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Weak regional commercial and productive integration and monetary dependence on the economic poles are evidence of the consolidation of Latin America's peripheral position in the world economy. This research analyzes different monetary initiatives launched individually or collectively by countries in the region to alleviate this position, such as the petro, the SUCRE, or El Salvador's bet on the legal acceptance of bitcoin as a payment instrument. After identifying some of their limitations, we propose some basis for monetary coordination with which to advance in the dynamization of productivity and trade complementarity of the countries of the region.

The reform and opening-up of capital market is valued for promoting sustainable development, while its impact presented as the form of deregulation of short-selling on the green innovation of enterprises in developing countries remains unclear. The purpose of this study is to outline the significance of gradual reform of financial markets in developing countries for low-carbon transformation and provide implications for achieving carbon peaking and carbon neutrality goals.

Based on the green subdivided patent data and financial data of China’s A-share listed companies, this paper takes the implementation of securities margin trading program as a quasi-natural experiment and applies the difference-in-differences (DID) model to examine the impact of deregulation of short-selling constraints on the enterprises’ green transformation.

The findings reveal that the initiating securities margin trading program significantly enhances the green innovation performance of enterprises. These findings are valid after performing a series of robustness tests such as the parallel trend test, the placebo test and the methods to exclude other policy interference. Mechanism analyses demonstrate a two-faceted effect of the securities margin trading program on the green innovation of enterprises, in which short-selling policy increases the pressure on capital market deregulation and meanwhile induces the environmental protection investment. The heterogeneity results demonstrate that the impulsive effect imposed by securities margin trading program is more significant in experimental group samples with characteristics of lower financing constraints, belonging to heavy polluting industries and possessing better environmental supervision capability.

First, previous studies have focused on the impact of financial policies implemented by banking institutions on the green innovation of enterprises, but few literatures have explored the validity of relaxing short-selling restrictions or opening the capital market in the field of enterprise’s green transformation in developing country. From the view of securities market reform, this paper broadens the incentive and supervision effects of the relaxation of short-selling control on enterprise’s green innovation performance after the implementation of securities financing and securities lending policy in China’s capital market. Second, previous studies have explored the impact of command-and-control environmental regulations, as well as market-incentivized environmental regulations such as green finance, low-carbon pilots and environmental tax reform, on the green transition of enterprises. Recently the role of the securities market in the green development of enterprises has received more attention in academia. The pilot of margin financing and securities lending is essentially a market-incentivized regulatory tool, but there is few in-depth research on how it affects the green innovation of enterprises. This paper enriches the research on whether the market incentive financial regulation policy can contribute to the green transformation of enterprises under the Porter hypothesis. Third, some previous studies used the ordinary panel regression model to explore the impact of financial policy on enterprise’s innovation performance. However, due to the potential endogenous problems of the estimated model, it might get biased conclusions. Therefore, based on the method of quasi-natural experiment, this paper selects the margin trading pilot policy as an exogenous shock to solve the endogenous or reverse causality problem in traditional measurement model and applies the DID model to study the relationship between core indicator variables.

In this chapter we develop a new approach, based on the identification of strategy classes, to study how firms face multiple demands. The procedure that we propose (called Relational Class Analysis) stems from an analysis of the similarity of associative patterns across multiple observable outcomes, which reflect the underlying set of choices firms make to similarly address demands. Empirically, the study of 18 financial and extra-financial performance outcomes for 3,655 firms shows the existence of three main strategic classes. Drawing on our analysis, we redefine strategy as the set of committed decisions undertaken to resolve trade-offs between multiple concurrent objectives and discuss the implications of our approach for eight core questions for strategy and organizational theory.

Sustainability has become a priority for companies due to pressure from multiple stakeholders. In an overly competitive market, shareholders push for economic results, allowing lean manufacturing to establish itself as dominant paradigm in manufacturing. However, concerns grow regarding how lean implementation can allow companies to achieve sustainable development goals, or, if the resources required for a successful lean implementation can result in a detriment of environmental and social performance. This paper intends to help close the knowledge gap regarding the effects of lean manufacturing on sustainable performance from a triple bottom line perspective, and how operational, environmental and social outcomes interact between themselves.

Two models for the interaction between lean and sustainability were proposed. The first is called the “sand-cone” model, which poses that performance improvements derived from lean are cumulative on each one of the sustainability dimensions. The second is called the “trade-offs” approach. In this case, the resources required to improve one dimension of sustainability clash with those required by the others. Data were gathered from a sample of 133 Colombian metalworking companies and processed using structural equations models.

The results support the cumulative “sand-cone”, which follows a sequence of operational-environmental-social improvement in the presence of lean. For the “trade-offs” model, partial evidence suggests that they can occur in detriment of social performance.

The “sand-cone” and “trade-offs” are empirically tested for the first time in the context of sustainability, providing further knowledge into its interaction with lean manufacturing. The models’ results contribute to practitioners by providing a tested path for companies to improve their performance in a cumulative sequence that will provide better long-term results.

This study aims to use a qualitative approach to explore and clarify the mechanism by which heuristic-driven biases influence the decisions and performance of individual investors actively trading on the Pakistan Stock Exchange (PSX). It also aims to identify how to overcome the negative effect of heuristic-driven biases, so that finance practitioners can avoid the expensive errors which they cause.

This study adopts an interpretative approach. Qualitative data was collected in semistructured interviews, in which the target population was asked open-ended questions. The sample consists of five brokers and/or investment strategists/advisors who maintain investors’ accounts or provide investment advice to investors on the PSX, who were selected on a convenient basis. The researchers analyzed the interview data thematically.

The results confirm that investors often use heuristics, causing several heuristic-driven biases when trading on the stock market, specifically, reliance on recognition-based heuristics, namely, alphabetical ordering of firm names, name memorability and name fluency, as well as cognitive heuristics, such as herding behavior, disposition effect, anchoring and adjustment, repetitiveness, overconfidence and availability biases. These lead investors to make suboptimal decisions relating to their investment management activities. Due to these heuristic-driven biases, investors trade excessively in the stock market, and their investment performance is adversely affected.

This study provides a practical framework to explore and clarify the mechanism by which heuristic-driven biases influence investment management activities. To the best of authors’ knowledge, the current study is the first to focus on links between heuristic-driven biases, investment decisions and performance using a qualitative approach. Furthermore, with the help of a qualitative approach, the investigators also highlight some factors causing an increased use of heuristic variables by investors and discuss practical approaches to overcoming the negative effects of heuristics factors, so that finance practitioners can avoid repeating the expensive errors which they cause, which also differentiates this study from others.

In this paper, the authors take the central environmental protection inspection (CEPI) as an exogenous shock to study the reaction of the stock market in China. Using the event study method, the authors check how the first round of the first batch of CEPI supervision affects the cumulative abnormal return (CAR) of the listed firms on the Shenzhen or Shanghai stock exchange. This paper aims to discuss the aforementioned objective.

In this paper, the authors take the first round of the first batch of CEPI supervision as a clean exogenous shock to study its effects on the capital market. The authors collect daily trading data from the China stock market and accounting research (CSMAR) database, with the sample containing 1,950 Chinese firms listed on either the Shenzhen or Shanghai stock exchanges. And detailed information on CEPI supervision is obtained from the official website of the Ministry of Ecology and Environment of the People's Republic of China. The event study method is adopted to analyze the reaction of the stock market under CEPI supervision. Specifically, the authors constructed the cumulative abnormal return of each firm around the event day of CEPI. To capture the deterrent effects of CEPI supervision, the authors examine the situation of polluting and non-polluting firms in the supervised provinces, adjacent provinces and provinces that are not supervised or close to the supervised provinces, respectively.

This paper throws light on the following: (1) the polluting firms in the supervised provinces were negatively impacted by CEPI within 20 trading days of the event day, and its effects spread to the polluting firms in the neighboring provinces; (2) CEPI had a favorable impact on the non-polluting businesses in the provinces that are neither supervised nor close to the supervised provinces. The authors contend that it is because the investment is being forced out of the polluting sector and into the non-polluting sector, which is more pronounced in the provinces not directly or indirectly targeted by CEPI; (3) by comparison, the “looking back monitoring of the first round” has had no discernible detrimental impact on the firms' CAR, indicating an important role of psychology anticipation of investors in the stock market performance; (4) although not physically located in the supervised provinces, the downstream enterprises of the polluting firms suffer significantly from CEPI shock; (5) the effectiveness of CEPI supervision in the supervised provinces depends on the level of local environmental regulation and the ownership structure of the company. Private firms in the provinces with stronger environmental regulations suffer more from the CEPI shock; (6) the multivariate analysis shows that while enterprises with high ROE and financial leverage may be at risk of CAR loss, older, larger firms are less likely to experience CEPI shock; (7) the study of persistent effect reveals that the strike of CEPI supervision can last for at least 10 months after the event day and deterrent effect can be spread within the whole polluting industry.

In this paper, the authors only concentrate on the market reaction within 20 trading days after the event day. An analysis of long-term effects should be valuable to get a deeper knowledge of the capital market reaction to the CEPI policy. In addition, the paper only focuses on the first round of the first batch of CEPI. Since CEPI has been built as a constant regulation of local environmental performance, further study may need to track both the reaction of listed firms and investment behavior in the capital market.

Policy implications of the paper are as follows: First, for the policymakers, it is important to construct a constant environmental regulation system instead of a campaign movement. Second, for investors, as environmental issues are receiving increasing attention from both the government and the public, investment decisions should take into account firms' environmental performance, which can help reduce the risk from environmental regulations. Third, the firms in the polluting industry should take more action to reduce pollutant releases and adopt green technology, which is essential for sustainable development under environmental protection.

This paper contributes to the existing literature in the following aspects. First, the authors provide new evidence on the effects of environmental regulations as a shock to the stock market, which has been wildly concentrated in the literature about environmental policies evaluation and capital market reaction. Second, the authors supplement the literature on green finance and sustainability transformation, which has got increasing attention in recent years. Theoretically, by guiding investment and affecting the stock market performance, environmental regulations are considered to be an efficient way to stimulate polluting firms to transform into green development. The results of the paper support this intuition by showing that the CAR of the non-polluting firms in non-supervised provinces in fact benefit from the CEPI supervision.

This study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.

Employing a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.

The study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.

The study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.

Findings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.

The research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

This study aimed to investigate the role of the country's institutional quality on the environmental, social and governance (ESG) performance of its companies.

Over a four-year period (2016–2019), the study examined the ESG performance of 412 organizations situated in 19 countries. ESG performance was the dependent variable, and the independent variables were rule of law, economic freedom, education index and international trade freedom. These factors described the institutional quality of countries in the authors’ study.

The findings reveal that institutional quality has a major impact on ESG performance. Companies engage in more ESG practices when they operate in countries with greater economic freedom and international trade freedom. The authors corroborated the core assumption of institutional theory (IT), which argues that organizational behavior is determined by the country's institutional setting.

The findings, like all research, should be interpreted with caution. The authors’ research focused solely on large energy corporations. As a result, the conclusions cannot be applied to small companies or other industries. ESG performance can also be measured using different datasets.

If managers want their companies to perform better in terms of ESG, the authors recommend that they form a CSR committee and sign the Global Compact. This study may be valuable to international policymakers because they can underline that greater economic freedom, better education and greater international trade freedom all promote higher ESG performance.

To the best of the authors' knowledge, nearly all of research explores the relationship between ESG and financial performance. As a result, this study built on past research by investigating how national aspects affect corporate ESG performance.

For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction problem based on the CSI300 nearby futures by using high-frequency data recorded each minute from the launch date of the futures to roughly two years after constituent stocks of the futures all becoming shortable, a time period witnessing significantly increased trading activities.

In order to answer questions as follows, this study adopts the neural network for modeling the irregular trading volume series of the CSI300 nearby futures: are the research able to utilize the lags of the trading volume series to make predictions; if this is the case, how far can the predictions go and how accurate can the predictions be; can this research use predictive information from trading volumes of the CSI300 spot and first distant futures for improving prediction accuracy and what is the corresponding magnitude; how sophisticated is the model; and how robust are its predictions?

The results of this study show that a simple neural network model could be constructed with 10 hidden neurons to robustly predict the trading volume of the CSI300 nearby futures using 1–20 min ahead trading volume data. The model leads to the root mean square error of about 955 contracts. Utilizing additional predictive information from trading volumes of the CSI300 spot and first distant futures could further benefit prediction accuracy and the magnitude of improvements is about 1–2%. This benefit is particularly significant when the trading volume of the CSI300 nearby futures is close to be zero. Another benefit, at the cost of the model becoming slightly more sophisticated with more hidden neurons, is that predictions could be generated through 1–30 min ahead trading volume data.

The results of this study could be used for multiple purposes, including designing financial index trading systems and platforms, monitoring systematic financial risks and building financial index price forecasting.

Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined the information transparency effect in supply chain management. This study aims to fill this gap by exploring the significant role of information transparency on supply chain financing and its mechanism, taking trade credit as the starting point.

From the data set comprising 3,880 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges from 2011 to 2020, we obtain the basic picture of information transparency and trade credit. Panel fixed effects regression is used to test the hypotheses concerning the antecedents to trade credit.

The empirical results show that: first, information transparency can significantly support corporate access to trade credit and is found to facilitate financing by mitigating perceived risk. Second, among companies with higher levels of financing constraints, weaker market power and more concentration of suppliers, information transparency promotes trade credit more markedly. Third, the outbreak of COVID-19 causes a substantial increase in uncertainty and risk in external circumstances and then the effect of information transparency is weakened. Fourth, the contribution to trade credit is likely to be stronger for disclosures containing management transparency elements compared to single financial transparency.

To the best of our knowledge, this study is one of the first to explore the positive role of information transparency to supply chain financing, which to a certain extent makes up for the lack of information transparency research in the supply chain. It provides new ideas for enterprises to obtain trade credit financing and promote the improvement of supervision departments’ disclosure policies.