Lower Stock Price Research Articles

Risk committee and stock price crash risk in the Malaysian financial sector: the moderating role of institutional ownership

PurposeThe authors empirically investigate the impact of the existence of a stand-alone risk committee (RC) and its characteristics on the likelihood of stock price crash risk in listed financial firms on the Bursa Malaysia. The authors also test whether the effect of RC on crash risk is attenuating or amplifying by the level of institutional ownership.Design/methodology/approachThe authors use a principal components analysis (PCA) to aggregate and derive a factor score for risk committee characteristics (i.e. independence, qualification, and size) as a proxy for the effectiveness of RC. The study also employs two distinct stock price crash risk measurements to corroborate the findings and partition institutional ownership into dedicated and transient to examine the potential impact of institutional shareholding on RC-stock price crash risk association.FindingsRegression analysis reveals that only RC qualification has a significant negative impact on stock price crash risk. However, when RC characteristics are aggregated into one composite factor, the authors find that firms with effective RCs exhibit lower risk of stock price crash. The authors also find that firms with high level of institutional shareholdings and effective RCs are less likely to experience crash risk likelihood. The additional analyses indicate that the complementary moderating effect of institutional ownership on RC-crash risk nexus is likely to be driven by dedicated institutional ownership. The results are robust across two measures of stock price crash risk and regression specifications for a longer run window.Originality/valueThe study, to the best of the researchers' knowledge, is the first to provide evidence in an emerging market financial sector companies' perspective suggesting that effective RCs are individually and aggregately associated with lower stock price crash risk, which is further strengthened by dedicated institutional investors. These findings are unique and contribute to a small but growing body of literature documenting the need for effective RCs and specific institutional investors and their consequences of improvements in stock price crash risk environment. Results of our research in this area provide important insights to financial and capital market participants, investors, regulators, and policymakers in Malaysia.

The way digitalization is impacting international financial markets: Stock price synchronicity

AbstractThis paper investigates whether and how the development level of a country's digital economy affects stock price synchronicity. The results indicate that countries with high levels of digital economy development exhibit low stock price synchronicity. Additionally, by decomposing stock price synchronicity into systematic and firm‐specific stock return variations, we find that systematic (firm‐specific) variations of stock returns decrease (increase) with the level of a country's digitalization. These findings shed light on the future trend of stock price synchronicity in financial markets around the world and support the information‐based interpretation of stock price synchronicity.

Evaluation of ESG Ratings for Chinese Listed Companies From the Perspective of Stock Price Crash Risk

ESG investment strategy has attracted increasing attention from the financial market, and the inconsistency of enterprise ESG rating results of different rating agencies has gradually become the focus of attention of regulators and investors. In this article, the listed companies with ESG ratings in Shanghai and Shenzhen A-shares from 2016 to 2020 were selected as the research samples. Combined with difference-in-differences model and ordinary least squares methods, the rationality of these ESG ratings was evaluated by examining the difference in the impact of three international ESG rating agencies, such as Bloomberg, and three Chinese ESG rating agencies, such as Sino-securities, on the stock price crash risk. The research findings are as follows: First, after incorporating the ESG ratings of FTSE Russell, MSCI, and China Alliance of Social Value Investment, the stock price crash risk of enterprises is significantly reduced. Second, the company's share price crash risk will be lower when the ESG evaluation results of Bloomberg or MSCI is better. Third, compared with social indicators, investors pay more attention to the environmental performance of enterprises in decision making. Enterprises with high environmental scores have lower stock price crash risk. The findings of this article play an enlightening role for China to improve its ESG system, construct an ESG disclosure policy, and improve the market role of ESG rating.

Resilience of Environmental and Social Stocks under Stress: Lessons from the COVID‐19 Pandemic

This paper examines whether environmental and social (ES) activities affect the resiliency of firms during the COVID‐19 crisis. We study a sample of 330 firms operating in five developed countries: Canada, France, Japan, the UK and the US. Our analysis shows that US firms with a high ES ranking experienced a significantly lower stock price range volatility during the Covid stock market rundown of February‐March 2020. Such findings also hold for Japanese firms but only later on after the introduction of government support. In terms of returns, compared to their peers with a low ES ranking, Japanese and UK stock prices with a high ES ranking suffered more during and after the market rundown. For other countries, we do not find significant differences in stock price behavior based on ES ratings. Our findings suggest that engaging with ES activities is not associated with a better or worse performance during crisis times, which has important implications for investors and managers.

Nonlinear dynamics in real economy and financial markets: The role of dividend policies in fluctuations

This paper investigates how dividend policies may influence the creation and propagation of cycles between real economy and financial markets. We focus on the effect of a constant dividend policy on the stability of the aggregate economy, by means of a discrete dynamical framework in which managers, individuals and financial mediators coexist. We show the counter-intuitive effect of the dividend payout ratio: in a developed economy, an increase in dividends leads to a lower stock price level due to the cross-feedback effect between markets. Moreover, in non-developed economies the choice of managers and individuals may not influence the propagation of fluctuations, while in developed economies, high payout ratios and high sensitivity to market trends trigger a cross-feedback effect between the two markets that amplifies their volatility and drags the whole economy into fluctuations and cycles.

Asset pricing and nominal price illusion in China

Based on the Fama’s three-factor model (FF3) and five-factor model (FF5), this study adds a low-priced stock premium factor LPP, and then builds a new four-factor and six-factor model respectively to examine the impact of low-price premium (LPP) on the pricing of China’s stock market. The research indicates that LPP is a reliable and effective pricing component in China’s A-share market, and it may be used as a systematic factor in the Chinese stock market’s asset pricing model. The LPP factor shows a strong negative association with stock excess returns. And the inclusion of the LPP in the FF3 and FF5 still passes the robustness test. Meanwhile, the six-factor model created by combining the LPP factor with the FF5 could explain Chinese stock market pricing better.

Corporate pledgeable asset ownership and stock price crash risk

We investigate how a firm’s corporate pledgeable asset ownership (CPAO) affects the risk of future stock price crashes. Using pledgeable asset ownership and crash risk data for a large sample of U.S. firms, we provide novel empirical evidence that a firm’s risk of a future stock price crash decreases with an increase in its pledgeable assets. Our main findings are valid after conducting various robustness tests. Further channel tests reveal that firms with pledgeable assets increase their collateral value, thereby enhancing corporate transparency and limiting bad news hoarding, resulting in lower stock price crash risk. Overall, the results show that having more pledgeable assets enables easier access to external financing, making it less likely that managers will hoard bad news.

When danger strikes: A linguistic tool for tracking America’s collective response to threats

In today's vast digital landscape, people are constantly exposed to threatening language, which attracts attention and activates the human brain's fear circuitry. However, to date, we have lacked the tools needed to identify threatening language and track its impact on human groups. To fill this gap, we developed a threat dictionary, a computationally derived linguistic tool that indexes threat levels from mass communication channels. We demonstrate this measure's convergent validity with objective threats in American history, including violent conflicts, natural disasters, and pathogen outbreaks such as the COVID-19 pandemic. Moreover, the dictionary offers predictive insights on US society's shifting cultural norms, political attitudes, and macroeconomic activities. Using data from newspapers that span over 100 years, we found change in threats to be associated with tighter social norms and collectivistic values, stronger approval of sitting US presidents, greater ethnocentrism and conservatism, lower stock prices, and less innovation. The data also showed that threatening language is contagious. In all, the language of threats is a powerful tool that can inform researchers and policy makers on the public's daily exposure to threatening language and make visible interesting societal patterns across American history.

Comparative Analysis of Support Vector Machine and EGARCH Modelling of Zenith Bank Plc. Stock Price on Economic Growth in Nigeria

In this 21st century, stock exchange has become a crucial and determining factor for the global economy, any variability in this market affects personal, corporate financial activities and the economic growth a country. A lot of analysis using different models were explored by several authors. However, this study set out to investigates the statistical behaviour of Zenith Bank PLC stock price using Support Vector Machine (SVM) and EGARCH Model on economic growth in Nigeria by adopting quantitative techniques using the causal-comparative research method. The findings from this research shows a coefficient of the Zenith bank Low stock price at (0.546945) and high stock price at (0.453562) which indicates that low stock price is insignificant because is less than α = 0.05, while high stock price of greater than α = 0.05 is significant to predict the Zenith bank stock price. Findings from the study has further revealed that SVM mode approach is more appropriate than EGARCH model and recommends that stockholders, financial analyst and researchers who are investing in stock market should adapt the SVM model approach to determine the volatility rate or level of stochastic in the financial time series data.
 Keywords: Stock Price, Support Vector Machine (SVM), EGARCH Model, Stock Exchange, Economic Growth

Analisis Pengaruh EPS dan ROA terhadap Harga Saham Perusahaan yang terdaftar di Bursa Efek Indonesia

This study aims to provide empirical evidence about the analysis of the effect of EPS and ROA on stock prices of companies listed on the IDX. The population of this study amounted to 32 companies. The sample of this research is 9 companies listed on the IDX for the period 2016-2020. The method of determining the sample using purposive sampling method. The data used is secondary data collected using the nonparticipant observation method by downloading data from the IBM SPSS 25 website. The results of the partial study for EPS show a significance value of 0.000 < α = 0.05, which means that EPS has a significant influence on stock prices, this proves that the greater the fixed assets covering current liabilities does not cause the stock price to increase. The results of the partial study for ROA show a significance value of 0.228 > α = 0.05, which means that ROA has no significant effect on stock prices, which proves that companies that have high or low Return On Assets (ROA) do not necessarily have high or low stock prices. However, the results of simultaneous research, for the value of EPS and ROA showed a significance value of 0.000 < α = 0.05, which means that EPS and ROA have a significant effect on stock prices. For future research, it is better to add independent variables so that it can be known whether there are other variables that affect firm value.

Do Retail Investors Have a Preference for Low-priced Stocks?

Do Retail Investors Have a Preference for Low-priced Stocks?

IMPLEMENTASI PAKET SHINY PADA PEMODELAN MULTISCALE AUTOREGRESSIVE UNTUK DATA HARGA SAHAM BBRI

Stocks are an investment that attract people because they can earn large profits by having claim rights to the company's income and assets so investors have to observe stock price movements in the future to achieve investment goals. One of the statistical methods for time series data modeling is ARIMA. However, modeling assumptions must be fulfilled to use that method so an alternative model is proposed, namely nonparametric regression model, which has no modeling assumptions requirement. In this study, the nonparametric regression multiscale autoregressive (MAR) with two different filter and decomposition level J are compared to choose the best model and forecast it. The data are closing stock price, high stock price and low stock price of BBRI’s stocks that divided into 2 parts, namely in sample data from March 19, 2020 to February 4, 2021 to form a model and out sample data from February 5, 2021 to March 23, 2021 used for evaluation of model performance based on MAPE values. The chosen best model for each stock price are the MAR model with wavelet haar filter and decomposition level 5 for the closing stock price which produces a MAPE value of 1.194%, the MAR model with wavelet haar filter and decomposition level 5 for the high stock price which produces a MAPE value of 1.283%, and the MAR model with a wavelet haar filter and decomposition level 5 for the low stock price which produces a MAPE value of 1.141%, indicating that the models have excellent forecasting capability. In this study, Graphical User Interface (GUI) using R software with the help of shiny package is also built, making data analyzing easier and generating more interactive display output.

An Empirical Analysis of the Impact of Exchange Rates on Stock Prices

With the deepening of economic openness, the domestic capital market is increasingly linked to the foreign exchange market, and changes in the exchange rate of a country's currency are often accompanied by significant fluctuations in the level of stock prices. This paper selects the panel data of the stock prices of different listed companies and the exchange rate of RMB to SDR from the first quarter of 2017 to the fourth quarter of 2020 to conduct regression analysis and robustness test. The results show that there is a significant negative relationship between exchange rate (under the direct markup method) and stock prices. Compared with stocks with lower stock prices and B shares, stocks with higher stock prices and A shares are more affected by exchange rate changes. Therefore, China should be cautious in the process of promoting capital account opening and deregulation of exchange rate, strengthen the management of fluctuations in the foreign exchange and stock markets to prevent stock market bubbles, and promote the reform of the B-share market to improve the efficiency of corporate financing and make China's financial market more complete.

Tax enforcement efforts and stock price crash risk: Evidence from China

AbstractWe propose that firms in regions with strong tax enforcement efforts have low stock price crash risk. Using a large sample of Chinese firms from 2003 to 2017, we find that tax enforcement efforts negatively affect future crash risk. This negative effect is stronger among state‐owned companies but weaker when information opacity is higher for firms. These results are robust to alternative measures, additional controls, and additional analyses. We also show that tax avoidance and accounting conservatism are two potential channels through which tax enforcement efforts affect crash risk. The findings contribute to the literature by elaborating that tax enforcement efforts not only alleviate tax‐avoiding activities but also can act as a governance mechanism in reducing crash risk in an emerging economy context.

Fear in the Stock Market: How COVID-19 Affects Preference for High- and Low-Priced Stocks

Does fear create a bias in favor of high-priced stocks? An analysis of the S&P 500 stock prices during the COVID-19 market crash showed that high-priced stocks outperformed low-priced ones (study 1). Experimental data further confirmed that fear induced by thoughts about the pandemic increased individuals’ preference for high-priced stocks when they were forced to choose one stock from a set of alternatives (study 2). Although fear generally decreased the preference for stocks when the market trended downward, this decrease was less for high-priced stocks than for low-priced ones (study 3). Reasons for and implications of this bias are discussed.

Looking Back and Looking Forward: (Re)Interpreting Consumer Insights in a Time of Transition

Looking Back and Looking Forward: (Re)Interpreting Consumer Insights in a Time of Transition

AN ANALYSIS OF ABNORMAL RETURNS ASSOCIATED WITH STOCK SPLIT

A stock split is when a company’s outstanding shares are divided into multiple shares by issuing more shares to current shareholders without eroding their stake’s value. The company typically takes these actions to increase liquidity and marketability, lower stock prices, attract new investors and so on. The purpose of this study is to examine the impact of stock splits on the stock returns during the study period. Companies listed on the Bombay Stock Exchange (BSE) and those included in the S&P BSE 500 Index are included in the stock split data. The study period covers 14 years, between 2008 and 2021. Market model event study methodology is being employed to analyze the average abnormal returns (AARs), cumulative abnormal returns (CARs) and cumulative AAR (CAARs) using an event window period consisting of 31 days ([Formula: see text]). The study is largely based on secondary information from the CMIE Prowess IQ Database and the official BSE website. The [Formula: see text]-test, mean and standard deviation were used to investigate the influence of stock split announcements on share prices and the performance of stock splits before and after the announcement. The study found that on ([Formula: see text]), ([Formula: see text]), ([Formula: see text]) and ([Formula: see text]) and on the day of the announcement ([Formula: see text]), the market reacted favorably with significant positive abnormal returns. On ([Formula: see text]) and ([Formula: see text]) days, however, there were significant negative abnormal returns. The null hypothesis is accepted as the CAR for the whole 31-day event window, which is 0.0221, with a [Formula: see text]-statistic of 1.692, which is insignificant.

Corruption risk and stock market effects: Evidence from the defence industry

Motivated by the finding that corruption is rampant in the defence sector globally, we examine the stock market effects of firm-level corruption risk disclosure in the defence industry. We find that the disclosure of corruption risk scores have information content. Our multivariate tests show that the market reacts negatively to firms that have low corruption risk. Our study supports the ‘greasing the wheels’ hypothesis which suggests that corruption is a cost of doing business. Further, companies with low corruption risk experience lower stock price volatility after the disclosure of corruption risk scores. Finally, we also find that the disclosure of lower corruption risk is associated with an increase in firm-level market liquidity.

Firm-specific investor sentiment, stock price synchronicity, and crash risk

ABSTRACT This article investigates the impact of firm-specific investor sentiment on stock price synchronicity and further examines the relationship between stock price synchronicity and crash risk. By analysing the dataset of the Chinese stock market, we find that higher firm-specific investor sentiment induces lower stock price synchronicity, which is inconsistent with the argument supported by a majority of previous studies that low price synchronicity represents high price informativeness. We also find a negative relationship between price synchronicity and future crash risk, supporting the view that in an irrational market, less return comovement is not associated with more firm-specific information but noise.

Top executives’ great famine experience and stock price crash risk

Using Chinese stock market data, we examine the impact of top executives’ great famine experience on stock price crash risk. We provide insights on the consequences of early-life disaster experience and the underlying mechanisms through which top executives’ famine experience affects crash risk. Evidence shows that, firms led by top executives who experienced the great famine in early-life have lower stock price crash risk. In addition, these firms have higher information transparency and lower information risk, which ultimately reduce the future stock price crash risk. And the effect varies with top executives’ growth stage, firm characteristics, and external monitoring.