2. Overview
This chapter discusses the nature of market risk and appropriate measures
Dollar exposure
RiskMetrics
Historic or back simulation
Monte Carlo simulation
Links between market risk and capital requirements

3. Trading exposes banks to risks
Trading Risks
Trading exposes banks to risks
1995 Barings Bank
1996 Sumitomo Corp. lost $2.6 billion in commodity futures trading
1997 market volatility in Eastern Europe and Asia
1998 continuation with Russian bonds
AllFirst/ Allied Irish $691 million loss
Partly preventable with software
Rusnak currently serving 7 ½ year sentence for fraud
Allfirst sold to Buffalo based M&T Bank

4. Emphasizes importance of:
Implications
Emphasizes importance of:
Measurement of exposure
Control mechanisms for direct market risk—and employee created risks
Hedging mechanisms

5. Market Risk
Market risk is the uncertainty resulting from changes in market prices .
Affected by other risks such as interest rate risk and FX risk
It can be measured over periods as short as one day.
Usually measured in terms of dollar exposure amount or as a relative amount against some benchmark.

6. Market Risk Measurement
Important in terms of:
Management information
Setting limits
Resource allocation (risk/return tradeoff)
Performance evaluation
Regulation
BIS and Fed regulate market risk via capital requirements leading to potential for overpricing of risks
Allowances for use of internal models to calculate capital requirements

7. Calculating Market Risk Exposure
Generally concerned with estimated potential loss under adverse circumstances.
Three major approaches of measurement
JPM RiskMetrics (or variance/covariance approach)
Historic or Back Simulation
Monte Carlo Simulation

8. JP Morgan RiskMetrics Model
Idea is to determine the daily earnings at risk = dollar value of position × price sensitivity × potential adverse move in yield or,
DEAR = Dollar market value of position × Price volatility.
Can be stated as (-MD) × adverse daily yield move where,
MD = D/(1+R)
Modified duration = MacAulay duration/(1+R)

9. Confidence Intervals
If we assume that changes in the yield are normally distributed, we can construct confidence intervals around the projected DEAR. (Other distributions can be accommodated but normal is generally sufficient).
Assuming normality, 90% of the time the disturbance will be within 1.65 standard deviations of the mean.

10. Confidence Intervals: Example
Suppose that we are long in 7-year zero-coupon bonds and we define “bad” yield changes such that there is only 5% chance of the yield change being exceeded in either direction. Assuming normality, 90% of the time yield changes will be within 1.65 standard deviations of the mean. If the standard deviation is 10 basis points, this corresponds to 16.5 basis points. Concern is that yields will rise. Probability of yield increases greater than 16.5 basis points is 5%.

11. Confidence Intervals: Example
Price volatility = (-MD)  (Potential adverse change in yield)
= (-6.527)  ( ) = %
DEAR = Market value of position  (Price volatility)
= ($1,000,000)  (.01077) = $10,770

12. Confidence Intervals: Example
To calculate the potential loss for more than one day:
Market value at risk (VARN) = DEAR × N
Example:
For a five-day period,
VAR5 = $10,770 × 5 = $24,082

13. Foreign Exchange & Equities
In the case of Foreign Exchange, DEAR is computed in the same fashion we employed for interest rate risk.
For equities, if the portfolio is well diversified then
DEAR = dollar value of position × stock market return volatility where the market return volatility is taken as 1.65 sM.

14. Aggregating DEAR Estimates
Cannot simply sum up individual DEARs.
In order to aggregate the DEARs from individual exposures we require the correlation matrix.
Three-asset case:
DEAR portfolio = [DEARa2 + DEARb2 + DEARc2 + 2rab × DEARa × DEARb + 2rac × DEARa × DEARc + 2rbc × DEARb × DEARc]1/2

15. Historic or Back Simulation
Advantages:
Simplicity
Does not require normal distribution of returns (which is a critical assumption for RiskMetrics)
Does not need correlations or standard deviations of individual asset returns.

16. Historic or Back Simulation
Basic idea: Revalue portfolio based on actual prices (returns) on the assets that existed yesterday, the day before, etc. (usually previous 500 days).
Then calculate 5% worst-case (25th lowest value of 500 days) outcomes.
Only 5% of the outcomes were lower.

17. Estimation of VAR: Example
Convert today’s FX positions into dollar equivalents at today’s FX rates.
Measure sensitivity of each position
Calculate its delta.
Measure risk
Actual percentage changes in FX rates for each of past 500 days.
Rank days by risk from worst to best.

18. Weaknesses
Disadvantage: 500 observations is not very many from statistical standpoint.
Increasing number of observations by going back further in time is not desirable.
Could weight recent observations more heavily and go further back.

19. Monte Carlo Simulation
To overcome problem of limited number of observations, synthesize additional observations.
Perhaps 10,000 real and synthetic observations.
Employ historic covariance matrix and random number generator to synthesize observations.
Objective is to replicate the distribution of observed outcomes with synthetic data.

20. BIS (including Federal Reserve) approach:
Regulatory Models
BIS (including Federal Reserve) approach:
Market risk may be calculated using standard BIS model.
Specific risk charge.
General market risk charge.
Offsets.
Subject to regulatory permission, large banks may be allowed to use their internal models as the basis for determining capital requirements.

21. BIS Model Specific risk charge: General market risk charge:
Risk weights × absolute dollar values of long and short positions
General market risk charge:
reflect modified durations  expected interest rate shocks for each maturity
Vertical offsets:
Adjust for basis risk
Horizontal offsets within/between time zones

22. Web Resources
For information on the BIS framework, visit:
Bank for International Settlement
Federal Reserve Bank

23. Large Banks: BIS versus RiskMetrics
In calculating DEAR, adverse change in rates defined as 99th percentile (rather than 95th under RiskMetrics)
Minimum holding period is 10 days (means that RiskMetrics’ daily DEAR multiplied by 10)*.
Capital charge will be higher of:
Previous day’s VAR (or DEAR  10)
Average Daily VAR over previous 60 days times a multiplication factor  3.
*Proposal to change to minimum period of 5 days under Basel II, end of 2006.

24. Pertinent Websites
American Banker
Bank of America
Bank for International Settlements
Federal Reserve
J.P.Morgan/Chase
RiskMetrics