Stock Price Risk Research Articles

The Brownian motion, Wiener process, and Pu migration as examples of random walk

The theory of random walks holds significance across various domains. To this end, this paper discusses the application of random walk theory in the modeling and analysis of complex systems, including the Brownian motion, Wiener process, and Pu migration. The first part mainly explains the concepts of Brownian motion and random walks, as well as their relationship. The core characteristic is the independence and normal distribution of increments, which makes it a special model of random walks. The next part is the Wiener process, which is a continuous time stochastic process. It can describe random phenomena and solve complex problems in finance, encompassing areas such as stock price prediction, option pricing, and risk management. The last part is about Pu migration, with the clear introduction of Pu migration in biology. The authors discuss why the random walk theory can be regarded as the better approach to analysis this problem. Thus, this paper highlights the importance of the random walk in solving many scientific issues.

The Relationship between Credit Rating and Environmental, Social, and Governance Score in Banking

The present paper investigates the relationship between stock prices, credit ratings, and ESG scores for banks internationally. First, it describes stock prices and ESG scores at an annual frequency, as well as stock price and credit risk at a daily frequency. The relationships between (a) stock price and credit rating returns with ESG score returns and (b) among ESG scores are examined by pairwise annual correlation, and daily correlations are examined between price and credit rating returns. Furthermore, Granger causality is used to examine the relationships between the following: (a) price and ESG score annual returns; (b) price and credit rating daily returns; and (c) total and pillar annual ESG scores. This study makes a significant contribution to the literature by providing a detailed temporal analysis using both annual and daily data frequencies, which is relatively rare in the field. There is evidence of statistically and empirically important relations in the form of pairwise correlations. The regressions reveal a low significance of few ESG score changes in explaining credit rating changes. A unique aspect of this paper is the comprehensive analysis of 16 granular ESG scores, including overall scores, pillar scores, and sub-scores, allowing for a multi-faceted understanding of how specific ESG factors impact financial metrics. We found evidence of the significance of COVID-19 in all research questions. Additionally, this paper highlights the impact of the COVID-19 pandemic on the relationships between ESG scores, credit ratings, and stock prices, offering timely insights into the heightened importance and volatility of ESG factors during crisis periods. Future research needs to shed more light on this relationship, however.

The effect of geopolitical uncertainty on stock liquidity: evidence from Taiwan misfired missile event

ABSTRACT We investigate the effect of geopolitical uncertainty on stock liquidity by using the Taiwan misfired missile event as a natural experiment. This exogenous event provides us with a unique opportunity to overcome the challenges of time recognition and confounding economic effects in the identification. We find that geopolitical uncertainty has a significantly negative effect on the stock liquidity of Taiwan-related firms. The mechanism test shows that the increased stock price risk and information asymmetry are the two main channels through which geopolitical uncertainty decreases stock liquidity. Moreover, we find that firms’ higher information transparency and regulators’ timely information disclosure on geopolitical events can effectively mitigate the negative impact of geopolitical uncertainty on stock liquidity.

Prediction of The Islamic Stock Price Index and Risk of Loss Using The Long Short-Term Memory (LSTM) and Value At Risk (VaR)

Prediction of The Islamic Stock Price Index and Risk of Loss Using The Long Short-Term Memory (LSTM) and Value At Risk (VaR)

Executive compensation adjustment and the risk of stock price

Executive compensation adjustment and the risk of stock price

Biodiversity management and stock price crash risk

AbstractThis study explores the link between corporate biodiversity management and the risk of sudden declines in future stock prices, an area largely overlooked in empirical research despite the societal significance of biodiversity loss. We posit that robust corporate biodiversity efforts mitigate the suppression of negative information, consequently reducing the risk of abrupt stock price declines. Leveraging a global dataset and innovative biodiversity management metrics from Moody's ESG Solutions (former Vigero Eiris), our multivariate regression analysis demonstrates that companies with stronger biodiversity structures and actions exhibit lower stock price crash risk. In an additional analysis, we focus on environmental inspections as a possible conduit for releasing negative information on biodiversity management. Using a subsample of North American firms that were inspected by the U.S. Environmental Protection Agency (EPA), we find that firms which experience an inspection record an increase in their stock price crash risk.

Empirical Analysis of the Impact of Chinese Commercial Banks on Financial Market Risk Based on the CoVaR Method

The paper conducts an empirical analysis using the CoVaR model and data sourced from weekly individual stock returns of listed Chinese commercial banks to examine the impact of individual commercial banks on the entire financial system. Overall, the stock price risk of Chinese commercial banks exhibits a negative spillover effect on the financial market. Based on dCoVaR values from 2006 to 2023 and in conjunction with financial events related to the market over the 17-year period, it is evident that significant events lead to notable negative spillover effects by commercial banks stock price risk on the entire financial system, highlighting their crucial influence on financial market risk.

Decisions regarding the role of bad news and asymmetric effects in the Middle East stock markets

This paper aims to study the impact of the COVID-19 pandemic, the Russian invasion of Ukraine, and the Turkey-Syria earthquake on the Middle East’s developed, emerging, and frontier markets. For this purpose, panel data of nine Middle East financial markets listed in Morgan Stanley from January 2, 2018, to July 27, 2023, were analyzed using multi criteria. In the event study, two approaches were deducted to analyze the price impact: 1) a standard event study and 2) an independent sample, following Brown and Warner (1985). The generalized autoregressive conditional heteroskedasticity (GARCH) group captures asymmetric and leverage effects. The results show volatility in financial market index returns and the impact of bad news and leverage in all markets. However, this effect is asymmetric across markets, indicating a low integration. Moreover, the negative impact of COVID-19 was more pronounced than that of both the Russian invasion of Ukraine and the Turkey-Syria earthquake. This study’s findings can help investors make informed investment decisions and select optimal portfolios. It will also add to the existing body of knowledge by shedding new light on the factors that influence stock price volatility and risk management in Middle Eastern international fiscal issues.

Effect of Stock Split on Abnormal Return, Trading Volume Activity, Stock Price, Bid-Ask Spread, and Systematic Risk of Companies

Go-public companies can use various techniques and strategies to collect capital for their companies. One of them is by carrying out corporate actions. Stock Split is a company strategy that increases the liquidity of a stock by breaking it into several shares. This study was conducted to see the effect of stock split on whether there were differences in abnormal returns, trading volume activity, stock price, bid-ask spread, and systematic risk at companies that conducted stock split in the 2018-2020 period. A total of 40 companies registered on the IDX and conducted stock split from 2018-2022 to be selected samples using the purposive sampling method. In data processing, software-based technology is used SPSS 25. Based on the calculation and results of data analysis, there are differences in the abnormal return variable before and after the stock split is carried out. While other variables, namely trading volume activity, stock price, bid-ask spread, and systematic risk, no difference between before and after stock split is carried out by the company.

Can good ESG performance reduce stock price crash risk? Evidence from Chinese listed companies

AbstractAgainst the backdrop of growing worldwide attention towards environmental, social, and governance (ESG) considerations, this study investigates how ESG performance affects the probability of stock price crashes. The research explores samples of Chinese A‐share listed companies during the period from 2010 to 2019. The outcomes indicate that commendable ESG performance lowers the likelihood of stock price crashes, and these results persist robust even after executing a series of robustness and endogeneity examinations. Moreover, the available evidence indicates that good ESG performance mitigates the risk of stock price crashes by curbing both earnings management and corporate risk. However, the positive influence of good ESG performance on reducing the risk of stock price crashes diminishes when analyst coverage increases. Furthermore, the heterogeneity analysis infers that the effect of good ESG performance in reducing stock price crash risk is more significant for non‐state companies. Heightened economic policy uncertainty weakens the effect of good corporate ESG performance in mitigating stock price crash risk. Of the three ESG performance dimensions—environmental, social, and corporate governance—the latter is the most effective in lessening such risks. This research carries notable implications for reinforcing the ESG disclosure arrangement in China and other developing economies. It also guides government institutions and regulators in the creation of policies that foster high‐calibre economic progress.

Risk analysis of China's financial market collapse based on cloud computing and machine learning algorithms

AbstractIn recent years, with the rapid advancement of hardware and software algorithms, information technology has penetrated every aspect of our lives, creating waves of digital transformation in enterprises represented by four underlying technologies, namely: ‘artificial intelligence, big data, cloud computing, and blockchain’. As a result, digital technology has emerged as the primary force behind industrial transformation and upgrading, as well as high‐quality development. Using the data of Shanghai and Shenzhen A‐share listed companies from 2007 to 2020, this paper empirically examines the impact of the digital transformation of listed companies on their stock price crash risk and its mechanism using a two‐way fixed effect model with time and individual effects. It can be seen from the research results that, overall, enterprise digital transformation can significantly reduce the risk of a stock price crash. Further analysis reveals that this risk‐inhibiting effect is more apparent for private enterprises and small and medium‐sized enterprises. In terms of impact mechanism, digital transformation can reduce the risk of a stock price crash by improving the quality of enterprise information internally, while the more analysts pay attention to an issue, the more obvious the role of digital transformation in reducing the risk of a stock price crash for enterprises externally. However, it is worth noting that if the stock price of an enterprise crashes, blindly implementing digital transformation may increase the crash risk. The paper illustrates the practical importance of digital technology from the perspective of enterprises in stabilizing the crash risk of stock prices and improving the performance of the capital market. Meanwhile, it contributes to theoretical research on the impact of digital transformation on microeconomic entities and provides practical knowledge and evidence for enterprises to accelerate digital transformation.

Impact of Brand Capital on the Stock Price Crash Risk, an Empirical Study

The factors influencing the financial market are rapidly becoming more complex. The impact of non-financial factors on the performance of a company’s common stock can increase in ways that were not previously expected. This study investigated how brand capital affects the risk of stock prices in Iraqi private banks listed on the Iraq Stock Exchange failing by identifying the likelihood of a crash caused by a negative deviation in the distribution of returns on ordinary shares. As a result, the current study’s concept is to review an analytical knowledge framework of the nature of that relationship, its changes, and its impact on the pricing of ordinary shares of the banks of the researched sector for the years 2009 to 2017, as well as by the 21 banks listed during that time and by the 588 observations using the expanded market model to determine quarterly changes in stock prices. In addition to testing the negative coefficient of skewness and the down-to-up volatility models to test the contribution of brand capital in reducing the risk of stock collapse, The test results showed that brand capital is closely related to the significant and adverse risks of a stock crash. Additionally, the first’s impact is inverse, as its content highlights the role that the research sample banks’ brand capital played in lowering the dangers of stock price crashes.

Insight into the risk-resistant function of ESG performance: An organizational management perspective

PurposeThis study aims to examine the risk-resistant role of environmental, social and governance (ESG) performance in the capital market, focusing on an organizational standpoint. Furthermore, it aims to offer management decision advice to companies seeking protection against stock market risks. Conclusions obtained through this research have the potential to enrich the economic consequences of ESG performance, provide practical implications for enhancing corporate ESG performance, improving corporate information quality and stabilizing capital market development.Design/methodology/approachBased on the data of Chinese A-share listed companies from 2009 to 2020, this study examines the risk-resistant function of ESG performance in the capital market. The impact of ESG performance on management behavior is analyzed from the perspective of organizational management and the three mechanisms of pre-event, during the event and post-event.FindingsThis paper demonstrates that companies that effectively implement ESG practices are capable of effectively mitigating risks associated with stock price crashes. Heterogeneity analysis reveals that the inhibitory effect of ESG performance on stock price crash risk is more pronounced in nonstate-owned enterprises and enterprises with higher levels of marketization. After controlling for issues such as endogeneity, the conclusions of this paper are still valid. The mechanism analysis indicates that ESG performance reduces the risk of stock price crash through three paths of organizational management: pre-event, during the event and post-event. That is, ESG performance plays the role of restraining managers’ opportunistic behavior, reducing information asymmetry and boosting investor sentiment.Originality/valueThis paper provides new insights into the relationship between ESG performance and stock price crash risk from an organizational management perspective. This study establishes three impact mechanisms (governance effect, information effect and insurance effect), offering a theoretical basis for strategic corporate decisions of risk management. Additionally, it comprehensively examines the contextual differences in the role of ESG performance, shedding light on the specific domains where ESG practices are influential. These findings offer valuable insights for promoting stable development in the capital market and fostering the healthy growth of the real economy.

The impact of green financial development on stock price crash risk from the perspective of information asymmetry in Chinese listed companies.

Solving the crash risk problem of corporate stock price caused by information asymmetry can mitigate the negative externality of its carbon emission to become green, low-carbon, and high-quality development. Green finance generally profoundly impacts micro-corporate economics and macro-financial systems but remains a giant puzzle of whether they can effectively resolve the crash risk. This paper examined the impact of green financial development on the stock price crash risk using the sample data of non-financial listed companies in Shanghai and Shenzhen A stock market in China from 2009 to 2020. We found that green financial development significantly inhibits the stock price crash risk; this is more obvious in listed companies with a high level of asymmetric information. And companies in high-level regions of green financial development attracted more attention from institutional investors and analysts. As a result, they disclosed more information about their operational status, thus reducing the crash risk of corporate stock price from the torrential public pressure of lousy environmental details. Therefore, this study will help continuously discuss the costs, benefits, and value promotion of green finance for synergy between corporate performance and environmental performance to improve ESG capabilities.

Controlling Shareholder Pledges and Cost of Equity Capital: Analyzing Empirical Evidence from A-Share Listed Companies

With the constant increase in China’s stock pledge transactions, controlling shareholders’ equity pledges may result in inadequate investment, which government regulatory authorities, investors, and financial management departments should be aware of. Taking China’s A-share listed companies from 2013 to 2019 as a sample, this paper examines the impact of controlling shareholder pledge on equity capital cost. It is found that the equity capital cost of listed companies increases significantly after controlling shareholder pledge, and high-quality audit reports help reduce the influence of controlling shareholder pledge on it. In addition, the mechanism test shows that controlling shareholder pledge impacts the equity capital cost by reducing stock liquidity and increasing the tunneling behavior of large shareholders. Further research shows that under controlling shareholder pledges, improving the quality of information disclosure can help reduce the equity capital cost, while stock price risk can increase the equity capital cost.

Is Cryptocurrency Risky as An Investment Instrument? Analysis of Return and Risk with A Comparison of Sharia Stocks

Cryptocurrency instruments show an increase in the number of investors in Indonesia, the increase in cryptocurrency investors is even bigger than the number of stock investors in the Indonesian capital market, even though stock investors also increase. The increase in stock and cryptocurrency investors is an indication that the investment climate in Indonesia is starting to improve, this must be accompanied by increased financial literacy regarding the returns and risks of an investment instrument, this research is important considering that understanding the returns and risks of an investment instrument is crucial in the decision making. The test in this study uses a descriptive statistics and independent sample t-test, if the sample does not meet the requirements of the parametric statistical test, it will use the nonparametric statistical test Mann Whitney Test, which aims to determine whether there is a difference in return and risk of cryptocurrencies and sharia stock prices for the period January 2015 to October 2021. This study finds that there are significant differences in the returns and risk of cryptocurrencies and Sharia Stocks. Based on descriptive statistics, the standard deviation of cryptocurrency returns is greater than the standard deviation of Sharia stocks, indicating that cryptocurrency risks are higher than Sharia Stocks.

PERBANDINGAN RISIKO PASAR (BETA SAHAM) PADA 9 SEKTOR PERUSAHAAN DI PASAR MODAL

The objective of this research is to identify the effects of market risk (stock beta) across nine sectors of companies in capital market on the return produced during the Covid-19 pandemic in Indonesia in the short and the long term. This quantitative research uses two variables: stock returns in composite index obtained from idx.co.id as the dependent variable and market risk (stock beta) and the index of the nine sectors as the independent variables. The results of the analysis indicate that four hypotheses were proven in the long term; they are agricultural sector, basic industry sector, consumption goods sector, and property sector. The said finding indicates that, during the Covid-19 pandemic, anytime the stock price and the market risk increase, the stock return of the composite index will drop. Hence, when the stock price and the market risk of those sector rise, the number of investors buying the four sectoral stock will decrease. In the short term, three hypotheses were accepted; they are in agricultural sector, basic industry sector, and consumption goods sector. During the Covid-19 pandemic, any increase in the sectors’ stock price and market risk will be followed by a decline in the composite index’s return because when the stock price and market risk increase, the number of investors

Forecasting Daily Stock Volatility: A Comparison between GARCH and Recurrent Neuro-networks

Forecasting the volatility of financial derivatives and securities returns has always been the core of financial research. Accurate volatility forecast is integral to financial risk management, which is vital for investors and supervision authorities. Traditional time series models (e.g., ARCH and GARCH models) have been famous tools for volatility forecasting. However, those models cannot capture non-linear correlations, and prediction capability is unsatisfactory. In this paper, we use multifactorial deep learning algorithms RNN, LTSM, and GRU with sentiment data to predict the future volatility of Apple (AAPL), then compare the accuracy of prediction with the GARCH model. According to the analysis, the prediction accuracy of LSTM and GRU significantly improved compared with the GARCH model. These results shed light on guiding further exploration of stock volatility prediction using deep learning algorithms. Besides, it advises investors to choose efficient stock price volatility forecasting and risk management tools.

Economic policy uncertainty, non-financial enterprises' shadow banking activities and stock price crash risk

At present, the structural contradiction between Economic Financialization and the real economy's long-term weakness has become increasingly prominent. As China enters a “new normal” stage of economic growth, the real investment rate drops, non-financial enterprises continuously allocate resources to the shadow banking system. The financial economy becomes increasingly divorced from reality. This leads us to the questions: will the shadow banking behavior of non-financial companies exacerbate the risk of stock price crash risk? How does the increase in economic policy uncertainty affect the relationship between non-financial companies' shadow banking activities and stock price crash risk?This article uses non-financial listed companies' data from 2007 to 2017 and conducts empirical analysis to answer this question. The study finds that companies engaged in high-leverage, high-risk shadow banking business exacerbate stock crash risk. This effect is only pronounced in non-state-owned enterprises and low social trust regions. The increase in the degree of economic policy uncertainty positively impacts the relationship between non-financial companies' shadow banking business and stock price crash risk. The theoretical mechanism is as follows: the rise in economic policy uncertainty amplifies the positive relationship between shadow banking activities of non-financial companies and stock price crashes by increasing bank loans, investors' sensitivity to external information, risk cross-contagion, and inefficient investment mechanisms. Various robustness tests do not change the research conclusion. This paper has important theoretical and policy guidance significance for reviewing the existing diversified shadow banking system and preventing systemic risks.

Hedge Strategy Analysis and Financial Analysis of Yunnan Baiyao

Plenty of companies actively employ financial instruments to hedge looming risks. Although hedging may reduce risks such as exchange rate risk and potential price risk, hedging is also likely to make companies suffer from loss. Options, one of the financial derivatives, bring holders rights instead of obligation to buy or sell the underlying asset at a fixed price. In 2020, Yunnan Baiyao declared that the group intended to conduct stock buybacks hedge the stock price risk of its repurchase plan. The cost of buyback was reduced in that this repurchase plan was combined with OTC put options. Yunnan Baiyao is the leading company in the pharmaceutical and health industry and its market value reached ￥134.24bn which ranked second among its peers as of 2021. Based on this stock purchase plan of Yunnan Baiyao, this article aims to analyze the financial situation of the company and the application of put options in the plan.