Exchange Rate Forecasting and Portfolio Optimization Based on Deep Learning and Evolutionary Computation
[1]Li Zhangxiao,Song Wei,Tian Ye.Exchange Rate Forecasting and Portfolio Optimization Based on Deep Learning and Evolutionary Computation[J].Journal of Zhengzhou University (Engineering Science),2019,40(01):92-96.[doi:10.13705/j.issn.1671-6833.2019.01.014]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 01
Page number:
92-96
Column:
Public date:
2019-01-10
- Title:
- Exchange Rate Forecasting and Portfolio Optimization Based on Deep Learning and Evolutionary Computation
- Keywords:
- Forex forecasting; Portfolio optimization; recurrent neural network; evolutionary algorithm
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2019.01.014
- Abstract:
- The techniques in deep learning and evolutionary computation were adopted to forecast the exchange rate and to optimize the portfolio respectively. Firstly, recurrent neural network is used to build an exchange rate forecasting model, to forecasting the price of instrument and to calculate its expected yield. Then, a bi-objective portfolio model, i.e., maximizing the expected yield and minimizing the risk. For approximating the real market, the proposed model could allow long and short selling, and could also consider the influence of spread. Based on the expected yields of multiple instruments and the proposed portfolio model,a multi-objective evolutionary algorithm was adopted to search for the optimal portfolio. According to the back test on the historical data of multiple instruments, it was verified that the proposed approach could make profit in the exchange market
- References:
- -
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Last Update:
2019-03-02