The best of two worlds: Forecasting high frequency volatility for cryptocurrencies and traditional currencies with Support Vector Regression
作者：
Highlights：
• Proposal of novel machine learning method to estimate volatility.
• Study of new market known as cryptocurrency market.
• Comparison between other volatility models.
• Evaluation of the models predictive power using statistical tests.
• Machine learning model yielded better results for low and high frequencies.
摘要
•Proposal of novel machine learning method to estimate volatility.•Study of new market known as cryptocurrency market.•Comparison between other volatility models.•Evaluation of the models predictive power using statistical tests.•Machine learning model yielded better results for low and high frequencies.
论文关键词：Volatility forecasting,Machine learning,GARCH,Cryptocurrency,Support vector machines,Exchange rates
论文评审过程：Received 11 September 2017, Revised 1 December 2017, Accepted 2 December 2017, Available online 6 December 2017, Version of Record 22 December 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.004
