Cryptocurrency Trading: A Comprehensive Survey.
作者： Carmine Ventre , Lingbo Li , Leslie Kanthan , Fan Wu , Michail Basios
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摘要: Since the inception of cryptocurrencies, an increasing number financial institutions are getting involved in cryptocurrency trading. It is therefore important to summarise existing research papers and results on This paper provides a comprehensive survey trading research, by covering 118 various aspects (e.g.,cryptocurrency systems, bubble extreme condition, prediction volatility return,crypto-assets portfolio construction crypto-assets, technical others). also analyses datasets, trends distribution among objects (contents/properties) technologies, concluding with promising opportunities
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I. Rish, An empirical study of the naive Bayes classifier ,(2001)
Geoffrey E. Hinton, Ruslan Salakhutdinov, Deep Boltzmann machines international conference on artificial intelligence and statistics. pp. 448- 455 ,(2009)
Matthew Wiener, Andy Liaw, Classification and Regression by randomForest ,(2007)
Ryan Farell, An Analysis of the Cryptocurrency Industry ,(2015)
Ben Vogelvang, Econometrics: Theory and Applications with EViews ,(2004)
Shlomo Havlin, Shlomo Havlin, Fengzhong Wang, H. Eugene Stanley, Philipp Weber, Philipp Weber, Irena Vodenska-Chitkushev, Relation between volatility correlations in financial markets and Omori processes occurring on all scales Physical Review E. ,vol. 76, pp. 016109- ,(2007) , 10.1103/PHYSREVE.76.016109
G. Holmes, A. Donkin, I.H. Witten, WEKA: a machine learning workbench intelligent information systems. pp. 357- 361 ,(1994) , 10.1109/ANZIIS.1994.396988
Robert Flood, Robert Hodrick, Paul Kaplan, An Evaluation of Recent Evidence on Stock Market Bubbles Social Science Research Network. ,(1986) , 10.3386/W1971
William Johnson, Bea Calo, Global trading system ,(2001)
Jerome H. Friedman, Greedy function approximation: A gradient boosting machine. Annals of Statistics. ,vol. 29, pp. 1189- 1232 ,(2001) , 10.1214/AOS/1013203451