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1 – 10 of 999Suvra Roy, Ben R. Marshall, Hung T. Nguyen and Nuttawat Visaltanachoti
The purpose of this study is to investigate (1) how managers respond to stock price crashes, (2) why they respond and (3) how their responses affect shareholders.
Abstract
Purpose
The purpose of this study is to investigate (1) how managers respond to stock price crashes, (2) why they respond and (3) how their responses affect shareholders.
Design/methodology/approach
This study employs a panel regression with various firm-level controls and firm- and year-fixed effects. The sample is comprised of 101,532 firm-year observations with 11,727 unique firms from 1950 to 2019. Using mutual fund flow redemption pressure as an exogenous variable to stock price crashes, the paper provides further evidence of the causality of documented findings.
Findings
Management becomes more focused on improving transparency, raising investment efficiency, reducing agency conflicts and regaining the trust of shareholders by investing in social capital and employee welfare. These actions increase firm value. This study also suggests that management undertakes these actions out of concern for their tenure of employment.
Originality/value
The catalysts of stock price crashes are well documented, but much less is known about what happens following stock price crashes. This study provides more insights into the understanding of corporate crisis management practices following adverse events.
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Ahmed S. Baig, Muhammad Imran Chaudhry and R. Jared DeLisle
In this paper, the authors study the phenomenon of price clustering in the Pakistan Stock Exchange (PSX), a market viewed as one of the best-performing stock markets in the world…
Abstract
Purpose
In this paper, the authors study the phenomenon of price clustering in the Pakistan Stock Exchange (PSX), a market viewed as one of the best-performing stock markets in the world during 2014–2017. The authors study the effect of stock-level variables on price clustering and analyze the determinants of the cross-sectional patterns of price clustering in the PSX, in particular the causal link between price clustering and political instability.
Design/methodology/approach
The authors' dataset comprises daily observations on 100 PSX stocks spanning from January 1, 2009 to June 30, 2019. The authors use multivariate regression and spectral analysis to shed light on the dynamics of stock price clustering in PSX.
Findings
The authors document abnormally high levels of stock price clustering, particularly on integer increments, in PSX. The nature of stock price clustering in PSX is consistent with the negotiation hypothesis of Harris (1991). The levels of stock price clustering on PSX are persistent and contain a cyclical component. Furthermore, the authors find that political uncertainty in Pakistan is a significant contributor to the high levels of price clustering on PSX. The authors' conclusions are robust to alternative econometric specifications and different measures of price clustering and political uncertainty.
Practical implications
The authors' findings are of interest to investors and policymakers. Since price clustering decreases market quality and degrades the information content of stock prices, the authors' study shows that price efficiency in PSX has not improved despite major reforms over the last decade. One practical implication of the authors' results is that investors should be cautious while rebalancing portfolios around political events such as general elections because stock price clustering increases in the PSX during these periods. As a result, stock prices are likely to deviate from their intrinsic values.
Originality/value
Research on price clustering is limited to developed markets, and emerging/frontier markets have been largely overlooked. The phenomenon of price clustering in the PSX has yet to be studied, despite the relevance of the PSX for emerging/frontier market investors.
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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.
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Thai-Ha Le, Long Hai Vo and Farhad Taghizadeh-Hesary
This study examines the co-integration relationships between Association of Southeast Nations (ASEAN) stock indices as a way to assess the feasibility of policy initiatives to…
Abstract
Purpose
This study examines the co-integration relationships between Association of Southeast Nations (ASEAN) stock indices as a way to assess the feasibility of policy initiatives to strengthen market integration in ASEAN and identify implications for portfolio investors.
Design/methodology/approach
The authors employ threshold co-integration tests and a non-linear autoregressive distributed lag (NARDL) model to study the asymmetric dynamics of ASEAN equity markets. The study’s data cover the 2009–2022 period for seven member states: Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam.
Findings
The authors find evidence supporting co-integration relationships; adjustment toward equilibrium is asymmetric in the short run and symmetric in the long run for these countries. While co-movement in ASEAN equity markets seems encouraging for initiatives seeking to foster financial integration in regional economies, the benefits for international portfolio diversification appear to be neutralized.
Originality/value
The issue of stock market integration is important among policymakers, investors and academics. This study examines the level of stock market integration in ASEAN during the 2009–2022 period. For this purpose, advanced co-integration techniques are applied to different frequencies of data (daily, weekly and monthly) for comparison and completeness. The empirical analysis of this study is conducted using the Enders and Siklos (2001) co-integration and threshold adjustment procedure. This advanced co-integration technique is superior compared to other co-integration techniques by permitting asymmetry in the adjustment toward equilibrium.
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Patrik Jonsson, Johan Öhlin, Hafez Shurrab, Johan Bystedt, Azam Sheikh Muhammad and Vilhelm Verendel
This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?
Abstract
Purpose
This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?
Design/methodology/approach
A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.
Findings
The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.
Practical implications
The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.
Originality/value
The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?
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Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of…
Abstract
Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.
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Jason X. Wang, Tsan-Ming Choi, Lincoln C. Wood, Karin Olesen and Torsten Reiners
Sustainable supply chain management (SSCM), driven by the downstream buyers' power, transfers sustainability responsibilities to the upstream supplier. In contrast to the…
Abstract
Purpose
Sustainable supply chain management (SSCM), driven by the downstream buyers' power, transfers sustainability responsibilities to the upstream supplier. In contrast to the heavily-focused buyers' perspective in the literature, the authors investigate how this buyer-driven SSCM influences suppliers' performance, using the measure of stock market reaction.
Design/methodology/approach
Grounded by the resource dependence theory (RDT), the authors empirically analyze the power effect on suppliers. Event study methodology and regression analysis are used, based on a sample of 1977 paired supplier observations from 1990 to 2016.
Findings
The result suggests that although a negative stock market reaction for suppliers in SSCM exists, the effect is less negative at a high level of buyer and supplier dependence. For the investigation of the “consolidated SSCM initiative,” where buyers acquire exogenous power by collaboratively managing SSCM with their peers, the authors uncover that the negative impact of this consolidated SSCM initiative can be mitigated by the high interdependence that generates relational norms in the dyads.
Research limitations/implications
The authors focus on dyadic relationships. Future research can use the study's findings to study the SSCM diffusion to lower-tier suppliers.
Practical implications
This paper has good managerial implications for both suppliers and buyers. The authors propose dependence-based strategies for supplier managers to reduce uncertainty in SSCM. Moreover, buyer managers can use the study's findings to strengthen suppliers' commitment.
Originality/value
The novelty of examining the suppliers' perspective contributes to exploring the supply chain impact of SSCM. The authors extend RDT and show that high dependence is not necessarily detrimental to suppliers in this buyer-driven SSCM context. The interesting finding of interdependence in the context of the consolidated SSCM initiative brings new insights that relational norms constrain the leverage of power in the dyads and are beneficial to the power-disadvantageous suppliers.
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Sándor Erdős and Patrik László Várkonyi
The purpose of this study is to examine herd behaviour under different market conditions, examine the potential impact of the firm size and stock characteristics on this…
Abstract
Purpose
The purpose of this study is to examine herd behaviour under different market conditions, examine the potential impact of the firm size and stock characteristics on this relationship, and explore how herding affects market prices in the German market.
Design/methodology/approach
The authors apply a method that does not rely on theoretical models, thus eliminating the biases inherent in their application. This technique is based on the assumption that macro herding manifests itself in the synchronicity (comovement) of stock returns.
Findings
The study’s findings show that herding is more pronounced in down markets and is more pronounced when market returns reach extreme levels. Additionally, the authors have found that there is stronger herding among large companies compared to small companies, and that stock characteristics considered have no effect on the degree of macro herding. Results also suggest that the contemporaneous market-wide information drives macro herding and that macro herding facilitates the incorporation of market-wide information into prices.
Practical implications
The study’s results strongly support the idea of directional asymmetry, which holds that stocks react quickly to negative macroeconomic news while small stocks react slowly to positive macroeconomic news. Additionally, the study’s results suggest that the contemporaneous market-wide information drives macro herding and that macro herding facilitates the rapid incorporation of market-wide information into prices.
Originality/value
To the best of the researchers’ knowledge, this is the first study that examines macro herding for a major financial market using a herding measure based on the co-movement of returns that does not rely on theoretical models.
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Felix Reschke and Jan-Oliver Strych
The authors explore how the sentiment expressed by emojis in comments on stocks is associated with the stocks' subsequent returns.
Abstract
Purpose
The authors explore how the sentiment expressed by emojis in comments on stocks is associated with the stocks' subsequent returns.
Design/methodology/approach
By applying our own analyzer, the authors find a sentiment effect of emojis on stocks returns separately to the plain text-expressed sentiment in Reddit posts about meme stocks such as Gamestop during the Covid-19 pandemic.
Findings
The authors document that a one-standard deviation change in emoji sentiment magnitude measured as the quantity of positive emoji sentiment posts over the previous hour is associated with an 0.06% (annualized: 109.2%) one-hour abnormal stock return compared to a mean of 0.03% (annualized: 54.6%). If the stock exhibits a higher intra-hour volatility, a proxy for uninformed noise trading, this relation is more pronounced and even stronger compared to stock return's relation to plain text sentiment.
Research limitations/implications
The authors are not able to show causation that is open to future research. It also remains an open question how emojis impact market price efficiency.
Practical implications
Emojis are positively related to stock returns in addition to plain text-expressed content if they are discussed heavily by retail investors in Internet boards such as Reddit.
Social implications
Shared emotions expressed by emojis might have an influence on how disconnected individuals make homogeneous decisions. This argument might explain our found relation of emojis and stock returns.
Originality/value
So, the study findings provide empirical evidence that emojis in Reddit posts convey information on future short-term stocks returns distinct from information expressed in plain text, in the case of volatile stocks, with a higher magnitude.
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Yan He, Ruixiang Jiang, Yanchu Wang and Hongquan Zhu
We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that…
Abstract
We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that the past loser-and-illiquid stock portfolios tend to outperform the past winner-and-liquid stock portfolios in the 1–12 months holding period. The excess return is significantly associated with the market-wide liquidity factor even when we control the three Fama-French and momentum factors. Cross-sectionally, the liquidity beta significantly affects the excess return even with control of other risk betas and other traditional liquidity proxies.
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