An Alberta-based VAR Structural Model

International Financial Reporting Standards (IFRS) for loss allowances are changing, and financial institutions are proactively adapting existing methodologies and developing new ones to remain compliant. The main ingredient in the myriad of evaluations that banks are required to perform for compliance is risk assessment. The first goal of this research project is to review best practice risk models, with a special focus on modeling the evolution of changes in creditworthiness for industry sectors. In particular the project aims to estimate and forecast the probability a portfolio of loans’ changes in creditworthiness, and thus becomes more or less risky. State of the arts machine learning and time-series techniques are used to improve forecasting abilities of the existing models and allow for model validation using different forecasting samples.

Intern: 
Nathan Becker
Faculty Supervisor: 
Valentina Galvani;Sebastian Fossati Pereira
Province: 
Alberta
Partner: 
Partner University: 
Discipline: 
Program: