Investigate the Operation of Random forest and Deep neural networks on Statistical Arbitrage Strategy

Subject Areas : Financial engineering

alireza  Fazlzadeh ¹ (department of management and business, Tabriz University, Tabriz, Iran)
Jafar  Haghigha ² (Department of management and business, Tabriz University, Tabriz, Iran)
Faranak  Pourkeivan ³ (Department of management and business, Tabriz University, Tabriz, Iran)
vahid  ahmadian ⁴ (Department of Accounting, tarbiat modares university, Tehran, iran)

Received: 2018-11-06 Accepted : 2019-05-18 Published : 2019-09-23

Keywords: Random forest, Statistical arbitrage, Deep neural networks,

Abstract :

 In this research, the statistical analysis of random forest effects has been done. Also, to evaluate the performance of the random forest algorithm in the field of statistical arbitrage compared to other models presented in the previous research, the comparison of the results from the application of this algorithm with deep neural network algorithm has been done. The models are taught with stock price information and the output from this technique categorizes stocks according to the position of buying and selling. Using this strategy, profitable positions are identified in market shares for profit. The results showed that the model of random forest with less error classification than deep neural network model. Using this strategy, profitable positions are identified in market shares for profit. The results showed that the model of random forest with less error classification than deep neural network model.