Neural network foreign exchange trading system using CCS-IRS basis: Empirical evidence from Korea

作者：

Highlights：

• Developed a Neural Network foreign exchange trading system using CCS-IRS basis.

• The NN foreign exchange trading model outperforms XGBoost and LR model in USDKRW.

• The NN trading model outperforms a buy-n-hold and sell-n-hold strategies in USDKRW.

• The CCS-IRS basis replaces the CDS premium as a new leading indicator in USDKRW.

摘要

•Developed a Neural Network foreign exchange trading system using CCS-IRS basis.•The NN foreign exchange trading model outperforms XGBoost and LR model in USDKRW.•The NN trading model outperforms a buy-n-hold and sell-n-hold strategies in USDKRW.•The CCS-IRS basis replaces the CDS premium as a new leading indicator in USDKRW.

论文关键词：CCS-IRS basis,Chaos analysis,Correlation dimension,Foreign exchange trading,Neural networks,USDKRW

论文评审过程：Received 5 May 2021, Revised 17 May 2022, Accepted 31 May 2022, Available online 3 June 2022, Version of Record 9 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117718