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Open Access
Article
Publication date: 19 September 2024

Srivatsa Maddodi and Srinivasa Rao Kunte

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes…

Abstract

Purpose

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Design/methodology/approach

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Findings

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

Originality/value

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

Details

Journal of Capital Markets Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-4774

Keywords

Article
Publication date: 11 April 2024

Everton Anger Cavalheiro, Kelmara Mendes Vieira and Pascal Silas Thue

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the…

Abstract

Purpose

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

Design/methodology/approach

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

Findings

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Practical implications

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

Originality/value

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

Details

Review of Behavioral Finance, vol. 16 no. 5
Type: Research Article
ISSN: 1940-5979

Keywords

Open Access
Article
Publication date: 12 July 2024

Stiven Agusta, Fuad Rakhman, Jogiyanto Hartono Mustakini and Singgih Wijayana

The study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for…

Abstract

Purpose

The study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.

Design/methodology/approach

The study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.

Findings

Incorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.

Research limitations/implications

The study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.

Practical implications

Governments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.

Originality/value

Studies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

Details

Asian Journal of Accounting Research, vol. 9 no. 4
Type: Research Article
ISSN: 2459-9700

Keywords

Article
Publication date: 26 December 2023

Ulf Holmberg

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market…

Abstract

Purpose

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders.

Design/methodology/approach

This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further.

Findings

The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy.

Research limitations/implications

One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics.

Practical implications

The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools.

Originality/value

Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision.

Details

Journal of Economic Studies, vol. 51 no. 7
Type: Research Article
ISSN: 0144-3585

Keywords

Open Access
Article
Publication date: 15 August 2024

Nükhet Taylor and Sean T. Hingston

Fueled by the soaring popularity of the digital medium, consumers are increasingly relying on dynamic images to inform their decisions. However, little is known about how changes…

Abstract

Purpose

Fueled by the soaring popularity of the digital medium, consumers are increasingly relying on dynamic images to inform their decisions. However, little is known about how changes in the presentation of movement impacts these decisions. The purpose of this paper is to document whether and how movement speed–a fundamental characteristic of dynamic images in the digital medium–influences consumers' risk judgments and subsequent decisions.

Design/methodology/approach

Three experimental studies investigate the impact of movement speed displayed in the digital medium, focusing on different risk-laden domains including health (pilot study), gambling (Study 1) and stock market decisions (Study 2).

Findings

The authors find that faster movement speed displayed in the digital medium elevates consumers’ feelings of risk and elicits cautionary actions in response. The authors reveal a mechanism for this effect, showing that faster movement reduces feelings of control over outcomes, which predicts greater feelings of risk.

Research limitations/implications

Future work could expand upon these findings by systematically examining whether certain individuals are more susceptible to movement speed effects in the digital medium. Research could also investigate whether different ways of experiencing movement speed (e.g. physical movement) similarly influence risk judgments and whether movement speed can have positive connotations outside of risky domains.

Practical implications

The authors offer important insights to marketing practitioners and public policymakers seeking to guide consumers’ judgments and decisions in risk-laden contexts through the digital medium.

Originality/value

By showing how movement speed alters judgments in risk-laden contexts, the authors contribute to literature on risk perception and the growing body of literature examining how moving images shape consumers’ behaviors.

Details

European Journal of Marketing, vol. 58 no. 13
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 17 September 2024

Emmanuel Joel Aikins Abakah, Nader Trabelsi, Aviral Kumar Tiwari and Samia Nasreen

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and…

Abstract

Purpose

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

Design/methodology/approach

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Findings

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

Practical implications

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

Originality/value

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

Details

The Journal of Risk Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1526-5943

Keywords

Article
Publication date: 30 August 2024

Silky Vigg Kushwah, Payal Goel and Mohd Asif Shah

The current study immerses itself in the realm of diversification prospects within a select group of preeminent global stock exchanges. Specifically, the study casts its…

Abstract

Purpose

The current study immerses itself in the realm of diversification prospects within a select group of preeminent global stock exchanges. Specifically, the study casts its discerning gaze upon the financial hubs of the United States, Hong Kong, Germany, France, Amsterdam and India. In this expansive vista of international financial markets, the present analytical study aims to unravel the multifaceted opportunities that lie therein for astute portfolio management and strategic investment decisions.

Design/methodology/approach

The study encompasses daily time series data spanning from 2019 to 2022. To assess the interconnectedness among these stock indices, advanced statistical techniques, including Johansen cointegration methods and vector autoregressive (VAR) models, have been applied.

Findings

The research outcomes reveal both unidirectional and bidirectional relationships between the Indian, Hong Kong and US stock exchanges, encompassing both short-term and long-term time frames. Interestingly, the empirical findings indicate the presence of diversification opportunities between the Indian stock exchange and the stock exchanges of Germany, France and Amsterdam.

Research limitations/implications

These insights hold significant value for both Indian and international investors, including foreign institutional investors (FIIs), domestic institutional investors (DIIs) and retail investors, as they can utilize this knowledge to construct more effective and diversified investment portfolios by understanding the intricate interconnections between these prominent global stock exchanges.

Originality/value

This research undertaking aspires to bring coherence to a landscape rife with divergent interpretations and methodological divergences. We are poised to offer a comprehensive analysis, a beacon of clarity amidst the murkiness, to shed light on the intricate web of interconnections that underpin the world's stock exchanges. In so doing, we seek to contribute a seminal piece of scholarship that transcends the existing ambiguities and thus empowers the field with a deeper understanding of the multifaceted dynamics governing international stock markets.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2054-6238

Keywords

Open Access
Article
Publication date: 4 July 2024

Shinta Amalina Hazrati Havidz, Maria Divina Santoso, Theodore Alexander and Caroline Caroline

This study aims to identify the financial attributes of non-fungible tokens (NFTs) as safe havens, hedges or diversifiers against traditional (stock indices, foreign exchange…

Abstract

Purpose

This study aims to identify the financial attributes of non-fungible tokens (NFTs) as safe havens, hedges or diversifiers against traditional (stock indices, foreign exchange, gold and government bonds) and digital (Bitcoin and Ethereum) assets.

Design/methodology/approach

The quantile via moments was utilized, and the data spanned from 20 September 2021 to 31 January 2022. The authors incorporated feasible generalized least squares (FGLS) and difference-generalized method of moments (diff-GMM) as the robustness check.

Findings

Overall, NFTs offer strongly safe havens, hedging and diversifier attributes against cryptocurrencies, while weak properties for traditional assets. The specific findings are: (1) Bored Ape Yacht Club (BAYC) serves as a strong hedge for Bitcoin during market rise; (2) Mutant Ape Yacht Club (MAYC) serves as a strong safe haven against Bitcoin during market bull; (3) Crypto punk (CP) provides strong safe havens properties for gold during market turmoil while serving as a strong hedge against gold and Bitcoin on average and (4) the three blue-chip NFTs are powered by Ethereum blockchain, thus serving as a diversifier against Ethereum.

Practical implications

Bitcoin investors are suggested to include NFTs in their investment portfolio to mitigate the losses when Bitcoin falls. Meanwhile, the inclusion of crypto punk is advised for risk-averse investors who invest in gold. NFTs are powered by the Ethereum blockchain, indicating co-movement among them and thus, serve as diversifiers. Policymakers and regulators are suggested to watch closely over NFTs' great development and restructure the existing policies and thus, stabilization of asset markets can be achieved.

Originality/value

The originality aspects are: (1) focusing on the three blue-chip NFTs (i.e. BAYC, MAYC and CP) that are categorized as the largest NFTs by floor market capitalization; (2) testing the NFT attributes (safe havens, hedges or diversifiers) against traditional and digital assets, a.k.a., cryptocurrencies and (3) panel setting on 14 countries with the highest NFT users.

Details

Asian Journal of Accounting Research, vol. 9 no. 4
Type: Research Article
ISSN: 2459-9700

Keywords

Open Access
Article
Publication date: 6 June 2024

André L. Cavalcanti, João J. M. Ferreira, Pedro Mota Veiga, Marina Dabic and Natanya Meyer

This study aims to analyze the entrepreneurial intention (EI) manifested by potential entrepreneurs for LGBT (lesbian, gay, bisexual, and transgender) and traditional markets…

Abstract

Purpose

This study aims to analyze the entrepreneurial intention (EI) manifested by potential entrepreneurs for LGBT (lesbian, gay, bisexual, and transgender) and traditional markets, thereby tracing a comparative EI for both markets. The intention is to understand the vision of potential future entrepreneurs related to markets focused on the LGBT public (i.e. if entrepreneurs perceive this market as an option for future business).

Design/methodology/approach

Using a quantitative research design, data were collected from a sample of 157 students in Brazil and analyzed by applying structural equation modeling.

Findings

This study primarily identified a difference between EI when comparing the focus on LGBT and traditional markets. Results show that the impact of personal attitude is significantly higher on EI for general markets (all markets) than for markets focused on LGBT audiences. Furthermore, the impact on entrepreneurship for traditional markets is generally significantly lower than for the LGBT market.

Originality/value

The study explored the EI for LGBT markets, which has not been studied extensively. It aims to gain a better understanding of various aspects that may influence the decision-making and perceptions of potential future entrepreneurs. Furthermore, the study compares traditional and LGBT audiences, providing valuable insights for potential future entrepreneurs in both scenarios. This comparison is a unique contribution to the literature and contributes to important analyses and debates.

Details

International Journal of Entrepreneurial Behavior & Research, vol. 30 no. 11
Type: Research Article
ISSN: 1355-2554

Keywords

Article
Publication date: 17 September 2024

Arjun Hans, Farah S. Choudhary and Tapas Sudan

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these…

Abstract

Purpose

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

Design/methodology/approach

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

Findings

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

Research limitations/implications

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Originality/value

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

Details

International Journal of Accounting & Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1834-7649

Keywords

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