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This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

This study examined Indian institutional investors' holding data to understand their investment strategy (Portfolio Concentration/Diversification) and explored whether their skills were associated with their portfolio strategy and performance. The study introduced a new proxy to identify skilled investors by forecasting abnormal returns. Moreover, the study also highlighted where skilled Indian investors put their money for long-term investment.

This study measures portfolio concentration based on the number of holdings, the Hirschman–Herfindahl index (HHI) and benchmarks adjusted industry concentration. The study introduced a new proxy to identify skilled investors. We measured Investors' performance with the help of Carhart's four factors model and examined the relationship between variables through various regression models.

The study concluded a negative relationship between portfolio concentration and performance. However, skilled Indian investors get rewards from portfolio concentration decisions. It was found that skilled investors with few stocks and an industry concentration in their portfolio show a positive association between concentration and fund performance. Additionally, this study found Indian investors showing their faith in the financial sector for long-term investment.

This study examined Indian institutional investors' portfolio concentration strategy and introduced a new proxy to measure investors' skills.

We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that the past loser-and-illiquid stock portfolios tend to outperform the past winner-and-liquid stock portfolios in the 1–12 months holding period. The excess return is significantly associated with the market-wide liquidity factor even when we control the three Fama-French and momentum factors. Cross-sectionally, the liquidity beta significantly affects the excess return even with control of other risk betas and other traditional liquidity proxies.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

This study examines the effects of corporate governance on market returns during the first four waves of the COVID-19 crisis.

Event study and linear regression methods were applied on a sample of 293 US firms.

The results show that differences in abnormal returns are more significant during the second wave of COVID-19 and the two following waves. Moreover, estimations show that good corporate governance alleviated the effect of COVID-19 during the second wave and the two following waves. However, corporate governance did not affect abnormal returns during the first wave. Furthermore, evidence highlights that the effect of corporate governance is more observed in the industries most affected by COVID-19 than in the least affected industries.

Many studies have attempted to investigate the effect of corporate governance on stock returns during the first wave of the pandemic. However, to the authors' knowledge, this is the first study that focuses on different waves that occurred during 2020 and 2021.

The purpose of this paper is to investigate the effect of equity market misvaluation on manager behavior. Using a sample of 535 French-listed over 2000–2018, the authors analyze whether corporate investment decision is sensitive to equity market overvaluation.

The study adopts market-to-book (M/B) decomposition developed by Rhodes-Kropf and Viswanathan (2004, RKV) that proxies for market misvaluation at the firm and industry levels. The authors conducted a long-term performance analysis via a portfolio sorting procedure and a Carhart (1997) four-factor pricing model. The authors tested the relationship between equity misvaluation, corporate investment decisions and equity issuance. The authors ran several robustness tests.

The empirical results show that equity market misvaluation affects corporate investment positively as the stock price deviates further away from its fundamental. Based on market timing theory, the authors find that corporate investment occurs in periods of high valuation motivated by equity issuance to benefit from the low cost of capital. This effect is more prominent for financially constrained firms. Consistent with the catering channel, the authors find that the misvaluation-investment nexus is more pronounced in firms with short-horizon investors. By examining the stocks’ long-term performance of misvalued firms, via a sorting portfolio procedure, the authors find that undervalued firms outperform and generate higher abnormal returns (Jensen’s alpha) than overvalued firms, suggesting that mispricing-driven investment appear to be short-lived and lead to lower return in the long term.

Corporate decision-makers and governance structures should pay attention to the rationality of the corporate investment decision in the context of equity market misvaluation. Managers who focus on maximizing the stock market value in the short-run at the expense of its long-term performance must give preference to value-creating investment, not driven by an external mechanism such as equity market mispricing. More generally, investors and portfolio managers must take into account the market mispricing process in decision-making. Nonetheless, from the portfolio sorting perspective, decision-makers must act in terms of high governance quality to mitigate suboptimal investment due to stock market mispricing (Jensen, 2005). Finally, equity market overvaluation, leading managers to invest via equity financing in particular, should be a signal to attract investors’ attention to seize the window of opportunity and embark on a short-term portfolio strategy. Such a strategy promises high returns in the short term.

This paper investigates jointly two theoretical channels: equity market timing and catering. The authors propose for the analysis three components of the M/B decomposition to dissociate market misvaluation at the firm and industry level from the fundamental component of market value (growth). This procedure provides a better understanding of the role of firm and industry misvaluation in explaining corporate investments. The authors provide evidence of the equity market misvaluation via a portfolio sorting procedure and a Carhart (1997) four-factor pricing model. The authors examine the effect of misvaluation on both the investment and the financing decisions.

This study aims to examine the impact of the beginning of the Russia–Ukraine war and the Wagner Group’s attempted military coup against Putin’s regime on the European defense sector, consisting of weapons manufacturers.

The authors use the event study methodology to quantify the impact. That is, the authors assume that markets are efficient, and abnormal stock returns around the event dates capture the magnitudes of the impacts of the two events studied on European defense sector companies. The authors use the capital asset pricing model and two different multifactor models to estimate expected stock returns, which serve as the benchmark necessary to obtain abnormal returns.

The start of the war on February 24, 2022, when the Russian forces invaded Ukraine, was followed by high positive abnormal returns of up to 12% in the next few days. The results are particularly strong if multiple factors are used to control for the risk of the defense stocks. Conversely, the authors find a negative impact of the rebellion initiated by the mercenary Wagner Group’s chief, Yevgeny Prigozhin, on June 23, 2023, on the abnormal returns of defense industry stocks on the first trading day after the event.

To the best of the authors’ knowledge, this is the first study of the impact of the Russia–Ukraine war on the defense sector. Furthermore, this is the first study to measure the financial implications of the military coup initiated by the Wagner Group. The findings contribute to a rapidly growing literature on the financial implications of military conflicts around the world.

This study aims to establish the effect of environmental, social and governance (ESG) practices on Australian energy and utility investment performance.

Conventional and ESG-rated portfolios are constructed using monthly returns and ESG scores of S&P/ASX 300 listed energy and utility firms from 2014 to 2022. Portfolio performance is estimated using a four-factor regression model, controlling for any economic shocks associated with the COVID-19 pandemic.

The findings show that the lower the ESG score associated with the overall ESG and environmental portfolios, the greater the performance compared to the market (but not the conventional and other ESG portfolios). High ESG scores do not appear to influence the performance of the energy and utility portfolios, which contrasts expectations that the uptake of ESG should deliver superior risk-return outcomes for investors. The findings also indicate that a contrarian investment approach may be a reasonable performance indicator for high-rated ESG portfolios. ESG practices did not impact portfolio performance during the COVID-19 pandemic.

This research has contributed to the literature by offering ESG investment insights for policymakers, regulators, fund managers and investors. Consistent with the agency perspective on ESG practices and efficient market hypothesis, the evidence implies that, regardless of ESG scores (either high or low), investors should consider investing passively in diversified energy and utility portfolios or low-cost index fund equivalents.

Investors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.

On 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.

Our empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.

Individuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.

The study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).