March 31 Workshop: Advanced Forecasting Using Hierarchical Models

Traditional statistical models apply a single set of coefficients by pooling a large dataset or for specific cohorts.

Hierarchical models learn from feature behavior across dimensions or timeframes.

Suhrud Dagli and Jing Liu host an informative workshop applying hierarchical models to a variety of mortgage and structured finance use cases, including:

• Changes in beta and covariance of portfolios across time
• Loan performance across geographies and history – e.g., combining credit performance data from 2008 with unemployment-driven credit issues in 2020.
• Issuer-level prepayment performance