Impact of Environmental,Social,and Governance(ESG)Factors on Stock Prices and Investment Performance

This study examines the relationship between Environmental,Social,and Governance(ESG)factors and stock prices as well as investment performance.ESG factors have become increasingly relevant in investment decisions as investors prioritize companies with sustainable practices.Using a sample of publicly-traded companies,this research analyzes the impact of ESG factors on stock prices and investment returns.The findings suggest that companies with strong ESG performance tend to have higher stock prices and better investment performance than those with weak ESG performance.The study also highlights the significance of the individual components of ESG,such as environmental policies and corporate governance practices,on stock prices and investment returns.Overall,this research provides valuable insights for investors seeking to incorporate ESG factors into their investment decision-making processes.

Effects of dietary tryptophan and stocking density on the performance,meat quality,and metabolic status of broilers

Background： Highly automated cage-rearing systems are becoming increasingly popular in China. However, a high stocking density can cause oxidative stress and decrease broiler performance. The tryptophan （TRP） derivative 5-hydroxytryptophan （5-HT） has been shown to preserve membrane fluidity in birds suffering from oxidative stress Therefore, this experiment was conducted to determine the effects of dietan/TRP supplementation on performance, breast meat quality and oxidative stress in broilers reared in cages with a high or low stocking density. Methods： Female Arbor Acres broilers （25-d-old, n = 144） were randomly allocated to 1 of 4 treatments. The birds were fed a diet based on corn, soybean meal, cottonseed meal and corn gluten meal containing either 0.18 or 0.27% TRP and were housed with stocking densities of 11 or 15.4 birds/m2 in a 2 x 2 factorial experiment. Broiler performance was evaluated from d 25 to 42. Eight birds from each treatment were slaughtered on d 42 and plasma and breast muscle samples were collected to measure biochemical indices. Results： A higher stocking density tended to be associated with reduced weight gain （P 〈 0.10）, and significantly increased plasma glutamic-pyruvic transaminase （GPT） activity （P 〈 0.001）. Increased dietary TRP significantly reduced the activities of lactic dehydrogenase and GPT while increasing total cholesterol in the plasma （P 〈 0.01）, reducing drip loss of breast muscle （P 〈 0.10） and improving feed efficiency （P 〈 0.10）. Conclusions： An increase in dietary TRP, ].S-fold higher than the standard supplementation level, can alleviate oxidative stress as well as improve welfare and feed efficiency in broilers reared in cages with a high stocking density.

The Relationship Between Intellectual Capital （IC） and Stock Market Performance： Empirical Evidence From Italy

Intellectual capital （IC） is an important source of value for companies. The competitive firm invests in new productive ideas through scientific and technological researches of the human factor and services. The traditional factors of＂old economy＂ based on physical assets have been replaced or at least reinforced, with the belief that the ＂new economy＂ takes its steps mainly through IC. The knowledge workers, at every organizational level, have the knowledge that allows the organization to be competitive and deal with the complexity of the environment by creating intellectual added value. In particular, the proposed analysis consists with an empirical way to show other financial indicators and market-to-book （MTB） value from the perspective of creating value for shareholders based on the dynamics of companies＇ performance, as value-added intellectual capital （VAICTM） is capable of expressing a direct relationship with the return on equity （ROE）. The traditional financial information cannot ensure the high efficiency of a stock market and the need for IC reporting to explain intangible asset contribution in company performance.

Research Progress on Effects of Stocking Density on Performance, Health and Welfare of Duck

Stocking density is an important factor for animal production performance.It appears particularly urgent and important to research systematically on stocking density for the dual restriction of environmental protection and animal welfare.This review dealt with the influence of stocking density on ducks'productivity and health through production performance,animal behavior and animal welfare,and analyzed the possible mechanism of high stocking density reducing production performance,resulting in abnormal behavior and stress,causing welfare and health problems.We consider that it might be associated with heat stress,more spatial competition(to gather the food,drinking water,sports area,etc.),as well as the quality deterioration of litter and house air caused by high stocking density.Finally,we put forward some suggestions on the study of stocking density's effects on ducks,and proposed the future work that need to be studied and problems that need to be solved imminently.

Performance of Islamic and conventional stock indices:empirical evidence from an emerging economy

Background:This study aims to investigate the extent to which the conditional volatilities of both Shari’ah compliant stock and conventional stock are related to those of interest rate and exchange rate in the emerging economy of Pakistan.Methods:We used KMI 30 and KSE 100 indices for Islamic and conventional stock for the period of July 2008 to November 2013.We employed Generalized Autoregressive Conditional Heteroskedastic in the mean(GARCH-M)model.This framework relaxes constancy assumption of classical linear regression(CLRM)model and allows exchange rate and interest rate volatility to evolve over time.The GARCHM framework also reveals results about risk-return trade-off in the context of both Islamic and conventional stock indices.Results:The findings show positive and statistically significant effect of interest rate volatility on KSE-100,whereas KMI-30 remains unaffected by the same.Exchange rate volatility is found to be significant for both conventional and Islamic indices.The relationship of risk coefficient(γ)and stocks returns,as expected,is positive and statistically significant for both KMI-30 and KSE-100.This result is consistent with the theory of risk-return trade-off.The results of parametric t-test show significant difference between returns of both indices.This implies that Shari’ah compliant stock index(KMI-30)of Pakistan underperforms its conventional counterpart.Conclusion:By using different performance measures(Sharp ratio,Jensen alpha,Treynor ratio),this study also investigates the hypothesis that Islamic stock index has inferior performance compared with unscreened conventional counterparts due to availability of a smaller investment universe,increased monitoring costs,and limited diversification.

Stock Performance of the Property Sector in Malaysia

Property investment in Malaysia is increasingly popular among local and foreign investors. The strong support by the government through the relaxation and lifting of certain restrictions and regulations on property ownerships, have attracted investments in the Malaysian property market. This research studies the factors affecting the performance of 36 property firms listed on the Main Board of Bursa Malaysia from 2003 to 2007. This research employed ordinary least squares （OLS） method to represent all the variables comprising stock performance, return on assets （ROA）, return on equity （ROE）, debt ratio （DR）, net profit margin （NPM）, effective tax rate （ETR）, earnings per share （EPS）, and price earning （PE） ratio. Results show that ROA, ROE, and EPS have strong significant relationships with the property stock performance. Although it is a small sample size, some relevant changes and modifications can be included in future studies to obtain better results.

Stock Market Measures and Market Performance

Sri Lanka is considered a highly fluctuating economy in the South Asian region.Understanding the behavior of economics is of utmost important to obtain the maximum benefit.Stock market can be considered as one of the key influencers to the economy whereas the behavior of the stock market would highly define the behaviors of the economic system.It is required to identify the stock market measures and their contribution for the market development to recognize the influence of stock market.The immense importance of its actions on the market performance leads to find more about the stock market’s measures.This research contains the evidence of the study conducted to identify the stock markets development and behavior measures such as all share price index,market capitalization,dividend yield,price to earnings ratio and shares traded equity.All of these variables were used to obtain a model to describe and predict performance of stock market over the time.The secondary data from the CSE(Colombo Stock Exchange)is studied which the trend analysis was conducted for each series of data and results were used for the analysis.A statistical analysis was carried out to identify the measures of stock market depicts that all the measures of the stock market have influences on the stock market development except for the dividend yield,a useful fact in the process of decision making in many aspects.

Deep Learning-Based Stock Price Prediction Using LSTM Model

The stock market is a vital component of the broader financial system,with its dynamics closely linked to economic growth.The challenges associated with analyzing and forecasting stock prices have persisted since the inception of financial markets.By examining historical transaction data,latent opportunities for profit can be uncovered,providing valuable insights for both institutional and individual investors to make more informed decisions.This study focuses on analyzing historical transaction data from four banks to predict closing price trends.Various models,including decision trees,random forests,and Long Short-Term Memory(LSTM)networks,are employed to forecast stock price movements.Historical stock transaction data serves as the input for training these models,which are then used to predict upward or downward stock price trends.The study’s empirical results indicate that these methods are effective to a degree in predicting stock price movements.The LSTM-based deep neural network model,in particular,demonstrates a commendable level of predictive accuracy.This conclusion is reached following a thorough evaluation of model performance,highlighting the potential of LSTM models in stock market forecasting.The findings offer significant implications for advancing financial forecasting approaches,thereby improving the decision-making capabilities of investors and financial institutions.

An Empirical Test of Relation Between Executive Stock Options and Firm Performance

Numerous firms adopted executive stock options plan for their executives. This study examines empirically the hypothesis that stock options help to improve the firml＇s operating performance. The empirical tests reveal a positive relation between the stock options and performance; also indicate that there is a positive relation between quantity of manager＇s stock options and firm＇s size.

Empirical Analysis of the Relationship Between Altman’s Z-Score and Stock Performance Based on Airline Companies Listed in the United States

This research looks at any relevance between Altman’s Z-score and the stock market performance of airline companies in the United States(US).Nearly a thousand pieces of data on various aspects of operation and financial status from 81 airline companies in the US are available.Additionally,stock return is used as an indicator of firm stock performance in this paper.In order to satisfy the purpose of determining the relationship between Z-score and stock performance as well as what may be inferred from high stock returns with regard to Z-score,two different regression processes are carried out.The first regression tests the relationship between Z-score and stock return,while the second regression examines whether there is a difference in Z-scores between well-performing airline companies and poorly performing ones using dummy variables.The results reveal that there is a significant positive correlation between the Z-scores of US airline companies and their stock performance;besides,high stock returns potentially imply relatively high Z-scores and vice versa.Therefore,one of the crucial steps that US airline companies must make is to strengthen their balance sheets in order to draw investors to make investments in their businesses.

Using Data Mining with Time Series Data in Short-Term Stocks Prediction: A Literature Review

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on shorttime stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

Analysis of Economic Performance in Mergers and Acquisition

Based on the methods of financial analysis, the direct earnings in mergers and acquisition M&A, profit or loss from stock price fluctuation, influence on the earning per stock(EPS) and revenue growth after M&A were analyzed in detail. And several quantitative models were established in relevant part accordingly. It can be useful to improve the present low efficiency in the M&A performance in Chinese capital market.

The Post-Merger Performance： Evidence From Italy

The objective of this paper is to investigate whether mergers create value for shareholders in both the short and long term. For this purpose, 120 announcements of mergers that were registered in Italy during the period 1994-2006 among listed companies were examined. The short-term analysis was conducted using the event study methodology in order to estimate the cumulative abnormal returns （CARs） in the time window around the announcement date （-10, ＋10）. In this work, the sample of 120 mergers was divided into two sub-samples： the first considers the mergers that were carried out in all sectors of the economy, and the second focuses only on bank mergers. From the results obtained it would appear that, while the sub-sample of all mergers registered a statistically significant value creation for the shareholders of both the bidder and target companies, values also confirmed by combined analysis, the second sub-sample registered negative values for bidder companies and positive values for target companies. Negative values also seem to be confirmed by the results of the combined analysis both at the date of announcement and throughout the entire period of observation. For the long-term analysis, the Buy and Hold Abnormal Returns （BHARs） methodology was used, with which it was possible to observe the returns for three years. In the 36 months following the merger, the portfolios showed a significant destruction of value

An Empirical Analysis of the Determinants of the Performance of the Global Private Equity Funds Markets

Over the last decade, the private equity （PE） industry, primarily venture capital and leveraged buyout investments, has matured massively. Consequently, public interest towards that particular asset class has increased rapidly. This study seeks to empirically assess the determinants of private equity funds＇ （PEFs） performance around the world. The study comprises a panel data of 103 publicly traded PEFs globally for the period of 2007-2013. Generalized least squares （GLS） technique is employed to regress the explanatory variables. The objective is accentuated on the major contributing factors that make a PEF successful. The analysis, in this paper, examines the effect of fund size, investment size, geographical focus, and industrial specialization on return. The empirical results provide evidence that： （1） Fund size and industrial specialization were observed to have an insignificant influence on the funds＇ returns in our panels; （2） Investment size is positively related to fund performance, indicating that larger deal sizes exhibited superior performance level; and （3） Geographical focus exhibited a negative association with fund performance, leading to the conclusion that limited geographical deployment of funds or absence of market diversification resulted in a fall in funds＇ returns. Consequently, to proxy for return of funds, stock prices of listed PEFs under LPEQ listings were employed.

企业ESG表现缓解了股价延迟吗?--基于我国A股上市公司的经验证据

以2008—2021年华证ESG评级上市公司为研究样本,探究企业ESG表现对股价延迟的影响及作用机制。结果表明:企业ESG表现能够有效缓解股价延迟,股票流动性水平、分析师关注和内部控制质量是企业ESG表现缓解股价延迟的重要作用路径。截面异质性分析发现:企业ESG表现对股价延迟的缓解作用在非国有企业、非政企关联企业以及审计质量较高组中更强。研究结论为提升我国资本市场信息效率提供了新的线索,为推动企业ESG实践提供了必要启示。

管理层股权激励对企业ESG表现的影响研究

如何激励管理层主动履行ESG责任是近年来学术研究的热点话题。基于2011—2022年中国沪深A股非金融类上市企业数据,对管理层股权激励与企业ESG表现之间的关系进行了实证分析。研究结果如下:管理层股权激励正向影响企业ESG表现;作用机制检验显示,管理层股权激励可以通过增加分析师关注和降低代理成本两方面促进企业ESG责任履行;异质性检验发现,在信息透明度越高、融资约束越低的企业中,管理层股权激励对企业ESG表现的正向影响程度越大。

企业ESG与资本市场表现——来自股票流动性的证据

在经济社会发展绿色化、低碳化态势下,ESG理念在资本市场中的地位日益凸显。文章基于2015—2021年我国A股上市公司数据,研究ESG表现对企业股票流动性的影响。研究发现,ESG表现显著提升了企业股票流动性,该效应在国有企业、大规模企业以及市场化程度较高的地区企业中更显著。机制分析表明,企业ESG有利于提升投资者情绪和信息透明度,进而促进股票流动性。进一步研究发现,企业良好ESG表现所带来的股票流动性显著提升了企业价值和企业创新。发掘企业ESG在金融市场的作用效果,为活跃资本市场提供新的经验证据。

企业提高ESG表现能够降低股价崩盘风险吗?

本文以2011—2020年沪深A股上市公司为对象,运用企业ESG表现对股价崩盘风险影响的处理效应模型(Treatment effect model)考察ESG表现对股价崩盘风险的影响。研究结果表明,企业提高ESG表现会抑制股价崩盘风险,符合“价值假说”。影响机制检验表明,媒体与分析师关注度正向调节ESG表现对股价崩盘风险的抑制作用,发挥“互补效应”;企业提高ESG表现通过缓解委托代理冲突抑制股价崩盘风险。进一步分析发现,ESG表现对股价崩盘风险的抑制作用仅在非国有企业和所处地区市场化水平较低的企业中成立,且抑制股价崩盘风险是ESG表现提升企业价值的重要路径。上述结论为推动上市公司履行ESG投资责任、完善风险管理机制和实现企业长期价值提供了经验参考。

海洋牧场建设效益评价研究进展与展望

建设海洋牧场是中国海洋渔业转型升级的关键策略,旨在通过人工干预的方式促进海洋渔业资源增殖和生态环境修复。人工鱼礁和增殖放流是海洋牧场建设的重要手段,人工鱼礁通过改善海域生态环境为鱼类提供适宜的栖息地,增殖放流则直接补充特定的海洋生物种群。文章综述了海洋牧场的发展历程、建设现状及效益评价方法,分析了人工鱼礁的水下物理状态、流场效应、规模效应及其渔业增殖效应,强调了科学布设的重要性;总结了增殖放流标记回捕、统计量分析和模型分析等效应评估方法。尽管中国在这些领域已经取得了显著进展,但仍面临人工鱼礁建设规模与生态效益的关系不明确、增殖放流效果评价的准确度有待提升以及缺乏成熟的定量评估模型等挑战。此外,还提出了未来的研究方向及建议,包括完善评价指标体系、强化技术创新、构建定量评估模型以及加强政策和管理指导等,以期推动海洋牧场科研和实践的发展,实现海洋渔业资源的可持续利用和海洋生态平衡。

饲养密度对笼养白羽肉鸡生长性能、羽毛评分、血清生化和免疫指标的影响

试验旨在探究不同饲养密度对笼养白羽肉鸡生长性能、羽毛评分、血清生化和免疫指标的影响。试验选取504只体重相近、健康状况良好的1日龄科宝白羽肉鸡母雏,随机分为3组,每组8个重复(笼)。7~14日龄3组饲养密度分别为16只/m^(2)、17只/m^(2)、18只/m^(2),15~39日龄3组饲养密度为13只/m^(2)、14只/m^(2)、15只/m^(2)。结果显示:(1)不同饲养密度对7~14日龄和15~28日龄肉鸡平均采食量和料重比产生显著影响(P<0.05),且15~28日龄时,14只/m^(2)组平均日增重显著高于13只/m^(2)组(P<0.05),13只/m^(2)组料重比显著高于15只/m^(2)组(P<0.05)。29~39日龄13只/m^(2)组和14只/m^(2)组平均日增重显著高于15只/m^(2)(P<0.05);(2)不同饲养密度对肉鸡14日龄主翼羽长度产生显著影响(P<0.05);(3)不同饲养密度对肉鸡14日龄和39日龄羽毛评分产生显著影响(P<0.05);(4)不同饲养密度对肉鸡血清中碱性磷酸酶(ALP)活力、三碘甲状腺原氨酸(T3)和甲状腺素(T4)的含量产生显著影响(P<0.05),17只/m^(2)组显著高于16只/m^(2)组和18只/m^(2)组(P<0.05),14只/m^(2)组显著高于13只/m^(2)组和15只/m^(2)组(P<0.05);(5)不同饲养密度对肉鸡14日龄和39日龄血清中白细胞介素-4(IL-4)、白细胞介素-6(IL-6)、白细胞介素-10(IL-10)和白细胞介素-1β(IL-1β)含量产生显著影响(P<0.05)。研究表明,笼养科宝白羽肉鸡7~14日龄适宜饲养密度为17只/m^(2),15~39日龄适宜饲养密度为14只/m^(2)。