Firm Stock Research Articles

Connecting the stocks of major energy firms in China to identify the systemic risk

This study mainly identifies systemic risks among energy firm stocks. By using a financial network approach on 198 major energy firms in China, the study finds that energy firms are accompanied with systemic risk due to extensive stock return and stock risk connections. Return connection is less severe and long-lasting than risk connection, but they are all buffeted to varying degrees by economic activities, such as stock market volatility, energy policy, and public event like COVID-19. Structural analysis further finds that heterogeneity and asymmetry exist in energy firms' bidirectional ability of price and risk information processing; relatively extreme asymmetry cases can be observed from risk connection ability. Multiple centrality indicators screen out some systemically important energy firms from exchanges of both return and risk information. All these characteristics could provide implications for policy making, corporate response, and portfolio construction.

How does family exit affect family business financialization?

This paper examines how the family exit of family businesses affects financialization, using family-owned firms in China's stock markets as samples. The study shows that family exit from executive positions to increase the proportion of non-family member executives has a facilitating effect on corporate financialization, and controlling family's reduced shareholding has a dampening effect on corporate financialization; providing equity incentives to executives helps to dampen the facilitating effect of family exit at the managerial level on corporate financialization compared to compensation incentives; and family exit reduces the degree of corporate financialization by increasing the level of corporate financing constraints.

Voluntary Delisting of Russian Companies at Different Stages of Corporate Life Cycle

Nowadays, the number of companies leaving the stock exchange is steadily increasing. Researchers and practitioners continue to actively discuss the reasons for voluntary delisting and explore the factors that influence the probability of it. However, the results of existing studies are heterogeneous and inconclusive, indicating the need for further research. Thispaper continues the line of research on the determinants of voluntary delisting by studying the delisting of Russian companies. Unlike previous studies, we identify and compare the factors that influence the decision to delist at different stages of the organization’s life cycle. We argue that delisting factors, although specific to each company, should remain similar for firms at the same stage of development. The company-related factors that we test include investment expenditures, profitability, stock volatility and book-to-market ratio. The study is based on a sample of 162 public Russian companies traded on the Moscow Exchange, of which 75 delisted between 2011 and 2019. The Bloomberg database was used to generate the sample of companies. Using the panel probit regression model, we found that firms with greater investment expenditures are less likely to delist at the Introduction and more likely at the Maturity and Decline stages. The results of our research also show that firm stock volatility had a positive effect on the delisting probability of Russian firms at all stages of theirlife cycle, except for the Introduction stage. Finally, we demonstrate that companies at the Introduction and Growth stages are more likely to leave the stock exchange if they have a greater book-to-market ratio. The results of our study can be used by financial analysts and academics to analyze the probability of delisting of public companies at different life cycle stages.

Market reactions to layoff announcements during crises: Examining impacts and conditioners

There is limited research on the effect of layoff announcements on stock returns during difficult economic conditions. We use event study and cross-sectional analysis to examine the impacts of layoff announcements on stock market returns during recent crises. Findings reveal that layoff announcements significantly negatively impact firm stock returns in both the short and medium terms, with firm leverage, price-to-book ratio, liquidity, return on assets, volatility, and past returns being significant conditioners. Results highlight the reaction of markets to layoff announcements and the importance of considering firm and market characteristics in forecasting the impact of layoff announcements on stock performance.

A new multilayer network for measuring interconnectedness among the energy firms

In this paper, we study the connectedness among 32 energy firms listed in the United States from January 2014 to November 2022. Specifically, we construct a new linear model based on Diebold and Yilmaz's (2012, 2014) approach and Granger causality to estimate the correlation between firms. In addition, we construct a multilayer network containing information on returns, volatilities and extreme risks and measure the network's topological properties from static and dynamic perspectives, respectively. Our empirical results suggest that multilayer networks can be of great use in understanding the relationships among energy firm stocks. Some interesting points include: the oil & gas sector dominates the energy sector; we should focus more on firms with large market capitalization, which are usually strong influence points in the network; the volatility layer is more connected than the return and risk layers; and the impact of the COVID-19 on energy firms is broader and more profound than that of Brexit, the US shale gas revolution, and the US-China trade war.

TAXI! Do Mutual Funds Pursue and Exploit Information on Local Companies?

AbstractWe use New York City (NYC) taxi data to identify trips between mutual fund offices and local firm headquarters. NYC funds overweight the stocks of local firms they visit via taxi, and firm visits are associated with superior investment performance. Firm visits are elevated prior to earnings announcements, and mutual fund trades that are associated with firm taxi visits predict earnings surprises. The results are generally stronger when fund and firm executives share educational connections. Additional tests support the conclusion that funds’ local bias and investment performance are driven by portfolio managers’ efforts and ability to actively gather material information.

Spillover effects of crash and jump events: evidence from Chinese market

PurposeThis paper aims to investigate the spillover effects of jump and crash events among Chinese nonfinancial firms.Design/methodology/approachThis 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).FindingsThe 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.Research limitations/implicationsPortfolio 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.Practical implicationsThis study has important implications for portfolio investment managers and policymakers.Originality/valueTo 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.

Is investing in the renewable energy stock market both financially and ESG efficient? A COVID-19 pandemic analysis

The aim of this paper is to provide a tool for finding investments in the stocks of energy firms that achieve both good financial and reasonable environmental, social, and governance (ESG) performance. Our methodology entails two steps and is based on diversification-consistent DEA models. The first step involves constructing a financially efficient frontier of investment portfolios by applying the model originally proposed by Branda (Omega 52:65–76. 10.1016/j.ejor.2007.04.014, 2015). In the second step, a new DEA model is proposed in order to find the ESG-efficient portfolios among the ones already identified in the first step and to rank them with respect to their ESG performance. This model is parameterised by a weighting system that allows us to assign different importance to the various ESG outputs. Additionally, the proposal allows an evaluation of both ESG and financial efficiency related to the financial energy market over two periods (the pre-COVID-19 and COVID-19 periods), considering renewable energy and non-renewable energy firms both jointly and separately. The results support the better financial performance of the renewable energy stock market compared with that of the non-renewable energy market.

Stock Price Reaction to Impromptu Managerial Soft Information in Conference Calls

We examine managerial behavior during conference calls vis-à-vis the informational impact on firm stock prices. Implementing an unsupervised machine learning algorithm, we document statistically and economically meaningful relationships between impromptu soft information divulged during calls and stock prices. Managers who choose to divulge more impromptu soft information in the Q&A session experience improved liquidity and less volatility, accompanied with lower abnormal returns. Conditioned on earnings surprise, large positive-surprise impromptu soft information results in larger returns and positive drift, indicating that investors do not completely trust the positive signal initially, with confidence growing over time evidenced as prices adjust to equilibrium.

Supply chain network structures and firm financial performance: the moderating role of international relations

PurposeThis paper examines the relationship between supply chain network structures and firm financial performance and the moderating role of international relations. In this study, which is grounded in social capital theory and applies the perspective of systemic risk, the authors theorize the effects of supply chain network structures on firm performance.Design/methodology/approachThe authors extracted data from two Chinese databases and constructed a supply chain network of the firms concerned based on nearly 4,300 supply chain relations between 2009 and 2018. The authors adopted the fixed effects model to investigate the relationship between supply chain network structures and firm financial performance.FindingsThe econometrics results indicate that network structures, including the degree, centrality, clustering coefficients and structural holes, are significantly related to firm financial performance. A significant and negative relationship exists between international relations and firm financial performance. The authors also find that international relations strongly weaken the relationship between supply chain network structures and firm financial performance.Originality/valueThis study, which collects secondary data from developing countries (e.g. China) and explores the impacts of supply chain network structures on firm stock performance, contributes to the existing literature and provides practical implications.

Institutional and individual investors' short‐term reactions to the COVID‐19 crisis in China

AbstractThis study examines how the severity of the local COVID‐19 crisis affected the investment divergence between institutional and individual investors in China. The COVID‐19 crisis significantly increased both environmental uncertainty and fear sentiment. We predict that individual investors, who are at an information disadvantage and rely more on heuristics, are more likely than institutional investors to decrease their investments in stocks of firms headquartered in provinces with more severe COVID‐19 crisis. We find that the number of newly confirmed local COVID‐19 cases is positively associated with the investment divergence between institutional and individual investors. Further analysis shows that the investment divergence is much lower for firms that have higher information disclosure quality, are followed by more analysts and engage Big 4 auditors. We also find that subsequent price reversals are faster for stocks with higher net investments by institutional investors and slower for stocks with higher net investments by individual investors. Lastly, we find that institutional investors increase their investments in undervalued stocks of firms located in provinces with more severe COVID‐19 crisis and firms less affected by the pandemic, whereas individual investors decrease such investments. The results suggest that institutional investors are more sophisticated in identifying undervalued stocks and analysing the impact of the information about the pandemic prevention policies on firms' operations. Our main results hold after a battery of robustness tests.

Sovereign wealth funds in the post-pandemic era

Sovereign wealth funds (SWFs) have over $11.5 trillion in assets under management as of February 2023. Most of these 176 funds are sponsored by non-Western countries and their growth has made SWFs important international investors, particularly in private equity funding. We first define SWFs, then discuss their evolution into today’s categories of stabilization, savings, and development/strategic funds. We discuss the documented importance of SWF funding sources – oil sales revenues versus excess reserves from export earnings – and summarize the empirical literature studying how SWFs allocate funds geographically and across asset classes. Next, we summarize empirical evidence on the impact of SWF stock investments on target firm financial and operating performance and discuss the evidence showing that the announcement of SWF investment causes target firm stock prices to rise in the short term, but the positive impact is significantly less than the positive return following large stock purchases by private investors, and the longer-term effect of SWF investment on target firms is generally negative. SWFs’ recent focus on promoting ESG policies of investee companies is assessed and briefly compared to the effectiveness of other institutional investors’ ESG efforts.

Follow the Money

Abstract I study, both empirically and theoretically, the economic and financial consequences of corporate lobbying. Firms lobby politicians to increase their share of government contracts, but political competition creates firm-level risk, inflating their cost of capital and reducing their incentive to invest in research and development (R&D). I document an annual 6–8% return premium for stocks of high-lobbying firms, which compensates investors for political risk. An estimated model in which firms can lobby and innovate and investors are risk averse replicates key features of corporate lobbying in the U.S., including the well-established paradox that lobbying contributions are small relative to the policies at stake. The model predicts that if investors ceased seeking compensation for political risk, R&D investment would increase by 6% and the innovation rate by 0.4% points. The risk-premium costs of lobbying are quantitatively and economically important even if the resources “wasted” on lobbying are objectively small.

CEO discretionary power, unconstrained stock ownership, and stock trading: Theory and evidence

This paper examines CEOs' holding and trading of unconstrained firm stock they own, i.e., vested and sellable firm shares. I first develop a theoretical model of why CEOs hold sellable shares in their own firm when doing so is riskier than holding a more diversified portfolio. In this model, greater stock ownership allows the CEO to exercise discretionary power more easily and extract rents from the company. My model predicts that CEOs desire to hold more firm stock and therefore are less likely to sell stock when they have greater discretionary power. This empirical prediction is supported by tests that measure discretionary power based on the principal component analysis of three proxies. Using stock trading data in S&P 1500 firms, I find that discretionary power is negatively (positively) associated with the CEO's stock sale (purchase). The results are weaker in industries where rent extraction is more difficult. Further, results hold for both founder and non-founder CEOs, and are robust to a battery of sensitivity tests. Overall, this study provides new insights concerning CEOs' decisions to own their companies' stock.

THE IMPACT OF TWITTER ON FIRM VALUE

ABSTRACT Twitter is a leading firm in social media information with important implications across various spheres ranging from politics to the capital markets. This study examines the impact of Twitter on firm value. We analyze the returns on publicly traded stocks of firms that start to use Twitter. We find that the Return on Twitter (ROT) initiation events are positive and statistically significant for latter initiations. We find evidence that the positive impact of using Twitter accrued to companies that adopted Twitter use more recently indicating that the value of using Twitter became more known to investors as Twitter developed. There are differing impacts on firm value from initiating a Twitter account for companies in different industries. Furthermore, we show that abnormal returns are far more significantly negative for smaller firms than larger firms when sorted by their size. Keywords Twitter, Event Study, Cumulative Abnormal Return, Firm Value

Initial Evidence on the Market Impact of the iXBRL Adoption

SYNOPSISIn June 2018, the SEC adopted Inline eXtensible Business Reporting Language (iXBRL), which embeds XBRL data into HTML-formatted annual reports to improve the accessibility and usefulness of the information disclosures to investors. This study assesses the effectiveness of iXBRL by examining its impact on informational efficiency and information asymmetry. Using a sample that includes iXBRL voluntary adopters before 2019, we find that iXBRL adoption lowers stock return drift and facilitates information being impounded into firm stock prices following the filing of annual reports. We also find that unlike XBRL, iXBRL reduces information asymmetry in the long run. These findings are consistent with the SEC’s intention of adopting iXBRL to combine human-readable and machine-readable information. Our study provides initial evidence on the effectiveness of iXBRL in communicating information to the external users of annual reports.

An effective deep learning model with reduced error rate for accurate forecast of stock market direction

Prediction using ML models is not well adapted in many portions of business decision-making due to a lack of clarity and flexibility. In order to provide a positive risk-adjusted price for stocks by evaluating historical transaction data and retaining more accuracy with a reduced error rate, the suggested framework aims to use deep learning method. The deep learning methodology, which can handle time-series data, is applied in this work. The measurements of MSE and RMSE error rates, which indicate how far the measured values are from the regression line, are used to produce the findings. The dispersion of these residuals is evaluated by RMSE. It demonstrates how densely the data is clustered around the line of best fit. In this work, a novel deep learning approach is compared to deep LSTM, GA, and Harris Hawk optimization. Outcomes were obtained and exhibited for the various firm stocks dataset as part of this investigation, which amply demonstrates the usefulness of the proposed strategy with a lower error rate.

Institutional trading and information processing: Evidence from complicated firms and easy‐to‐analyze firms

AbstractIn this article, I examine institutional trading within two groups of firms with different demands on investor information processing: conglomerate firms and stand‐alone firms. On average, institutional trading in conglomerate firm stocks yields significantly lower returns than institutional trading in stand‐alone firm stocks. Inferior returns following institutional trading in conglomerate firm stocks persist across small and large firms. Moreover, financial institutions with a low concentration of conglomerate firms in their portfolios are more profitable in their trading. This study provides evidence that skilled institutional investors intentionally focus their information‐processing efforts on easy‐to‐analyze firms.

Directors' and Officers' liability insurance and cross section of expected stock returns: A mispricing explanation

To add to the literature on asset-pricing anomaly detection, this study tests the cross-sectional relationship between directors' and officers' liability insurance coverage (D&O insurance) and expected stock returns. A unique, near-complete sample of Taiwanese company stocks is used to document the D&O insurance anomaly that reveals stocks with high-D&O insurance significantly outperforming those with low-D&O insurance by 7% to 13% annually, after accounting for well-known risk factors. This high-minus-low D&O insurance return premium is robust to alternative weighting approaches and to the Fama–MacBeth regressions, which simultaneously control for various standard returns predictors and corporate governance measures. Furthermore, a D&O insurance-mimicking factor is used to document that the characteristic of D&O insurance can subsume the covariance of the D&O insurance-mimicking factor to predict returns, thus rejecting the rational risk explanation of the D&O insurance anomaly in favor of the behavioral mispricing explanation. Further evidence indicates that stocks of firms with high- (low-) D&O insurance tend to be undervalued (overvalued) and the high-minus-low D&O insurance return premium is concentrated among those undervalued stocks and is stronger in the presence of high limits-to-arbitrage, which are interpreted as consistent with the behavioral mispricing explanation.

The market value of SMEs: a comparative study between private and listed firms in alternative stock markets

This study aims to compare the market value of private firms and publicly listed small and medium-sized firms (SMEs) in alternative stock markets through a private discount approach with estimates of value based on discounted cash flow projections and along with a comparable multiples approach. The valuation methodology applied in this study yielded a final sample that included 232 observations between public and private companies in the Spanish market. To calculate the discount, we apply the different approaches of discounted cash flow and multiples, such as valuation, earnings, book value, and revenue. Our results conclude there is no private discount, instead, the outcomes of this article suggest a premium over public firms for some ratios. The negative private company discounts mean a premium and, on the other hand, some multiples suggest a discount according to the method of valuation. This paper proves private discounts resulted does not have any comparable value within the same country although all firms in Spain use the same currency. We value the discounted cash flows of our forecasts using a discount rate based on the Capital Asset Pricing Model (CAPM), so our study can also be viewed as a test sensitivity of CAPM-based approaches to equity risk premium, terminal value, and growth rate. Furthermore, we compare historical transaction multiples of privately held companies with transaction multiples of similar publicly held firms.