Search results

1 – 10 of 496
Article
Publication date: 26 September 2023

Mohammed Ayoub Ledhem and Warda Moussaoui

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric…

Abstract

Purpose

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

Design/methodology/approach

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

Findings

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

Practical implications

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

Originality/value

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Details

Journal of Modelling in Management, vol. 19 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

Open Access
Article
Publication date: 19 April 2024

Qingmei Tan, Muhammad Haroon Rasheed and Muhammad Shahid Rasheed

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a…

Abstract

Purpose

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Design/methodology/approach

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

Findings

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

Originality/value

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

Details

China Accounting and Finance Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1029-807X

Keywords

Article
Publication date: 17 April 2024

Prince Kumar Maurya, Rohit Bansal and Anand Kumar Mishra

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

Abstract

Purpose

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

Design/methodology/approach

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

Findings

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

Originality/value

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 24 October 2021

Maqsood Ahmad

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management…

1233

Abstract

Purpose

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

Design/methodology/approach

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

Findings

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

Practical implications

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Originality/value

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

Details

Qualitative Research in Financial Markets, vol. 16 no. 3
Type: Research Article
ISSN: 1755-4179

Keywords

Open Access
Article
Publication date: 4 August 2022

Pramath Nath Acharya, Srinivasan Kaliyaperumal and Rudra Prasanna Mahapatra

In the research of stock market efficiency, it is argued that the stock market moves randomly and absorbs all the available information. As a result, it is quite impossible to…

1161

Abstract

Purpose

In the research of stock market efficiency, it is argued that the stock market moves randomly and absorbs all the available information. As a result, it is quite impossible to make predictions about the possible future movement by the investors. But literatures have detected certain calendar anomalies where a day(s) in a week or month(s) in a year or a particular event in a year becomes conducive for investors to earn more than the normal. Hence, the purpose of this study is to find out the month of the year effect in the Indian stock market.

Design/methodology/approach

In this study, daily time series data of Sensex and Nifty from 1996 to 2021 is used. The study uses month dummies to capture the effect. Different variants of generalised autoregressive conditional heteroskedasticity (GARCH) models, both symmetric and asymmetric, are used in the study to model the conditional volatility in the presence month effect.

Findings

This study found the September effect in the return series of both the stock market. Apart from that, asymmetric GARCH models are found to be the best fit model to estimate conditional volatility.

Originality/value

This study is an endeavour to study month of the year effect in the Indian context. This research will provide valuable insight for studying the different calendar anomalies.

Details

Vilakshan - XIMB Journal of Management, vol. 21 no. 1
Type: Research Article
ISSN: 0973-1954

Keywords

Article
Publication date: 10 February 2023

Tahir Akhtar

This study compares the motives of holding cash between developed (Australian) and developing (Malaysian) financial markets.

Abstract

Purpose

This study compares the motives of holding cash between developed (Australian) and developing (Malaysian) financial markets.

Design/methodology/approach

For the period 2006–2020, the t-test, fixed-effect and generalised method of moment (GMM) model have been applied to a sample of 1878 (1,165 Australian and 713 Malaysian) firms.

Findings

The empirical results reveal that firms in developed financial markets hold higher cash compared to the developing financial markets. The findings confirm that motives to hold cash differ between developed and developing financial markets. The GMM findings further show that cash holdings (CH) in Australia are higher due to higher ratios of cash flow, research and development (R&D) and return on assets (ROA), and lower due to larger dividend payments. In the Malaysian market, however, cash flows and R&D are ineffectual, ROA falls and dividend payments rise CH.

Practical implications

The study helps managers, practitioners and investors understand that firms' distinct economic, institutional, accounting and financial environments are important. To attain the desired outcomes, they must thus comprehend and consider these considerations while developing suitable liquidity strategies.

Originality/value

To the authors' best knowledge, this is the initial research demonstrating how varied cash motives and their ramifications are in developed and developing financial markets. Therefore, this study identifies the importance that CH motives varied among financial markets and that findings from a particular market cannot be generalised to other markets because of the market and financial structural variations.

Details

Kybernetes, vol. 53 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 30 October 2023

Guido Migliaccio and Andrea De Palma

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real…

1243

Abstract

Purpose

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

Design/methodology/approach

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

Findings

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

Research limitations/implications

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Practical implications

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

Social implications

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

Originality/value

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 11
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 29 January 2024

Galen Trail

The purpose of this commentary is to discuss a framework (the Revised Model of Sport Consumer Behavior – R-MSCB; Trail, 2019) to accomplish the following objectives. (1) Provide a…

Abstract

Purpose

The purpose of this commentary is to discuss a framework (the Revised Model of Sport Consumer Behavior – R-MSCB; Trail, 2019) to accomplish the following objectives. (1) Provide a framework for sport marketers and sport organizations to use in their own market research. (2) Designate the processes needed to generate results and knowledge that sport organizations, sport marketers and associated corporate partners can use to improve marketing campaigns. (3) Provide suggestions for analytic techniques and measurement constructs/instruments that will facilitate market research within the sport industry.

Design/methodology/approach

The author created a 140-item questionnaire for the pre-survey and a 50-item questionnaire for the post-survey. The pre-survey was given at the beginning of the season, and the post-survey was given at the end of the season. The research group has generated a sequence of 13 studies and has collected pre-survey responses from over 7,800 people across 4 continents, 8 sports and 13 teams (data collections), with more teams still planned and over 2,000 post-season survey responses with data collection continuing.

Findings

This project, with its 13 studies, will provide sport organizations with the theories/frameworks, knowledge and processes to do their own market research in a more effective and efficient manner and will show sport organizations how to understand the complexities of sport consumer behavior, the motivations behind it and how it varies extensively across individuals. The author will show sports organizations how to collect data from their consumers using valid and reliable measures and constructs that will allow them to segment their consumers, how to effectively market to those segments and how to establish long-lasting relationships that make a satisfied and loyal customer.

Originality/value

This paper provides the framework and guidelines so that sport marketers and researchers can identify specific variables, constructs and relationships that will further their own objectives when attempting to explain sport consumer behavior. Using their own market research, they can implement the results/output in association with the Communications Strategy Model to create more effective and efficient marketing and communications campaigns and consequently drive key performance indicators (KPIs) and improve revenue streams.

Details

International Journal of Sports Marketing and Sponsorship, vol. 25 no. 2
Type: Research Article
ISSN: 1464-6668

Keywords

Open Access
Article
Publication date: 19 April 2024

Daniel Werner Lima Souza de Almeida, Tabajara Pimenta Júnior, Luiz Eduardo Gaio and Fabiano Guasti Lima

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

Abstract

Purpose

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

Design/methodology/approach

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

Findings

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

Originality/value

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

Details

Journal of Economics, Finance and Administrative Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2077-1886

Keywords

Open Access
Article
Publication date: 27 February 2024

Helga Habis

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

Abstract

Purpose

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

Design/methodology/approach

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

Findings

We show that our extended model yields a Pareto efficient outcome.

Practical implications

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Social implications

Long-term modelling and sustainability can be modelled in our setting.

Originality/value

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

Details

Journal of Economic Studies, vol. 51 no. 9
Type: Research Article
ISSN: 0144-3585

Keywords

1 – 10 of 496