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Article
Publication date: 15 August 2024

Srivatsa Maddodi and Srinivasa Rao Kunte

This study explores the complex impact of COVID-19 on India's financial sector, moving beyond simplistic public health vs. economy views. We assess market vulnerabilities and…

Abstract

Purpose

This study explores the complex impact of COVID-19 on India's financial sector, moving beyond simplistic public health vs. economy views. We assess market vulnerabilities and analyze how public sentiment, measured through Google Trends, can predict stock market fluctuations. We propose a novel framework using Google Trends for financial sentiment analysis, aiming to improve understanding and preparedness for future crises.

Design/methodology/approach

Hybrid approach leverages Google Trends as sentiment tool, market data, and momentum indicators like Rate of Change, Average Directional Index and Stochastic Oscillator, to deliver accurate, market insights for informed investment decisions during pandemic.

Findings

Our study reveals that the pandemic significantly impacted the Indian financial sector, highlighting its vulnerabilities. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.95% maximum accuracy in forecasting stock market values during such events.

Originality/value

To the best of authors knowledge this model's originality lies in its focus on short-term impact, novel data fusion and methodology, and high accuracy.• Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of COVID-19 on market behavior.• Novel data fusion and framework: A novel framework of sentiment analysis was introduced in the form of Trend Popularity Index. Combining trend popularity index with momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods.• High predictive accuracy: Achieving the prediction accuracy (98.93%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

Details

Managerial Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 27 June 2024

Suhaib Al-Khazaleh, Dr Nemer Badwan, Ibrahim Eriqat and Zahra El Shlmani

The purpose of this study is to evaluate the linkage between stock markets in Middle Eastern countries before and during the COVID-19 pandemic by using daily and monthly data sets…

Abstract

Purpose

The purpose of this study is to evaluate the linkage between stock markets in Middle Eastern countries before and during the COVID-19 pandemic by using daily and monthly data sets for the period from 2011 to 2021.

Design/methodology/approach

The multivariate BEKK-GARCH model was computed to evaluate the existence of non-linear linkage among Middle Eastern stock markets. A correlation approach was used in this study to determine the type of linear connectivity between Middle Eastern stock markets. The study used monthly and daily data sets covering the years 2011 to 2021 to investigate the linkage between stock returns and the volatility spillover between the stock markets in Palestine, Jordan, Syria and Lebanon, both before and during COVID-19. To understand the types of relationships between markets before and during COVID-19, the daily data set was split into two periods.

Findings

Results from the pre-COVID-19 suggest that the Syria stock market is not related to any stock market in the Middle East markets; the Palestine and Lebanon stock markets exhibit a weak relationship, but Jordan and Palestine stock markets are strongly linked. Conversely, results from COVID-19 evince a very strong bidirectional volatility spillover between Middle East stock markets. Overall, the results indicate the existence of increased linkage during the COVID-19.

Research limitations/implications

The data collection on a daily and monthly basis, both before and during COVID-19, presents certain limitations for the paper. Another limitation is that the data cannot be generalized to all other Middle Eastern countries; rather, the conclusions drawn can only be applied to these four countries. This is especially true if the scholars collected most of the necessary data but were unable to obtain certain data for various reasons.

Practical implications

These findings have implications for risk management, market regulation and the growth of local stock markets. Facilitating the growth of smaller, more specialized markets to improve integration with other Middle Eastern markets is one of the goals of the domestic stock market development policy. To ensure financial stability, Middle Eastern stock market linking policies should consider spillover risk and take steps to minimize it. Enhancing the range of investment opportunities accessible to shareholders and functioning as confidential risk-sharing mechanisms to facilitate improved risk management in Middle Eastern stock markets will not only significantly influence the mobilization of private capital to promote investment and local economic growth but also lay groundwork for integrated market platforms.

Originality/value

This paper adds to the body of literature by demonstrating the nature of the connections between these small markets and the larger markets in the Middle East region. Information from the smaller markets provides institutional insights that enhance the body of existing research, guide the formulation of evidence-based policies and advance financial literacy in these markets. This study contributes by comparing data from different stock markets to better understand the type and strength of the link and relationship between Middle Eastern stock markets, as well as any underlying or reinforcing factors that might have contributed to the relationship and the specific types of links that these markets shared prior and during COVID-19.

Details

Journal of Chinese Economic and Foreign Trade Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-4408

Keywords

Article
Publication date: 16 July 2024

Sirine Ben Yaala and Jamel Eddine Henchiri

This study aims to predict stock market crises in the Middle East North Africa (MENA) regions by leveraging the nonlinear autoregressive neural network with exogenous inputs…

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Abstract

Purpose

This study aims to predict stock market crises in the Middle East North Africa (MENA) regions by leveraging the nonlinear autoregressive neural network with exogenous inputs (NARX) model with two measures of investor sentiment: the ARMS indicator and Google Trends' search volume of positive and negative words.

Design/methodology/approach

Employing a novel approach, this study utilizes the NARX model with ten neurons in the hidden layer and the Levenberg–Marquardt training algorithm. It evaluates model performance through learning, validation and test errors, as well as correlation analysis between predicted and actual crises.

Findings

The NARX model, incorporating investor sentiment, has proven to be a reliable tool for forecasting crises, helping market participants understand data complexity and avoid crisis consequences. The divergence in how investors interpret market news, with some focusing solely on negative developments and others valuing positive outcomes, highlights the predictive nature of the optimistic and pessimistic sentiments captured by the model.

Research limitations/implications

This study advocates for integrating behavioral approaches into stock market crisis prediction, highlighting the significance of investor sentiment and deep learning. It advances crisis mechanism understanding and opens avenues in behavioral finance. Integration of these findings into finance and economics education could enhance students' risk understanding and mitigation strategies.

Practical implications

The adoption of NARX models, incorporating investor sentiment, empowers market participants to proactively manage crises, adjust strategies, enhance asset protection and make informed decisions. These models enable them to minimize losses, maximize returns and diversify portfolios effectively in response to market fluctuations. These insights also guide policymakers such as governments, regulatory institutions and financial organizations in formulating crisis prevention and mitigation policies, bolstering economic and financial stability.

Social implications

This research reduces economic uncertainty, safeguards individuals' savings and investments and promotes a stable financial climate.

Originality/value

This study is one of the first attempts to demonstrate the detection and prediction of stock market crises, specifically in the MENA stock market, using the NARX model. It offers a robust forecasting model using machine learning and investor sentiment, providing decision-making support for investment strategies and policy development aimed at enhancing financial and economic stability.

Details

Journal of Financial Regulation and Compliance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1358-1988

Keywords

Article
Publication date: 2 July 2024

Sylva Alif Rusmita, Dian Filianti, Ega Nuriayu Mayasani and Khairunnisa Abd Samad

This study aims to determine the role of gold as a safe haven, hedge and asset diversification for Shariah stock in conditions of extreme stock market declines.

Abstract

Purpose

This study aims to determine the role of gold as a safe haven, hedge and asset diversification for Shariah stock in conditions of extreme stock market declines.

Design/methodology/approach

Quantitative approach is used by applying the threshold generalized autoregressive conditional heteroskedasticity (TGARCH) model to capture bad or good news in the market condition and quantile regression method to obtain the extreme values of stock returns in several market conditions. The data used were the daily closing price of gold and the Jakarta Islamic Index from January 2011 to October 2022.

Findings

The average conditions show gold does not have a hedge property and only acts as an asset diversification. Second, gold has a substantial, safe haven property in every economic condition. However, the safe-haven property of gold seemed to weaken during the most extreme stock market decline. Thus, although gold appears as a safe haven and asset diversification, it remains a risky investment and only provides a minor role in the face of the extreme stock market period.

Practical implications

This research provides a discourse and literature for Islamic investors and investor managers to choose the right investment instrument in various economic conditions where gold has a function as diversification and safe haven in their asset portfolio under any other asset portfolio conditions which is also in line with modern portfolio theory. For policymakers, the study can be used as material for consideration in making policies related to the accessibility of gold as an investment instrument.

Originality/value

This study presents the originality by using the price of Antam gold as a proxy for gold investment during the latest research year data and focusing on case studies in Islamic capital market in Indonesia. Moreover, this research provides quantile regression that sharply discussion in various economics condition.

Details

Journal of Islamic Accounting and Business Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1759-0817

Keywords

Article
Publication date: 23 May 2024

Muhammad Abubakr Naeem, Shabeer Khan and Mohd Ziaur Rehman

This study investigates the dynamic interdependence between Islamic and conventional stock markets in the Gulf Cooperation Council (GCC) economies and the influence of global…

Abstract

Purpose

This study investigates the dynamic interdependence between Islamic and conventional stock markets in the Gulf Cooperation Council (GCC) economies and the influence of global financial uncertainties on this interconnection.

Design/methodology/approach

The study employs the time-varying parameter vector autoregressions (TVP-VAR) technique and analyzes daily data from December 1, 2008 to July 14, 2021.

Findings

The research reveals robust interconnectedness within individual countries between Islamic and conventional stock markets, particularly during crises. Islamic stock markets exhibit greater susceptibility to spillover effects compared to conventional stocks. The UAE and Kingdom of Saudi Arabia (KSA) stock markets are identified as net transmitters of spillovers, while Oman, Bahrain and Kuwait receive more spillovers than they transmit. Global financial uncertainty measures (GVZ, USEPU and UKEPU) positively influence financial market interconnectedness, with EVZ exhibiting a negative impact while VIX and OVX remain statistically insignificant.

Practical implications

Investors and portfolio managers in Oman, Bahrain and Kuwait should carefully evaluate the UAE and KSA markets before making investment decisions due to the latter's role as net transmitters in the region. Additionally, it is emphasized that Islamic and conventional stocks should not be considered interchangeable asset classes for risk hedging.

Social implications

Investors must be aware that Islamic and conventional stocks cannot be used as an alternative asset class to hedge risk.

Originality/value

The present article offers valuable insights for practitioners and researchers delving into the comparative analysis of Islamic and conventional stock markets within the GCC context. It enhances our comprehension of the dynamic interdependence between Islamic and conventional stock markets in the GCC economies and the impact of global financial uncertainties on this intricate relationship.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 7 March 2024

Manpreet Kaur, Amit Kumar and Anil Kumar Mittal

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered…

Abstract

Purpose

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

Design/methodology/approach

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

Findings

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

Originality/value

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 19 February 2024

Tchai Tavor

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Abstract

Purpose

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Design/methodology/approach

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Findings

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

Originality/value

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 26 February 2024

Zaifeng Wang, Tiancai Xing and Xiao Wang

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty…

Abstract

Purpose

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

Design/methodology/approach

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Findings

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Research limitations/implications

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Practical implications

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

Social implications

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

Originality/value

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 2 January 2024

Nazreen Tabassum Chowdhury, Nurul Shahnaz Mahdzan and Mahfuzur Rahman

This study aims to explore the underlying issues of behavioural biases in relation to stock market participation and the challenges of individual investors in Bangladesh. The…

Abstract

Purpose

This study aims to explore the underlying issues of behavioural biases in relation to stock market participation and the challenges of individual investors in Bangladesh. The study identifies behavioural biases affecting individuals’ stock market participation, their circumvention strategies and the importance of financial knowledge in encouraging the participation of individuals in the stock market.

Design/methodology/approach

Semi-structured interviews were used in this study to gather information from industry researchers, individual investors, brokers and institutional advisors. Twenty-two experts were contacted, and 13 agreed to participate in the interviews. The study then uses the thematic analysis method to report its findings.

Findings

This research shows that investors’ behavioural biases (such as loss aversion, herding, trust, gambler’s fallacy and risk tolerance) are among Bangladesh’s primary drivers of stock market participation. Circumvention strategies (such as poor corporate governance and agency costs) also play a part in individuals’ participation. These influences are in addition to the obvious factors of investment risks, poor infrastructure, poor regulation enforcement and the need for more sufficient investment products.

Research limitations/implications

This study conducted 13 interviews with expert subjects, which is a small sample size. However, the findings achieved saturation and cannot be ignored. Future research should use quantitative or experimental methods with a large sample size to validate the current findings.

Originality/value

This study is pioneering in the Bangladesh stock market, exploring the behavioural biases of investors’ participation in the market. This paper provides valuable insights into investor participation by discovering the underlying behavioural biases that have been continually ignored; these insights may also be relevant in frontier markets in Asian countries.

Details

Qualitative Research in Financial Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1755-4179

Keywords

Article
Publication date: 8 January 2024

Deevarshan Naidoo, Peter Brian Denton Moores-Pitt and Joseph Olorunfemi Akande

Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant…

Abstract

Purpose

Understanding which market to invest in for a well-diversified portfolio is fundamental in economies that are highly vulnerable to fluctuations in exchange rates. Extant literature that has considered phenomenon hardly juxtapose the markets. The purpose of this study is to examine the effects of exchange rate volatility on the Stock and Real Estate market of South Africa. The essence is to determine whether the fluctuations in the exchange rate influence the markets prices differently.

Design/methodology/approach

The Generalised Autoregressive Conditional Heteroskedasticity [GARCH (1.1)] model was used in establishing the effect of exchange rate volatility on both markets. This study used monthly South African data between 2000 and 2020.

Findings

The results of this study showed that increased exchange rate volatility increases stock market volatility but decreases real-estate market volatility, both of which revealed weak influences from the exchange rates volatility.

Practical implications

This study has implication for policy in using the exchange rate as a policy tool to attract foreign portfolio investment. The weak volatility transmission from the exchange rate market to the stock and real estate market indicates that there is prospect for foreign investors to diversify their investments in these two markets.

Originality/value

This study investigated which of the assets market, stock or housing market do better in volatile exchange rate conditions in South Africa.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

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