1. The role of a quantitative tool in Mtds analysis
UNCTAD, World Bank and IMF Workshop
Geneva, February

2. What is a risk model? Why is it useful?
Outline
What is a risk model? Why is it useful?
The structure of a simple scenario analysis model
Model input, engine and output
Description of the simulation process
Implementation issues
How are scenario models used in practice?
Off-the-shelf or in-house developed model?
Scenario analysis vs. stochastic modeling
Summary

3. What is a Model?
A “model” is a representation of a system for the purpose of studying it
A specific representation of something more general and usually more complex
We need a model to
understand the relationships between the components of a system
to predict how system will operate under a new policy or in a new environment

4. What MAY WE Need a Model: PROBLEM DEFINITION
Public Debt Management (PDM) uses bonds/bills/loans to meet financing needs of the government considering
the costs
the risks associated
and other macroeconomic policies
The objective is to find an “optimum” combination of debt (debt management strategy) in terms of
maturity (short vs. long term)
coupon structure (zero-coupon or coupon bonds)
interest type (fixed vs. floating rate)
currency (local vs. foreign)

5. What MAY WE Need a Model: PROBLEM DEFINITION
Complexities :
Objectives are conflicting
Borrowing short term is generally less costly,
but more risky
Uncertainty in
macroeconomic variables
market conditions

6. What MAY WE Need a Model?
In the area of public debt management, models can be used
to evaluate different strategies under alternative scenarios for future interest rates and exchange rates in a systematic analysis
Simplified representation of the debt process
to provide an understanding of the trade-off between cost and risk in the portfolio
requires clear definition of cost and risk
to help make decisions about the composition of public debt
Supports the identification and choice of indicators/targets

7. Risk Models in Debt Management
Models are widely used by debt managers to provide input to decision-making, and to better understand the cost and risk trade-offs
Provides supplement to qualitative analysis
A model should only contain elements that are needed to answer specific questions
Additional details => additional complexity

8. Is a Model Needed to Develop a Debt Strategy?
No, recent examples include
Indonesia, Peru, Colombia
In the above cases, the strategy was initially formulated as broad guidelines based on “intuition”
More domestic debt
Longer maturity etc.
A natural next step is providing more precision in the form of targets for specific risk indicators – this requires a model

9. The Structure of a Scenario Analysis Model
INPUT
Existing debt cash flows
Macro Variables
Primary fiscal balance
Structure of new debt
Borrowing strategy
Financial variables
- Exchange rates
- Interest rates
OUTPUT
Cost
Risk
ENGINE
Cash-flow

10. The Structure of a Scenario Analysis Model
How much to finance?
Funding needs
How to finance with which instruments? (Strategies)
Which instruments: maturity, currency type, interest rate type etc.
At what price to finance? (Scenarios)
Interest rates and exchange rates
Time Horizon and unit for cost measurement
Medium to long term time horizon
Local currency?

11. Basic Budget Arithmetic – the Foundation for the Scenario Analysis Model
Primary Balance
- Interest payments
= Fiscal Balance
- Principal payments
= Funding need
Future debt charges and redemptions – and therefore future funding needs – will depend on the borrowing actions as well as market rates
A higher than expected funding need can be the result of loose fiscal policy and/or higher market rates

12. INPUT: EXISTING DEBT CASH FLOWS
Cash flows based on outstanding balance as of a specific date (often end of previous fiscal year)
By currency
Domestic debt
Foreign currency debt (USD, EUR, JPY, etc)
By interest rate
Fixed
Floating
Information should be available from debt recording system

13. What are the future paths for the macro economy?
Input: Macroeconomic Variables In
What are the future paths for the macro economy?
Primary balance projections
Expenditure plans
Projected revenues
This will determine the new borrowing requirement
Projections for GDP growth and revenues if used for cost and risk indicators
These variables are usually exogenous (though some countries have tried to use structural models to link interest rates and GDP)

14. What is amount of new debt that needs to be issued?
Input: Structure of New Debt
What is amount of new debt that needs to be issued?
Primary balance
Maturing existing debt
Interest cost of existing debt
Maturing ‘new’ debt
Interest cost of ‘new’ debt
Assumption: Funding need fully covered by borrowing
Select a borrowing strategy: For example, all domestic, 50% 1 year / 50% 5 year

15. Scenarios for future market rates
Input: Financial Variables
Scenarios for future market rates
Exchange rates
E.g. existing rates, Interest Rate Parity etc.
Interest rate
E.g. existing rates, forward rates etc.
Among potential scenarios for future market rates a baseline scenario is chosen – this will function as the basis for measuring cost and risk
A sound design of the base scenario is vital for the risk analysis

16. Model Output: Cost and Risk
Risk Scenario 1
Risk1,X
Baseline Scenario
Cost1,X
Time

17. Cash Flow Simulation
Decide on the time frame of analysis, e.g. 5 years
The debt service flows generated by the baseline scenario for a given new debt issuance strategy will be defined as the expected cost
The sensitivity of a borrowing strategy to market rates can be analyzed by comparing cost and risk under alternative scenarios for market rates
Different borrowing strategies can be analyzed by comparing cost and risk for one or more risk scenarios for market rates

18. Example of Model Output
Interest to GDP, end of period
Debt to GDP, end of period
The above charts are based on the future cash flows generated by a model
Identifying the preferred strategy is typically difficult – different cost indicators will give different ranking

19. Using Debt Portfolio Modeling in Practice
Pre-requisites for modeling
High quality and timely data on the outstanding debt portfolio
Dedicated staff with good knowledge of spreadsheets and finance
Issues for modeling
Selection of market variable scenarios, or period of history for parameterizing a simulation, may be difficult when the economy has been through periods of instability
The process of developing a model represents a considerable investment

20. Typical Experiences from Working with Risk Modeling
Not the main basis for decision-making, rather a supplement to experience, sound judgment etc. – provide additional information for making better choices
Increase knowledge of the cost/risk trade offs
Requires dedicated resources, time-consuming
Clarifies framework for decision-making

21. Off-the-Shelf or In-House-Developed Model?
Model development requires
Adequate staff and software
Time – often trial and error
Focus on key person risk
Buying an off-the-shelf model is tempting, but supply is very limited – and will often imply acquiring a black box
The MTDS Analytical Tool

22. Deterministic vs. Stochastic Scenario Analysis
A simple deterministic scenario analysis model provides a basis for more advanced stochastic models
In stochastic models the number of market scenarios are increased from a few to several thousand
Allows quantification of cost and risk
Cost-at-Risk models are related to the VaR concept
“What is the maximum cost of the debt in a given year with a probability of 95%”

23. Summary
A scenario model provides input on the direction and magnitude of risks – requires clear definition of cost and risk
A simple scenario analysis model can provide input on
The costs and risks of the existing borrowing strategy
The choice between alternative borrowing strategies
Strategic targets can be derived from the cost/risk analysis
Trial and error process that is very time consuming
A simple scenario model provide the basis for more advanced Cost-at-Risk models

24. In LieU of Conclusion
“Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.
…all models are approximations. Essentially, all models are wrong, but some are useful.”
George E.P. Box

25. “A theory has only the alternative of being right or wrong
“A theory has only the alternative of being right or wrong. A model has a third possibility: it may be right, but irrelevant.”
Manfred Eigen

26. “I can never satisfy myself until I can make a mechanical model of a thing. If I can make a mechanical model, I can understand it. As long as I cannot make a mechanical model all the way through I cannot understand.”
William Thomson Kelvin

27. “Everything Should Be Made as Simple as Possible, But Not Simpler’
Attributed to Albert Einstein