Fall 2022 Hands-on Modeling Workshop
We would like to thank all participants for their active contributions to the workshops which helped to make the event truly productive for everyone involved!
Content
- Lectures combined with hands-on simulation exercises
- Exposition of the GIMM macroprudential modeling framework: equations, transimission mechanisms, key features
- Implementation of macroprudential policies in the framework
- Generating top-down stress-testing scenarios based on external scenario inputs
- Generating and analyzing financial cycles within the model
- Role of macroprudential policies in smoothing financial cycles
Benefits
Participants received the following:
- Complete modeling framework - equations, documentation, understanding of key transmission channels
- Commented codes - model files, simulation files, data files, reporting files
- Presentations
When and where
Dates: November 1–3, 2022
Place: Prague, Czech Republic
Detailed workshop content
Area 1: Introduction into GIMM macroprudential modeling framework
| TOPIC | CONTENT |
|---|---|
| Principles of macroprudential modeling | What is different in macroprudential modeling? Role of nonlinearities Macro-financial feedback loops Modeling macroprudentail policies Modularity of the framework |
| Framework introduction | Purpose, use cases Overview of the key blocks Overview of nonlinearities and feedback loops |
| Banking sector | Banking sector balance sheet Time evolution of a loan portfolio Credit risk and credit performance Portfolio segmentation |
| Credit risk | Credit risk, link to macro Credit risk and allowances Role of nonlinearities |
| Simulation: Credit performance shock | Basic shock to credit performance, impact on bank balance sheet |
| Interest rate setting | Stock-flow dynamics Forward-looking cost-plus pricing Credit risk and interest rates Price vs non-price lending conditions |
| Simulation: Credit performance shock, cont. | Impact on interest rates, lending conditions |
| Credit creation | Link between macro and credit Lending conditions Demand for new credit Credit market equilibrium Deleveraging - flows vs stocks |
| Simulation: Credit performance shock, cont. | Impact on credit creation |
| Bank capital | Bank capital accumulation Key P&L items Bank dividends, recapitalization Bank behavior under stress |
| Simulation: Credit performance shock, cont. | Impact on bank P&L, capital position |
| Macro-financial feedbacks | Linking the financial sector to macroeconomy Negative feedback loops Role of nonlinearities |
| Simulation: Credit performance shock, cont. | Impact on macroeconomy Role of nonlinearities |
| Model parameterization | Estimation vs calibration (Un)Feasibility of estimation Available strategies |
| Simulation: Boom-and-bust scenario | Irrational exuberance Boom and bust cycle Asset price cycle |
Area 2: Macroprudential policy simulations
| TOPIC | CONTENT |
|---|---|
| Capital-based policy tools | Modeling CAR-based regulation Leverage regulation |
| Simulations | Introducing capital buffers Estimating costs and benefits of capital-based policies Varying assumptions about recapitalization, retained earnings |
| Volume-based policy tools | Modeling credit caps Modeling DTI, DSTI limits |
| Simulations | Introducing credit caps Introducing DTI, DSTI |
| Credit gap (un)estimability | Feasibility of estimating financial cycle position Forecasting vs scenario building |
Area 3: Data-based simulations
| TOPIC | CONTENT |
|---|---|
| Delta method | Using data and macro forecast as inputs Building scenarios of top of macro baseline Using delta method in EBA-style stress-testing exercises |
| Simulation: Delta Method | Creating a downside scenario on top of macro baseline Introducing financial shocks on top of macro baseline |
| Simulation: Policy Interventions | Adding macroprudential interventions on top of macro baseline |