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Incorporating self-interaction corrections (SIC) significantly improves chemical reaction barrier height predictions made using density functional theory methods. We present a detailed orbital-by-orbital analysis of these corrections for three semi-local density functional approximations (DFAs) situated on the three lowest rungs of Jacob's ladder of approximations. The analysis is based on Fermi–Löwdin Orbital Self-Interaction Correction (FLOSIC) calculations performed at several steps along the reaction pathway from the reactants (R) to the transition state (TS) to the products (P) for four representative reactions selected from the BH76 benchmark set. For all three functionals, the major contribution to self-interaction corrections of the barrier heights can be traced to stretched bond orbitals that develop near the TS configuration. The magnitude of the ratio of the self-exchange–correlation energy to the self-Hartree energy (XC/H) for a given orbital is introduced as an indicator of one-electron self-interaction error. XC/H = 1.0 implies that an orbital's self-exchange–correlation energy exactly cancels its self-Hartree energy and that the orbital, therefore, makes no contribution to the SIC in the FLOSIC scheme. For the practical DFAs studied here, XC/H spans a range of values. The largest values are obtained for stretched or strongly lobed orbitals. We show that significant differences in XC/H for corresponding orbitals in the R, TS, and P configurations can be used to identify the major contributors to the SIC of barrier heights and reaction energies. Based on such comparisons, we suggest that barrier height predictions made using the strongly constrained and appropriately normed meta-generalized gradient approximation may have attained the best accuracy possible for a semi-local functional using the Perdew–Zunger SIC approach. [ABSTRACT FROM AUTHOR]

We study the drift and cyclical components in U.S. Treasury bonds. We find that bond yields are drifting because they reflect the drift in monetary policy rates. Empirically, modeling the monetary policy drift using demographics and productivity trends, plus long-term inflation expectations, leads to cyclical deviations of bond prices from their drift that predict bond returns in- and out-of-sample. These bond cycles can be interpreted as term premia or/and temporary deviations from rational expectations in a behavioral framework. Through the lens of our model, we detect a significant role of the latter in determining the cyclical properties of yields with short maturities. [ABSTRACT FROM AUTHOR]

We confirm prior evidence that bonds on average are offered at prices below their immediate post-offer secondary market prices. However, in cases where banks lead–manage their own bond offerings the underpricing is significantly less as compared with other non-self-marketed offerings. These findings are robust across various matched samples and selection models. Our results suggest that the bond offering process is characterized by substantive agency conflicts between shareholders of corporations (issuers) and underwriters. [ABSTRACT FROM AUTHOR]

In this article, the author illustrates the application of a financial database called Bloomberg Professional in a fixed income lesson plan. Most business school programs include a finance course that covers bond pricing and spreads, such as a corporate finance or fixed income course. Bloomberg Professional allows students to interact with primary data and engage in experiential learning about bond spreads. The article explains Bloomberg Professional and the benefits of experiential learning. The author also provides a detailed lesson plan. Instructors can implement this lesson plan to achieve both financial education and information literacy goals. [ABSTRACT FROM AUTHOR]

The selective C−F bonds functionalization in available trifluoromethyl compounds is an economic route for obtaining high‐value organic fluorine compounds. However, due to the high C−F bonds dissociation energy in trifluoromethyl group, the strength of the bond decreases continuously during defluorination, posing a challenge in modifying such molecules without over‐conversion. Over the past few years, there has been significant progress in developing efficient methods for constructing difluoromethylene unit, using approaches such as radical chemistry, photochemistry, electrochemistry, and organometallic chemistry. These methods involve difluorocarbon radicals, difluorocarbon cations, difluorocarbon anions, and trifluoromethyl carbenes as intermediates. In this review, we summarized the recent five years of research achievements in this field for selective single C−F bond cleavage in trifluoromethyl aromatic and carbonyl compounds to gain diverse difluoromethylene‐containing organic molecules via different intermediate strategies. [ABSTRACT FROM AUTHOR]

The United Nations Sustainable Development Goals (SDGs) made an urgent call for action by all the countries across the globe, with an aim to end poverty, improve health and education, reduce inequality, and spur economic growth – all of this is intended to be achieved while tackling climate change and working to protect environment and preserve earth. However, these goals cannot be achieved unless money is mobilised to finance climate change mitigation and adaptation efforts across the world. In response, various manifestations of green bonds have appeared in the market and these are considered as a bridge to the achievement of the SDGs – this is because climate mitigation and adaptation are integral to successful implementation of the SDGs. Using the Capital Asset Pricing Model, Fama–French Three Factor, Carhart Four Factor and Fama–French Five Factor pricing models, our study provides empirical evidence that the announcement of green bonds issuance lead to positively abnormal return on stocks. We divided our dataset into two parts. The first part of the dataset is from 01/01/2013 to 30/06/2018 and later part analyses the period from 01/07/2018 to 30/06/2022. The consistent results highlight the firms' and investors' efforts towards climate action (SDG13) and strongly suggest that green bonds play an important role as a bridge to the SDGs. [ABSTRACT FROM AUTHOR]

Two intermediary-based factors—a corporate bond dealer inventory measure and a broad intermediary distress measure—explain more than 40 |$\%$| of the puzzling common variation in credit spread changes beyond canonical structural factors. A simple intermediary-based model with partial market segmentation accounts for intermediary factors' explanatory power and delivers three further implications with empirical support. First, whereas bond sorts on risk-related variables produce monotonic loading patterns on intermediary factors, non-risk-related sorts produce no pattern. Second, dealer inventory comoves with corporate-credit assets only, whereas intermediary distress comoves with both corporate-credit and non-corporate-credit assets. Third, dealers' inventory responds to (instrumented) bond sales by institutional investors. [ABSTRACT FROM AUTHOR]

Flexible and highly ultraviolet (UV) sensitive materials garner considerable attention in wearable devices, adaptive sensors, and light‐driven actuators. Herein, a type of nanofilms with unprecedented fully reversible UV responsiveness are successfully constructed. Building upon this discovery, a new system for ultra‐fast, sensitive, and reliable UV detection is developed. The system operates by monitoring the displacement of photoinduced macroscopic motions of the nanofilms based composite membranes. The system exhibits exceptional responsiveness to UV light at 375 nm, achieving remarkable response and recovery times of < 0.3 s. Furthermore, it boasts a wide detection range from 2.85 µW cm−2 to 8.30 mW cm−2, along with robust durability. Qualitative UV sensing is accomplished by observing the shape changes of the composite membranes. Moreover, the composite membrane can serve as sunlight‐responsive actuators for artificial flowers and smart switches in practical scenarios. The photo‐induced motion is ascribed to the cis–trans isomerization of the acylhydrazone bonds, and the rapid and fully reversible shape transformation is supposed to be a synergistic result of the instability of the cis‐isomers acylhydrazone bonds and the rebounding property of the networked nanofilms. These findings present a novel strategy for both quantitative and qualitative UV detection. [ABSTRACT FROM AUTHOR]

Traditional insurance's earthquake contingency costs are insufficient for earthquake funding due to extreme differences from actual losses. The earthquake bond (EB) links insurance to capital market bonds, enabling higher and more sustainable earthquake funding, but challenges persist in pricing EBs. This paper presents zero-coupon and coupon-paying EB pricing models involving the inconstant event intensity and maximum strength of extreme earthquakes under the risk-neutral pricing measure. Focusing on extreme earthquakes simplifies the modeling and data processing time compared to considering infinite earthquake frequency occurring over a continuous time interval. The intensity is accommodated using the inhomogeneous Poisson process, while the maximum strength is modeled using extreme value theory (EVT). Furthermore, we conducted model experiments and variable sensitivity analyses on EB prices using earthquake data from Indonesia's National Disaster Management Authority from 2008 to 2021. The sensitivity analysis results show that choosing inconstant intensity rather than a constant one implies significant EB price differences, and the maximum strength distribution based on EVT matches the data distribution. The presented model and its experiments can guide EB issuers in setting EB prices. Then, the variable sensitivities to EB prices can be used by investors to choose EB according to their risk tolerance. [ABSTRACT FROM AUTHOR]

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. From the viewpoint of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long-term discount rate to estimate the rate when taking historical US and UK data, and to further contribute to the discussion about the urgency of climate action in the context of environmental economics and stochastic methods. Century-long historical records of 3-month bonds, 10-year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond-pricing models, which are designed for nominal rates that are assumed to be positive. We, therefore, use the Ornstein–Uhlenbeck model, which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long-term discount rate is 1.7% for the UK and 2.2% for the US. The value of 1.4% used by Stern is less than a standard deviation from our estimated long-run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the need for immediate and substantial spending to combat climate change. [ABSTRACT FROM AUTHOR]

Policymakers and managers have increasingly adopted green bonds as a direct financing tool to address environmental degradation and climate change in emerging economies; however, the increasing green washing sentiments in the green bond market raise questions on whether green bonds can nudge polluting businesses to achieve green transformation. Therefore, this study joins the controversial debate by investigating the impact of green bond issuance on corporate environmental responsibilities and the potential impact mechanisms and economic consequences. Using the data of Chinese listed enterprises from 2011 to 2020 and the staggered issuance of green bonds as plausibly exogenous shocks, we determine that the enterprises in the experimental group that issued green bonds increased their environmental performance compared to their counterparts. Furthermore, this positive link is maintains after a series of robustness tests. Moreover, we identify that green bond issuance plausibly enhances environmental responsibility engagements through two governance channels, namely, internal management and external supervision. This beneficial effect appears more pronounced for subsamples of firms in low-polluting industries, without environmental subsidies and with higher managerial abilities. Furthermore, economic consequences indicate that the issuance of green bonds primarily motivates speculative shareholder benefits, as evidenced by short-term increases in stock yields but with limited impact on the short-run financial performance. Overall, these findings offer new evidence supporting that green financing tools could play a helpful hand toward environmental sustainability. [ABSTRACT FROM AUTHOR]

Public sector corruption affects economic and financial outcomes, such as GDP growth, foreign direct investment, and government funding costs. Less is known about the spillovers from perceptions of public sector corruption on the private sector corporate bond market. In this paper, we assess the role of public sector corruption perception on corporate bond market variables in Europe using data of both country-level corporate bond indexes and firm-level corporate bond market issuances. At the aggregate country level, we find some evidence that country indices of corporate bonds' yields and coupons are higher in countries with more corruption. While we do not find effects of corruption on coupon rates at the individual firm level, we show that higher government corruption perception increases their yield to maturity and reduces the amounts raised by corporations through their bond issuances. [ABSTRACT FROM AUTHOR]

Interest rate dynamics are influenced by various economic factors, and central bank meetings play a crucial role concerning this subject matter. This study introduces a novel approach to modeling interest rates, focusing on the impact of central banks' scheduled interventions and their implications for pricing bonds and path-dependent derivatives. We utilize a modified Skellam probability distribution to address the discrete nature of scheduled interest rate jumps and combine them with affine jump-diffusions (AJDs) in order to realistically represent interest rates. We name this class the AJD–Skellam models. Within this class, we provide closed-form formulas for the characteristic functions of a still broad class of interest rate models. The AJD–Skellam models are well-suited for using the interest rate version of the Fourier-cosine series (COS) method for fast and efficient interest rate derivative pricing. Our methodology incorporates this method. The results obtained in the paper demonstrate enhanced accuracy in capturing market behaviors and in pricing interest rate products compared to traditional diffusion models with random jumps. Furthermore, we highlight the applicability of the model to risk management and its potential for broader financial analysis. [ABSTRACT FROM AUTHOR]

As a core component of power conversion systems, insulated gate bipolar transistor (IGBT) modules continually suffer from severe thermal damage caused by temperature swings and shear stress, resulting in fatigue failure. Bond wires falling off is one of the failure modes of IGBT modules. Given that the number of fallen-off bond wires is a significant parameter to evaluate the health status of the IGBT modules, this paper proposes an online identification model to recognize the number of fallen-off bond wires during normal operation. Firstly, a database containing datum V c e , o n − T j − I C (collector–emitter on-state voltage V c e , o n , chip junction temperature T j , collector current I C ) planes with different fallen-off bond wires is built based on an offline aging test. Secondly, a Foster network model and a special circuit are designed to measure the junction temperature T j and the collector–emitter on-state voltage V c e , o n , respectively. Thirdly, the feature points of the IGBT module represented by V c e , o n , T j , and I C are given to the database to recognize the number of fallen-off bond wires according to the position of the feature points in the datum plane. The experimental results show that the proposed method can determine the fallen-off bond wires under the operation condition. [ABSTRACT FROM AUTHOR]

The current status quo for the EU green bond market is that it is a purely private regulation by way of market self-discipline, i. e. the ICMA Green Bond Principles, which is to be complied with by the bond issuers as good practice, but that has been criticised for not being sufficient, leaving a regulatory vacuum and causing the "legitimacy deficit problem. To solve the regulatory vacuum pain point. the EU has recently established the landmark EU Green Bond Regulation, which should bring some certainty to define "green " and green safeguard requirements for issuers. This article starts by examining the pain points under the current regulatory vacuum, and the inadequacy of the private regulation Bitch as the ICMA Green Bond Principles . It further provides an overview to the new EUGBR framework under the context of the EU green agenda, and makes an assessment of the key aspects of EUGBR, considering the related legislative purposes. It makes a further impact assessment to evaluate what factors would affect the market uptake of it in practice. [ABSTRACT FROM AUTHOR]

In this study, we propose an implementation of the multifactor Heath-Jarrow-Morton (HJM) interest rate model using an approach that integrates principal component analysis (PCA) and Monte Carlo simulation (MCS) techniques. By integrating PCA and MCS with the multifactor HJM model, we successfully capture the principal factors driving the evolution of short-term interest rates in the US market. Additionally, we provide a framework for deriving spot interest rates through parameter calibration and forward rate estimation. For this, we use daily data from the US yield curve from June 2017 to December 2019. The integration of PCA, MCS with multifactor HJM model in this study represents a robust and precise approach to characterizing interest rate dynamics and compared to previous approaches, this method provided greater accuracy and improved understanding of the factors influencing US Treasury Yield interest rates. [ABSTRACT FROM AUTHOR]

This paper empirically assesses the performance of green bond indices and the causality of that performance using a range of financial and commodity data. We present new insights from the novel application of datasets, neural networks and performance measurements. We find that green bond indices do not outperform the market when factors beyond market return are considered. We find that Brent crude oil has the most significant effect on certain indices, a finding that contrasts with other studies on green bonds. A greater sensitivity to oil prices and global green equities also evinces a negative impact on a green bond index's ability to outperform the market. For the first time, a linear causal relationship is established between Title Transfer Facility (TTF) returns and green bond index returns. Additionally, a fundamental shift in causal relationships is observed over the COVID-19 period. In this way, we contribute to the literature on sustainable green bonds and the impact of COVID-19. These insights provide more clarity to market participants for navigating the uncertainties of both the global energy transition and the postpandemic period. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology to price bonds jointly issued by a group of countries—Eurobonds in the euro-area context. We consider two types of bonds; the first is backed by several and joint guarantees (SJGs), and the second features several but not joint guarantees (SNJGs). The pricing of SJG and SNJG bonds reflects different assumptions regarding the pooling of debtors' fiscal resources. We estimate fiscal limits for the six largest euro-area economies over 2008–2021 and deduce counterfactual Eurobond prices. For the five-year maturity, SNJG bond yield spreads would have been about three times larger than SJG ones over the estimation sample. Hence, issuing SJG bonds could result in gains at the aggregate level. Notwithstanding, our model also predicts that gains may temporarily vanish in periods of acute fiscal stress. We finally envision postissuance redistribution schemes, whereby gains stemming from the issuance of SJG bonds could be shared among participating countries; we argue that these schemes may alleviate the reduction in market discipline resulting from common bonds issuance. This paper was accepted by David Sraer, finance. Funding: This work has benefited from financial support from the Swiss National Science Foundation [Grant 182293]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4740. [ABSTRACT FROM AUTHOR]

In this paper, we propose an extended credit migration model with asymmetric fixed boundaries and multiple ratings, for a more precise depiction of credit changes in the real world. A model with three ratings is established and analyzed as an example, and then the results are generalized to a general multirating form model. We prepare the model meaningfully by arranging the asymmetric boundaries in a suitable order. A PDE system problem is deduced, and the existence and uniqueness of the solution for the problem are obtained using PDE techniques, which further ensure the rationality of the model. Due to the flexible configuration of asymmetric boundaries, the multirating model has various types of structures in the buffer zones where the credit rating keeps its original state. For instance, the two buffers in the three-rating model may be separated, connected, or intersected, as presented in the numerical results for different boundary parameters. [ABSTRACT FROM AUTHOR]

This research paper distinguishes between stocks and bonds as distinct financial instruments and addresses the relative lack of computational finance research in bond price forecasting compared to stock market prediction. To bridge this gap, we propose and evaluate three forecasting models using historical bond price data: Support Vector Regression (SVR), Facebook Prophet, and RNN-LSTM. We also look into the possibility of increasing forecast accuracy by adding sentiment analysis as a new parameter. Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Square Percentage Error (MSPE) are some of the evaluation metrics used for model comparison. Our findings show that when sentiment encoding is included as a contributing element, Facebook Prophet beats the other models and exhibits improved accuracy. This study has useful implications for improving bond price forecasting methodologies and makes significant contributions to the field of computational finance. [ABSTRACT FROM AUTHOR]

A proposed model is used to account for both the recovery rate and regime-switching uncertainties for pricing credit-risky bonds. A two-factor hazard rate model (TFHRM) is also considered, where the dynamics of both instantaneous forward rates and asset values are modeled using Markov-modulated geometric Brownian motions (MMGBMs). Moreover, a macroeconomic factor is incorporated into the MMGBMs. The model complexity is resolved through the introduction of an endogenous intensity function and a recovery rate under the TFHRM. A semi-closed-form solution for pricing defaultable bonds is derived along with a pricing formula for credit spread. A credit cycle is constructed to reflect changes in industry characteristics and macroeconomic factors. The empirical study demonstrates that the inclusion of a stochastic recovery rate increases the model's pricing accuracy, and the results indicate a close interaction among business cycles, recovery rates, and credit ratings. [ABSTRACT FROM AUTHOR]

In this paper, we concentrate on the European option pricing problem in incomplete markets by taking Vasicek stochastic interest rate model into account and expanding it in accordance with a Lévy process named Variance Gamma (VG) process. In doing so, first, we prove the existence and uniqueness of the solution to the stochastic differential equation of this model. Then, by the means of the hedging and replicating techniques, pricing formulas for the bond and, in succession, for European options are established. Finally, from a numerical point of view, we will analyze the value of a bond based on our consideration model and also, we will study a European call option bond price. All these results are reported through the Monte-Carlo simulation method. [ABSTRACT FROM AUTHOR]

The growing interest in the financial materiality of Environmental, Social, and Governance (ESG) ratings has prompted recent investigations into their risk pricing impact in the corporate bond market. The specific implications for the Architecture, Engineering, and Construction (AEC) industry have not been explored, as prior work has primarily focused on broad-based ESG integration. To fill this gap, our study employed an interpretable machine learning technique using a sample universe of U.S. corporate bonds spanning from 2010 to 2021 to estimate the impact of ESG ratings on corporate bond issuance spreads. The results revealed an average ESG benefit of 10 basis points across all sectors. However, it is important to note that the effects of ESG ratings on bond pricing demonstrate variation across sectors and individual ESG constituent ratings. Significantly, our findings show that social and governance ratings emerge as the primary drivers influencing bond issuance costs, whereas the impact of environmental scores is comparatively less significant. Within AEC-related industries, empirical data on the influence of ESG ratings indicate discounted pricing by the market is particularly channeled through environmental and governance scores. These findings emphasize the value-added impact of enhanced ESG performance on the cost of debt financing, presenting a financially material opportunity for operational and management decision-making. By adopting sustainable strategies to improve ESG performance, organizations in the AEC industry can potentially achieve lower costs of debt when issuing bonds to secure financing for construction projects. The managerial implications extend to policymakers, corporate managers, and creditors, as they all stand to benefit from the financial implications of ESG performance. [ABSTRACT FROM AUTHOR]

This paper studies the issuing pricing character of green bonds with the evidence from China and further analyzes the reason why green factor affects bond issuing pricing by analyzing credit rating's intermediary effect and exploring the mediating of policy incentives and third-party green certification. Furthermore, heterogeneity analysis is conducted to analyze how green factor impacts on bond issuing pricing at different quantiles and for companies in different industries or with different ownership. The findings include: (1) Green factor generally reduces the issuance interest rate of green bonds, though this effect is not significant at the low quantiles or at the early development stage. (2) Green factor's impact on bond issuing pricing occurs partly by improving bond credit rating, fully by this way for companies in the construction industry, but directly for companies in other industries. (3) For non-state-owned companies, green factor has direct effect on bond issuing pricing, but this effect is not significant for state-owned companies. (4) Third-party green certification and incentive policies enhance the reducing effect of green factor on the issuance interest rate. This study provides a theoretical reference for environment-friendly investors, financiers with green projects and the regulators caring about green finance. [ABSTRACT FROM AUTHOR]

We investigate the impact of credit spreads on the stochastic duration and convexity of corporate bonds with respect to the very metrics for equivalent Treasury bonds. We show that the credit spread has two interacting effects on both the duration and convexity of a corporate coupon bond compared to those of an equivalent Treasury coupon bond. For bond convexity, we newly uncover that the first effect originates from the duration of the Treasuries; from both the duration and convexity of the coupon bonds' conditional survival probability; and from the covariance between the default-free short rate and the credit spread. The second driver stems from the weighting of the convexities of the zero-coupon bonds. We provide necessary and sufficient conditions for the duration and convexity of defaultable corporate coupon bonds to be smaller than those of equivalent Treasury bonds. Since interest rates and credit spreads are, by and large, negatively correlated, our numerical results support the notion that not only durations but also convexities of defaultable corporate bonds may be smaller than those of equivalent Treasuries. [ABSTRACT FROM AUTHOR]

The intensity, hardness, and extent of catastrophic accidents in recent decades have led insurance companies to seek resources to raise the capital to deal with the caused damage by these accidents. One of the most effective tools to cover the risk of catastrophic events such as earthquakes, floods, etc., which is widely used in the world, is catastrophic bonds. The purpose of this study is to provide a model for the pricing of catastrophic bonds. Because earthquake catastrophic damage causes major changes to corporate assets as well as investment trends, a jump sentence is added to the study model to indicate the severity and probability of damage. To produce the time discretization, the suggested methodology employs a one-order correct expression in the first process. To generate the full-discretization in the second level, the spectral collocation method approach that relies on the Chebyshev basis of the second kind is presented. Adding the jump sentence causes the original model to become an integral differential model, which approximates using the spectral method. Also, based on the derivatives in the obtained model, we approximated the derivative operator by using this type of base. The numerical investigation confirms the temporal discretized formulation's stability and convergence. We also approximated the integral sentence using the expansion of Gauss-Laguerre quadrature and presented numerical results. [ABSTRACT FROM AUTHOR]

A transparent, rules based, portfolio construction algorithm is proposed for convertible bond arbitrage. Feature selection is based on a mark-to-market approach where the volatility from the embedded conversion option is implied from the traded credit spread and bond price. The resulting volatility term structure created by linking the bond implied volatility to listed equity volatilities provides a forward looking rich versus cheap feature extraction. Each bond's relative value translates to its arbitrage potential as a long volatility position. The approach is back tested across all U.S. dollar bonds from 2014. The resulting portfolio returns track and outperform published index benchmarks, thereby producing a smart beta index. [ABSTRACT FROM AUTHOR]

This article demonstrates that rating-based capital requirements, through their impact on insurers' investment demand, affect corporate bond prices. Consistent with insurers' low demand for investment-grade bonds with a rating close to noninvestment-grade, these bonds outperform. Consistent with insurers' high (low) demand for investment-grade bonds with high (low) systematic risk exposure, these bonds underperform (outperform). Insurer demand, measured by insurer holdings, explains most of these pricing effects. We identify rating-based capital requirements as the driver of insurer demand, and thus the pricing effects, by showing that the effects do not exist before these requirements' implementation in 1993. [ABSTRACT FROM AUTHOR]

I build a search model of bond and credit default swap (CDS) markets with endogenous investor participation and show that shorting bonds through CDS increases the liquidity and price of bonds. By allowing investors to trade the credit risk of bonds without trading the bonds, CDS introduction expands the set of feasible trades and attracts investors into the credit market. Because search is nondirected within the credit market, new investors also trade bonds and consequently increase their price and liquidity. My results suggest that naked CDS bans increased sovereigns' borrowing costs and thereby exacerbated the 2010–2012 European debt crisis. [ABSTRACT FROM AUTHOR]

Tetrafluoromethane (CF4), the simplest perfluorocarbons, is a permanently potent greenhouse gas due to its powerful infrared radiation adsorption capacity. The highly symmetric and robust C-F bond structure makes its activation a great challenge. Herein, we presented an innovated approach that efficiently activates C-F bond utilizing protonated sulfate (-HSO4) modified Al2O3@ZrO2 (S-Al2O3@ZrO2) catalyst, resulting in highly efficient CF4 decomposition. By combining in situ infrared spectroscopy tests and density function theory simulations, we demonstrate that the introduced -HSO4 proton donor has a stronger interaction on the C-F bond than the hydroxyl (-OH) proton donor, which can effectively stretch the C-F bond for its activation. Consequently, the obtained S-Al2O3@ZrO2 catalyst achieved a stable 100% CF4 decomposition at a record low temperature of 580 °C with a turnover frequency value of ~8.3 times higher than the Al2O3@ZrO2 catalyst without -HSO4 modification, outperforming the previously reported results. This work paves a new way for achieving efficient C-F bond activation to decompose CF4 at a low temperature. [ABSTRACT FROM AUTHOR]

In this study, we consider an intensity-based model for pricing a commodity-linked bond with credit risk. Recently, the pricing of a commodity-linked bond with credit risk under the structural model has been studied. We extend the result using an intensity-based model, stochastic volatility model, and stochastic convenience yield model. In the intensity-based model, the credit event by the counterparty occurs at the time of first jump in a stochastic Poisson process, in which intensity is modeled as the sum of two CIR prosesses. We assume that the underlying asset follows the stochastic volatility and convenience yield models. Using the measure change technique, we explicitly derive the commodity-linked bond pricing formula in the proposed model. As a result, we provide the explicit solution for the price of the commodity-linked bond with stochastic convenience yield, stochastic volatility, and credit risk as single integrations. In addition, we present several examples to demonstrate the effects of significant parameters on the value of commodity-linked bond using numerical integration. In particular, examples are provided, focusing on the behavior of prices based on effects of recovery rate. [ABSTRACT FROM AUTHOR]

This study delves into the temporal dynamics within the equity market through the lens of bond traders. Recognizing that the riskless interest rate fluctuates over time, we leverage the Black-Derman-Toy model to trace its temporal evolution. To gain insights from a bond trader's perspective, we focus on a specific type of bond: the zero-coupon bond. This paper introduces a pricing algorithm for this bond and presents a formula that can be used to ascertain its real value. By constructing an equation that juxtaposes the theoretical value of a zero-coupon bond with its actual value, we can deduce the risk-neutral probability. It is noteworthy that the risk-neutral probability correlates with variables like the instantaneous mean return, instantaneous volatility, and inherent upturn probability in the equity market. Examining these relationships enables us to discern the temporal shifts in these parameters. Our findings suggest that the mean starts at a negative value, eventually plateauing at a consistent level. The volatility, on the other hand, initially has a minimal positive value, peaks swiftly, and then stabilizes. Lastly, the upturn probability is initially significantly high, plunges rapidly, and ultimately reaches equilibrium. [ABSTRACT FROM AUTHOR]

We explore whether life insurers use a unique reinsurance arrangement to manage assets tied to their regulatory capital. Typical reinsurance allows insurers to reduce their regulatory capital by transferring liabilities (reserves), and the associated assets, to reinsurers. With modified coinsurance (ModCo), insurers maintain control of their liabilities and assets while transferring regulatory capital requirements to the reinsurer. Holding fixed an insurer's reported capital, we find that ModCo allows insurers to report higher risk‐based capital ratios. Insurers with ModCo are less likely to fire sale downgraded bonds. We also find suggestive evidence of regulatory arbitrage, as most ModCo is purchased from reinsurers in countries with low capital requirements or within the same insurance group. [ABSTRACT FROM AUTHOR]

The pressure-induced structural phase transition of XeO3 is studied by first principle calculations. The transition from P212121 to Pnma accompanied by a drastic reduction of volume is found at 2.18 GPa. The symmetrilized Xe−O2 bonds give rise to the better symmetry of high pressure phase. O-hopping between different possible local minima and the motion of Xe along the y axis may be responsible for phase transition. Results of electron localization function indicate that three ipsilateral Xe−O bonds lead to a lone-pair contour of Xe6+. [ABSTRACT FROM AUTHOR]

Human mortality has been improving faster than expected over the past few decades. This unprecedented improvement has caused significant financial stress to pension plan sponsors and annuity providers. The widely recognized Lee–Carter model often assumes linearity in its period effect as an integral part of the model. Nevertheless, deviation from linearity has been observed in historical mortality data. In this paper, we investigate the applicability of four nonlinear time-series models: threshold autoregressive model, Markov switching model, structural change model, and generalized autoregressive conditional heteroskedasticity model for mortality data. By analyzing the mortality data from England and Wales and Italy spanning the years 1900 to 2019, we compare the goodness of fit and forecasting performance of the four nonlinear models. We then demonstrate the implications of nonlinearity in mortality modeling on the pricing of longevity bonds as a practical illustration of our findings. [ABSTRACT FROM AUTHOR]

This study uses disaggregated establishment-level data to identify a firm's exposure to physical climate risk and examines investors' reaction to natural disasters in both the U.S. corporate bond and stock markets. We find that, when a firm is exposed to disasters, investors overreact by depressing the current bond and stock prices, causing future returns to be higher. However, firms with a strong environmental profile experience lower selling pressure on their bonds and stocks, although their fundamentals weakened following disasters. The evidence suggests that corporate investment in improving environmental profiles pays off when climate change risk is materialized. This paper was accepted by Colin Mayer, Special Section of Management Science on Business and Climate Change. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2021.4018. [ABSTRACT FROM AUTHOR]

This study addresses the imminent threat of phosphorus (P) depletion, investigating anaerobically digested livestock manure as a high-concentration P alternative. To achieve this objective, Visual MINTEQ software, a general-purpose software used for chemical equilibrium modeling, was employed to simulate the alteration in P species fractions at different pH levels. The investigation further examined the variation in P release rates and electrical energy consumption across various pretreatment processes as influenced by pH levels. The results indicate a significant pH influence on P release, with enhanced efficacy under both acidic and alkaline conditions. At pH 2, total P concentration peaked at 684 mg·L−1, with 83.0% reactive P, in contrast with pH 10 conditions, which exhibited 504 mg·L−1 and 48.4%, respectively. P release increased with reaction time across all pretreatment processes. Sonication notably increased P release by 126.9%, with the highest reactive P release efficiency at 2.09 mg·L−1·Wh−1, emerging as an optimal process. Simulation results using Visual MINTEQ software indicate that the inclination for P release in alkaline conditions can be ascribed to the heightened presence of hydroxyapatite, brushite, and Ca-Fe (III)-phosphate bonds with rising pH levels. These simulation results, which are consistent with the experimental results, affirm the crucial influence of cations in determining P release on pH values. [ABSTRACT FROM AUTHOR]

This paper develops an approximation to arbitrage-free bond yields in Gaussian shadow rate term structure models. In this class of models, yields are constrained to be above an effective lower bound, thus rendering standard bond pricing methods inapplicable. I propose approximating the nonlinear relationship between yields and state variables using moments of the censored normal distribution. In an empirical application, this approximation technique is accurate to within a fraction of a basis point. As I show, minimizing the yield approximation error is crucial for model estimation as even seemingly small errors can lead to economically meaningful inference biases. [ABSTRACT FROM AUTHOR]

The structural complexity of glycans poses a serious challenge in the chemical synthesis of glycosides, oligosaccharides and glycoconjugates. Glycan complexity, determined by composition, connectivity, and configuration far exceeds what nature achieves with nucleic acids and proteins. Consequently, glycoside synthesis ranks among the most complex tasks in organic synthesis, despite involving only a simple type of bond-forming reaction. Here, we introduce the fundamental principles of glycoside bond formation and summarize recent advances in glycoside bond formation and oligosaccharide synthesis. [ABSTRACT FROM AUTHOR]

In this paper, an effective numerical method is proposed for a linear complementarity problem (LCP) arising in the valuation of American bond options under the Cox–Ingersoll–Ross (CIR) model. Firstly, a variable substitution is used to simplify the linear complementary model. Secondly, the finite difference method is adopted to discretize the simplified model, and an equivalent variational form is obtained. Based on the positive definiteness of the discretized matrix, a projection and contraction method (PCM) is adopted for the resulting discretized variational problem. Finally, numerical experiments highlight the effectiveness and performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This study examines the impacts of the US inflation rate on the bond prices of G7 countries across different maturities using inflation-induced equity market volatility (EMV) to better account for bond price determinants. The regression model, a GED-GARCH (1,1) procedure, is adopted to deal with the volatility clustering and fat tail features in bond return estimation. The testing results indicate that the inflation rate has a negative effect on bond returns across different maturities, although an exception occurs for longer maturities in Japan. Evidence shows that US inflation has a significant impact on bond returns for the non-US G7 countries. The negative effects from US inflation are more profound than those from the domestic market (expect in Japan). This study introduces the equity market volatility arising from inflation or the Fed's interest rate change; this variable produces market volatility that has a positive effect on bond returns, offsetting part of the original negative effect from a rise in inflation. [ABSTRACT FROM AUTHOR]

This paper models wealth concentration in 11 EU members from the CEE region using official data for the period between 1995 and 2021 and applies panel econometric methods. The analysis uses the world inequality database (WID.world) for deriving wealth distribution and inequality measures. Our results suggest that inequality and wealth concentration grow at the expense of the middle class and the poorer half of the population. Regression results suggest that the main contributors to wealth inequality are the Great Recession of 2008-2009, inflation, house prices, and bond prices, while GDP per capita, equity prices and various interest rates restore a more equal net wealth distribution. Other variables are also found to have direct or indirect (instrumental variables) associations with the wealth concentration (the dependent variables). [ABSTRACT FROM AUTHOR]

The layer bonding performance of hydraulic engineered cementitious composites (HECCs) plays an important role in their application in hydraulic buildings. This performance encompasses the bonding between layers of HECCs, as well as between HECCs and normal mortar (NM) layers. The influence of various factors on the layer bonding performance of HECCs was investigated. These factors included different pouring intervals (0 min, 20 min, 40 min, 60 min, 2.5 h, 7 days, 14 days, and 28 days), pouring directions (horizontal and vertical), degree of saturation (100%, 70%, 50%, 30%, and 0%), and surface roughness (varying sand-pour roughness). It was found that longer pouring interval times led to a decrease in the layer bonding performance, and the strength of the layer bonding fell below 50% compared to concrete without layers, with the lowest recorded strength being only 1.12 MPa. The layer's horizontal flexural strength surpassed the vertical flexural strength, but the horizontal compressive strength fell below the vertical compressive strength. Additionally, the bonding performance of the substrate at 0% saturation was 15–20% lower compared to other saturation levels. Notably, roughness significantly enhanced the performance of HECC layers, with improvements reaching a maximum of 180–200%. Furthermore, the layer performance of HECCs and NM experienced an improvement of 20.5–37.5%. [ABSTRACT FROM AUTHOR]

This paper analyzes the state-dependent volatility transmission mechanism between oil, stock, dollar, and bond prices to further examine the role of oil price uncertainty in financial markets. To this end, we extend the Diebold and Yilmaz (2014) spillover framework by incorporating a Markov-switching model and a Bayesian MCMC algorithm. We find that oil prices spills the highest degree of volatility to other markets during crises. The interdependence between the stock and oil markets is solid and stable, regardless of the regime shift. In contrast, the effect of oil price uncertainty on the foreign exchange or bond market during crises is double that during non-crisis periods. This suggests that oil price is closely related to other asset classes and reinforces its role as a risk transmitter during a crisis. [ABSTRACT FROM AUTHOR]

Due to their high lipophilicity and strong electron‐withdrawing property, more and more attention has been paid to introducing trifluoromethylseleno and fluoroalkylseleno moieties into organic molecules. In this short review, we categorize the synthesis of compounds that combine selenium and fluorinated moieties into two main types: trifluoromethylselenolation (CF3Se) and fluoroalkylselenolation (RfSe, except CF3Se). This review aims to provide a summary of the recent advances in direct C−H trifluoromethylselenolation and fluoroalkylselenolation from the synthesis of trifluoromethylselenolation and fluoroalkylselenolation reagents to their application. Based on the method of how the RfSe group was introduced, the main content is divided into three parts: transition‐metal‐free reactions, transition‐metal‐mediated/catalyzed reactions and photo‐catalyzed reactions. The general substrate scope, mechanism and limitations would also be discussed so that we hope the review will serve as an inspiration for further research in this appealing research field. [ABSTRACT FROM AUTHOR]

In this paper, we derive stochastic Leibniz formulas for Volterra integrals under enlarged filtrations. We investigate both pure-jump and Brownian Volterra processes under diverse initially enlarged filtration approaches. In these setups, we compare the ordinary with the stochastic (Doleans-Dade) exponential of a Volterra process and provide the corresponding martingale conditions. We also consider backward stochastic Volterra integral equations (BSVIEs) under enlarged filtrations and obtain the related solution formulas. We finally propose an anticipative Heath Jarrow Morton (HJM) forward rate model of Volterra-type and infer the associated bond price representation. In an introductory section, we compile various facts on deterministic and stochastic Leibniz formulas for parameter integrals. [ABSTRACT FROM AUTHOR]