IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i10p5383-d552611.html
   My bibliography  Save this article

The Nexus of Sophisticated Digital Assets with Economic Policy Uncertainty: A Survey of Empirical Findings and an Empirical Investigation

Author

Listed:
  • Nikolaos A. Kyriazis

    (Department of Economics, University of Thessaly, 38333 Volos, Greece)

Abstract

This paper sets out to explore the nexus between economic policy uncertainty (EPU) and digital currencies. An integrated survey takes place based on eleven primary studies. Furthermore, an econometric analysis is conducted by the threshold ARCH, simple asymmetric ARCH and non-linear ARCH specifications covering the bull and the bear markets as well as the highly volatile period up to the present. Threshold ARCH is found to provide the best fit for estimations. Outcomes reveal that Bitcoin is strongly connected with EPU while Ethereum and Litecoin are not but are strongly linked with Bitcoin performance. Moreover, weak negative effects of the VIX on both cryptocurrencies are detected while oil exerts weak positive impacts on Ethereum. Overall, Ethereum and Litecoin could serve for diversifiers against Bitcoin or hedgers against traditional assets during highly stressed periods with the advantage of not being affected by economic policy uncertainty news.

Suggested Citation

  • Nikolaos A. Kyriazis, 2021. "The Nexus of Sophisticated Digital Assets with Economic Policy Uncertainty: A Survey of Empirical Findings and an Empirical Investigation," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5383-:d:552611
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/10/5383/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/10/5383/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Shan & Tong, Mu & Yang, Zhongyi & Derbali, Abdelkader, 2019. "Does gold or Bitcoin hedge economic policy uncertainty?," Finance Research Letters, Elsevier, vol. 31(C), pages 171-178.
    2. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    3. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    4. Selgin, George, 2015. "Synthetic commodity money," Journal of Financial Stability, Elsevier, vol. 17(C), pages 92-99.
    5. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    6. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis & Corbet, Shaen, 2021. "Herding behaviour and price convergence clubs in cryptocurrencies during bull and bear markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    7. Muller, Ulrich A. & Dacorogna, Michel M. & Dave, Rakhal D. & Olsen, Richard B. & Pictet, Olivier V. & von Weizsacker, Jacob E., 1997. "Volatilities of different time resolutions -- Analyzing the dynamics of market components," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 213-239, June.
    8. Jareño, Francisco & González, María de la O & Tolentino, Marta & Sierra, Karen, 2020. "Bitcoin and gold price returns: A quantile regression and NARDL analysis," Resources Policy, Elsevier, vol. 67(C).
    9. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    10. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    11. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
    12. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    13. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    14. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    15. Beneki, Christina & Koulis, Alexandros & Kyriazis, Nikolaos A. & Papadamou, Stephanos, 2019. "Investigating volatility transmission and hedging properties between Bitcoin and Ethereum," Research in International Business and Finance, Elsevier, vol. 48(C), pages 219-227.
    16. Νikolaos A. Kyriazis & Paraskevi Prassa, 2019. "Which Cryptocurrencies Are Mostly Traded in Distressed Times?," JRFM, MDPI, vol. 12(3), pages 1-12, August.
    17. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    18. Kaiser, Lars & Stöckl, Sebastian, 2020. "Cryptocurrencies: Herding and the transfer currency," Finance Research Letters, Elsevier, vol. 33(C).
    19. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    20. Higgins, Matthew L & Bera, Anil K, 1992. "A Class of Nonlinear ARCH Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-158, February.
    21. Yaw‐Huei Wang & Kuang‐Chieh Yen, 2019. "The information content of the implied volatility term structure on future returns," European Financial Management, European Financial Management Association, vol. 25(2), pages 380-406, March.
    22. Brauneis, Alexander & Mestel, Roland & Riordan, Ryan & Theissen, Erik, 2021. "How to measure the liquidity of cryptocurrency markets?," Journal of Banking & Finance, Elsevier, vol. 124(C).
    23. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    24. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
    25. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    26. Nikolaos A. Kyriazis, 2020. "The Effects Of Gold, Stock Markets And Geopolitical Uncertainty On Bitcoin Prices And Volatility," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-15, December.
    27. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    28. Siwen Zhou, 2021. "Exploring the driving forces of the Bitcoin currency exchange rate dynamics: an EGARCH approach," Empirical Economics, Springer, vol. 60(2), pages 557-606, February.
    29. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
    30. Papadamou, Stephanos & Kyriazis, Νikolaos A. & Tzeremes, Panayiotis G., 2019. "Unconventional monetary policy effects on output and inflation: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 295-305.
    31. Stephanos Papadamou & Costas Siriopoulos & Nikolaos A. Kyriazis, 2020. "A survey of empirical findings on unconventional central bank policies," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(7), pages 1533-1577, April.
    32. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    33. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    34. Nikolaos A. Kyriazis, 2021. "Trade Policy Uncertainty Effects on Macro Economy and Financial Markets: An Integrated Survey and Empirical Investigation," JRFM, MDPI, vol. 14(1), pages 1-20, January.
    35. Yu, Miao, 2019. "Forecasting Bitcoin volatility: The role of leverage effect and uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    36. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    37. Cheng, Hui-Pei & Yen, Kuang-Chieh, 2020. "The relationship between the economic policy uncertainty and the cryptocurrency market," Finance Research Letters, Elsevier, vol. 35(C).
    38. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    39. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
    40. Bouri, Elie & Gupta, Rangan, 2021. "Predicting Bitcoin returns: Comparing the roles of newspaper- and internet search-based measures of uncertainty," Finance Research Letters, Elsevier, vol. 38(C).
    41. Al-Yahyaee, Khamis Hamed & Rehman, Mobeen Ur & Mensi, Walid & Al-Jarrah, Idries Mohammad Wanas, 2019. "Can uncertainty indices predict Bitcoin prices? A revisited analysis using partial and multivariate wavelet approaches," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 47-56.
    42. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Bayesian Graphical Models for STructural Vector Autoregressive Processes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 357-386, March.
    43. Yen, Kuang-Chieh & Cheng, Hui-Pei, 2021. "Economic policy uncertainty and cryptocurrency volatility," Finance Research Letters, Elsevier, vol. 38(C).
    44. Gurdgiev, Constantin & O’Loughlin, Daniel, 2020. "Herding and anchoring in cryptocurrency markets: Investor reaction to fear and uncertainty," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    45. Das, Debojyoti & Le Roux, Corlise Liesl & Jana, R.K. & Dutta, Anupam, 2020. "Does Bitcoin hedge crude oil implied volatility and structural shocks? A comparison with gold, commodity and the US Dollar," Finance Research Letters, Elsevier, vol. 36(C).
    46. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    47. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    48. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
    49. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    50. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    51. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    52. Νikolaos A. Kyriazis, 2021. "The effects of geopolitical uncertainty on cryptocurrencies and other financial assets," SN Business & Economics, Springer, vol. 1(1), pages 1-14, January.
    53. Ur Koumba & Calvin Mudzingiri & Jules Mba, 2020. "Does uncertainty predict cryptocurrency returns? A copula-based approach," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 13(1), pages 67-88, January.
    54. Capie, Forrest & Mills, Terence C. & Wood, Geoffrey, 2005. "Gold as a hedge against the dollar," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(4), pages 343-352, October.
    55. Nikolaos A. Kyriazis, 2020. "Is Bitcoin Similar to Gold? An Integrated Overview of Empirical Findings," JRFM, MDPI, vol. 13(5), pages 1-19, May.
    56. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    57. Wang, Gang-Jin & Xie, Chi & Wen, Danyan & Zhao, Longfeng, 2019. "When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin," Finance Research Letters, Elsevier, vol. 31(C).
    58. Vidal-Tomás, David & Ibáñez, Ana M. & Farinós, José E., 2019. "Herding in the cryptocurrency market: CSSD and CSAD approaches," Finance Research Letters, Elsevier, vol. 30(C), pages 181-186.
    59. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Al-Jarrah, Idries Mohammad Wanas & Hamdi, Atef & Kang, Sang Hoon, 2019. "Volatility forecasting, downside risk, and diversification benefits of Bitcoin and oil and international commodity markets: A comparative analysis with yellow metal," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 104-120.
    60. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
    61. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis G., 2021. "Non-linear causal linkages of EPU and gold with major cryptocurrencies during bull and bear markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Inzamam Ul Haq & Apichit Maneengam & Supat Chupradit & Wanich Suksatan & Chunhui Huo, 2021. "Economic Policy Uncertainty and Cryptocurrency Market as a Risk Management Avenue: A Systematic Review," Risks, MDPI, vol. 9(9), pages 1-24, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    2. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    3. Nikolaos A. Kyriazis, 2020. "Is Bitcoin Similar to Gold? An Integrated Overview of Empirical Findings," JRFM, MDPI, vol. 13(5), pages 1-19, May.
    4. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2022. "When bitcoin lost its position: Cryptocurrency uncertainty and the dynamic spillover among cryptocurrencies before and during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    5. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis G., 2021. "Non-linear causal linkages of EPU and gold with major cryptocurrencies during bull and bear markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    6. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    7. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    8. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    9. Long, Shaobo & Pei, Hongxia & Tian, Hao & Lang, Kun, 2021. "Can both Bitcoin and gold serve as safe-haven assets? — A comparative analysis based on the NARDL model," International Review of Financial Analysis, Elsevier, vol. 78(C).
    10. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    11. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    12. Elsayed, Ahmed H. & Gozgor, Giray & Yarovaya, Larisa, 2022. "Volatility and return connectedness of cryptocurrency, gold, and uncertainty: Evidence from the cryptocurrency uncertainty indices," Finance Research Letters, Elsevier, vol. 47(PB).
    13. Anastasiadis Panagiotis & Katsaros Efthymios & Koutsioukis Anastasios-Taxiarchis & Pandazis Athanasios, 2020. "GARCH Modelling of High-Capitalization Cryptocurrencies' Impacts During Bearish Markets," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(3), pages 87-106.
    14. Wu, Wanshan & Tiwari, Aviral Kumar & Gozgor, Giray & Leping, Huang, 2021. "Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures," Research in International Business and Finance, Elsevier, vol. 58(C).
    15. Mustafa Tevfik Kartal & Mustafa Kevser & Fatih Ayhan, 2023. "Asymmetric effects of global factors on return of cryptocurrencies by novel nonlinear quantile approaches," Economic Change and Restructuring, Springer, vol. 56(3), pages 1515-1535, June.
    16. Siwen Zhou, 2021. "Exploring the driving forces of the Bitcoin currency exchange rate dynamics: an EGARCH approach," Empirical Economics, Springer, vol. 60(2), pages 557-606, February.
    17. Nikolaos A. Kyriazis, 2021. "Investigating the diversifying or hedging nexus of cannabis cryptocurrencies with major digital currencies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 845-861, December.
    18. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    19. Simran, & Sharma, Anil Kumar, 2023. "Asymmetric impact of economic policy uncertainty on cryptocurrency market: Evidence from NARDL approach," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    20. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5383-:d:552611. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.