Run incentives in funds and banks
Models of first-mover advantage show when redemption or withdrawal terms encourage runs, and how swing pricing or deposit insurance change the incentive.
GRA · Financial Stability
Spatial financeWhere capital meets hazard, exposure and transition
Financial economics and macro-finance at Financial Stability
Financial economics explains how institutions fund themselves, price risk and respond to incentives. On this platform it supplies the theory behind runs, leverage cycles, liquidity spirals and moral hazard, and the reasoning that links regulation to behaviour.
01Register
Financial economics and macro-finance at Financial Stability on the record.
Method recordSTEM method
- MethodFinancial economics and macro-finance
- StewardFinancial Stability
- Applied inFinancial Stability
- Data4 inputs
- Checks3 validation steps
- Canonical pageSTEM Commons
02Application
What financial economics and macro-finance does here.
Financial economics and macro-finance study how asset prices, credit and financial institutions interact with the real economy. They explain how shocks are amplified or absorbed through balance sheets and markets. In financial stability, risk management and systemic risk and capital markets and investment, financial economics traces how physical, health or cyber shocks transmit to credit, sovereign debt and markets. It informs macroprudential policy and the pricing of risk. The canonical description is on the STEM Commons.
Leverage cycles
Margins and haircuts that loosen in booms and tighten in busts are analysed to show how they drive asset prices and credit together.
Implicit guarantees
Funding cost differences between large and small banks are studied to estimate the value creditors place on expected public support.
03Monitor
Econometric model.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Econometric model
Financial stability · Financial economics · Run R-8025
Estimates stableGRA · Financial Stability
Estimates
robust standard errors
| Credit-to-GDP gap | −0.04 | 0.16 | [−0.3, 0.6] | Yes |
| Countercyclical buffer | 0.56 | 0.07 | [−0.2, 0.7] | No |
| Systemic risk index | 0.51 | 0.10 | [−0.4, 0.4] | No |
| Household debt service ratio | 0.54 | 0.08 | [−0.5, 0.7] | Yes |
Method card
- Method
- Financial economics and macro-finance
- Sample
- 2093 obs
- Design
- panel, fixed effects
- Label
- MODELLED
Residuals by group
04Data
What the method consumes.
Datasets and records used by financial economics and macro-finance on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Bank and fund balance sheets | Funding structure | Published statistics |
| Market prices and spreads | Risk pricing | OBSERVED |
| Margin and haircut data | Leverage conditions | REPORTED |
| Fund flow data | Investor behaviour | REPORTED |
05Stress test
How a shock to assets becomes a system loss.
The equity the system loses after interbank contagion, against the initial hit, as leverage, interconnection and recovery rates change, the core of a macroprudential stress test. Teaching model with stated illustrative values, not a prediction.
Controls
- Fall in external assets
- 2.0%
- Leverage (assets over equity)
- 10 times
- Interbank share of assets
- 10%
- Recovery on interbank claims
- 40%
- Banks in the system
- 20
- Core banks
- 20% of banks
Readouts
- Equity lost to the initial shock
- 18.0%
- Equity lost after contagion
- 45.0%
- Added by contagion (DebtRank)
- 27.0 points
- Banks in default
- 0
Numbers, methods and sources
| Round | System equity lost (%) | Banks in default |
|---|---|---|
| 0 | 18.00 | 0 |
| 1 | 28.80 | 0 |
| 2 | 35.28 | 0 |
| 3 | 39.17 | 0 |
| 4 | 41.50 | 0 |
| 5 | 42.90 | 0 |
| 6 | 43.74 | 0 |
| 7 | 44.24 | 0 |
| 8 | 44.55 | 0 |
| 9 | 44.73 | 0 |
| 10 | 44.84 | 0 |
| 11 | 44.90 | 0 |
| 12 | 44.94 | 0 |
| 13 | 44.96 | 0 |
| 14 | 44.98 | 0 |
| 15 | 44.99 | 0 |
| 16 | 44.99 | 0 |
| 17 | 45.00 | 0 |
| 18 | 45.00 | 0 |
| 19 | 45.00 | 0 |
| 20 | 45.00 | 0 |
| 21 | 45.00 | 0 |
| 22 | 45.00 | 0 |
| 23 | 45.00 | 0 |
| 24 | 45.00 | 0 |
| 25 | 45.00 | 0 |
| 26 | 45.00 | 0 |
| 27 | 45.00 | 0 |
| 28 | 45.00 | 0 |
| 29 | 45.00 | 0 |
| 30 | 45.00 | 0 |
Methods
- DebtRank Battiston and others (2012), Scientific Reports 2:541
- Differential DebtRank Bardoscia and others (2015), PLOS ONE 10
- Contagion in financial networks Gai and Kapadia (2010), Proc. R. Soc. A 466
- Clearing in financial networks Eisenberg and Noe (2001), Management Science 47
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme's own evidence.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Financial Stability in Foundry
- Tested at Financial Stability in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Financial Stability in Reports
- Taught in Faculty of Finance and Economics in Academy
06Validation
How results are checked.
Models are back-tested against historical market episodes and crises. Results are compared with supervisory data and alternative specifications.
| Check | How it is done |
|---|---|
| Identification | Causal claims state how confounding factors were addressed |
| Out-of-sample episodes | Mechanisms are checked against episodes not used to build them |
| Institutional detail | Models reflect the actual contract terms and rules of the institutions studied |
Relationships estimated in calm periods may break down in stress. Hidden leverage and interconnections are often unobserved.
07Exposure, loss and capital
What it means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Transmission channels
How a shock in Financial economics and macro-finance at Financial Stability reaches credit, market, underwriting, liquidity and operational risk, and feeds back.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
09Stewardship
Who maintains the method.
Financial Stability stewards financial economics and macro-finance for the Consortium and reviews how it is applied across platforms.
10Questions
Questions and answers.
What are the limits of financial economics and macro-finance in this field?
Relationships estimated in calm periods may break down in stress. Hidden leverage and interconnections are often unobserved.
How are results checked?
Models are back-tested against historical market episodes and crises. Results are compared with supervisory data and alternative specifications.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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