Search results

The purpose of this paper is to utilize the initial public offerings (IPO) market to research the effect the stock market crash of 1987 had on the market psyche.

The paper compares the number of IPOs, as well as accounting data during the years surrounding the 1987 crash to determine if there is a change in financial quality. The underwriting fee structure, underpricing and short term price changes during one year prior to and one year following the 1987 crash are examined, as well as the long term returns surrounding the crash.

The stock market crash of 1987 did change the market psyche in the short to medium term. Results show greater risk aversion in the post crash period, as evidenced by fewer IPOs from riskier firms. Pricing is found to be more rational – less one day run‐up, less upward adjustment from offering range, and less likely to be overpriced in intermediate and longer terms.

The paper demonstrates the importance of market sentiment and may illuminate the causes of market cycles.

The purpose of this paper is to explore the impact of product market competition on the risk of stock price crash based on the degree of industry competition and the competitive position of enterprises.

This paper chooses the data of Shanghai and Shenzhen A-share listed companies from 2009 to 2017 as samples and uses a threshold regression model to explore the impact of product market competition on the risk of a stock price crash.

The results show that: the overall level of industry competition is negatively correlated with the risk of stock price crash; the competitive position of enterprises and the risk of a stock price crash. The correlation is not significant: for high competitive enterprises, the degree of industry competition is negatively correlated with the risk of stock price crash; for low competitive enterprises, the degree of industry competition is positively correlated with the risk of a stock price crash and the conclusions obtained have passed the robustness test.

This paper not only enriches the literature on the relationship between product market competition and the risk of stock price crash but also has reference significance for supervisors to allocate resources to supervise information disclosure of listed companies.

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.

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.

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.

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.

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.

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.

Purpose − The purpose of this paper is to review an explanation for the causes of the stock market crash in 1987, update the empirical support for that argument, and compare to recent market developments. Design/methodology/approach − While the market crash on October 19, 1987 was the largest one‐day S&P 500 drop in percentage terms in history (20.47 percent) there was also a large market drop (10.12 percent) in the three trading days before the 1987 crash. Previous research has shown show that the three‐day decline was the largest in more than 40 years, large enough that the drop was news itself (the October 16, 1987 drop immediately before the crash was also an extremely large one‐day decline). The theoretical model of Jacklin et al. show how a surprise significant drop in the market could have provided information to the market that could directly lead to an immediate crash. Findings − The paper follows the stock market for 20 years after 1987, and finds the magnitude of the market decline immediately preceding October 19, 1987 was still a significant outlier − only one three‐day period in the 20 years after 1987 had as large a market decline. The paper documents the large market movements and volatility in the period beginning in fall 2008 and suggests that this “crash” is different than what occurred in 1987. Research limitations/implications − This paper's main limitations lie in the implications drawn about the causes of the 2008 crash. Practical implications − This paper provides evidence on the causes of the 1987 crash and implications for the 2008 decline. The 1987 crash was due in part to characteristics news but also to the market and trading strategy, the 2008 “crash” is more likely a response to fundamental economic news. Originality/value − This paper uses empirical evidence since 1987 to look back on the causes of the 1987 crash.

Rapid stock market growth without real economic back-up has led to the 2015 Chinese Stock Market Crash with thousands of stocks hitting the down limit simultaneously multiple times. The authors provide a detailed analysis of structural breaks in heavy-tailedness and asymmetry properties of returns in Chinese A-share markets due to the crash using recently proposed robust approaches to tail index inference. The empirical analysis points out to heavy-tailedness properties often implying possibly infinite second moments and also focuses on gain/loss asymmetry in the tails of daily returns on individual stocks. The authors further present an analysis of the main determinants of heavy-tailedness in Chinese financial markets. It points out to liquidity and company size as being the most important factors affecting the returns’ heavy-tailedness properties. At the same time, the authors do not observe statistically significant differences in tail indices of the returns on A-shares and the coefficients on factors affecting them in the pre-crisis and post-crisis periods.

The purpose of this paper is to investigate whether analysts’ optimism affects the stock crash risk.

The sample covers 49,246 firm-year observations for the period between 1995 and 2015. The authors use OLS regressions with firm and year fixed effects for analyses.

The study finds that there is a positive association between analysts’ optimism and stock crash risk. Such a positive impact is more pronounced for firms with opaque information environment and for analysts who are considered ex ante credible.

The results indicate that analysts’ optimism can be an important source of stock crash risk.

The findings can be useful for informational users of analyst reports. Given that information provided by analysts might have negative consequences, the empirical results can be useful in assessing future stock return behaviors.

This paper has the potential to shed light on the large literature of crash risk. Prior studies suggest that crash is driven by the agency tension between shareholders and managers. It remains possible that crashes could be caused by overpriced stocks in the absence of bad news hoarding. The paper investigates crash from a perspective, financial analysts, that is underexplored.

In this paper we provide an in‐depth comparative analysis of the shares of listed firms in three Southeast Asian stock markets, namely, Indonesia, Malaysia and Thailand, that had experienced the most violent fluctuations in the 1997 market crash. Our purpose is to present broad lessons from the experiences of these countries that could be helpful to understand the behavior of stock markets under severe financial crisis. Several new results are found: (1) There were local price bubbles prior to the market crash in each country. (2) Price momentum may have contributed to the share price increase prior to the crash but not during the period of crisis or the market reversal. (3) The price bubbles in these countries were mainly among the most liquid and most volatile shares. (4) Asset liquidity was found to cause returns to behave differently in quiet versus extraordinary period.

This study aims to investigate the relationship between corporate tax avoidance and stock price crash risk and the moderating effects of corporate governance.

This study investigates the relationship between corporate tax avoidance and stock price crash risk using the sample consisting of listed firms in Vietnam for the period of 2011–2020 using panel regressions.

The authors find that there is a positive relationship between tax avoidance and stock price crash risk. Foreign ownership weakens the impacts of tax avoidance on stock price crash risk, while managerial ownership strengthens the impacts. Female Chief Executive Officers (CEOs) and female chairpersons weaken this relationship. Board gender diversity and state ownership have insignificant moderating impacts.

These findings could help the stock market build better internal monitoring mechanisms to reduce the impacts of tax avoidance on future stock price crash risk. Investors can recognize the characteristics of corporate governance, especially foreign ownership, managerial ownership, female CEOs and female chairpersons when making investment decisions. The policy makers should consider policies to attract foreign investment and support women entrepreneurship.

This paper contributes to the literature on the impacts of tax avoidance on stock price crash risk in emerging countries. This paper is the first to investigate the influence of corporate governance mechanisms including state ownership, foreign ownership, female CEOs and chairpersons and board gender diversity on this relationship.

This paper aims to investigate the spillover effects of jump and crash events among Chinese nonfinancial firms.

This sample consists of more than 1.5 million weekly observations of over 3,000 Chinese listed firms over the period 1991–2015. The authors utilize univariate tests to compare the post-event performance of matched peer and non-peer control firms and cross-sectional regressions of their abnormal returns/cumulative abnormal returns (ARs/CARs) and returns on assets (ROAs).

The authors find that extreme risk-adjusted abnormal stock returns (stock price crashes and jumps) generate statistically significant ARs/CARs in the same directions in industry, size, leverage, and geographical location matched peer firms in Chinese stock market. Further tests reveal that peer firms' response to the crash event is pronounced more in the group of firms about which the information asymmetry is high between investors and firms.

Portfolio investors can adjust their portfolios accordingly by selling stocks of the matching rival firms during a crash period. Policymakers may develop policies so as to protect the interests of small investors in the events of crashes in the markets. They can reduce the information asymmetry between the firms and the investors by making information about the firms more transparent, so as to reduce the contagion in case of crash event.

This study has important implications for portfolio investment managers and policymakers.

To the best of authors' knowledge, this is the first study that combines the jump and crash events and attempts to assess their spillover effects on other firms in Chinese stock market.