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BUFN 722
ch-10
Market Risk
BUFN722- Financial Institutions ch10 - 1
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
BUFN722- Financial Institutions ch10 - 2
Market Risk:
• Market risk is the uncertainty resulting from
changes in market prices . 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.
BUFN722- Financial Institutions ch10 - 3
Market Risk Measurement
• Important in terms of:
Management information
Setting limits
Resource allocation (risk/return tradeoff)
Performance evaluation
Regulation
BUFN722- Financial Institutions ch10 - 4
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
BUFN722- Financial Institutions ch10 - 5
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)
BUFN722- Financial Institutions ch10 - 6
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.
BUFN722- Financial Institutions ch10 - 7
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%.
BUFN722- Financial Institutions ch10 - 8
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
Note if MD = -6.527, what is R?
BUFN722- Financial Institutions ch10 - 9
Confidence Intervals: Example
• To calculate the potential loss for more than
one day:
Market value at risk (VAR) = DEAR × N
• Example:
For a five-day period,
VAR = $10,770 × 5 = $24,082.45
BUFN722- Financial Institutions ch10 - 10
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.
BUFN722- Financial Institutions ch10 - 11
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
BUFN722- Financial Institutions ch10 - 12
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.
BUFN722- Financial Institutions ch10 - 13
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.
BUFN722- Financial Institutions ch10 - 14
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.
BUFN722- Financial Institutions ch10 - 15
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.
BUFN722- Financial Institutions ch10 - 16
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.
BUFN722- Financial Institutions ch10 - 17
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.
BUFN722- Financial Institutions ch10 - 18
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
BUFN722- Financial Institutions ch10 - 19
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.
BUFN722- Financial Institutions ch10 - 20
Overview
• The Corporate Treasurer’s Financial Risk
Management Problem- Manage Risk – Not
avoid it
The Market Value of the Firm and Channels of Risk
• Accounting Measures of Foreign Exchange
Exposure
Exposure of the Balance Sheet: Translation
Exposure
Exposure of the Income Statement: Transaction
Exposure
U.S. Accounting Conventions: Reporting
BUFN722- Financial Institutions ch10 - 21
Accounting Gains and Losses
Overview
• Economic Measures of Foreign Exchange
Exposure
The Regression Approach
The Scenario Approach
• Empirical Evidence on Firm Profits, Share
Prices, and Exchange Rates
• Arguments for Hedging Risks at the
Corporate Level
BUFN722- Financial Institutions ch10 - 22
Overview
• Financial Strategies Toward Risk Management
The Currency Profile and Suitable Financial
Hedging Instruments
• Policy Issues - International Financial Managers
Problems in Estimating Economic Exposure
Picking an Appropriate Hedge Ratio
The International Investor’s Currency Risk
Management Problem
The Value at Risk Approach
BUFN722- Financial Institutions ch10 - 23
Overview
• Policy Issues - Public Policymakers
Disclosure of Financial Exposure
Financial Derivatives and Corporate Hedging
Policies
BUFN722- Financial Institutions ch10 - 24
The Corporate Treasurer’s
Financial Risk Management Problem
• Corporate treasurers are directly responsible
for managing the firm’s exposure to
financial risk.
• The risks that remain are held by the
investor, who can reduce these risks through
a diversified portfolio of shares, or by
applying some of the same hedging
techniques available to the corporate
treasurer.
BUFN722- Financial Institutions ch10 - 25
• Credit risk Types of Risk
• Risk of default or failure of borrower or counterparty;
unwilling to service loan; e.g., 1998 Russia 90-day
moratorium on debt pay.
• Market risk
• Adverse changes in market prices, rates, exchange rates
• Liquidity risk
• Cash flows not sufficient to meet bank’s financial
commitments
• Interest rate risk
• Earnings & returns fluctuate with changes in interest rates
• Operational risk
• Potential losses due to breakdown in information,
communication, transaction processing, settlement systems,
fraud, unauthorized transactions by employees
• Cross-border risk
BUFN722- Financial Institutions ch10 - 26
Credit Risk Management
• Screening
• Monitoring
• Long-term customer relationships
• Loan commitments
• Collateral
• Compensating balances
• Credit rationing
BUFN722- Financial Institutions ch10 - 27
Market Risk Management
The Value at Risk (VAR) Approach
The VAR approach is a relatively new approach for
measuring the exposure of financial assets.
It can be applied to any portfolio of assets (and
liabilities) whose market values are available on a
periodic basis and whose price volatilities (s) can
be estimated.
Assuming normal price distributions, calculate the
loss in value of the portfolio if an unlikely (say, 5%
chance) adverse price movement occurs. The result
of this calculation is the value at risk.
BUFN722- Financial Institutions ch10 - 28
Value at Risk (VAR)
• Value at Risk
• Estimates the largest expected loss to a particular
investment position for a specified confidence
level
• Applying Value At Risk
Deriving The Maximum Dollar Loss
• VAR = estimated potential loss from its trading
business that could result from adverse
movements in market prices.
Common Adjustments To The Value-At-Risk
Applications
BUFN722- Financial Institutions ch10 - 29
VAR
VAR is a risk measurement that estimates the largest expected loss to a
particular investment position for a specified confidence level. This method
became popular in the late 1990s after some mutual funds & pension funds
experienced abrupt large losses. VAR is intended to warn investors about
potential maximum loss that could occur. If investors are uncomfortable
with the potential loss that could occur in a day or week, they can revise
their investment portfolio to make it less risky.
VAR focuses on pessimistic portion of probability distribution of returns from
the investment of concern. E.g., a port. mgr. Uses a 90% confidence level,
which estimates the max. daily expected loss to an asset in 90% of the
trading days over an upcoming period. The higher the confidence level
desired, the larger the maximum expected loss that might occur for a given
type of investment. E.g., one may expect that the daily loss from holding a
particular asset won’t be worse than -5% when using a 90% confidence level
& < -8% if a 99% confidence level.In essence the more confidence
investors have that the actual loss won’t be > the expected maximum loss,
the further they move into the left tail of the probability distribution.
VAR is also used to measure risk of a portfolio. Some assets have high risk when assessed
individually, but low risk when part of a portfolio because the likelihood of a large loss
probabilities of simultaneous losses in all ofch10 - 30
in the port. Is influenced by theBUFN722- Financial Institutions the
component assets for the period of concern.
• More precisely, VaR measures the worst possible loss that
Applying Value at Risk
a bank could expect to suffer over a given time interval,
under normal market conditions, at a given confidence
level. E.g., a bank might calculate that the daily VaR of its
trading portfolio is $35 million at a 99% confidence
interval. This means that there is only 1 chance in 100 that
a loss > $35 million would occur on any given day. Note:
this is NOT a maximum loss; e.g., if a bank regularly
measures VaR at the 99% confidence level, the actually
losses should exceeds its estimate 1% of the time, or 1 day
out of 100.
• Methods of determining the maximum expected loss
Use of historical returns
• Example: count the percentage of days an asset drops a certain
level
BUFN722- Financial Institutions ch10 - 31
Use of standard deviation
Applying Value at Risk
• Deriving the maximum dollar loss
Apply the maximum percentage loss to the
value of the investment
• Common adjustments to the value-at-risk
applications
Investment horizon desired
Length of historical period used
Time-varying risk
Restructuring the investment portfolio
BUFN722- Financial Institutions ch10 - 32
• Easy toWidespread usage of VaR
understand
1. BIS meeting at Basel in 1995, at which major
central banks amended the 1988 accord requiring
financial institutions to hold capital against their
exposure to market risk; this created an incentive
for banks to develop sophisticated internal risk
measurement systems to calculate VaR and thus
avoid more regulatory requirements. Therefore, in
1998, large banks with substantial trading
businesses began using their own internal measures
of market risk to adjust their capital requirements.
They use a VAR model, usually with a 99 percent
confidence interval
2. JP Morgan made its RiskMetrics system available
BUFN722- the Institutions
free from charge overFinancialInternet; this systemch10 - 33
Regulation of Capital
Testing the validity of a bank’s VAR
• Uses backtests with actual daily trading gains or
losses
• If the VAR is estimated properly, only 1 percent of
the actual trading days should show results worse
than the estimated VAR
Related stress tests
• Bank identifies a possible extreme event to estimate
potential losses
BUFN722- Financial Institutions ch10 - 34
Exact computation of VaR depends on
assumptions about:
• Distribution of price changes, normal or otherwise
• Extent to which today’s change in the price of an
asset may be correlated to past price changes
• Extent to which the characteristics of mean U and
standard deviation (volatility) are stable over time
• Relationship between 2 or more different price
moves
• Data series to which these assumptions apply.
• Financial managers use historical market data on
BUFN722- Financial Institutions ch10 - 35
various financial asses to create their VaR model.
JP Morgan’s VaR
• Maximum estimated losses in the market
value of a given position that may be
incurred before the position is neutralized or
reassessed.
• VaRx = Vx x dV/dP x Dpi
Vx = market value of position x
dV/dP = sensitivity to price move per $
market value
Dpi = adverse price movement over time i;
e.g, if the time horizon is one day, then VaR
BUFN722- Financial Institutions ch10 - 36
becomes daily earnings at risk
JP Morgan’s assumptions in its measure of
VaR
• Prices of financial instruments follow a
stable random walk; thus, price changes are
normally distributed
• Price changes are serially uncorrelated;
there is no correlation between change
today and changes in the past
• Standard deviation (volatility) of price or
rate changes is stable over time; i.e., past
movements may be used to characterize
future movements.
• Interrelationships between 2 different price
movements follow a joint normal
BUFN722- Financial Institutions ch10 - 37
Drawbacks of VaR
• Markets are NOT normal
• Portfolios are non-linear
• Volatility is NOT constant
• Markets move together but no one knows
how
BUFN722- Financial Institutions ch10 - 38
Portfolio Stress Testing
• Technique that relies on computer modeling of different
scenarios and computation of results of those scenarios on a
bank’s portfolio.
• E.g., Sept 11 bombing of WTC; political assassination
• E.g., Mexican peso devalued by 30%.
• All assets in portfolio are revalued using new environment,
creating a new estimate for the return on the portfolio
• Many such scenarios lead to many such exercise, so that a range
of values for return on the portfolio is derived
• By specifying the probability for each scenario, mangers can
then generate a distribution of portfolio returns, from which
VaR can be measured
• The advantage of this method is that it allows risk managers to
evaluate possible scenarios that may be completely absent from
historical data.
• Chase management devised an incentive package that reduced
compensation if risk taking did not lead to appropriate rewards,
BUFN722- Financial Institutions ch10 - 39
helping it create a more conservative risk portfolio overall.
Flaws of stress testing
• Subjective- difficult to brainstorm scenarios
that have never occurred
• Choice of scenarios may be affected by
bank’s portfolio position, itself – where
portfolio is invested
• Poor handling of correlations – stress testing
examines effect of a large movement on one
financial variable at a time, so it is not well
suited to large, complex portfolios such as
those held by international banks.
• Stress testing is supplement to VaR, not a
replacement BUFN722- Financial Institutions ch10 - 40
BIS 2000 Study on Stress Testing
• Financial institutions relied mostly on four
different techniques in stress testing (technique
and “stress test result”)
1. Simple sensitivity test
Change in portfolio value for 1 or more shocks to a single
risk factor
2. Scenario analysis
Change in portfolio value if scenario were to occur
(historical or hypothetical)
3. Maximum loss
Sum of individual trading units’ worst case scenarios
4. Extreme value theory
BUFN722- Financial Institutions ch10 - 41
Probability distribution of extreme losses
Operational Risks
• Most difficult to quantify
• “Rogue trader” losses
• Risk of computer or telephone outage
disrupting operations systems in critical
areas
• Best safeguard is internal control.
BUFN722- Financial Institutions ch10 - 42
• GAP = RSA – RSLInterest Rate Risk
• Repricing or funding gap
GAP: the difference between those assets whose interest
rates will be repriced or changed over some future period
(RSAs) and liabilities whose interest rates will be repriced or
changed over some future period (RSLs
• Rate Sensitivity
the time to reprice an asset or liability
a measure of an FI’s exposure to interest rate changes in
each maturity “bucket”
GAP can be computed for each of an FI’s maturity buckets
• Multiply GAP times change in interest rate reveals effect
on bank income
• Alternative method: Duration gap analysis examines
sensitivity of market value of financial institution’s net
interest rates; duration measuresch10 - 43
worth to changes in BUFN722- Financial Institutions
Calculating GAP for a Maturity Bucket
DNIIi = (GAP)j Dij = (RSAj - RSLj) Dij
where
DNIIj = change in net interest income in the ith
maturity bucket
GAPj = dollar size of the gap between the book
value of rate-sensitive assets and rate-
sensitive liabilities in maturity bucket i
Dij = change in the level of interest rates
impacting assets and liabilities in the
jth maturity bucket
BUFN722- Financial Institutions ch10 - 44
Duration Model
Duration gap - a measure of overall interest rate
risk exposure for an FI
D = - %D in market value of a security
D i/(1 + i)
BUFN722- Financial Institutions ch10 - 45
Policy Issues - Public Policymakers
Disclosure of Financial Exposure
The possibility that individual firms may face
substantial exposure to exchange rate changes,
as well as the increased trading in financial
derivatives in recent years, create a genuine
concern among investors and regulators
regarding corporate exposure to financial risks.
Note that a firm without a financial position
may still face substantial currency and interest
rate risk due to its ongoing operations.
BUFN722- Financial Institutions ch10 - 46
Policy Issues - Public Policymakers
Financial Derivatives and Corporate Hedging
Policies
The findings of various studies were consistent
with the notion that firms used derivatives to
lower the variability of their cash flows or
earnings.
It was also found that the likelihood of using
derivatives was positively related to foreign
pretax income, foreign sales, and foreign-
denominated debt.
BUFN722- Financial Institutions ch10 - 47
The Market Value of the Firm
• The market value of a firm at time t (MVt) is
the summation of the firm’s cash flows
(CF) over time discounted back to their
present value by an appropriate discount
T
factor (i): CFt
MVt
t 0 it
t
1
• Cash flows in each currency are discounted at
their own appropriate interest rate and
multiplied by a spot exchange rate.
BUFN722- Financial Institutions ch10 - 48
The Market Value of the Firm
• The sensitivity of the market value of the
firm to a change in an exchange rate
measures exchange rate exposure.
• For the $/€ exchange rate, the sensitivity
measure can be expressed as:
MV
S$ / €
BUFN722- Financial Institutions ch10 - 49
Channels of Exposure to
Foreign Exchange Risk
Direct Economic Home Currency Home Currency
Exposure Strengthens Weakens
Sales Abroad Unfavorable Favorable
Revenue worth less Revenue worth
in home currency more
terms
Source Abroad Favorable Unfavorable
Inputs cheaper in Inputs more
home currency expensive
terms
Profits Abroad Unfavorable Favorable
Profits worth less Profits worth more
BUFN722- Financial Institutions ch10 - 50
Channels of Exposure to
Foreign Exchange Risk
Indirect Economic Home Currency Home Currency
Exposure Strengthens Weakens
Competitor that Unfavorable Favorable
sources abroad Competitor’s Competitor’s
margins improve margins decrease
Supplier that Favorable Unfavorable
sources abroad Supplier’s margins Supplier’s margins
improve decrease
Customer that Unfavorable Favorable
sells abroad Customer’s margins Customer’s
decrease margins improve
Customer that Favorable Unfavorable
sources abroad Customer’s margins Customer’s margins
improve decrease
BUFN722- Financial Institutions ch10 - 51
The Market Value of the Firm and Channels of Risk
• Note that virtually any firm could be exposed to
exchange rate risk through a financial channel.
• In the long run however,
The firm can make changes in response to an
unexpected exchange rate change.
Other economic events that follow the exchange rate
change may lessen the impact on the firm.
• Nevertheless, the short-run exposure is critical
since the firm must survive the shock to get to the
long run.
BUFN722- Financial Institutions ch10 - 52
Accounting Measures of
Foreign Exchange Exposure
• Net = exposed – liabilities exposed
exposure assets
• Accounting exposure can be subdivided into
translation and transaction exposures.
• Translation exposure focuses on the book
value of assets and liabilities as measured in
the firm’s balance sheet.
• Transaction exposure focuses on the economic
value of transactions denominated in foreign
currency that are planned or forecast to occur
in the next reporting period.
BUFN722- Financial Institutions ch10 - 53
U.S. Accounting Conventions
Reporting Accounting Gains and Losses
• Under Statement 52 of the Financial Accounting
Standards Board (FASB-52), translation gains and
losses are accumulated in a translation adjustment
account.
• FASB-52 focuses on a parent’s net investment in a
foreign operation to measure the effect of
exchange rate changes.
• Transaction gains and losses represent realized
exchanges and are reported in current income.
• Under FASB-133, derivatives that do not qualify
as hedges of the underlying exposures must be
marked-to-market, with the resulting gains or
losses included in either current or deferred
BUFN722- Financial Institutions ch10 - 54
income.
Economic Measures of
Foreign Exchange Exposure
• Economic exposure captures the entire
range of effects on the future cash flows of
the firm, including the effects of exchange
rate changes on customers, suppliers, and
competitors.
• MV/S reflects economic exposure. Two
approaches for measuring economic
exposure are the regression approach and
the scenario approach.
BUFN722- Financial Institutions ch10 - 55
The Regression Approach
• The regression approach directly measures
the exposure of a firm to exchange rate
changes by estimating the relationship
between the firm’s market value at time t
(MVt)and the spot rate (St) using the
equation:
MVt = a + b St + et
• The coefficient b measures the sensitivity of
the market value of the firm to the exchange
BUFN722- Financial Institutions ch10 - 56
rate.
The Regression Approach
• To interpret the regression analysis, three results need
to be examined:
The magnitude of b.
• b > 0 an asset exposure in the foreign currency
• b < 0 a liability exposure
• b = 0 no exposure to the exchange rate
The t-statistic of b.
• Statistical significance is necessary for confidence in
the results.
The R2 of the regression.
• R2 measures the percentage of variation in the market
value explained by the exchange rate.
BUFN722- Financial Institutions ch10 - 57
The Regression Approach
• To measure the firm’s exposure to multiple exchange
rates, a multiple regression can be estimated:
MVt = a + b1 S$/€,t + b2 S$/£,t + b3 S$/¥,t + et
• If the firm has data on cash flows at the level of a
subsidiary or project, the exposure of these smaller
units can also be measured:
CFt = a + b St + et
• Note that exposure tends to be lower in the long run
due to PPP (which tends to hold better in the longer
run) and the ability of firms to make adjustments in
response to exchange rate changes.
BUFN722- Financial Institutions ch10 - 58
The Scenario Approach
• Given a scenario, we can estimate the firm’s
cash flows (and its market value)
conditional on an exchange rate path.
• The scenario approach is well suited to a
spreadsheet analysis where one is
encouraged to ask a variety of “what-if”
questions.
BUFN722- Financial Institutions ch10 - 59
The Scenario Approach
Consider the impact of a permanent 5% appreciation of the US$,
holding all other factors constant.
Present Value of Cash Flows
(Millions)
A*
The slope measures the
exposure of the firm at
the initial exchange rate.
$39.577
$35.222 O
A
- 15% - 10% - 5% 5% 10% 15%
$/A$ $0.5435 $0.5682 $0.5952 $0.6250 $0.6563 $0.6875 $0.7188
A$/$ A$1.84 A$1.76 A$1.68 A$1.60 A$1.52 A$1.45 A$1.39
BUFN722- Financial Institutions ch10 - 60
The Scenario Approach
Suppose the firm can pass along part of the exchange rate change
to its Australian customers.
Present Value of Cash Flows
(Millions)
A*
The slope of BOB* is flatter
than AOA* since the firm has B*
less exposure now.
$39.577
$35.222 O
B
A
- 15% - 10% - 5% 5% 10% 15%
$/A$ $0.5435 $0.5682 $0.5952 $0.6250 $0.6563 $0.6875 $0.7188
A$/$ A$1.84 A$1.76 A$1.68 A$1.60 A$1.52 A$1.45 A$1.39
BUFN722- Financial Institutions ch10 - 61
Empirical Evidence on
Firm Profits, Share Prices, & Exchange Rates
• During the Bretton Woods pegged-rate
period, the general stock market index
tended to move up (down) immediately
after a devaluation (revaluation) of the local
currency.
• Studies also indicated that exposure
coefficients vary from firm to firm within
the same industry and over time, and that
exchange rate changes can have a
substantial impact on the overall economy.
BUFN722- Financial Institutions ch10 - 62
Arguments for
Hedging Risks at the Corporate Level
• Shareholders may not favor hedging since they can select
well-diversified portfolios to rid themselves of firm-
specific risks.
• However, in view of transaction costs and taxes, hedging
that reduces the volatility of cash flows may be favored.
If the tax credits of a firm which has incurred losses over
several successive periods cannot be carried forward to
reduce future tax payments, then another firm with a less
volatile pattern of earnings will enjoy greater after-tax cash
flows and a higher market value.
A firm with more volatile cash flows is also more open to
the costs of financial distress.
• For the same reasons, banks and bondholders will prefer
firms with less volatile cash flows (holding average cash
flows equal) and reward them with greater borrowing - 63
ch10
capacities and higher credit ratings.
Financial Strategies
Toward Risk Management
• An important step in the process of
determining the appropriate financial
hedging instruments for a firm is to analyze
the nature of the firm’s currency cash flows.
• Note that a hedging strategy may offset
certain risks, while leaving open or
increasing other risks.
BUFN722- Financial Institutions ch10 - 64
Financial Strategies
Toward Risk Management
Characteristics of Suitable Financial
Currency Exposure Hedging Instruments
Frequency Single period Single contract (futures/options)
of cash flows
Multiple Sets (“strips”) of contracts/swaps
periods or present value hedge
Currency Single Contracts on one currency
dimension currency
Multiple Contracts on an index (ECU,
currencies US$) or synthetic hedge
BUFN722- Financial Institutions ch10 - 65
Financial Strategies
Toward Risk Management
Characteristics of Suitable Financial
Currency Exposure Hedging Instruments
Certainty Certain, Naïve hedge to match contract
about cash contractual size of financial instrument and
flows cash flows exposure
Uncertain, Option hedge or dynamic futures
estimated cash hedge to match probability of
flows cash flows
BUFN722- Financial Institutions ch10 - 66
Policy Issues
International Financial Managers
Problems in Estimating Economic Exposure
Using market data presumes that financial
markets are efficient, and that share prices
respond quickly and appropriately to exchange
rate changes.
The approach is unsuitable for newly organized
or reorganized firms for which there is not a
large sample of consistent observations.
For the exposure coefficient to be useful, the
relationship between exchange rate changes and
market value must remain stable in the future.
BUFN722- Financial Institutions ch10 - 67
Policy Issues
International Financial Managers
Picking an Appropriate Hedge Ratio
If the exchange rate is expected to change favorably,
hedging may not be desirable.
Complete hedging may be achieved by taking offsetting
positions (-bi ).
Otherwise, an intermediate solution may be chosen,
with hedge positions in between 0 and bi .
Note that the more direct approach is to restructure the
firm’s long-term financing, so as to permanently alter
the firm’s financial exposure.
BUFN722- Financial Institutions ch10 - 68
Policy Issues
International Financial Managers
The International Investor’s Currency Risk
Management Problem
A portfolio’s exposure to foreign exchange risk
can be measured using the regression approach
in much the same way as the treasurer measures
the firm’s exposure.
The investor can hedge foreign exchange risk
using forward contracts, or retain the risk using
a risk-return decision criterion.
BUFN722- Financial Institutions ch10 - 69
Pertinent Websites
For information on the BIS framework, visit:
Bank for International Settlements www.bis.org
Federal Reserve www.federalreserve.gov
Citigroup www.citigroup.com
J.P.Morgan/Chase www.jpmorganchase.com
Merrill Lynch www.merrilllynch.com
RiskMetrics www.riskmetrics.com
BUFN722- Financial Institutions ch10 - 70
