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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.

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.

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.

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.

The purpose of this paper is to study the impact of the 2016 presidential election polls on the stock market.

The empirical model includes daily stock returns as the dependent variable and past asset prices, 10-year treasury rates, opinion polls and VIX (market uncertainty) as explanatory variables with a one-year lag. The model was estimated using two sets of daily polling data: from July 1, 2015, to November 8, 2016, and from June 1, 2016, to November 8, 2016. Additional descriptive statistics, such as means and standard deviations, were also calculated.

The estimated results did not reveal any statistically significant effects of opinion polls in favor of one candidate over another on stock returns. Simple statistical tests, however, show that the market performed better when Trump held a polling advantage over Clinton.

To the best of the authors’ knowledge, this is the only study that has examined the effects of the 2016 presidential election polls on the US stock market. This study adds value to the understanding of the relationship between election polls and the stock market in the USA.

The authors evaluate the Sell in May effect in the Canadian context to comprehensively explore the Sell in May effect as well as its interactions with the size effect and risk and with multiple indices.

The authors use ordinary least squares (OLS) regressions to examine the Sell in May effect and Huber M-estimation to handle potential outliers. They also use the generalized autoregressive conditional heteroskedasticity (GARCH) models to explore the role of risk in the Sell in May effect.

The results demonstrate that the Sell in May effect is present in all three main Canadian stock market indices. More telling, the anomaly is strongest in small cap indices and in indices that give equal weighting to small and large cap stocks. They do not find that the effect is driven by risk.

While several papers have explored the Sell in May phenomenon in several countries, little scholarly attention has been paid to this effect in Canada and to its interaction with the size effect. The authors contribute to the literature by examining of the interactions between Sell in May and the size effect in Canada. They examine the Sell in May effect using CFMRC value-weighted and equally weighted indices of all Canadian companies. They also incorporate in their analysis the role of risk.

In October 2016, Timothy Sloan, the newly appointed CEO of American banking giant Wells Fargo, faced a massive public-relations crisis. A few weeks earlier, a United States government agency had announced the results of its regulatory review of the bank and exposed a shocking practice common in the retail division, in which aggressive community bankers had created more than a million fraudulent accounts and credit card applications on behalf of unaware customers for the past several years. Over the next few weeks, the bank—and Sloan's predecessor, John Stumpf, in particular—suffered from harsh criticism from politicians, journalists, and former employees alike, ultimately forcing Stumpf's resignation. As Sloan sought to minimize the public-image backlash and restore general trust in Wells Fargo, he struggled to construct the best communication strategy for the bank's next chapter.

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.

Employee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand the exercise decision of the employees. This is an important financial decision that is dependent on both rational and psychological factors. This paper aims to study the mediating role of Herding Bias on Personality Traits and the employees' decision to exercise ESOs.

The data were collected through a self-structured questionnaire from 210 employees of Banks and NBFCs [Non-Banking Financial Companies] who have received and exercised the ESOs. SPSS MACRO version 25 was used to understand the mediational effect of Herding Bias on Personality Traits and Employees' decision to exercise their ESOs.

The results showed that Personality Traits affect the employees' decision to exercise their ESOs. The study also shows a partial negative mediating effect of Herding Bias on Personality Traits and employees' decision to exercise ESOs.

Limited study has been conducted on how the employees make their decision to exercise ESOs. Although extant studies have touched upon the importance of including behavioural biases in ascertaining the exercise decision of the employees, the predictors of the behavioural biases have not been studied under this context. To the best of the author's knowledge, this study is the first in itself to study the inter-linkage between Personality Traits, Herding Bias and employees' decision to exercise ESOs.

Investors' behavior in financial markets is often under the influence of various psychological and cognitive factors, as well as personality characteristics. This research explores which behavioral factors and personality traits affect investment decisions and, consequently, investment performance.

A survey analysis was conducted on a sample of 310 investors in Croatia. Partial least squares structural equation modeling was used to obtain the results.

Overconfidence heuristic, prospect theory elements, emotions and stability and plasticity (as big two personality dimensions) positively affect investment decisions, while herding has a negative effect. Investment decisions, observed through the preference for long-term investments, consequently have a positive effect on the investment performance satisfaction.

This research proposes a unique comprehensive model of the effect of numerous different cognitive and psychological behavioral factors on investment decisions. Furthermore, the influence of investment decisions on investment performance is observed simultaneously. Understanding human behavior based on their personal characteristics can help investors to make better investment decisions. Advisors can learn from human behavior and guide their clients in the right direction when it comes to stock investment. Scientists will be able to replicate the model with other data and make comparative analyses.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

The purpose of this study is to investigate the impact of an industry’s connectedness to foreign countries on knowledge sourcing.

The authors examine the research model through probit regression techniques to the 472,303-patent data across 16 industries derived from the United States Patent and Trademark Office.

The results suggest that international connectedness increases the accessibility of foreign knowledge and helps the accumulation of technological capability. Thus, this paper provides a better understanding that international connectedness can be critical for exploiting knowledge dispersed worldwide and influencing intra- and interindustry knowledge-sourcing behavior in the home country.

While prior studies have mainly paid attention to the relationship between parents and subsidiaries in foreign countries for international knowledge sourcing, the authors attempt to analyze international and local knowledge sourcing with a broader set of knowledge sourcing channels at an aggregate level. By considering an industry’s export intensity and inward foreign direct investment, this study reveals specifically how the extent of an industry’s international connectedness influences knowledge sourcing from both abroad and locally.