılık, Ankara
  • Uçkun, N., & Dal, L. (2021). Kripto para yatırımcılarında finansal risk toleransı. Muhasebe ve Finansman Dergisi, (89), 155-170. https://doi.org/10.25095/mufad.852118
  • Umar, Z., Usman, M., Umar, M., & Ktaish, F. (2024). Interdependencies and risk management strategies between green cryptocurrencies and traditional energy sources. Energy Economics, 136, 107742. https://doi.org/10.1016/j.eneco.2024.107742
  • Ye, W., Wong, W. K., Arnone, G., Nassani, A. A., Haffar, M., & Faiz, M. F. (2023). Crypto currency and green investment impact on global environment: A time series analysis. International Review of Economics & Finance, 86, 155-169. https://doi.org/10.1016/j.iref.2023.01.030
  • Yousaf, I., Abrar, A., Yousaf, U. B., & Goodell, J. W. (2024). Environmental attention and uncertainties of cryptocurrency market: Examining linkages with crypto-mining stocks. Finance Research Letters, 59, 104672. https://doi.org/10.1016/j.frl.2023.10467

Kahverengi kripto ve yeşil kripto paraların yatırımcı risk toleransı ile ilişkilisi: Yerli yatırımcılar bazında A-ARDL ve NARDL yöntemleri ile bir değerlendirme

Yıl 2025, Cilt: 27 Sayı: 1, 130 - 153

Öz

Yapılan bu çalışmanın amacı kahverengi kripto ve yeşil kripto para fiyatlarının yerel yatırımcıların risk toleransları ile ilişkisini ortaya koymaktır. Bu amaç doğrultusunda yerel gerçek kişi ve yerel tüzel kişi risk toleransları çalışmanın bağımsız değişkenlerini oluşturmaktadır. Araştırmada değişkenler arasında simetrik ve asimetrik uzun dönem ilişkini sınamak her bir test yöntemi için dört farklı araştırma modeli oluşturulmuştur. Test sonuçlarna göre yerel yatırımcıların risk toleransları kripto para fiyatları arasında simetrik ilişki yoktur. Ancak, yerel gerçek kişi risk toleransı ile kahverengi kripto ve yeşil kripto fiyatları arasında ve yerel tüzel kişi risk toleransı ile kahverengi kripto ve yeşil kripto fiyatları arasında asimetrik eşbütünleşme ilişkileri bulunmaktadır. Bu sonuçlara göre kahverengi ve yeşil kripto para fiyatlarındaki değişimler yerel yatırımcıların risk toleransını etkilemektedir. Özellikle, yeşil kripto para olan Stellar ve Tron fiyatları belirtilen risk toleransları üzerinde asimetrik etkilere sahiptirler.

Kaynakça

  • Aydoğan, B., Cayirli, O., & Vardar, G. (2024). Impact of Macroeconomics Factors on Cryptocurrency Pricing: Evidence from Bitcoin and Ethereum Markets. Computational Economics, 1-36. https://doi.org/10.1007/s10614-024-10804-0
  • Bajwa, I. A. (2025). Reinvestment intentions in cryptocurrency: Examining the dynamics of risks and investor risk tolerance. Digital Business, 5(1), 100104. https://doi.org/10.1016/j.digbus.2024.100104
  • Benzekri, M.K.& Özütler, H.Ş. (2021). Bitcoin fiyat hareketleri üzerine: ARIMA ile kısa vadeli bir fiyat tahmini. İktisat Politikası Araştırmaları Dergisi, 8(2), 293-309. http://dx.doi.org/10.26650/JEPR.946081
  • Bouri, E., Gupta, R., Lau, M., & Roubaud, D. (2019). Risk aversion and Bitcoin returns in normal, bull, and bear markets (No. 201927).
  • Breusch, T. S. (1978). Testing for autocorrelation in dynamic linear models. Australian Economic Papers, 17, 334-55. http://dx.doi.org/10.1111/j.1467-8454.1978.tb00635.x
  • Dilek, Ş., & Furuncu, Y. (2019). Bitcoin mining and its environmental effects. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 33(1), 91-106.
  • Dyhrberg, A. H. (2016). Bitcoin, gold and the dollar–A-GARCH volatility analysis. Finance Research Letters, 16, 85-92. https://doi.org/10.1016/j.frl.2015.10.008
  • Esparcia, C., Fakhfakh, T., & Jareño, F. (2024). The green, the dirty and the stable: Diversifying equity portfolios by adding tokens of different nature. The North American Journal of Economics and Finance, 69, 102020.
  • Foley, S., Frijns, B., Garel, A., & Roh, T. Y. (2022). Who buys Bitcoin? The cultural determinants of Bitcoin activity. International Review of Financial Analysis, 84, 102385. https://doi.org/10.1016/j.irfa.2022.102385
  • Gemici, E., Gök, R., & Bouri, E. (2023). Predictability of risk appetite in Turkey: Local versus global factors. Emerging Markets Review, 55, 101018. https://doi.org/10.1016/j.ememar.2023.101018
  • Gerrans, P., Abisekaraj, S. B., & Liu, Z. F. (2023). The fear of missing out on cryptocurrency and stock investments: Direct and indirect effects of financial literacy and risk tolerance. Journal of Financial Literacy and Wellbeing, 1(1), 103-137.
  • Goodkind, A. L., Jones, B. A., & Berrens, R. P. (2020). Cryptodamages: Monetary value estimates of the air pollution and human health impacts of cryptocurrency mining. Energy Research & Social Science, 59, 101281. https://doi.org/10.1016/j.erss.2019.101281
  • Göksu, S., & Balkı, A. (2023). ARDL ve NARDL eşbütünleşme analizleri: Adım adım E-views uygulaması. Serüven Yayınevi, Ankara-Türkiye
  • Gurdgiev, C., & O’Loughlin, D. (2020). Herding and anchoring in cryptocurrency markets: Investor reaction to fear and uncertainty. Journal of Behavioral and Experimental Finance, 25, 100271. https://doi.org/10.1016/j.jbef.2020.100271
  • Haq, I. U. (2023). Time‐frequency comovement among green financial assets and cryptocurrency uncertainties. Economic Notes, 52(1), e12216.
  • Hayashi, F., & Routh, A. (2024). Financial Literacy, Risk Tolerance, and Cryptocurrency Ownership in the United States. Federal Reserve Bank of Kansas City Working Paper, (24-03).
  • Kılıç, M., & Altan, İ. M. (2023). Are green cryptocurrencies safe? Investigation of the green and non-green cryptocurrencies. Akademik Yaklaşımlar Dergisi, 14(2), 651-663.
  • Lashkaripour, M. (2023). How carbon is priced in cryptocurrencies. Available at SSRN 4560309.
  • Malladi, R.K., Dheeriya, P.L. (2021) Time series analysis of cryptocurrency returns and volatilities. Journal of Economics and Finance, 45, 75–94. https://doi.org/10.1007/s12197-020-09526-4
  • Meyer, J. H., Friederich, F., Matute, J., & Schwarz, M. (2024). My money—My problem: How fear‐of‐missing‐out appeals can hinder sustainable investment decisions. PsychoLy & Marketing.
  • Naeem, M. A., Nguyen, T. T. H., Karim, S., & Lucey, B. M. (2023). Extreme downside risk transmission between green cryptocurrencies and energy markets: the diversification benefits. Finance Research Letters, 58, 104263. https://doi.org/10.1016/j.frl.2023.104263
  • Ögel, S., & Ögel, İ. Y. (2021). The interaction between perceived risk, attitude, and intention to use: An empirical study on bitcoin as a cryptocurrency. In new challenges for future sustainability and wellbeing (pp. 211-241). Emerald Publishing Limited.
  • Önk.H, & Saygın, O. (2022). Bitcoin, risk iştahı, BIST100 endeksi ilişkisi: Türkiye örneği. International Journal of Disciplines in Economics & Administrative Sciences Studies, 8(42), 419-427. https://doi.org/10.29228/ideas.62987
  • Patel, R., Gubareva, M., & Chishti, M. Z. (2024). Assessing the connectedness between cryptocurrency environment attention index and green cryptos, energy cryptos, and green financial assets. Research in International Business and Finance, 70, 102339. https://doi.org/10.1016/j.ribaf.2024.102339
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
  • Robba, M., Sorgente, A., & Iannello, P. (2024). Disentangling the “crypto fever”: An exploratory study of the psychoLical characteristics of cryptocurrency owners. Current Research in Behavioral Sciences, 6, 100151.
  • Sam, C. Y., McNown, R., & Goh, S. K. (2019). An augmented autoregressive distributed lag bounds test for cointegration. Economic Modelling, 80, 130-141.
  • Sridharan, U., Mansour, F., Ray, L. and Huning, T. (2023). Effect of risk attitude on cryptocurrency adoption for compensation and spending. Journal of Financial Economic Policy, 15(4/5), 337-350. https://doi.org/10.1108/JFEP-04-2023-0099 Syed, A. A., Ahmed, F., Kamal, M. A., Ullah, A., & Ramos-Requena,
  • J. P. (2022). Is there an asymmetric relationship between economic policy uncertainty, cryptocurrencies, and global green bonds? Evidence from the United States of America. Mathematics, 10(5), 720.
  • Tabachnick, B. G., & Fidell, L. S. (2015). Using multivariate statistics. (6.basım). Allyn & Bacon / Pearson Education. 6. Basımdan Çeviri: Mustafa Baloğlu, Nobel Akademik Yayıncılık, Ankara
  • Uçkun, N., & Dal, L. (2021). Kripto para yatırımcılarında finansal risk toleransı. Muhasebe ve Finansman Dergisi, (89), 155-170. https://doi.org/10.25095/mufad.852118
  • Umar, Z., Usman, M., Umar, M., & Ktaish, F. (2024). Interdependencies and risk management strategies between green cryptocurrencies and traditional energy sources. Energy Economics, 136, 107742. https://doi.org/10.1016/j.eneco.2024.107742
  • Ye, W., Wong, W. K., Arnone, G., Nassani, A. A., Haffar, M., & Faiz, M. F. (2023). Crypto currency and green investment impact on global environment: A time series analysis. International Review of Economics & Finance, 86, 155-169. https://doi.org/10.1016/j.iref.2023.01.030
  • Yousaf, I., Abrar, A., Yousaf, U. B., & Goodell, J. W. (2024). Environmental attention and uncertainties of cryptocurrency market: Examining linkages with crypto-mining stocks. Finance Research Letters, 59, 104672. https://doi.org/10.1016/j.frl.2023.10467
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Finans, Finans ve Yatırım (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Gönül Çifçi 0000-0002-5788-7461

Erken Görünüm Tarihi 23 Mart 2025
Yayımlanma Tarihi
Gönderilme Tarihi 16 Eylül 2024
Kabul Tarihi 8 Mart 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 27 Sayı: 1

Kaynak Göster

APA Çifçi, G. (2025). Kahverengi kripto ve yeşil kripto paraların yatırımcı risk toleransı ile ilişkilisi: Yerli yatırımcılar bazında A-ARDL ve NARDL yöntemleri ile bir değerlendirme. Afyon Kocatepe Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 27(1), 130-153. https://doi.org/10.33707/akuiibfd.1551277


22365