Search Results (120)

Maintaining well integrity is essential in the oil and gas industry to prevent environmental hazards, operational risks, and economic losses. Cement bond log (CBL) tools are essential in evaluating cement bonding and ensuring wellbore stability. This study presents a patent landscape review of CBL technologies, based on 3473 patent documents from the Lens.org database. After eliminating duplicates and irrelevant entries, 167 granted patents were selected for in-depth analysis. These were categorized by technology type (wave, electrical, radiation, neutron, and other tools) and by material focus (formation, casing, cement, and borehole fluid). The findings reveal a dominant focus on formation evaluation (59.9%) and a growing reliance on wave-based (22.2%) and other advanced tools (25.1%), indicating a shift toward high-precision diagnostics. Geographically, 75% of granted patents were filed through the U.S. Patent and Trademark Office, and 97.6% were held by companies, underscoring the dominance of corporate innovation and the minimal presence of academia and individuals. The review also identifies notable patents that reflect significant technical innovations and discusses their role in advancing diagnostic capabilities. These insights emphasize the need for broader collaboration and targeted research to advance well integrity technologies in line with industry goals for operational performance and safety. Full article

Based on firm-level data of Japanese listed companies for the period of 2013–2022, this study conducts an empirical analysis to investigate how the issuance of green bonds influences corporate environmental and financial performance. The results show that the green bond issuance demonstrates a reduction in corporate greenhouse gas emission intensity and energy consumption intensity in the long term. Moreover, the issuance of green bonds enhances the financial performance of firms in the long run. However, the positive effect of green bond issuance on corporate environmental and financial performance is significant only among firms that have set specific quantitative environmental targets. In addition, for manufacturing and transportation green bond issuers that have set specific quantitative environmental targets, the improvement in environmental performance is evident in both the long and short term. Full article

This study investigates the influence of exposure to climate change on the readability of narrative disclosures in annual reports. Analyzing a sample of 38,229 firm-year observations from 2002 to 2022, the study provides evidence supporting the information obfuscation hypothesis. Specifically, it finds that exposure to climate change is linked to less readable annual reports. This effect is both statistically and economically significant; a one standard deviation increase in climate change exposure leads to an 8.5% reduction in readability. Moreover, this effect is particularly evident among firms operating in environmentally sensitive industries, as well as those characterized by weak corporate culture. Additional tests indicate that the different aspects of climate change exposure (opportunity, physical, and regulatory) are individually associated with a decrease in readability of annual reports, with the physical dimension exerting the most significant impact. The findings underscore the necessity of implementing measures to mitigate climate change exposure and enhance sustainable business environments, such as transitioning to renewable energy sources (such as solar, wind, and hydro), minimizing dependence on fossil fuels, minimizing emissions from industries and transportation, sourcing low-carbon materials, adopting circular economy models, directing capital toward climate-friendly projects, and managing climate risks through catastrophe bonds and climate insurance. The significance of these actions is underscored by the impact of climate change on firms’ information environments, as documented in the current study. Full article

The United Kingdom has long been a frontrunner in green finance, establishing programs like the Green Finance Institute to promote corporate engagement in sustainable initiatives. The Green Finance Strategy, enacted in 2019, aligns UK financial procedures with international standards, including the EU taxonomy for sustainable Activities. The study examined how sustainable finance enhances the corporate reputation of the firms listed on the London Stock Exchange. A purposive sampling yielded 17 years of data from 143 non-financial companies from the Thomson Reuters Eikon DataStream between 2007 and 2023. In dealing with the issue of endogeneity and auto-serial correlation, the Generalized Methods of Movement (GMM) was employed to provide reliable and unbiased estimation results. The study revealed a positive impact of green bond issues, environmental expenditures, and policies for emission reduction on corporate reputation. The moderating relationship between green bond issues, environmental expenditures, and board diversity revealed a positive and significant relationship with corporate reputation. Managers should ensure that their endorsed activities gain public recognition and align with sustainability goals, particularly by emphasizing the issuance of green bonds in their financing strategy. They should also collaborate with environmental experts and stakeholders to ensure that the outcomes of funded projects are evaluated in line with international ESG standards. Full article

As global climate change intensifies and carbon emission policies become increasingly stringent, carbon risk has emerged as a crucial factor influencing corporate operations and financial markets. Based on data from A-share listed companies in China from 2009 to 2022, this paper empirically examines the pricing mechanism of carbon risk in the Chinese capital market and explores how different corporate signaling behaviors affect the carbon risk premium. The findings reveal the following: (1) Carbon risk exhibits a significant positive premium (annualized at about 1.33% per standard deviation), which remains robust over longer time windows and after replacing the measurement variables. (2) Heterogeneity analysis shows that the carbon risk premium is not significant in high-energy-consuming industries or before the signing of the Paris Agreement, possibly due to changes in investor expectations and increased green awareness. Additionally, a significant difference in the carbon risk premium exists between brown and green stocks, reflecting a “labeling effect” of green attributes. (3) Issuing green bonds, as an active corporate signaling behavior, effectively mitigates the carbon risk premium, indicating that market investors highly recognize and favor firms that actively convey green signals. (4) A “greenwashing” indicator constructed from textual analysis of environmental information disclosure suggests that greenwashing leads to a mispricing of the carbon risk premium. Companies that issue false green signals—publicly committing to environmental protection but failing to implement corresponding emission reduction measures—may mislead investors and create adverse selection problems. Finally, this paper provides recommendations for corporate carbon risk management and policy formulation, offering insights for both research and practice in the field. Full article

Amid accelerating globalization and urbanization, regional revitalization has become a key policy direction for countries to address regional decline. Among these, social capital and community empowerment can significantly promote regional development. Social capital emphasizes how trust, norms, and reciprocity facilitate collective action, while community empowerment focuses on improving residents’ participation and autonomous decision-making capacity. Existing research primarily focuses on cases from Europe and America; there is no in-depth exploration of the interaction between regional revitalization and social capital in Taiwan. Notably, systematic studies are lacking regarding the mechanisms through which University Social Responsibility (USR) programs engage and promote community development. This study takes the Wanli and Jinshan districts in northern Taiwan as case study examples. We employ action research and qualitative research methods to analyze the role of social capital and community empowerment in regional revitalization. This paper reviews how internal trust and cooperation within a community build bonding social capital. It explores how USR programs promote collaboration between communities and external resources through bridging social capital. The findings indicate that bonding social capital can enhance community cohesion and support regional revitalization efforts; bridging social capital can introduce academic, corporate, and governmental resources, providing technical and financial support for community innovation. The participatory mechanism of USR programs not only fosters civic awareness development but also offers a cross-organizational cooperation platform for regional revitalization, enabling communities to integrate internal and external resources more effectively. The results of this study indicate that bonding and bridging social capital can achieve complementary effects through USR programs, further promoting community empowerment and regional development. This study deepens the application of social capital theory in regional revitalization. It provides an empirical basis for policymakers and academic institutions to optimize the planning and implementation of future USR programs. While the study focuses on a geographically bounded set of cases and employs an exploratory qualitative design, these choices enabled a rich, context-sensitive understanding of how regional self-governance and community capital may be strengthened in practice. Future research could extend this line of inquiry by examining additional locales, adopting longitudinal perspectives, and integrating mixed-method approaches, thereby further amplifying the robustness and applicability of the propositions advanced here. Full article

I show that house prices can be modeled using machine learning (kNN and tree-bagging) and a small dataset composed of macroeconomic factors (MEF), including an inflation metric (CPI), US Treasury rates (10-yr), Gross Domestic Product (GDP), and portfolio size of central banks (ECB, FED). This set of parameters covers all the parties involved in a transaction (buyer, seller, and financing facility) while ignoring the intrinsic properties of each asset and encompassing local (inflation) and liquidity issues that may impede each transaction composing a market. The model here takes the point of view of a real estate trader who is interested in both the financing and the price of the transaction. Machine learning allows for the discrimination of two periods within the dataset. First, and up to 2015, I show that, although the US Treasury rates level is the most critical parameter to explain the change of house-price indices, other macroeconomic factors (e.g., consumer price indices) are essential to include in the modeling because they highlight the degree of openness of an economy and the contribution of the economic context to price changes. Second, and for the period from 2015 to today, I show that, to explain the most recent price evolution, it is necessary to include the datasets of the European Central Bank programs, which were designed to support the economy since the beginning of the 2010s. Indeed, unconventional policies of central banks may have allowed some institutional investors to arbitrage between real estate returns and other bond markets (sovereign and corporate). Finally, to assess the models’ relative performances, I performed various sensitivity tests, which tend to constrain the possibilities of each approach for each need. I also show that some models can predict the evolution of prices over the next 4 quarters with uncertainties that outperform existing index uncertainties. Full article

This study investigates the relationship between bond-specific factors, macroeconomic variables, and green bond (GB) yields issued in the Indonesian bond market. The study sample includes 468 GBs issued by 30 issuers from both corporate and government entities from 2018 to 2023. This research method uses panel regression techniques with the random effects models to test hypotheses on two estimation model specifications. The study results reveal that interest, inflation, and exchange rates are significantly and positively related to GB yields. Bond-specific factors have different impacts, where coupons and maturity have a positive relationship with GB yields, while bond issuers have an adverse effect. Bond rating and issuance size as specific factors are shown to have no impact on GB yields. In the model with the moderating role of rating, the study’s results show that coupons still directly impact GB yields positively, while the influence of maturity is negative. The interaction of maturity and rating positively impacts GB yield. Different findings suggest that interactions with coupons weaken the impact of ratings on GB yields. The results of this study contribute to the financial literature on the determinants of the GB market and the role of bond ratings as a moderator. The study also provides new insights into Indonesia’s GB market, which includes developing countries. The findings can also help companies, investors, regulators, and researchers better understand the GB market. Full article

This paper explores the hypothesis that the returns of asset classes can be predicted using common, systematic risk factors represented by the level, slope, and curvature of the US interest rate term structure. These are extracted using the Nelson–Siegel model, which effectively captures the three dimensions of the yield curve. To forecast the factors, we applied autoregressive (AR) and vector autoregressive (VAR) models. Using their forecasts, we predict the returns of government and corporate bonds, equities, REITs, and commodity futures. Our predictions were compared against two benchmarks: the historical mean, and an AR(1) model based on past returns. We employed the Diebold–Mariano test and the Model Confidence Set procedure to assess the comparative forecast accuracy. We found that Nelson–Siegel factors had significant predictive power for one-month-ahead returns of bonds, equities, and REITs, but not for commodity futures. However, for 6-month and 12-month-ahead forecasts, neither the AR(1) nor VAR(1) models based on Nelson–Siegel factors outperformed the benchmarks. These results suggest that the Nelson–Siegel factors affect the aggregate stochastic discount factor for pricing all assets traded in the US economy. Full article

This study examines the effects of internal governance mechanisms on the issuance of green bonds and investigates whether firms issuing green bonds exhibit distinct corporate governance characteristics, especially regarding board gender diversity and corporate social responsibility (CSR) committees. The analysis is based on a sample of 64 green bond announcements between 2013 and 2022. Based on the Generalized Least Squares Regression model, empirical results show that the presence of a CSR committee is positively and significantly associated with the issuance of green bonds. In other words, companies with a CSR committee are more likely to issue green bonds. In addition, companies with a lower debt ratio are more likely to issue green bonds. Full article

Greenwashing undermines the trustworthiness and integrity of environmental, social, and governance (ESG) reporting. It undermines disclosure quality, confuses decision making, destabilizes financial markets, and reduces the probability that people will trust the supplied information. This research utilizes a comprehensive literature review and bibliometric analysis to investigate the scholarly dialogue around ESG disclosure and strategies to counteract corporate “greenwashing”. This study’s objectives were achieved by bibliometric analysis, using the statistical programming tools R Studio R 3.6.0+, Biblioshiny 4.2.0, and VOSviewer 1.6.20. We acquired bibliometric data from the Scopus database for the period 2012–2024. We established the optimal sample size via the PRISMA methodology, including both inclusion and exclusion criteria. Greenwashing is a multifaceted issue that manifests in many forms, shapes, and intensities, as seen by the data. This obstructs the advancement of apparatus for prevention, quantification, and detection. Moreover, the results indicate that sustainable finance is adversely affected by greenwashing, particularly for green loans and green bonds. Moreover, the findings indicate that corporate greenwashing is a distinct kind of greenwashing. Full article

This study, within the framework of uncertainty theory, employs an uncertain differential equation with jumps to model the asset value process of a company, establishing a structured model of uncertain credit risk that incorporates jumps. This model is applied to the pricing of two types of credit derivatives, yielding pricing formulas for corporate zero-coupon bonds and Credit Default Swap (CDS). Through numerical analysis, we examine the impact of asset value volatility and jump magnitude on corporate default uncertainty, as well as the influence of jump magnitude on the pricing of zero-coupon bonds and CDS. The results indicate that an increase in volatility levels significantly enhances default uncertainty, and an expansion in the magnitude of negative jumps not only directly elevates default risk but also leads to a significant increase in the value of zero-coupon bonds and the price of CDS through a risk premium adjustment mechanism. Therefore, when assessing corporate default risk and pricing credit derivatives, the disturbance of asset value jumps must be considered a crucial factor. Full article

As investors increasingly incorporate non-financial performance metrics into investment decisions, CSR has become valuable due to its implications for voluntary disclosures and third-party ratings. Building on this premise, our study examines how green-bond issuance signals environmental commitment and is associated with ESG performance and valuation. While other studies examine this association, we go a step further and identify the green-bond features which are associated with ESG ratings. Using the Bloomberg database, we downloaded corporate green-bond data for 2550 green bonds. We use signaling theory as the foundation of the study. We deploy regression to test the relationships. Our findings show that green-bond features are associated with enhanced environmental and ESG disclosure scores but not with reductions in CO₂ emissions relative to sales. The findings show weak associations of ESG with green-bond features. Taken together, the results contradict ‘greenwashing’ claims. However, the findings confirm that companies effectively signal environmental commitment through green-bond issuance. These insights enhance the understanding of green bonds’ nature and dimensions while providing meaningful implications for corporate policy. Full article

We show that U.S. open-end actively managed domestic bond mutual fund managers possess selection and short-term timing skills based on monthly returns from 1999 to 2016. Parametric tests bias against finding evidence of manager skill, and correction for precision of alpha matters most when true alpha is uncertain. Our bootstrap simulations use precision-adjusted alpha (t(α)) controlling for luck without relying on parametric statistics. We find: the top 50 percent of bond mutual fund managers generate positive precision-adjusted alpha net of expense; selection skill contributes to long-term fund performance; and timing skill adds to short-term fund results, especially for government bond funds compared to corporate bond funds. Full article

Using a structural VAR model, this paper investigates how oil price shocks and US uncertainty affect emerging market corporate bond returns. The key finding is that the response of emerging market corporate bond returns varies significantly depending on the underlying sources of oil price changes. Oil supply shocks generally have a negative impact on corporate bond returns, while aggregate demand and oil market-specific demand shocks lead to a temporary increase in returns, followed by a gradual fall. That is, when oil price increases are driven by stronger global economic activity or by speculative demand reflecting increased risk appetite, they can lead investors to search for higher yields in emerging markets, and thus raise corporate bond returns in the short term. Conversely, an unexpected rise in US uncertainty strengthens investors’ risk aversion and results in a substantial decline in emerging market corporate bond returns. These findings have crucial policy implications not only for portfolio strategies of global investors, but also for government authorities in emerging market economies. Full article