Open Access

ARTICLE

Stock Market Trading Based on Market Sentiments and Reinforcement Learning

by K. M. Ameen Suhail¹, Syam Sankar¹, Ashok S. Kumar², Tsafack Nestor³, Naglaa F. Soliman^4,*, Abeer D. Algarni⁴, Walid El-Shafai⁵, Fathi E. Abd El-Samie^4,5

1 Department of Computer Science & Engineering, NSS College of Engineering, Palakkad, 678008, Kerala, India
2 Department of Electronics and Communication Engineering, NSS College of Engineering, Palakkad, 678008, Kerala, India
3 Unité de Recherche de Matière Condensée, D'Electronique et de Traitement du Signal (URAMACETS), Department of Physics, University of Dschang, P. O. Box 67, Dschang, Cameroon
4 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, 84428, Saudi Arabia
5 Department Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

* Corresponding Author: Naglaa F. Soliman. Email:

Computers, Materials & Continua 2022, 70(1), 935-950. https://doi.org/10.32604/cmc.2022.017069

Received 20 January 2021; Accepted 16 May 2021; Issue published 07 September 2021

Abstract

Stock market is a place, where shares of different companies are traded. It is a collection of buyers’ and sellers’ stocks. In this digital era, analysis and prediction in the stock market have gained an essential role in shaping today's economy. Stock market analysis can be either fundamental or technical. Technical analysis can be performed either with technical indicators or through machine learning techniques. In this paper, we report a system that uses a Reinforcement Learning (RL) network and market sentiments to make decisions about stock market trading. The system uses sentiment analysis on daily market news to spot trends in stock prices. The sentiment analysis module generates a unified score as a measure of the daily news about sentiments. This score is then fed into the RL module as one of its inputs. The RL section gives decisions in the form of three actions: buy, sell, or hold. The objective is to maximize long-term future profits. We have used stock data of Apple from 2006 to 2016 to interpret how sentiments affect trading. The stock price of any company rises, when significant positive news become available in the public domain. Our results reveal the influence of market sentiments on forecasting of stock prices.

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Keywords

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