Big data tools for Islamic financial analysis

• Author: Emna Mnif,Anis Jarboui,M. Kabir Hassan,Khaireddine Mouakhar
• Date: 01 January 2020
• DOI: http://doi.org/10.1002/isaf.1463
• Published date: 01 January 2020

RESEARCH ARTICLE

Big data tools for Islamic financial analysis

Emna Mnif

1

| Anis Jarboui

2

| M. Kabir Hassan

3

| Khaireddine Mouakhar

4

1

Lartige Laboratory, Sfax University, Sfax,

Tunisia

2

ISAAS, Sfax University, Sfax, Tunisia

3

Department of Economics and Finance,

University of New Orleans, New Orleans, LA,

USA

4

EM Normandie, Laboratoire Métis, Le Havre,

France

Correspondence

M. Kabir Hassan, Department of Economics

and Finance, University of New Orleans. New

Orleans, LA 70148, USA.

Email: mhassan@uno.edu

Summary

Behavioural science states that emotions, principles and the manner of thinking can

affect the behaviour of individuals and even investors in their decision making on

financial markets. In this paper, we have tried to measure the investor sentiment by

three means of big data. The first is based on a search query of a list of words related

to Islamic context. The second is inferred from the engagement degree on social

media. The last measure of sentiment is built, based on the Twitter API classified into

positive and negative directions by a machine learning algorithm based on the naive

Bayes method. Then, we investigate whether these sensations and emotions have an

impact on the market sentiment and the price fluctuations by means of a vector

autoregression model and Granger causality analysis. In the final step, we apply the

agent-based simulation by means of the sequential Monte Carlo method with

the control of our Twitter measure on Islamic index returns. We show, then, that the

three social media sentiment measures present a remarkable impact on the contem-

poraneous and lagged returns of the different Islamic assets studied. We also give an

estimation of the parameters of the latent variables relative to the agent model

studied.

KEYWORDS

agent-based simulation, big data, Islamic finance, sentiment analysis, sequential Monte Carlo

simulation

1|INTRODUCTION

The number of Muslims in 2010 is estimated at 1.6 billion worldwide,

or 23.4% of the world population. Thus, they have more than $800

billion to invest. This capital is currently increasing by about 15% per

year. The recent build-up of liquidity in Muslim countries is attracting

the attention of stakeholders in the financial market. That is why

many analysts agree to study the Islamic financial market to detect

the sources of growth and performance and provide returns in the

future. As a part of these studies, this work aims to analyse the behav-

iour of the investor by quantifying the emotional component and

assessing the factors affecting the performance of Islamic stock

markets.

By analysing Islamic finance, it is observed that it is simulta-

neously ethical and behavioural finance. Indeed, this finance is a com-

partment of ethical finance because it is characterized by a moral and

socially responsible dimension and could meet a need that goes

beyond funding (Guéranger, 2009). Islamic finance is based on the

respect of Islamic principles. It acts out as a specific filtering material

and exclusion sector, which could deflect the behaviour of an investor

to one choice or another. This is why we have chosen to address this

issue not yet addressed massively by researchers, part of the evalua-

tion framework of the Islamic sentimental dimension and its impact

on the Islamic financial market.

Nowadays, Internet technologies are used by companies and indi-

viduals more and more. In other words, social media represents an

Received: 22 June 2019 Revised: 12 October 2019 Accepted: 28 November 2019

DOI: 10.1002/isaf.1463

© 2020 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/isaf Intell Sys Acc Fin Mgmt. 2020;27:10–21.

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