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1 – 10 of 753Anjali Srivastava, Rima Assaf, Dharen Kumar Pandey and Rahul Kumar
Understanding and mitigating stock price crash risk is vital for investors and regulators to ensure financial market stability. This study aims to unveil significant research…
Abstract
Purpose
Understanding and mitigating stock price crash risk is vital for investors and regulators to ensure financial market stability. This study aims to unveil significant research trends and opportunities.
Design/methodology/approach
This study adopts the bibliometric and systematic review approach to analyse 485 Scopus-indexed articles through citation, keyword co-occurrence, bibliographic coupling, and publication analyses and delve into the depth of crash risk literature.
Findings
This bibliometric review reveals not only a surge in crash risk publications over the last decade but also delineates several emerging thematic threads within this domain. We identify seven distinct themes that have gained prominence in recent literature: bad news hoarding, board characteristics, capital market factors, corporate policies, ownership impact, corporate governance, and external environmental influences on crash risk. This thematic analysis provides a comprehensive overview of the evolving landscape of crash risk research and underscores the multifaceted nature of factors contributing to market instability.
Practical implications
This study makes a substantial contribution by furnishing a thorough examination of existing studies, pinpointing areas where knowledge is lacking, and shedding light on emerging trends and debates within the crash risk literature.
Originality/value
This study identifies current research trajectories and propels future exploration into agency perspectives, audit quality, and corporate disclosures within crash risk literature.
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Investigation of the anomalies associated with crashes and jackpots in the Chinese stock market.
Abstract
Purpose
Investigation of the anomalies associated with crashes and jackpots in the Chinese stock market.
Design/methodology/approach
We propose a logit model to predict the events of crashes and jackpots in the Chinese stock market. The model introduces a new variable of the price-to-sales ratio and takes into account the market states, Up and Down.
Findings
The anomalies associated with crashes and jackpots are not related to variations in economic conditions, but are associated with limits to arbitrage. High-liquidity stocks have strong mispricing effects. The institutions’ speculative trading will push liquid stock prices further away from their fundamentals but avoid buying illiquid stocks with a higher probability of price crashes and jackpots.
Originality/value
We propose a logit model to predict the extreme events of both crash and jackpot in the Chinese stock market. Our model effectively disentangles from CRASHP and JACKP. Compared with the traditional model, it substantially enhances in-sample and out-sample predictions. Based on the predictions of the extreme events, we find two strong and robust pricing effects associated with ex ante CRASHP and JACKP in the Chinese stock market.
Yunqi Fan, Guanglei Hu and Xiaoxue Chen
This study aims to examine whether mandatory audit partner rotation is associated with future stock price crash risk.
Abstract
Purpose
This study aims to examine whether mandatory audit partner rotation is associated with future stock price crash risk.
Design/methodology/approach
This study makes use of a regulatory change from the Ministry of Finance of China and the China Securities Regulation Commission, which requires mandatory rotation of audit partners since 2004, as a natural experiment to establish causality and applies a difference-in-difference research design.
Findings
Audit partner rotation leads to a significant decrease in future stock price crash risk in the departing partner’s final year of tenure preceding mandatory rotation, consistent with peer monitoring argument of mandatory rotation. Inconsistent with other arguments, including client-specific knowledge, fresh perspective and auditor independence, no significant effect takes a place in the incoming partner’s first year of tenure following mandatory rotation. Mechanism analysis documents that mandatory audit partner rotation reduces stock price crash risk by improving audit quality and constraining managerial empire building.
Originality/value
The results shed new light on the capital market consequence of mandatory audit partner rotation and the cause of stock price crash risk.
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Hang Thu Nguyen and Hao Thi Nhu Nguyen
This study examines the influence of stock liquidity on stock price crash risk and the moderating role of institutional blockholders in Vietnam’s stock market.
Abstract
Purpose
This study examines the influence of stock liquidity on stock price crash risk and the moderating role of institutional blockholders in Vietnam’s stock market.
Design/methodology/approach
Crash risk is measured by the negative coefficient of skewness of firm-specific weekly returns (NCSKEW) and the down-to-up volatility of firm-specific weekly stock returns (DUVOL). Liquidity is measured by adjusted Amihud illiquidity. The two-stage least squares method is used to address endogeneity issues.
Findings
Using firm-level data from Vietnam, we find that crash risk increases with stock liquidity. The relationship is stronger in firms owned by institutional blockholders. Moreover, intensive selling by institutional blockholders in the future will positively moderate the relationship between liquidity and crash risk.
Practical implications
Since stock liquidity could exacerbate crash risk through institutional blockholder trading, firm managers should avoid bad news accumulation and practice timely information disclosures. Investors should be mindful of the risk associated with liquidity and blockholder trading.
Originality/value
We contribute to the literature by showing that the activities of blockholders could partly explain the relationship between liquidity and crash risk. High liquidity encourages blockholders to exit upon receiving private bad news.
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De-Wai Chou, Pi-Hsia Hung and Lin Lin
This study focuses on listed and over-the-counter (OTC) companies in the Taiwan Stock Exchange. It found that an increase in the ownership proportion of institutional investors…
Abstract
This study focuses on listed and over-the-counter (OTC) companies in the Taiwan Stock Exchange. It found that an increase in the ownership proportion of institutional investors (INs), including foreign investors, investment trusts, and dealers can enhance the informativeness of stock prices. The relationship between these factors follows an inverted U-shaped pattern, indicating that excessively high ownership ratios can actually lead to a decrease in the informativeness of stock prices. Additionally, increasing the ownership proportions of foreign investors and investment trusts can reduce the risk of stock price collapse, while dealers show no significant relationship in this regard. This study also reveals that the technical variable of the price deviation rate is an important explanatory factor for post-collapse returns. It is positively correlated with the magnitude of the price decline after a collapse, meaning that stocks with weaker pre-collapse performance experience larger post-collapse declines. When the data during the 2020 pandemic period are excluded, changes in foreign ownership ratios show a significant positive correlation with postcrash returns in both the long and short term. The significant correlation in the short term may be due to a high proportion of foreign ownership. Any reduction in this could put pressure on stock prices, and retail investors may follow suit and sell-off, using foreign investors as a reference. The significant correlation in the long term might be due to foreign investors themselves possibly also trying to avoid the pressure that their own short-term sell-offs could exert on stock prices. The changes in the ownership ratios of investment trusts and dealers indicate that medium and long-term changes have a significant impact on postcrash returns, while the changes in the major players' ownership show no significant correlation. When data from 2020 are included in the analysis, the significance of all INs decreases.
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Sirine Ben Yaala and Jamel Eddine Henchiri
This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events…
Abstract
Purpose
This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events, namely the subprime crisis of 2008, the political and social instability of 2011 and the COVID-19 pandemic.
Design/methodology/approach
Over the period 2004–2020, a log-periodic power law model (LPPL) has been employed which describes the price dynamics preceding the beginning dates of the crisis. In order to adjust the LPPL model, the Global Search algorithm was developed using the “fmincon” function.
Findings
By minimizing the sum of square errors between the observed logarithmic indices and the LPPL predicted values, the authors find that the estimated parameters satisfy all the constraints imposed in the literature. Moreover, the adjustment line of the LPPL models to the logarithms of the indices closely corresponds to the observed trend of the logarithms of the indices, which was overall bullish before the crashes. The most predicted dates correspond to the start dates of the stock market crashes identified by the CMAX approach. Therefore, the forecasted stock market crashes are the results of the bursting of speculative bubbles and, consequently, of the price deviation from their fundamental values.
Practical implications
The adoption of the LPPL model might be very beneficial for financial market participants in reducing their financial crash risk exposure and managing their equity portfolio risk.
Originality/value
This study differs from previous research in several ways. First of all, to the best of the authors' knowledge, the authors' paper is among the first to show stock market crises detection and prediction, specifically in African countries, since they generate recessionary economic and social dynamics on a large extent and on multiple regional and global scales. Second, in this manuscript, the authors employ the LPPL model, which can expect the most probable day of the beginning of the crash by analyzing excessive stock price volatility.
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Xiao Yao, Dongxiao Wu, Zhiyong Li and Haoxiang Xu
Since stock return and volatility matters to investors, this study proposes to incorporate the textual sentiment of annual reports in stock price crash risk prediction.
Abstract
Purpose
Since stock return and volatility matters to investors, this study proposes to incorporate the textual sentiment of annual reports in stock price crash risk prediction.
Design/methodology/approach
Specific sentences gathered from management discussions and their subsequent analyses are tokenized and transformed into numeric vectors using textual mining techniques, and then the Naïve Bayes method is applied to score the sentiment, which is used as an input variable for crash risk prediction. The results are compared between a collection of predictive models, including linear regression (LR) and machine learning techniques.
Findings
The experimental results find that those predictive models that incorporate textual sentiment significantly outperform the baseline models with only accounting and market variables included. These conclusions hold when crash risk is proxied by either the negative skewness of the return distribution or down-to-up volatility (DUVOL).
Research limitations/implications
It should be noted that the authors' study focuses on examining the predictive power of textual sentiment in crash risk prediction, while other dimensions of textual features such as readability and thematic contents are not considered. More analysis is needed to explore the predictive power of textual features from various dimensions, with the most recent sample data included in future studies.
Originality/value
The authors' study provides implications for the information value of textual data in financial analysis and risk management. It suggests that the soft information contained within annual reports may prove informative in crash risk prediction, and the incorporation of textual sentiment provides an incremental improvement in overall predictive performance.
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Mohammed Bouaddi, Omar Farooq and Catalina Hurwitz
The aim of this paper is to document the effect of analyst coverage on the ex ante probability of stock price crash and the ex ante probability stock price jump.
Abstract
Purpose
The aim of this paper is to document the effect of analyst coverage on the ex ante probability of stock price crash and the ex ante probability stock price jump.
Design/methodology/approach
This paper uses the data of non-financial firms from France to test the arguments presented in this paper during the period between 1997 and 2019. The paper also uses flexible quadrants copulas to compute the ex ante probabilities of crashes and jumps.
Findings
The results show that the extent of analyst coverage is positively associated with the ex ante probability of crash and negatively associated with the ex ante probability of jump. The results remain qualitatively the same after several sensitivity checks. The results also show that the relationship between the extent of analyst coverage and the probability of cash and the probability of jump holds when ex post probability of stock price crash and stock price jump is used.
Originality/value
Unlike most of the earlier papers on this topic, this paper uses the ex ante probability of crash and jump. This proxy is better suited than the ones used in the prior literature because it is a forward-looking measure.
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Suvra 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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This study aims to explore the relationship between chief executive officer (CEO) power and stock price crash risk in India. Furthermore, it seeks to analyse how insider trades…
Abstract
Purpose
This study aims to explore the relationship between chief executive officer (CEO) power and stock price crash risk in India. Furthermore, it seeks to analyse how insider trades may moderate the impact of CEO power on stock price crash risk.
Design/methodology/approach
A study of 236 companies from the S&P BSE 500 Index (2014–2023) have been analysed through pooled ordinary least square (OLS) regression in the baseline analysis. To enhance the results' reliability, robustness checks include alternative methodologies, such as panel data regression with fixed-effects, binary logistic regression and Bayesian regression. Additional control variables and alternative crash risk measure have also been utilised. To address potential endogeneity, instrumental variable techniques such as two-stage least squares (IV-2SLS) and difference-in-difference (DiD) methodologies are utilised.
Findings
Stakeholder theory is supported by results revealing that CEO power proxies like CEO duality, status and directorship reduce one-year ahead stock price crash risk and vice versa. Insider trades are found to moderate the link between select dimensions of CEO power and stock price crash risk. These findings persist after addressing potential endogeneity concerns, and the results remain consistent across alternative methodologies and variable inclusions.
Originality/value
This study significantly advances research on stock price crash risk, especially in emerging economies like India. The implications of these findings are crucial for investors aiming to mitigate crash risk, for corporations seeking enhanced governance measures and for policymakers considering the economic and welfare consequences associated with this phenomenon.
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