The problem of accurately classifying credit scores is critical for financial institutions to assess individual creditworthiness and effectively manage credit risk. Traditional methods often face limitations when processing large datasets, resulting in lower accuracy and longer processing time. To address this...
Keywords: portfolio credit risk; intensity-based models; factor models, Value-at-Risk, conditional inde- pendent dependence modelling, saddlepoint-methods, Fourier-transform methods, numerical methods JEL Classification: G33; G13; C02; C63; G32 . 1. Introduction Consider a credit portfolio ...
In addition, the authors assess a novel approach to dealing with the asymmetrical nature of the data. With an accuracy rate of 91 %, the SVM is the most accurate ML model for identifying the fraudulent use of credit card events. The author's [16] research shows that by modelling ...
The underlying Python library is split into a number of major modules: Utils - These are utility functions used to assist you with modelling a security. These include dates (Date), calendars, schedule generation, some finance-related mathematics functions and some helper functions. Market - These...
A pdf manual describing all of the functions can be found in the project directory. Overview FinancePy is a python-based library that is currently in beta version. It covers the following functionality: Valuation and risk models for a wide range of equity, FX, interest rate and credit derivat...
A pdf manual describing all of the functions can be found in the project directory. Overview FinancePy is a python-based library that is currently in beta version. It covers the following functionality: Valuation and risk models for a wide range of equity, FX, interest rate and credit derivat...
A pdf manual describing all of the functions can be found in the project directory.OverviewFinancePy is a python-based library that is currently in beta version. It covers the following functionality:Valuation and risk models for a wide range of equity, FX, interest rate and credit derivatives...
A pdf manual describing all of the functions can be found at the same repository. The Library Design The underlying Python library is split into a number of major modules: Finutils - These are utility functions used to assist you with modelling a security. These include dates (FinDate), cal...
A pdf manual describing all of the functions can be found in the project directory. Overview FinancePy is a python-based library that is currently in beta version. It covers the following functionality: Valuation and risk models for a wide range of equity, FX, interest rate and credit derivat...
The underlying Python library is split into a number of major modules: Utils - These are utility functions used to assist you with modelling a security. These include dates (Date), calendars, schedule generation, some finance-related mathematics functions and some helper functions. ...