Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting
作者：
Highlights：
• Extending the MSVR to the scenario of interval-valued time series forecasting.
• The parameters of MSVR are tuned using firefly algorithm (abbreviated to FA-MSVR).
• Assessing the forecasting ability of FA-MSVR on statistical and economic criteria.
• The experimental analysis is based on one- and multi-step-ahead forecasts.
• FA-MSVR is a promising method for interval forecasting of financial time series.
摘要
•Extending the MSVR to the scenario of interval-valued time series forecasting.•The parameters of MSVR are tuned using firefly algorithm (abbreviated to FA-MSVR).•Assessing the forecasting ability of FA-MSVR on statistical and economic criteria.•The experimental analysis is based on one- and multi-step-ahead forecasts.•FA-MSVR is a promising method for interval forecasting of financial time series.
论文关键词：Stock price forecasting,Interval-valued data,Multiple-output support vector regression,Firefly algorithm,Trading strategy
论文评审过程：Received 25 January 2013, Revised 9 September 2013, Accepted 9 October 2013, Available online 16 October 2013.
论文官网地址：https://doi.org/10.1016/j.knosys.2013.10.012
