1. GJR-GARCH Volatility Modeling under NIG and ANN for Predicting Top Cryptocurrencies. (2021). Saha, Pritam ; Nguyen, Nguyet ; Islam, Mohammad Rafiqul ; Mostafa, Fahad.
   In: JRFM.
   RePEc:gam:jjrfmx:v:14:y:2021:i:9:p:421-:d:628582.

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2. Bitcoin and Global Political Uncertainty €“ Evidence from the U.S. Election Cycle. (2020). Burggraf, Tobias.
   In: Economics Bulletin.
   RePEc:ebl:ecbull:eb-20-00047.

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1. Öğüt, H, M. Mete Doğanay, N.B. Ceylan, R. Aktaş (2012). Prediction of bank financial strength ratings: The case of Turkey. Economic Modelling, 29(3), 632-640.

2. Amiti M., Redding S., David Weinstein (2019) The impact of the 2018 trade war on U.S. prices and welfare NBER Working Paper No. 25672.

3. Aysan, A. F., Demir, E., Gozgor, G., & Lau, C. K. M. (2019). Effects of the geopolitical risks on Bitcoin returns and volatility. Research in International Business and Finance, 47, 511-518.

4. Baek, C., Elbeck, M. (2014). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters, 22(1), 30-34.
   Paper not yet in RePEc: Add citation now
   

5. Baker Scott R., Nicholas Bloom, Steven J. Davis (2016) Measuring Economic Policy Uncertainty, The Quarterly Journal of Economics, 131 (4), 1593–1636.

6. Bouoiyour, J. & Selmi, R. (2016) Bitcoin: a beginning of a new phase? Economics Bulletin, 36(3).

7. Bouri Elie, Peter Molnár, Georges Azzi, David Roubaud and Lars Ivar Hagfors (2017a) On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?, Finance Research Letters, 20, 192-198.
   Paper not yet in RePEc: Add citation now
   

8. Bouri, E., Gkillas, K., Gupta, R. (2019). Trade Uncertainties and the Hedging Abilities of Bitcoin. Department of Economics, University of Pretoria, Working Paper No. 201948.

9. Bouri, E., Gupta, R., Lau, C. K. M., Roubaud, D., Wang, S. (2018). Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles. The Quarterly Review of Economics and Finance, 69, 297-307.

10. Bouri, E., Jalkh, N., Molnár, P., Roubaud, D. (2017b) Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?. Applied Economics, 49(50), 5063-5073.
    Paper not yet in RePEc: Add citation now
    

11. Caldara, D., Iacoviello, M., Molligo, P., Prestipino, A., & Raffo, A. (2019). The Economic Effects of Trade Policy Uncertainty. Journal of Monetary Economics, https://doi.org/10.1016/j.jmoneco.2019.11.002.

12. Campbell, J.Y., (2008) Viewpoint: estimating the equity premium, Canadian Journal of Economics, 41, 1–21.

13. Cheng, H. P., Yen, K. C. (2019). The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market. Finance Research Letters, 101308.
    Paper not yet in RePEc: Add citation now
    

14. Ciaian, P., Rajcaniova, M., Kancs, D. (2016). The economics of Bitcoin price formation. Applied Economics, 48(19), pp.1799–1815.

15. Cong, Lin William, Zhiguo He, Jiasun Li (2019). Decentralized mining in centralized pools, Technical report, National Bureau of Economic Research.

16. Corbet, S., Meegan, A., Larkin, C., Lucey, B., Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics Letters, 165, 28-34.

17. Cortes C., Vapnik V. (1995) Support-Vector Networks, Machine Learning, vol 20, pp. 273-297.
    Paper not yet in RePEc: Add citation now
    
18. Davis, S.J., Liu, D., Sheng, X.S. (2019). Economic Policy Uncertainty in China since 1949: The View from Mainland Newspapers. Mimeo.
    Paper not yet in RePEc: Add citation now
    

19. Demir, E., Gozgor, G., Lau, C. K. M., Vigne, S. A. (2018). Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters, 26, 145-149 Fajgelbaum P., Goldberg P., Kennedy P., Khandelwal A. (2019) The return to protectionism, NBER Working Paper No. 25638, accessed at: http://www.econ.ucla.edu/pfajgelbaum/RTP.pdf Fang, L., Bouri, E., Gupta, R., Roubaud, D. (2019). Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?. International Review of Financial Analysis, 61, 29-36.

20. Glaser, Florian and Zimmermann, Kai and Haferkorn, Martin and Weber, Moritz Christian and Siering, Michael, Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions (April 15, 2014). ECIS 2014 (Tel Aviv). Available at SSRN: https://ssrn.com/abstract=2425247.
    Paper not yet in RePEc: Add citation now
    

21. Gozgor, G., Tiwari, A. K., Demir, E., Akron, S. (2019). The relationship between Bitcoin returns and trade policy uncertainty. Finance Research Letters, 29, 75-82.

22. Härdle, W., Lee Y-J, Schäfer D., Yeh Y-R (2009) Variable selection and oversampling in the use of smooth support vector machines for predicting the default risk of companies, Journal of Forecasting, 28(6), 512-534.

23. Hong, H. and Stein, J.C. (1999). A unified theory of under-reaction, momentum trading, and overreaction in asset markets. The Journal of Finance, 54(6), 2143-2184.

24. Jushan Bai and Serena Ng (2008). Forecasting economic time series using targeted predictors. Journal of Econometrics, 146(2), 304-317.

25. Khandani, A E., A J. Kim, A. W. Lo (2010), Consumer credit-risk models via machinelearning algorithms, Journal of Banking & Finance, 34(11), 2767-2787.

26. Klein, T., Thu, H.P., Walther, T. (2018). Bitcoin is not the New Gold–A Comparison of Volatility, Correlation, and Portfolio Performance. International Review of Financial Analysis, 59, 105–116.

27. Kristoufek, L. (2015). What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis. PLoS ONE, 10(4), pp.1–19.
    Paper not yet in RePEc: Add citation now
    
28. Nakamoto, S., 2008. Bitcoin: A Peer-To-Peer Electronic Cash System available at: https://Bitcoin.org/Bitcoin.pdf .
    Paper not yet in RePEc: Add citation now
    

29. Nan, Z., Kaizoji, T. (2019). Market efficiency of the Bitcoin exchange rate: Weak and semi-strong form tests with the spot, futures and forward foreign exchange rates. International Review of Financial Analysis. 64, 273-281.

30. Panagiotidis, T., Stengos, T., Vravosinos, O. (2018). On the determinants of Bitcoin returns: A LASSO approach. Finance Research Letters, 27, 235-240.

31. Panagiotidis, T., Stengos, T., Vravosinos, O. (2019). The effects of markets, uncertainty and search intensity on Bitcoin returns. International Review of Financial Analysis, 63, 220-242.

32. Plakandaras V., Gupta R., Gogas P., Papadimitriou T. (2015), Forecasting the U.S, Real House Price Index, Economic Modelling, 45, 259-267.

33. Rubio G., Pomares H., Rojas I., Herrera L.J. (2011) A heuristic method for parameter selection in LS-SVM: Application to time series prediction, International Journal of Forecasting, 27(3), 725-739.

34. Shahzad, S.J.H., Bouri, E., Roubaud, D., Kristoufek L., Lucey, B. (2019). Is Bitcoin a better safe-haven investment than gold and commodities? International Review of Financial Analysis, 63, 322-330.

35. Sockin, Michael, and Wei Xiong (2018). A model of cryptocurrencies, Unpublished manuscript, Princeton University.
    Paper not yet in RePEc: Add citation now
    
36. Tibshirani R. (1996), Regression shrinkage and selection via the lasso, Journal of the Royal Statistics Society B, 58 (1), 267-288.
    Paper not yet in RePEc: Add citation now
    
37. Vapnik, V., Boser, B., Guyon, I. (1992) A training algorithm for optimal margin classifiers, Fifth Annual Workshop on Computational Learning Theory, Pittsburgh, ACM, 144–152.
    Paper not yet in RePEc: Add citation now
    

38. Vidal-Tomás, D., Ibañez, A. (2018). Semi-strong efficiency of Bitcoin. Finance Research Letters, 27, 259-265.

39. Wang, G. J., Xie, C., Wen, D., Zhao, L. (2018). When Bitcoin meets economic policy uncertainty (EPU): Measuring risk spillover effect from EPU to Bitcoin. Finance Research Letters. https://doi.org/10.1016/j.frl.2018.12.028 Yermack, D. (2013). Is Bitcoin a Real Currency? An Economic Appraisal, NBER Working Paper No. 19747.

40. Yermack, David (2017). Corporate governance and blockchains, Review of Finance 21, 7–31.

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   In: Working Papers.
   RePEc:mad:wpaper:2024-270.

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2. Bankruptcy prediction using fuzzy convolutional neural networks. (2023). Serret, Vanessa ; ben Jabeur, Sami.
   In: Research in International Business and Finance.
   RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531922002306.

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   In: Finance Research Letters.
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   In: Risks.
   RePEc:gam:jrisks:v:9:y:2021:i:9:p:155-:d:622521.

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   In: Economic Modelling.
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9. Banks and shareholders credit ratings – evidence from the European market. (2019). Chodnicka-Jaworska, Patrycja.
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   RePEc:sgm:fmuwwp:32019.

   Full description at Econpapers || Download paper

10. Forecasting Bitcoin Returns: Is there a Role for the U.S. – China Trade War?. (2019). Plakandaras, Vasilios ; GUPTA, RANGAN ; Bouri, Elie.
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    Full description at Econpapers || Download paper

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    Full description at Econpapers || Download paper

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    RePEc:pre:wpaper:201548.

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