Optimal Investment With Default Risk

In this paper, we investigate how investors who face both equity risk and credit risk would optimally allocate their financial wealth in a dynamic continuous-time setup. We model credit risk through the defaultable zero-coupon bond and solve the dynamics of its price after pricing it. Using stochastic control methods, we obtain a closed-form solution to this investment problem and characterize its variation with respect to different factors in the economy. We find that non-zero recovery rate of the credit-risky bond affects investors' decision in a fundamental way. Because of this, investors try to time the market conditions in their decision making process. It also induces hedging term in this setup of otherwise deterministic investment opportunity set. Through numerical examples, we show that the inclusion of credit market is shown to be able to enhance investors' welfare.Default Risk; Corporate Bond; Asset Allocation; Welfare Analysis

Intangible Capital, Corporate Valuation and Asset Pricing

Recent studies have found unmeasured intangible capital to be large and important. In this paper we observe that by nature intangible capital is also very different from physical capital. We find it plausible to argue that the accumulation process for intangible capital differs significantly from the process by which physical capital accumulates. We study the implications of this hypothesis for rational firm valuation and asset pricing using a two-sector general equilibrium model. Our main finding is that the properties of firm valuation and stock prices are very dependent on the assumed accumulation process for intangible capital. If one entertains the possibility that intangible investments translates into capital stochastically, we find that plausible levels of macroeconomic volatility are compatible with highly variable corporate valuations, P/E ratios and stock returns.intangible capital; corporate valuation; stock return volatility

Intangible capital, corporate valuation and asset pricing

Recent studies have found unmeasured intangible capital to be large and important. In this paper we observe that by nature intangible capital is also very different from physical capital. We find it plausible to argue that the accumulation process for intangible capital differs significantly from the process by which physical capital accumulates. We study the implications of this hypothesis for rational firm valuation and asset pricing using a two-sector general equilibrium model. Our main finding is that the properties of firm valuation and stock prices are very dependent on the assumed accumulation process for intangible capital. If one entertains the possibility that intangible investments translates into capital stochastically, we find that plausible levels of macroeconomic volatility are compatible with highly variable corporate valuations, P/E ratios and stock return

Estimating China’s Energy and Environmental Productivity Efficiency: A Parametric Hyperbolic Distance Function Approach

Since the beginning of this century, China’s annual GDP growth is over 9%. This growth is fueled by large increases in energy consumption, led by a coal-dominated energy structure, and associated with higher sulfur dioxide emissions and industry dust. In 2008, China accounted for over 17% of the world’s total primary energy consumption and accounts for nearly three-quarters of global energy growth. At an average annual energy growth rate over 12% since 2000, China’s future share of primary energy consumption will continue to increase. A consequence of this growth is China becoming the global leader in sulfur and carbon dioxide emissions. To deal with these energy and environmental challenges, the government set energy saving and pollution reduction target objectives in the 11th Five Year Plan (2006-2010): relative to 2005 by 2010, saving national energy use per unit of GDP by 20% and reducing the country’s primary pollution emissions by 10%. These targets were then disaggregated into energy saving targets for each province. With this disaggregated scheme, similar to country’s target, 20 provinces were assigned a 20% energy saving target, seven provinces were assigned targets below 20%, varying from 12% to 17%, and four provinces were given targets above 20%. These allocation were generally not guided by technical or economic efficiency, and thus may not be optimal from the perspectives of equity and efficiency. Historically less energy efficiency provinces may have more potential to reduce their energy consumption and pollution emissions, while higher efficiency provinces may have less potential. The major objective is to determine the optimal targets for each province required to comply with the national Five Year Plan target. A comparison of the estimated optimal with the current government targets will then reveal the value of incorporating economic theory into the decision calculation of setting disaggregate targets. Determining optimal targets requires consideration of both desirable and undesirable comes from alternative feasible targets. An objective is then to delineate these comes as criterion for selection. The procedure employed is a parametric hyperbolic distance function approach with a translog specification. This procedure provides the flexibility of using energy, labor, and capital stock as inputs to produce the desirable output (GDP) and the undesirable output (sulfur dioxide emissions). The procedure will address the objectives by simultaneously estimating both the desirable and undesirable comes. Specifically, the production frontier and environmental productivity efficiency are estimated for each province. The hyperbolic distance function enables the estimation of efficiency scores by incorporating all types of inputs and outputs, and only requires information on input and outputs quantities but not on prices, making it possible to model the emissions in the production process, given nonmarket characteristics of emissions. Based on these parametric estimations, the optimal targets are determined. The trajectory of obtaining these optimal targets for each province is determined by estimating how each province can improve its productive performance through increasing its desirable output and reducing its undesirable output, while simultaneously saving energy inputs. The results provide an empirical measurement of energy efficiency with maximum potential of energy saving for each province at a given technology considering the diverse economic, industry, and energy consumption patterns in the provinces. With a panel data of 29 provinces in China from 2000-2007, the hyperbolic distance function allows us to measure environmental productivity change over time, and then decompose this environmental productivity change into efficiency change, which is the movement toward the frontier, and technical change, which is the shift of the frontier. These further analyses help us identify potential different contributions of productivity growth for each province in China, and examine how the energy saving program will affect the environmental productivity growth for each province.environmental productivity efficiency, hyperbolic distance function, China's energy policy, Environmental Economics and Policy, Productivity Analysis, Resource /Energy Economics and Policy,

Intangible capital, corporate valuation and asset pricing

Recent studies have found unmeasured intangible capital to be large and important. In this paper we observe that by nature intangible capital is also very different from physical capital. We find it plausible to argue that the accumulation process for intangible capital differs significantly from the process by which physical capital accumulates. We study the implications of this hypothesis for rational firm valuation and asset pricing using a two-sector general equilibrium model. Our main finding is that the properties of firm valuation and stock prices are very dependent on the assumed accumulation process for intangible capital. If one entertains the possibility that intangible investments translates into capital stochastically, we find that plausible levels of macroeconomic volatility are compatible with highly variable corporate valuations, P/E ratios and stock returns

Indirect influence in social networks as an induced percolation phenomenon

Significance Increasing empirical evidence in diverse social and ecological systems has shown that indirect interactions play a pivotal role in shaping systems’ dynamical behavior. Our empirical study on collaboration networks of scientists further reveals that an indirect effect can dominate over direct influence in behavioral spreading. However, almost all models in existence focus on direct interactions, and the general impact of indirect interactions has not been studied. We propose a new percolation process, termed induced percolation, to characterize indirect interactions and find that indirect interactions raise a plethora of new phenomena, including the wide range of possible phase transitions. Such an indirect mechanism leads to very different spreading outcomes from that of direct influences

A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models

This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties: (1) the new search direction possesses not only a sufficient descent property but also a trust region feature; (2) the presented algorithm has global convergence for nonconvex functions; (3) the numerical experiment showed that the new algorithm is more effective than similar algorithms

Pre-training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding

The latest biological findings observe that the traditional motionless 'lock-and-key' theory is not generally applicable because the receptor and ligand are constantly moving. Nonetheless, remarkable changes in associated atomic sites and binding pose can provide vital information in understanding the process of drug binding. Based on this mechanism, molecular dynamics (MD) simulations were invented as a useful tool for investigating the dynamic properties of a molecular system. However, the computational expenditure limits the growth and application of protein trajectory-related studies, thus hindering the possibility of supervised learning. To tackle this obstacle, we present a novel spatial-temporal pre-training method based on the modified Equivariant Graph Matching Networks (EGMN), dubbed ProtMD, which has two specially designed self-supervised learning tasks: an atom-level prompt-based denoising generative task and a conformation-level snapshot ordering task to seize the flexibility information inside MD trajectories with very fine temporal resolutions. The ProtMD can grant the encoder network the capacity to capture the time-dependent geometric mobility of conformations along MD trajectories. Two downstream tasks are chosen, i.e., the binding affinity prediction and the ligand efficacy prediction, to verify the effectiveness of ProtMD through linear detection and task-specific fine-tuning. We observe a huge improvement from current state-of-the-art methods, with a decrease of 4.3% in RMSE for the binding affinity problem and an average increase of 13.8% in AUROC and AUPRC for the ligand efficacy problem. The results demonstrate valuable insight into a strong correlation between the magnitude of conformation's motion in the 3D space (i.e., flexibility) and the strength with which the ligand binds with its receptor

Combined Structure-Based Pharmacophore and 3D-QSAR Studies on Phenylalanine Series Compounds as TPH1 Inhibitors

Tryptophan hydroxylase-1 (TPH1) is a key enzyme in the synthesis of serotonin. As a neurotransmitter, serotonin plays important physiological roles both peripherally and centrally. In this study, a combination of ligand-based and structure-based methods is used to clarify the essential quantitative structure-activity relationship (QSAR) of known TPH1 inhibitors. A multicomplex-based pharmacophore (MCBP) guided method has been suggested to generate a comprehensive pharmacophore of TPH1 kinase based on three crystal structures of TPH1-inhibitor complex. This model has been successfully used to identify the bioactive conformation and align 32 structurally diverse substituted phenylalanine derivatives. The QSAR analyses have been performed on these TPH1 inhibitors based on the MCBP guided alignment. These results may provide important information for further design and virtual screening of novel TPH1 inhibitors

Identifying and assessing a prognostic model based on disulfidptosis-related genes: implications for immune microenvironment and tumor biology in lung adenocarcinoma

IntroductionLung cancer, with the highest global mortality rate among cancers, presents a grim prognosis, often diagnosed at an advanced stage in nearly 70% of cases. Recent research has unveiled a novel mechanism of cell death termed disulfidptosis, which is facilitated by glucose scarcity and the protein SLC7A11.MethodsUtilizing the least absolute shrinkage and selection operator (LASSO) regression analysis combined with Cox regression analysis, we constructed a prognostic model focusing on disulfidptosis-related genes. Nomograms, correlation analyses, and enrichment analyses were employed to assess the significance of this model. Among the genes incorporated into the model, CHRNA5 was selected for further investigation regarding its role in LUAD cells. Biological functions of CHRNA5 were assessed using EdU, transwell, and CCK-8 assays.ResultsThe efficacy of the model was validated through internal testing and an external validation set, with further evaluation of its robustness and clinical applicability using a nomogram. Subsequent correlation analyses revealed associations between the risk score and infiltration of various cancer types, as well as oncogene expression. Enrichment analysis also identified associations between the risk score and pivotal biological processes and KEGG pathways. Our findings underscore the significant impact of CHRNA5 on LUAD cell proliferation, migration, and disulfidptosis.ConclusionThis study successfully developed and validated a robust prognostic model centered on disulfidptosis-related genes, providing a foundation for predicting prognosis in LUAD patients