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Sensors 2021, 21, 6319 15 of 16 References to devise trading strategies for cryptocurrencies and help investors and macroeconomic policymakers making better investment decisions. This article provides avenues for further research in digital currency portfolios by comparing our model with other existing evolutionary machine learning algorithms to achieve more accurate results. Author Contributions: Data curation, E.M. and S.M.; investigation, E.M. and V.L.; formal analysis and methodology, E.M., V.L., S.M., and C.M.-B.; writing—original draft, E.M.; writing—review and editing, V.L. and C.M.-B. All authors have read and agreed to the submitted version of the manuscript. Funding: This research was partially supported by FONDECYT, project grant number 1200525 (V.L.), from the National Agency for Research and Development (ANID) of the Chilean government under the Ministry of Science, Technology, Knowledge and Innovation. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The analyzed data and used codes are available under request. Acknowledgments: The authors would also like to thank the editor and two reviewers for their constructive comments which led to improving the presentation of the manuscript. Conflicts of Interest: The authors declare no conflict of interest. 1. Chahuan-Jimenez, K.; Rubilar, R.; de la Fuente-Mella, H.; Leiva, V. Breakpoint analysis for the COVID-19 pandemic and its effect on the stock markets. Entropy 2021, 23, 100. [CrossRef] 2. Dyhrberg, A.H. Bitcoin, gold and the dollar—A GARCH volatility analysis. Financ. Res. Lett. 2016, 16, 85–92. [CrossRef] 3. Makala, D.; Li, Z. Prediction of gold price with ARIMA and SVM. J. Phys. Conf. Ser. 2021, 1767, 012022. [CrossRef] 4. Salisu, A.A.; Ogbonna, A.E. The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect. Glob. Financ. J. 2021. [CrossRef] 5. Shen, M.; Zhu, L.; Xu, K. Blockchain: Empowering Secure Data Sharing; Springer: Singapore, 2020. 6. Sanchez, L.; Leiva, V.; Galea, M.; Saulo, H. Birnbaum-Saunders quantile regression and its diagnostics with application to economic data. Appl. Stoch. Model. Bus. Ind. 2021, 37, 53–73. [CrossRef] 7. Saulo, H.; Dasilva, A.; Leiva, V.; Sanchez, L.; de la Fuente-Mella, H. Log-symmetric quantile regression models. Stat. Neerl. 2021. [CrossRef] 8. Bouoiyour, J.; Selmi, R.; Wohar, M.E. Measuring the response of gold prices to uncertainty: An analysis beyond the mean. Econ. Model. 2018, 75, 105–116. [CrossRef] 9. Bouri, E.; Gupta, R.; Tiwari, A.K.; Roubaud, D. Does bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in- quantile regressions. Financ. Res. Lett. 2017, 23, 87–95. [CrossRef] 10. Dastgir, S.; Demir, E.; Downing, G.; Gozgor, G.; Lau, C.K.M. The causal relationship between bitcoin attention and bitcoin returns: Evidence from the copula-based granger causality test. Financ. Res. Lett. 2019, 28, 160–164. [CrossRef] 11. Kim, M.J.; Canh, N.P.; Park, S.Y. Causal relationship among cryptocurrencies: A conditional quantile approach. Financ. Res. Lett. 2021. [CrossRef] 12. Sim, N.; Zhou, H. Oil prices, us stock return, and the dependence between their quantiles. J. Bank. Financ. 2015, 55, 1–8. [CrossRef] 13. Mensi, W.; Sensoy, A.; Vo, X.V.; Kang, S.H. Impact of covid-19 outbreak on asymmetric multifractality of gold and oil prices. Resour. Policy 2020, 69, 101829. [CrossRef] 14. de la Fuente-Mella, H.; Rubilar, R.; Chahuan-Jimenez, K.; Leiva, V. Modeling COVID-19 cases statistically and evaluating their effect on the economy of countries. Mathematics 2021, 9, 1558. [CrossRef] 15. Yousaf, I.; Ali, S. Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic. Financ. Innov. 2020, 6, 1. [CrossRef] 16. Bustos, N.; Tello, M.; Droppelmann, G.; Garcia, N.; Feijoo, F.; Leiva, V. Machine learning techniques as an efficient alternative diagnostic tool for COVID-19 cases. Signa Vitae 2021. [CrossRef] 17. Iqbal, N.; Fareed, Z.; Wan, G.; Shahzad, F. Asymmetric nexus between covid-19 outbreak in the world and cryptocurrency market. Int. Rev. Financ. Anal. 2021, 73, 101613. [CrossRef] 18. Conlon, T.; Corbet, S.; McGee, R.J. Are cryptocurrencies a safe haven for equity markets? An international perspective from the covid-19 pandemic. Res. Int. Bus. Financ. 2020, 54, 101248. [CrossRef] [PubMed] 19. Mokni, K.; Ajmi, A.N. Cryptocurrencies vs. US dollar: Evidence from causality in quantiles analysis. Econ. Anal. Policy 2021, 69, 238–252. [CrossRef]PDF Image | Predicting Cryptocurrency Returns Based on the Gold Prices
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