The Experts below are selected from a list of 14439 Experts worldwide ranked by ideXlab platform
Raymond J Hawkins - One of the best experts on this subject based on the ideXlab platform.
-
corporate Default Behavior a simple stochastic model
Physical Review E, 2002Co-Authors: Ting Lei, Raymond J HawkinsAbstract:We compare observed temporal dynamics of corporate Default to a first-passage-time model and find that corporations Default as if via diffusive dynamics.
-
corporate Default Behavior a simple stochastic model
arXiv: Soft Condensed Matter, 2000Co-Authors: Ting Lei, Raymond J HawkinsAbstract:We compare observed corporate cumulative Default probabilities to those calculated using a stochastic model based on an extension of the work of Black and Cox and find that corporations Default as if via diffusive dynamics. The model, based on a contingent-claims analysis of corporate capital structure, is easily calibrated with readily available historical Default probabilities and fits observed Default data published by Standard and Poor's. Applying this model to the Standard and Poor's Default data we find that the difference in Default Behavior between credit ratings can be explained largely by a single variable: the "distance to Default" at the time the rating is given. The ability to represent observed Default Behavior by a single analytic expression and to differentiate credit-rating-dependent Default Behavior with a single variable recommends this model for a variety of risk management applications including the mapping of bank Default experience to public credit ratings.
Ting Lei - One of the best experts on this subject based on the ideXlab platform.
-
corporate Default Behavior a simple stochastic model
Physical Review E, 2002Co-Authors: Ting Lei, Raymond J HawkinsAbstract:We compare observed temporal dynamics of corporate Default to a first-passage-time model and find that corporations Default as if via diffusive dynamics.
-
corporate Default Behavior a simple stochastic model
arXiv: Soft Condensed Matter, 2000Co-Authors: Ting Lei, Raymond J HawkinsAbstract:We compare observed corporate cumulative Default probabilities to those calculated using a stochastic model based on an extension of the work of Black and Cox and find that corporations Default as if via diffusive dynamics. The model, based on a contingent-claims analysis of corporate capital structure, is easily calibrated with readily available historical Default probabilities and fits observed Default data published by Standard and Poor's. Applying this model to the Standard and Poor's Default data we find that the difference in Default Behavior between credit ratings can be explained largely by a single variable: the "distance to Default" at the time the rating is given. The ability to represent observed Default Behavior by a single analytic expression and to differentiate credit-rating-dependent Default Behavior with a single variable recommends this model for a variety of risk management applications including the mapping of bank Default experience to public credit ratings.
Im-yeong Lee - One of the best experts on this subject based on the ideXlab platform.
-
Survey of Digital Signature Technology for IoT Environment: Focused on KSI’s Global Timestamping Technique
Advances in Computer Science and Ubiquitous Computing, 2020Co-Authors: Gyeong-jin Ra, Im-yeong LeeAbstract:Digital signatures are security technologies that enable secure communication by providing user authentication, message integrity, and non-repudiation against electronic data in a network. The Default Behavior of a digital signature is to sign it through the signer’s own private key, and everyone can verify it through the public key. Digital signatures are an essential security element in networks and are being studied to suit various environments. With the recent industrial revolution in 4th decade, the advent of a super-connected society like IoT has increased the amount of data communication between networks. Therefore, electronic signature technology using DLT (Distributed Ledger Technology) is being studied as a secure and efficient electronic signature technology for distributed chains such as block chains. In this paper, we describe KSI (Keyless Signature Infrastructure), which is an electronic signature scheme using block chaining as well as various digital signature technologies. Then, the digital signature method is analyzed and compared, and the future direction of the digital signature is described.
-
survey of digital signature technology for iot environment focused on ksi s global timestamping technique
2018Co-Authors: Im-yeong LeeAbstract:Digital signatures are security technologies that enable secure communication by providing user authentication, message integrity, and non-repudiation against electronic data in a network. The Default Behavior of a digital signature is to sign it through the signer’s own private key, and everyone can verify it through the public key. Digital signatures are an essential security element in networks and are being studied to suit various environments. With the recent industrial revolution in 4th decade, the advent of a super-connected society like IoT has increased the amount of data communication between networks. Therefore, electronic signature technology using DLT (Distributed Ledger Technology) is being studied as a secure and efficient electronic signature technology for distributed chains such as block chains. In this paper, we describe KSI (Keyless Signature Infrastructure), which is an electronic signature scheme using block chaining as well as various digital signature technologies. Then, the digital signature method is analyzed and compared, and the future direction of the digital signature is described.
Liao Maozhong - One of the best experts on this subject based on the ideXlab platform.
-
a study on the occurrence mechanism model of Default Behavior of student borrowers in china
The Journal of Higher Education, 2010Co-Authors: Liao MaozhongAbstract:Lots of researches indicate that student loan Default is influenced by a great many factors.Whereas,how do these factors induce student Default? There has been some constraint to explain repayment Behavior mechanism with plan Behavior theory,so the paper constructs a ideal model for repayment Behavior choice of student borrowers.In this model,we found that repayment resources compose the matter bases of Behavior option,the repayment willingness is the dynamics of Behavior option,the repayment circumstance is the restraint mechanism,student borrowers' volition and real controlling abilities are the regulation mechanism of Behavior occurrence,the result from their Behavior option and social evaluation are the feedback mechanism of repayment Behavior.Thereby,the option of student repayment Behavior is an outcome of collective function by students' repayment willingness,repayment circumstance,available resources to repay,as well as the volition and controlling abilities of loan repayment Behavior.
Wanting Wang - One of the best experts on this subject based on the ideXlab platform.
-
how the small and medium sized enterprises owners credit features affect the enterprises credit Default Behavior
E3 Journal of Business Management and Economics, 2012Co-Authors: Wanting WangAbstract:Identifying and measuring credit risk of small and medium-sized enterprises should be different from that of large firms, for SMEs appear to be influenced by their owners more directly and significantly. This paper attempts to testify the relationship between Default Behaviors of SMEs and the credit features of their owners, so that a more appropriate and effective way of credit management of SMEs could be applied in practice. After segregating the owners’ characteristics data into variables of basic features, credit capacity features and credit will features, this paper implemented an empirical study of logistic regression analysis with repeat sampling data. The result demonstrates that, compared with the owners’ credit will variables, credit capacity features share more significant relationship with the SMEs’ credit Default Behavior. Specifically, the age of owner, the inquiry frequency of owners’ credit information for post-loan risk management and pro-loan approval purpose, and the proportion of overdue loans are the extreme significant variables which are valuable indicators in Default risk estimate model.
-
is the small and medium sized enterprises credit Default Behavior affected by their owners credit features
Mobile Adhoc and Sensor Systems, 2011Co-Authors: Rubing Yang, Xin Zhou, Wanting WangAbstract:Identifying and measuring credit risk of small and medium-sized enterprises should be different from that of large firms, for SMEs appear to be influenced by their owners more directly and significantly. This paper attempts to testify the relationship between Default Behaviors of SMEs and the credit features of their owners, so that a more appropriate and effective way of credit management of SMEs could be applied in practice. After segregating the owners' characteristics data into variables of basic features, credit capacity features and credit will features, this paper implement an empirical study of logistic regression analysis with repeat sampling data. The result demonstrates that, compare with the owners' credit will variables, variables reflected credit capacity features share more significant relationship with the SMEs' credit Default Behavior. Specifically, the age of owner, the inquiry frequency of owners' credit information for post-loan risk management and pro-loan approval purpose, and the proportion of overdue loans are the extreme significant variables which are valuable indicators in Default risk estimate model.
