Market RiskMarket Risk

Chapter 10

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K. R. Stanton

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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

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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

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Implications

Emphasizes importance of:

Measurement of exposure Control mechanisms for direct market risk—and

employee created risks Hedging mechanisms

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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.

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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

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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

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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)

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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.

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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%.

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Confidence Intervals: Example

Price volatility = (-MD) (Potential adverse change in yield)

= (-6.527) (0.00165) = -1.077%

DEAR = Market value of position (Price volatility)

= ($1,000,000) (.01077) = $10,770

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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

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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 M.

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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 + DEARb

2 + DEARc2

+ 2ab × DEARa × DEARb + 2ac × DEARa × DEARc + 2bc × DEARb × DEARc]1/2

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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.

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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.

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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.

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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.

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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.

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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.

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BIS Model

Specific 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

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Web Resources

For information on the BIS framework, visit:

Bank for International Settlement www.bis.org

Federal Reserve Bank www.federalreserve.gov

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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.

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Pertinent Websites

American Banker www.americanbanker.com

Bank of America www.bankofamerica.com

Bank for International Settlements www.bis.org

Federal Reserve www.federalreserve.gov

J.P.Morgan/Chase www.jpmorganchase.com

RiskMetrics www.riskmetrics.com