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Article
Publication date: 7 December 2021

Dorra Messaoud, Anis Ben Amar and Younes Boujelbene

Behavioral finance and market microstructure studies suggest that the investor sentiment and liquidity are related. This paper aims to examine the aggregate sentiment–liquidity…

Abstract

Purpose

Behavioral finance and market microstructure studies suggest that the investor sentiment and liquidity are related. This paper aims to examine the aggregate sentiment–liquidity relationship in emerging markets (EMs) for both the sample period and crisis period. Then, it verifies this relationship, using the asymmetric sentiment.

Design/methodology/approach

This study uses a sample consisting of stocks listed on the SSE Shanghai composite index (348 stocks), the JKSE (118 stocks), the IPC (14 stocks), the RTS (12 stocks), the WSE (106 stocks) and FTSE/JSE Africa (76 stocks). This is for the period ranging from February, 2002 until March, 2021 (230 monthly observations). We use the panel data and apply generalized method-of-moments (GMM) of dynamic panel estimators.

Findings

The empirical analysis shows the following results: first, it demonstrates a significant relationship between the aggregate investor sentiment and the stock market liquidity for the sample period and crisis one. Second, referring to the asymmetric sentiment, we have empirically given proof that the market is significantly more liquid in times of the optimistic sentiment than it is in times of the pessimistic sentiment. Third, using panel causality tests, we document a unidirectional causality between the investor sentiment and liquidity in a direct manner through the noise traders and the irrational market makers and also a bidirectional causality in an indirect channel.

Practical implications

The results reported in this paper have implications for regulators and investors in EMs. Firstly, the study informs the regulators that the increases and decreases in the stock market liquidity are related to the investor sentiment, not financial shocks. We empirically evince that the traded value is higher in the crisis. Secondly, we inform insider traders and rational market makers that the persistence of increases in the trading activity in both quiet and turbulent times is associated with investor participants such as noise traders and irrational market makers.

Originality/value

The originality of this work lies in employing the asymmetric sentiment (optimistic/pessimistic) in order to denote the sentiment–liquidity relationship in EMs for the sample period and the 2007–2008 subprime crisis.

Details

Journal of Economic and Administrative Sciences, vol. 39 no. 4
Type: Research Article
ISSN: 1026-4116

Keywords

Article
Publication date: 11 October 2023

Omid Sabbaghi

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Abstract

Purpose

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Design/methodology/approach

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

Findings

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

Originality/value

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

Details

Journal of Financial Reporting and Accounting, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-2517

Keywords

Article
Publication date: 9 February 2024

Alexandre Esteves and Pedro Piccoli

The purpose of this study is to investigate the influence of firm-specific investor sentiment on Brazilian companies’ accrual-based earnings management between 2010 and 2018. The…

Abstract

Purpose

The purpose of this study is to investigate the influence of firm-specific investor sentiment on Brazilian companies’ accrual-based earnings management between 2010 and 2018. The paper aims to bring deeper insight into the relationship between the investor expectations and managers’ decision-making in an emerging market.

Design/methodology/approach

The authors use the quantitative approach and apply a multiple linear regression model to test the relationship among the abnormal accruals, the firm-specific investor sentiment index and the control variables. The final sample includes data from 175 companies, between 2010 and 2018.

Findings

These results reveal a negative association between firm-specific investor sentiment and accrual-based earnings management, which could mean that the risk propensity of managers to manipulate earnings increases when they face known losses in the capital market.

Research limitations/implications

The research findings provide a valuable understanding of how emerging capital market expectations can influence managerial decisions, such as accrual-based earnings management. The geographical area of study was limited to only Brazil.

Originality/value

Previous studies on developed markets show that market-wide investor sentiment positively influences accrual-based earnings management. However, the present study shows that the firm-specific investor sentiment index has a significant and negative relationship with Brazilian companies’ earnings manipulation, whereas market sentiment indicates contradictory relationship in previous studies in the country.

Propósito

El propósito de este estudio es investigar la influencia del sentimiento de los inversionistas a nivel de empresa en la manipulación contable de las empresas brasileñas entre 2010 y 2018. El documento pretende aportar una visión más profunda sobre la relación entre las expectativas de los inversores y la toma de decisiones de los gestores en un mercado emergente.

Diseño/metodologia/enfoque

usamos el enfoque cuantitativo y aplicamos un modelo de regresión lineal múltiple para probar la relación entre las acumulaciones anormales, el índice de sentimiento de los inversores a nivel de empresa y las variables de control. La muestra final incluye datos de 175 empresas, entre 2010 y 2018.

Hallazgos

Los resultados revelan una asociación negativa entre el sentimiento de los inversores a nivel de empresa y la manipulación contable basada em acumulaciones, lo que podría significar que la propensión al riesgo de los administradores a manipular las ganancias aumenta cuando enfrentan pérdidas conocidas en el mercado de capitales.

Limitaciones/implicaciones de la investigación

los resultados de la investigación proporcionan una valiosa comprensión de cómo las expectativas de los mercados de capitales emergentes pueden influir en las decisiones de gestión, como la manipulación contable basada en acumulaciones. El área geográfica de estudio se limitó únicamente a Brasil y, en consecuencia, los hallazgos y conclusiones del estudio tuvieron sus límites.

Originalidad/valor

estudios anteriores sobre mercados desarrollados muestran que el sentimiento de los inversores a nivel de mercado influye positivamente en la manipulación contable. Sin embargo, el presente estudio muestra que el índice de sentimiento de los inversores a nivel de empresa tiene una relación significativa y negativa con la manipulación de las ganancias de las empresas brasileñas, mientras que el sentimiento del mercado indica una relación contradictoria en estudios anteriores en el país.

Details

Academia Revista Latinoamericana de Administración, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1012-8255

Keywords

Article
Publication date: 28 June 2022

Maqsood Ahmad

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management…

2044

Abstract

Purpose

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

Design/methodology/approach

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

Findings

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

Practical implications

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an 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 their financial management strategies.

Originality/value

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

Details

International Journal of Emerging Markets, vol. 19 no. 2
Type: Research Article
ISSN: 1746-8809

Keywords

Open Access
Article
Publication date: 28 September 2023

Amit Rohilla, Neeta Tripathi and Varun Bhandari

In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to…

Abstract

Purpose

In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.

Design/methodology/approach

The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.

Findings

The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.

Research limitations/implications

The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.

Originality/value

The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.

Article
Publication date: 14 November 2023

Barkha Dhingra, Shallu Batra, Vaibhav Aggarwal, Mahender Yadav and Pankaj Kumar

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a…

Abstract

Purpose

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

Design/methodology/approach

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

Findings

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

Originality/value

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

Details

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

Keywords

Book part
Publication date: 9 November 2023

Firda Nosita and Rifqi Amrulloh

The authors believe the COVID-19 pandemic has an impact on supply and demand. The potential decline in real sector performance leads to lower expectations of securities…

Abstract

The authors believe the COVID-19 pandemic has an impact on supply and demand. The potential decline in real sector performance leads to lower expectations of securities performance. The uncertainty of future performance can change investor behaviour. This study tried to gain insight into stock investor behaviour during the COVID-19 pandemic. The results showed that the majority of the investor realized and believed the pandemic would affect the stock market performance. Hence, they did not show herding behaviour and were very confident during the COVID-19 pandemic. The survey also indicates that investors tend to avoid risk rather than take the opportunity to buy at a lower price. Moreover, investors believe that the COVID-19 vaccine will soon be found, and the economy will return to normal. Government and self-regulated organizations (SRO) are responsible for making effective policies to convince the investors about the future prospect.

Details

Macroeconomic Risk and Growth in the Southeast Asian Countries: Insight from SEA
Type: Book
ISBN: 978-1-83797-285-2

Keywords

Article
Publication date: 7 November 2023

Te-Kuan Lee and Askar Koshoev

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is…

Abstract

Purpose

The primary objective of this research is to provide evidence that there are two distinct layers of investor sentiments that can affect asset valuation models. The first is general market-wide sentiments, while the second is biased approaches toward specific assets.

Design/methodology/approach

To achieve the goal, the authors conducted a multi-step analysis of stock returns and constructed complex sentiment indices that reflect the optimism or pessimism of stock market participants. The authors used panel regression with fixed effects and a sample of the US stock market to improve the explanatory power of the three-factor models.

Findings

The analysis showed that both market-level and stock-level sentiments have significant contributions, although they are not equal. The impact of stock-level sentiments is more profound than market-level sentiments, suggesting that neglecting the stock-level sentiment proxies in asset valuation models may lead to severe deficiencies.

Originality/value

In contrast to previous studies, the authors propose that investor sentiments should be measured using a multi-level factor approach rather than a single-factor approach. The authors identified two distinct levels of investor sentiment: general market-wide sentiments and individual stock-specific sentiments.

Details

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

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. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 2 November 2022

Clio Ciaschini and Maria Cristina Recchioni

This work aims at designing an indicator for detecting and forecasting price volatility and speculative bubbles in three markets dealing with agricultural and soft commodities…

Abstract

Purpose

This work aims at designing an indicator for detecting and forecasting price volatility and speculative bubbles in three markets dealing with agricultural and soft commodities, i.e. Intercontinental Exchange Futures market Europe, (IFEU), Intercontinental Exchange Futures market United States (IFUS) and Chicago Board of Trade (CBOT). This indicator, designed as a demand/supply odds ratio, intends to overcome the subjectivity limits embedded in sentiment indexes as the Bull and Bears ratio by the Bank of America Merrill Lynch.

Design/methodology/approach

Data evidence allows for the parameter estimation of a Jacobi diffusion process that models the demand share and leads the forecast of speculative bubbles and realised volatility. Validation of outcomes is obtained through the dynamic regression with autoregressive integrated moving average (ARIMA) error. Results are discussed in comparison with those from the traditional generalized autoregressive conditional heteroskedasticity (GARCH) models. The database is retrieved from Thomson Reuters DataStream (nearby futures daily frequency).

Findings

The empirical analysis shows that the indicator succeeds in capturing the trend of the observed volatility in the future at medium and long-time horizons. A comparison of simulations results with those obtained with the traditional GARCH models, usually adopted in forecasting the volatility trend, confirms that the indicator is able to replicate the trend also providing turning points, i.e. additional information completely neglected by the GARCH analysis.

Originality/value

The authors' commodity demand as discrete-time process is capable of replicating the observed trend in a continuous-time framework, as well as turning points. This process is suited for estimating behavioural parameters of the agents, i.e. long-term mean, speed of mean reversion and herding behaviour. These parameters are used in the forecast of speculative bubbles and realised volatility.

Details

Review of Behavioral Finance, vol. 16 no. 1
Type: Research Article
ISSN: 1940-5979

Keywords

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