An Efficient Word Embedding and Deep Learning Based Model to Forecast the Direction of Stock Exchange Market Using Twitter and Financial News Sites: A Case of Istanbul Stock Exchange (BIST 100)

Zeynep Hilal Kilimci,Ramazan Duvar

doi:10.1109/access.2020.3029860

Abstract

To forecast the movement directions of stocks, exchange rates, and stock markets are significant and an active research area for investors, analysts, and researchers. In this paper, word embedding and deep learning-based direction prediction of Istanbul Stock Exchange (BIST 100) is proposed by analyzing nine banking stocks with high volume in BIST 100. Though English news articles have been employed for forecasting of market direction previously, to the best of our knowledge, Turkish news articles and user comments from social media and different platforms have not been utilized with the combination of deep learning techniques and word embedding methods to predict the direction of Turkish stocks and market. For this objective, long short-term memory networks, recurrent neural networks, convolutional neural networks as deep learning algorithms and Word2Vec, GloVe, and FastText as word embedding models are evaluated. To demonstrate the effectiveness of proposed model, four different sources of Turkish news are collected. The news articles about stocks from Public Disclosure Platform (KAP), text-based technical analysis of each stock from Bigpara, user comments from both Twitter and Mynet Finans platforms are gathered. Experiment results demonstrate that the combination of deep learning techniques and word embedding methods have a great potential to predict the direction of BIST 100.

Highlights

The Istanbul Stock Exchange is expressed as BIST 100 index that is a frequently utilized abridgment for the Turkey’s stock exchange
EXPERIMENTAL RESULTS In this work, far-reaching experiments are accomplished with the combination word embedding and deep learning techniques for the purpose of forecasting the direction of BIST 100 by using high volume stock market shares in BIST 100
In this study, unlike the recent researches on forecasting the stock market direction, we focus on financial sentiment analysis using the Turkish data sets collected from both a social media platform and websites including technical analysis and news to analyze the stock market direction by evaluating high volume stocks in BIST 100

Summary

Introduction

The Istanbul Stock Exchange is expressed as BIST 100 index that is a frequently utilized abridgment for the Turkey’s stock exchange. Istanbul Stock Exchange (ISE) includes the following price indices. We focus on both fundamental and technical analysis are taken into account. For this purpose, different Turkish text resources are collected from different platforms to analyze the direction of movement of Istanbul Stock Exchange (BIST 100). The reason behind of focusing on fundamental and technical analysis is that some of investors can be influenced by comments made on various social media platforms and websites [1] and manage their own investments using this way. Choosing a social media environment such as Twitter [2,3] that keeps the pulse of the society and see the comments made in this environment as an investment tool for them can be considered normal for VOLUME XX, 2017

Methods

Results

Conclusion