Description
– – – – – COVID-19 – – Logit; – – CECLIFRS 9CCAR – – 1500… – Understand the role of liquidity, equity and many other key banking features – Engineer and select features – Predict defaults, payoffs, loss rates and exposures – Predict downturn and crisis outcomes using pre-crisis features – Understand the implications of COVID-19 – Apply innovative sampling techniques for model training and validation – Deep-learn from Logit Classifiers to Random Forests and Neural Networks – Do unsupervised Clustering, Principal Components and Bayesian Techniques – Build multi-period models for CECL, IFRS 9 and CCAR – Build credit portfolio correlation models for VaR and Expected Shortfal – Run over 1,500 lines of pandas, statsmodels and scikit-learn Python code – Access real credit data and much more …
