FX Derivatives
3. Hedging Exposure
FX Risk Management
 Exposure
At the firm level, currency risk is called exposure.
Three areas
(1) Transaction exposure: Risk of transactions denominated in FX with a
payment date or maturity.
(2) Economic exposure: Degree to which a firm's expected cash flows
are affected by unexpected changes in St.
(3) Translation exposure: Accounting-based changes in a firm's
consolidated statements that result from a change in St. Translation rules
are complicated: Not all items are translated using the same St. These
rules create accounting gains/losses due to changes in St.
We will say a firm is “exposed” or has exposure if it faces currency risk.
Q: How can FX changes affect the firm?
- Transaction Exposure
- Short-term CFs: Existing contract obligations.
- Economic Exposure
- Future CFs: Erosion of competitive position.
- Translation Exposure
- Revaluation of balance sheet (Book Value vs Market Value).
Example: Exposure.
A. Transaction exposure.
Swiss Cruises, a Swiss firm, sells cruise packages priced in USD to a
broker. Payment in 30 days.
B. Economic exposure.
Swiss Cruises has 50% of its revenue denominated in USD and only
20% of its cost denominated in USD. A depreciation of the USD will
affect future CHF cash flows.
C. Translation exposure.
Swiss Cruises obtains a USD loan from a U.S. bank. This liability has to
be translated into CHF. ¶
Measuring Transaction Exposure
Transaction exposure (TE) is very easy to identify and measure:
TE = Value of a fixed future transaction in FC x St
For a MNC  TE: consolidation of contractually fixed future currency
inflows and outflows for all subsidiaries, by currency. (Net TE!)
Example: Swiss Cruises.
Sold cruise packages for USD 2.5 million. Payment: 30 days.
Bought fuel oil for USD 1.5 million. Payment: 30 days.
St = 1.45 CHF/USD.
Thus, the net transaction exposure in USD is:
Net TE = (USD 2.5M -USD 1.5M) x 1.45 CHF/USD =CHF 1,450,000. ¶
 Netting
MNC take into account the correlations among the major currencies to
calculate Net TE
 Portfolio Approach.
A U.S. MNC: Subsidiary A with CF(in EUR) > 0
Subsidiary B with CF(in GBP) < 0
GBP,EUR is very high and positive.
Net TE might be very low for this MNC.
• Hedging decisions are usually not made transaction by transaction.
Rather, they are made based on the exposure of the portfolio.
Example: Swiss Cruises.
Net TE (in USD):
USD 1 million. Due: 30 days.
Loan repayment:
CAD 1.50 million. Due: 30 days.
St = 1.47 CAD/USD.
CAD,USD = .924 (from 1990 to 2001)
Swiss Cruises considers the Net TE (overall) to be close to zero. ¶
Note 1: Correlations vary a lot across currencies. In general, regional
currencies are highly correlated. From 2000-2007, the GBP and EUR
had an average correlation of .71, while the GBP and the MXN had an
average correlation of -.01.
Note 2: Correlations also vary over time.
Currencies from developed countries tend to move together... But,
not always!
Correlation: GBP/US D and MXN/US D
4-year Correlation
1
0.5
0
1985
-0.5
-1
1990
1995
2000
2005
• Q: How does TE affect a firm in the future?
MNCs are interested in how TE will change in the future (say, in T
days). After all, it is in the future that the transaction will be settled.
- MNCs do not know the future St+T, they need to forecast St+T.
- Et[St+T] has an associated standard error, which produces a
range
for (or an interval around ) St+T and, thus, TE.
- From a risk management perspective, it is important to know
how
much will be received from a FC inflow or how much will
be
needed to cover a FC outflow.
Range Estimates of TE
• St is very difficult to forecast. Thus, a range estimate of the Net TE
will provide a more useful number for risk managers.
The smaller the range, the lower the sensitivity of the Net TE.
• Three popular methods for estimating a range for Net TE:
(1) Ad-hoc rule (±10%)
(2) Sensitivity Analysis (or simulating exchange rates)
(3) Assuming a statistical distribution for exchange rates.
 Ad-hoc Rule
Instead of using a specific confidence interval (C.I.), which requires
(complicated calculations and/or unrealistic assumptions) many firms use
an ad-hoc rule to get a range: ±10% rule
It’s a simple and easy to understand: Get TE and add/subtract ±10% .
Example: Swiss Cruises has a Net TE= CHF 1.45 M due in 30 days
⇒ if St changes by ±10%, Net TE changes by ± CHF 145,000. ¶
Note: This example gives a range for NTE:
NTE ∈ [CHF 1.305M; CHF 1.595 M]
⇒ the wider the range, the riskier an exposure is.
Risk Management Interpretation: If SC is counting on the USD 1M to
pay CHF expenses, these expenses should not exceed CHF 1.305M. ¶
 Sensitivity Analysis
Goal: Measure the sensitivity of TE to different exchange rates.
Example: Sensitivity of TE to extreme forecasts of St.
Sensitivity of TE to randomly simulate thousands of St.
Data: 20 years of monthly CHF/USD % changes (ED)
Mean ()
Standard Error
-0.00152 m = -0.52%
0.00202
Median
Mode
Stand Deviation (σ)
Sample Variance (σ2)
Kurtosis
Skewness
Range
-0.00363
#N/A
0.03184
0.00101
0.46327
0.42987
0.27710
Minimum
Maximum
-0.11618
0.15092
Sum
Count
0.0576765
248
m = 3.184%
Example: Sensitivity analysis of Swiss Cruises Net TE (CHF/USD)
ED of St monthly changes over the past 20 years (1994-2014).
Extremes: 15.09% (on October 2011) and –11.62% (on Jan 2009).
Net TE (SC’s net receivables in USD): USD 1M.
(A) Best case scenario: largest appreciation of USD: 0.1509
NTE: USD 1M x 1.45 CHF/USD x (1 + 0.1509) = CHF 1,668,805.
(B) Worst case scenario: largest depreciation of USD: -0.1162
NTE: USD 1M x 1.45 CHF/USD x (1 – 0.1162) = CHF 1,281,510.
That is,
NTE ∈ [CHF 1,281,510, CHF 1,668,805]
Note: A risk manager will only care about the lower bound. That is, if
Swiss Cruises is counting on the USD 1 million to cover CHF expenses,
from a risk management perspective, the expenses to cover should not
exceed CHF 1,281,510. ¶
Note: Some managers may consider the range, based on extremes, too
conservative: NTE ∈ [CHF 1,281,510, CHF 1,668,805].
⇒ Probability of worst case scenario is low: Only once in 144 months!
Under more likely scenarios, we may be able to cover more expenses
with the lower bound.
A different range can be constructed through sampling from the ED.
Example: Simulation for SC’s Net TE (CHF/USD) over one month.
(i) Randomly pick 1,000 monthly st+30’s from the ED.
(ii) Calculate St+30 for each st+30 selected in (i). (Recall: St+30 = 1.45
CHF/USD x (1 + st+30))
(iii) Calculate TE for each St+30. (Recall: TE = USD 1M x St+30)
(iv) Plot the 1,000 TE’s in a histogram. (Simulated TE distribution.)
Based on this simulated distribution, we can estimate a 95% range
(leaving 2.5% observations to the left and 2.5% observations to the right)
=> NTE ∈ [CHF 1.3661 M; CHF 1.5443 M]
Practical Application: If SC expects to cover expenses with this USD
inflow, the maximum amount in CHF to cover, using this 95% CI, should
be CHF 1,366,100. ¶
 Assuming a Distribution
CIs based on an assumed distribution provide a range for TE.
For example, a firm can assume that St changes, st, follow a normal
distribution and based on this distribution construct a 95% CI.
Recall that a 95% confidence interval is given by [  1.96 ].
2.5%
2.5%
Example: CI range based on a Normal distribution.
Assume Swiss Cruises believes that CHF/USD monthly changes follow
a normal distribution. Swiss Cruises estimates the mean and the variance.
 = Monthly mean = -0.00152 ≈ -0.15%
2 = Monthly variance = 0.001014
(  = 0.03184, or 3.18%)
st ~ N(-0.00152, 0.001014).
st = CHF/USD monthly
changes.
Swiss Cruises constructs a 95% CI for CHF/USD monthly changes.
Recall that a 95% confidence interval is given by:
[-0.00152  1.96*0.03184] = [-0.06393; 0.06089].
Based on this range for st, we derive bounds for the net TE:
(A) Upper bound
NTE: USD 1M x 1.45 CHF/USD x (1 + 0.06089) = CHF 1,538,291.
(B) Lower bound
95% CI range based on a Normal Distribution and Var(97.5%)
2.5%
2.5%
NTE = CHF 1.45M
CHF 1.3573M
CHF 1.5383M
VaR(97.5): Minimun revenue within a 97.5% C.I.
=> NTE  [CHF 1.357 M, CHF 1.538 M]
• The lower bound, for a receivable, represents the worst case scenario
within the confidence interval.
There is a Value-at-Risk (VaR) interpretation:
VaR: Maximum expected loss in a given time interval within a (onesided) CI.
In our case, we can express the expected “loss” relative to today’s value:
VaR-mean: VaR – Net TE
Example (continuation): VaR(97.5) = CHF 1,357,302, the minimum
revenue to be received by SC in the next 30 days, within a 97.5% CI.
Then,
VaR-mean (97.5) = CHF 1.3573M – CHF 1.45M = CHF -0.0927M
• Summary
=> NTE  [CHF 1.357 M, CHF 1.538 M]
VaR(97.5) = CHF 1,357,302
If SC expects to cover expenses with this USD inflow, the maximum
amount in CHF to cover, within a 97.5% CI, should be CHF 1,357,302.
VaR-mean (97.5) = CHF -0.09527M
Relative to today’s valuation (or expected valuation, according to RWM),
the maximum expected loss with a 97.5% “chance” is CHF 95,270. ¶
● Summary NTE for Swiss francs:
- NTE = CHF 1.45M
- NTE Range:
- Ad-hoc:
NTE ∈ [CHF 1.305M; CHF 1.595 M].
- Simulation:
- Extremes: NTE ∈ [CHF 1.281 M, CHF 1,6688 M]
Simulation: NTE ∈ [CHF 1.3661 M; CHF 1.5443 M]
- Statistical Distribution (normal):
NTE  [CHF 1.357 M, CHF 1.538 M]
-
 Approximating returns
In general, we use arithmetic returns: st = St/St-1-1. Changing the
frequency is not straightforward.
But, if we use logarithmic returns –i.e., st=log(St)-log(St-1)-, changing the
frequency of the mean return () and return variance (2) is simple. Let
 and 2 be measured in a given base frequency. Then,
f =  T,
2f = 2 T,
Example: From Table VII.1: m= 0.0004 and m=.0329961. (These are
arithmetic returns.) We want to calculate the daily and annual percentage
mean change and standard deviation for the CHF/USD exchange rate.
We will approximate them using the logarithmic rule.
(1) Daily (i.e., f=d=daily and T=1/5)
d = (-0.00152) x (1/30) = .0000507
(0.006%)
d = (0.03184 ) x (1/30)1/2 = .00602 (0.60%)
 Approximating returns
(2) Annual (i.e., f=a=annual and T =12)
a = (-0.00152) x (12) = -.01824
a = (0.03184) x (12)1/2 = .110297
(-1.82%)
(11.03%)
The annual compounded arithmetic return is -.00152 =(1-.00152)12-1.
When the arithmetic returns are low, these approximations work well. ¶
Note I: Using these annualized numbers, we can approximate an
annualized VaR(97.5), if needed:
VaR(97.5) = USD 1M x 1.45 CHF/USD x [1 +(-.0182-1.96 0.1103)] =
= CHF 1,101,374. ¶
Note II: Using logarithmic returns rules, we can approximate USD/CHF
monthly changes by changing the sign of the CHF/USD. The variance
remains the same. Then, annual USD/CHF mean percentage change is
approximately 1.82%, with an 11.03% annualized volatility.
● Sensitivity Analysis for portfolio approach
Do a simulation: assume different scenarios -- attention to correlations!
Example: IBM has the following CFs in the next 90 days
Outflows
Inflows
St
Net Inflows
GBP 100,000
25,000
1.60 USD/GBP
(75,000)
EUR 80,000
200,000
1.05 USD/EUR
120,000
NTE (USD)= EUR 120K*1.05 USD/EUR+(GBP 75K)*1.60 USD/GBP
= USD 6,000 (this is our baseline case)
Situation 1: Assume GBP,EUR = 1. (EUR and GBP correlation is high.)
Scenario (i): EUR appreciates by 10% against the USD
Since GBP,EUR = 1, St = 1.05 USD/EUR * (1+.10) = 1.155 USD/EUR
St = 1.60 USD/GBP * (1+.10) = 1.76 USD/GBP
NTE (USD) =EUR 120K*1.155 USD/EUR+(GBP 75K)*1.76 USD/GBP
= USD 6,600. (10% change)
Example (continuation):
Scenario (ii): EUR depreciates by 10% against the USD
Since GBP,EUR = 1, St = 1.05 USD/EUR * (1-.10) = 0.945 USD/EUR
St = 1.60 USD/GBP * (1-.10) = 1.44 USD/GBP
NTE (USD)=EUR 120K*0.945 USD/EUR+(GBP 75K)*1.44 USD/GBP
= USD 5,400. (-10% change)
Now, we can specify a range for NTE
NTE ∈ [USD 5,400; USD 6,600]
Note: The NTE change is exactly the same as the change in St. If a firm
has matching inflows and outflows in highly positively correlated
currencies –i.e., the NTE is equal to zero-, then changes in St do not
affect NTE. That’s very good.
Example (continuation):
Situation 2: Suppose the GBP,EUR = -1 (NOT a realistic assumption!)
Scenario (i): EUR appreciates by 10% against the USD
Since GBP,EUR = -1, St = 1.05 USD/EUR * (1+.10) = 1.155 USD/EUR
St = 1.60 USD/GBP * (1-.10) = 1.44 USD/GBP
NTE (USD)= EUR 120K*1.155 USD/EUR+(GBP 75K)*1.44 USD/GBP
= USD 30,600. (410% change)
Scenario (ii): EUR depreciates by 10% against the USD
Since GBP,EUR = -1, St = 1.05 USD/EUR * (1-.10) = 0.945 USD/EUR
St = 1.60 USD/GBP * (1+.10) = 1.76 USD/GBP
NTE (USD)=EUR 120K*0.945 USD/EUR+(GBP 75K)*1.76 USD/GBP
= (USD 18,600). (-410% change)
Now, we can specify a range for NTE
 NTE ∈ [(USD 18,600); USD 30,600]
Example (continuation):
Note: The NTE has ballooned. A 10% change in exchange rates produces
a dramatic increase in the NTE range.
 Having non-matching exposures in different currencies with
negative correlation is very dangerous.
IBM will assume a correlation (estimated from the data) and, then, draw
many scenarios for St to generate an empirical distribution for the NTE.
From this ED, IBM will get a range –and a VaR- for the NTE. ¶
Managing TE
• A Comparison of External Hedging Tools
Transaction exposure: Risk from the settlement of transactions
denominated in foreign currency.
Example: Imports, exports, acquisition of foreign assets.
• Tools:
Futures/forwards (FH)
Options (OH)
Money market (MMH)
• Q: Which hedging tool is better?
• New tool: MMH
A money market hedge is based on a replication of IRPT arbitrage.
Let’s take the case of receivables denominated in FC
1) Borrow FC
2) Convert to DC
3) Deposit DC in domestic bank
4) Transfer FC receivable to cover loan from (1).
Under IRPT, step 4) involves buying FC forward, to repay loan in (1)
=> This step is not needed, instead, we just transfer the FC receivable.
Q: Why MMH instead of FH?
- under perfect market conditions
- under less than perfect conditions
 MMH = FH
 MMH  FH
Example:
Iris Oil Inc., a Houston-based energy company, has a large foreign
currency exposure in the form of a CAD cash flow from its Canadian
operations. The exchange rate risk to Iris is that the CAD may depreciate
against the USD. In this case, Iris’ CAD revenues, transferred to its USD
account will diminish and its total USD revenues will fall.
Situation: Iris will have to transfer CAD 300M into its USD account in
90 days.
Data:
St = 0.8451 USD/CAD
Ft,90-day = 0.8493 USD/CAD
iUSD = 3.92%
iCAD = 2.03%
Example (continuation):
Date
Spot market
Forward market
Money market
t
St = .8451 USD/CAD Ft,90-day = .8493 USD/CAD iUSD=3.92%;
iCAD=2.03%
t+90
Receive CAD 300M and transfer into USD.
Hedging Strategies:
1. Do Nothing:
Do not hedge and exchange the CAD 300M at St+90.
2. Forward Market:
At t, sell the CAD 300M forward and at time t+90 guarantee:
(CAD 300M) x (.8493 USD/CAD) = USD 254,790,000
Example (continuation):
3. Money Market
At t, Iris Oil takes the following three steps, simultaneously:
1) Borrow from Canadian bank at 2.03% for 90 days :
CAD 300M / [1+.0203x(90/360)] = CAD 298,485,188.
2) Convert to USD at St:
CAD 298,485,188 x 0.8451 USD/CAD = USD 252,249,832
3) Deposit in US bank at 3.92% for 90 days to guarantee at time t+90:
USD 252,249,832 x [1 + .0392x(90/360)] = USD 254,721,880.
Note: Both the FH and the MMH guarantee certainty at time t+90
FH delivers to Iris Oil:
USD 254,790,000
MMH delivers to Iris Oil: USD 254,721,880
=> Iris Oil will select the FH.
Example (continuation):
4. Option Market:
At t, buy a put. Use the options market. Available 90-day options
X
Calls
Puts
.82 USD/CAD
---0.21
.84 USD/CAD
1.58
0.68
.88 USD/CAD
0.23
---Buy the .84 USD/CAD put => Total premium cost of USD 2.04M.
In 90 days, the CF is:
Plus
Total
Net CF at t+90:
or
St+90 < .84 USD/CAD
St+90 > .84 USD/CAD
(.84 – St+90) CAD 300M
0
St+90 CAD 300M
St+90 CAD 300M
USD 252M
St+90 CAD 300M
USD 249,960,000
St+90 CAD 300M – USD 2.04M
for all St+90 < .84 USD/CAD
for all St+90 > .84 USD/CAD
Example (continuation):
5. Collar:
At time t, buy a put and sell a call.
Buy the .84 put at USD 0.0068 and finance it by selling the .88 call at
USD 0.0023. Thus, initial cost is reduced to USD 0.0045 per put
=> Total cost: USD 1.35M
Put (.84)
Call (.88)
Plus
Total
St+90 < .84 USD/CAD .84 < St+90 < .88
(.84 – St+90 ) CAD 300M
0
0
0
St+90 CAD 300M
St+90 CAD 300M
USD 252 M
St+90 CAD 300M
Net CF at t+90: USD 250.65M
or
St+90 CAD 300M – USD 1.35M
or
USD 262.65M
St+90> .88 USD/CAD
0
(.88– St+90) CAD 300M
St+90 CAD 300M
USD 264M
for all St+90 < .84 USD/CAD
for all .84 < St+90 < .88
for all St+90 > .88 USD/CAD
Note: This collar reduces the upside: establishes a floor and a cap.
Example (continuation):
6. Alternative: Zero cost insurance:
At time t, buy puts and sell calls with overall (or almost) matching
premium.
Buy the .84 put and finance it buy selling 3, .88 calls. Thus, no initial
cost (actually, it’s a small profit, which we’ll ignore). In 90 days:
St+90 < .84 USD/CAD .84 < St+90 < .88
St+90 > .88 USD/CAD
Put (.84)
(.84 – St+90) CAD 300M 0
0
3 Calls (.88)
0
0
3 (.88–St+90) CAD 300M
Plus
St+90 CAD 300M
St+90 CAD 300M St+90 CAD 300M
Total
USD 252 M
St+90 CAD 300M USD 792M–2St+90CAD 300M
Net CF at t+90: USD 252M
or
St+90 CAD 300M
or
USD 792 M – 2 St+90 CAD 300M
for all St+90 < .84 USD/CAD
for all .84 < St+90 < .88
for all St+90 > .88 USD/CAD
• Let’s plot all strategies:
Amount
Received in
t+90
Do Nothing
Put
USD 264M
USD 262.65M
Collar
Forward
USD 254.79M
USD 252M
USD 250.65M
USD 249.96M
Zero-cost Collar
.84
.8562
.88
St+90
• In order to make a decision regarding a hedging strategy, we need to
say something about St+90. For example, we can assume a distribution.
• We can use the ED to say something about future changes in St.
0.4
0.4
0.35
0.35
Relative Frequency
Relative Frequency
Example: Distribution for monthly USD/SGD changes from 1981-2009.
Then, we get the distribution for St+30 (USD/SGD).
0.3
0.25
0.2
0.15
0.1
0.05
0.3
0.25
0.2
0.15
0.1
0.05
0
0
More
-5
-3
-1
0
1
C hanges in USD / SGD (%)
3
5
M o re
0.6185
0.6315 0.6445
0.651
USD/SGD
0.6575 0.6705 0.6835
Example (continuation): Distribution for monthly USD/SGD changes
from 1981-2009. Raw data, and relative frequency for St+30 (USD/SGD).
st (SGD/USD)
Frequency
Rel frequency
St =1/.65*(1+st)
-0.0494 or less
2
0.0058
1.462
0.6838
-0.0431
2
0.0058
1.472
0.6793
-0.0369
1
0.0029
1.482
0.6749
-0.0306
3
0.0087
1.491
0.6705
-0.0243
6
0.0174
1.501
0.6662
-0.0181
20
0.0580
1.511
0.6620
-0.0118
36
0.1043
1.520
0.6578
-0.0056
49
0.1420
1.530
0.6536
0.0007
86
0.2493
1.540
0.6495
0.0070
52
0.1507
1.549
0.6455
0.0132
41
0.1188
1.559
0.6415
0.0195
29
0.0841
1.568
0.6376
0.0258
5
0.0145
1.578
0.6337
0.0320
7
0.0203
1.588
0.6298
0.0383
5
0.0145
1.597
0.6260
0.0446
0
0.0000
1.607
0.6223
0.0508 or +
3
0.0058
1.617
0.6186
• Examples assuming an explicit distribution for St+T
Example–Receivables: Evaluate (1) FH, (2) MMH, (3) OH and (4) NH.
Cud Corp will receive SGD 500,000 in 30 days. (SGD Receivable.)
Data:
• St = .6500 - .6507 USD/SGD.
• Ft,30 = .6510 - .6519 USD/SGD.
• 30-day interest rates:
iSGD: 2.65% - 2.75% & iUSD: 3.20% - 3.25%
• A 30-day put option on SGD: X = .65 USD/SGD and Pt= USD.01.
• Forecasted St+30:
Possible Outcomes
Probability
USD .63
18%
USD .64
24%
USD .65
34%
USD .66
21%
USD .68
3%
(1) FH: Sell SGD 30 days forward
USD received in 30 days = Receivables in SGD x Ft,30
= SGD 500,000 x .651 USD/SGD = USD 325,500.
(2) MMH: Borrow SGD for 30 days, Convert to USD, Deposit USD,
Repay SGD loan in 30 days with SGD payable
Amount to borrow = SGD 500,000/(1 + .0275x30/360) =
= SGD 498,856.79
Convert to USD (Amount to deposit in U.S. bank) =
= SGD 498,856.79 x .65 USD/SGD = USD 324256.91
Amount received in 30 days from U.S. bank deposit =
= USD 324256.91 x (1 + .032x30/360) = USD 325,121.60
(3) OH: Purchase put option.
X= .65 USD/CHF
Pt = premium = USD .01
Note: In the Total Amount Received (in USD) we have subtracted the
opportunity cost involved in the upfront payment of a premium:
USD .01 x .032 x 30/360 = USD .000027 (Total = USD 13.50)
=> Total Premium Cost: USD 5,013.50
E[Amount Received in USD] = 319,986.5 x .76 + 324,986.50 x .21 +
+ 329,986.50 x .03 = USD 321,336.5
(4) No Hedge: Sell SGD 500,000 in the spot market in 30 days.
Note: When we compare (1) to (4), it’s not clear which one is better.
Preferences will matter. We can calculate and expected value:
E[Amount Received in USD] = 315K x .18 + 320K x .24 + 325K x .34+
+ 330K x .21+ 335K x . 03 = USD 323,350
Conclusion: Cud Corporation is likely to choose the FH. But, risk
preferences matter. ¶
Example–Payables: Evaluate (1) FH, (2) MMH, (3) OH, (4) No Hedge
Situation: Cud Corp needs CHF 100,000 in 180 days. (CHF Payable.)
Data:
• St = .675-.680 USD/CHF.
• Ft,180 = .695-.700 USD/CHF.
• 180-day interest rates are as follows: iCHF: 9%-10%; iUSD: 13%-14.0%
• A 180-day call option on CHF: X=.70 USD/CHF and Pt=USD.02.
• Cud forecasted St+180:
Possible Outcomes
USD .67
USD .70
USD .75
Probability
30%
50%
20%
(1) FH: Purchase CHF 180 days forward
USD needed in 180 days = Payables in CHF x Ft,180
= CHF 100,000 x .70 USD/CHF = USD 70,000.
(2) MMH: Borrow USD for 180 days, Convert to CHF, Invest CHF,
Repay USD loan in 180 days
Amount in CHF to be invested = CHF 100,000/(1 + .09x180/360)
= CHF 95,693.78
Amount in USD needed to convert into CHF for deposit =
= CHF 95,693.78 x .680 USD/CHF = USD 65,071.77
Interest and principal owed on USD loan after 180 days =
= USD 65,071.77 x (1 + .14x180/360) = USD 69,626.79
(3) OH: Purchase call option.
Ct = premium = USD .02.
X= .70 USD/CHF
Note: In the Total USD Cost we have included the opportunity cost
involved in the upfront payment of a premium = USD 130.
• Preferences matter: A risk taker may like the 30% chance of doing
better with the OH than with the MMH.
(4) Remain Unhedged: Purchase CHF 100,000 in 180 days.
Preferences matter: Again, a risk taker may like the 30% chance of doing
better with the NH than with the MMH. (Actually, there is also an
additional 50% chance of being very close to the MMH.)
E[Amount to Pay in USD] = USD 70,100
Conclusion: Cud Corporation is likely to choose the MMH. ¶
Internal Methods
• These are hedging methods that do not involve financial instruments.
• Risk Shifting
Q: Can firms completely avoid exposure to exchange rate movements?
A: Yes! By pricing all foreign transactions in the domestic currency.
Example: Bossio Co., a U.S. firm, sells naturally colored cotton. Asuni,
a Japanese company, buys Bossio's cotton. Bossio Co. prices all exports
in USD. ¶
=> Currency risk is not eliminated. The foreign company bears it.
• Problem with risk-shifting: Reduces firm flexibility.
• Currency Risk Sharing
Two parties can agree -using a customized hedge contract- to share the
FX risk involved in the transaction.
Example: Asuni buys cotton for USD 1 million from Bossio Co.
Risk Sharing agreement:
• If St  [98 JPY/USD, 140 JPY/USD]  transaction unchanged.
(Asuni pays USD 1 M to Bossio Co.)
The range where the transaction is unchanged is called neutral zone.
• If St < 98 JPY/USD or St > 140 JPY/USD  both companies share
the risk equally.
Suppose that when Asuni has to pay Bossio Co., St = 180 JPY/USD.
The St used in settling the transaction is 160 JPY/USD (180 - 40/2).
Asuni's final cost = JPY 160 million = USD 888,889 < USD 1M. ¶
• Leading and Lagging (L&L)
Firms can reduce FX exposure by accelerating or decelerating the timing
of payments that must be made in different currencies:
 leading or lagging the movement of funds.
L&L is done between the parent company and its subsidiaries or between
two subsidiaries.
Example: Parent company: HAL (U.S. company).
Subsidiaries: Mexico, Brazil, and Hong Kong.
HAL Hong Kong's exposure is too large.
HAL orders HAL Mexico and HAL Brazil to accelerate (lead) its
payments to HAL Hong Kong. ¶
• L&L changes the assets or liabilities in one firm, with the reverse effect
on the other firm.
 L&L changes balance sheet positions.
Might be a good tool for achieving a hedged balance sheet position.
• Funds Adjustments
Key to hedging:
Match inflows and outflows denominated in the foreign currency.
Chinese subsidiary in U.S.
has positive CFs in USD
Increase USD purchases
Decrease CNY purchases
Decrease USD sales
Increase CNY sales
Increase USD borrowing
Reduce CNY borrowing
Italian subsidiary in U.S.
has negative CFs in USD
Decrease USD purchases
Increase EUR purchases
Increase USD sales
Decrease EUR sales
Reduce USD borrowing
Increase EUR borrowing
Example: Japanese and German carmakers have plants in the U.S.
Translation Exposure
Translation exposure: Risk from consolidating assets and liabilities
measured in foreign currencies with those in the reporting currency.
Assets and liabilities in a FC must be restated in terms of a DC.
This translation follows rules set up by a parent firm's government, an
accounting association (U.S. GAAP, or by the firm itself.
Problem: The translation involves complex rules that sometimes reflect a
compromise between historical and current exchange rates.
=> The translation might not end up with Assets=Liabilities.
• Examples of exchange rates used for translation:
- Historical rates may be used for some equity accounts, fixed assets,
inventories.
- Current exchange rates are used for current assets, liabilities, expenses
and income.
- Different exchange rates are used, imbalances will occur.
• Key issue: what to do with the resulting imbalance? It is taken to either
current income or equity reserves.
Note: Translation exposure does not directly affect cash flows, but some
firms are concerned about it because of its potential impact on reported
consolidated earnings.
Measuring Translation Exposure
There are several methods to translate foreign currency accounts into the
reporting currency. Two methods that predominate:
- Temporal method (monetary/nonmonetary method)
- Current rate method
Useful Terminology:
Monetary: there is a date (maturity) attached to the asset or liability.
Nonmonetary: items with no maturity (fixed assets, inventory).
Three exchange rates can be used:
S0: Historical exchange rate.
St: Current exchange rate at the date of balance.
SAVERAGE: Average exchange rate for the period.
FASB #8 - Temporal Method (U.S.: used from 1976-1982)
Premise: Historical-cost accounting
- Translate nonmonetary assets at S0, assets and liabilities use St
- Translate most income statements items at the SAVERAGE
- Translate shareholder equity at S0
- Bookkeeping exchange gains or losses are passed to the Income
statement
FASB #52 - Current Rate Method (U.S.: used since 12/15/1982)
- Translate most amounts at St
- Income statement items are translated at S0 or SAVERAGE
- Translate shareholder equity at S0
- Exchange gains or losses are not reflected in income statement rather
accumulate in an adjustment account in stockholders' equity:
Cumulative translation adjustment (CTA).
- Distinguished between functional currency (usually local currency) and
reporting currency (currency in which the parent firm prepares its own
financial statements)
- Exceptions to FASB #52
1. Accounts of subsidiaries whose operations are mostly with the parent
use parent’s currency as functional currency, translate using temporal
method.
2. Accounts of subsidiaries operating in hyperinflationary countries (over
100% over a three year period), functional currency must be the USD.
Summary of U.S. accounting standards
Monetary
(Assets, debt, etc)
Fixed
(P&E, inventory)
Gains/losses
reported:
1975-81
FASB #8
Temporal Method
St
S0
Income statement
1981-today
FASB #52
Current Rate Method
St
St
Separate equity account
Managing Translation Exposure
• Most popular method: balance sheet hedge.
Perfect balance sheet hedge: have an equal amount of exposed foreign
currency assets and liabilities on a firm's consolidated balance sheet.
 net translation exposure will be zero.
• Translation exposure is measured by currency: equality of exposed
balance sheet's items can be achieved on a worldwide basis.
Example: HAL HK has the following balance sheet (in HKD M).
Assets
Cash
Accounts receivable
Inventory
Net fixed plant and equip.
Total assets
Total exposed assets
Liabilities and Capital
Accounts payable
Notes payable
Long-term debt
Shareholder's equity
Total liabilities and capitsl
Total exposed liabilities
Net exposed assets
Balance
accounts
CR
M/NM
exposures
300
850
400
1,000
2,550
300
850
400
1,000
300
850
N.ex.
N.ex.
2,550
1,150
200
300
900
N.ex.
200
300
900
N.ex.
1,400
1,150
1,400
-250
200
300
900
1,150
2,550
Example (Continuation):
Net exposed assets
1,150 -250
St=.128 USD/HKD.
Exposure in USD - CR method:
HKD 1,150,000,000 x .128 USD/HKD = USD 147,200,000.
Exposure in USD - M/NM method:
HKD -250,000,000 x .128 USD/HKD = USD -32,000,000.
Management believes the HKD will depreciate 10% against the USD.
If St   HAL will have:
(1)
Translation loss = USD 14.72 million under the CR Method.
(2)
Translation gain = USD 3.2 million under the M/NM Method.
Example (Continuation):
Note: Under the CR Method the loss will go to the CTA.
Under the Temporal Method the gain will go to the income
statement and increase earnings.
HAL HK's functional currency is the HKD, HAL uses the CR Method.
HAL wants to avoid translation exposure in HKD:
HAL HK should borrow HKD 1,150,000,000, and then:
(1)
HAL HK could exchange the HKD for USD, or
(2)
HAL HK could transfer the borrowed HKD to HAL. ¶
Economic Exposure
Economic exposure (EE): Risk associated with a change in the NPV of a
firm's expected cash flows, due to an unexpected change in St.
• Economic exposure is:
Subjective.
Difficult to measure.
• We can use accounting data (changes in EAT) or financial/economic
data (returns) to measure EE. Economists tend to like more economic
data measures.
• Note: Since St is very difficult to forecast, the actual change in St can
be considered “unexpected.”
Measuring Economic Exposure
A Measure Based on Accounting Data
It requires to estimate the net cash flows of the firm (EAT or EBT) under
several FX scenarios. (Easy with an excel spreadsheet.)
Example: IBM HK provides the following info:
Sales and cost of goods are dependent on St
St = 7 HKD/USD
St = 7.70 HKD/USD
Sales (in HKD)
300M
400M
Cost of goods (in HKD)
150M
200M
Gross profits (in HKD)
150M
200M
Interest expense (in HKD) 20M
20M
EBT (in HKD)
130M
180M
Example (continuation):
A 10% depreciation of the HKD, increases the HKD cash flows from
HKD 130M to HKD 180M, and the USD cash flows from USD 18.57M
to USD 23.38.
Q: Is EE significant?
A: We can calculate the elasticity of CF to changes in St:
CF elasticity = % change in earnings / % change in St = .259/.10 = 2.59
Interpretation: We say, a 1% depreciation of the HKD produces a change
of 2.59% in EBT. Quite significant. But you should note that the change
in exposure is USD 4.81M. This amount might not be significant for
IBM! (Judgment call needed.) ¶
Note: Obviously, firms will simulate many scenarios to gauge the
sensitivity of EBT to changes in exchange rates.
A Regression based Measure and a Test
The CF elasticity gives us a measure, but it is not a test of EE. We still
need a jugdement call.
We know it is easy to test regression coefficients (t-tests or F-tests). We
use a use a regression to test for EE.
• Simple steps:
(1) Collect data on CF and St (available from the firm's past)
(2) Estimate the regression: CFt =  + ß St + t,
 ß measures the sensitivity of CF to changes in St.
 the higher ß, the greater the impact of St on CF.
(3) Test for EE  H0 (no EE): β = 0
H1 (EE): β ≠ 0
(4) Evaluation of this regression: t-statistic of ß and R2.
Rule: |tβ= ß/SE(ß)| > 1.96
=> ß is significant at the 5% level.
• We know that other variables also affect stock returns, for example, the
market portfolio, or the Fama-French factors.
One way to “control” for the changes in other variables that affect cash
flows is to use a multivariate regression:
CFt =  + ß St + δ1 X1,t + δ2 X2,t +... + δk Xk,t + t,
where Xi,t represent one of the kth variable that affects CFs.
Note: Sometimes the impact of St is not felt immediately by a firm.
 contracts and short-run costs (short-term adjustment difficult).
Example: For an exporting U.S. company a sudden appreciation of the
USD increases CF in the short term. Solution: use a modified regression:
CFt =  + ß0 St + ß1 St-1 + ß2 St-2 + ß3 St-3 + δ1 X1,t + ... + t.
The sum of the ßs measures the sensitivity of CF to St.
An Easy Measure of EE Based on Financial Data
Accounting data can be manipulated. Moreover, international
comparisons may be difficult. We can use financial data –stock prices!
We can easily measure how retursn and St move together: correlation.
Example: Kellogg’s and IBM’s EE.
Using monthly stock returns for Kellogg’s (Krett) and monthly changes
in St (USD/EUR) from 1/1994-2/2008, we estimate ρK,s (correlation
between Krett and st) = 0.154.
It looks small, but away from zero. We do the same exercise for IBM,
obtaining ρIBM,s=0.056, small and close to zero. ¶
• Better measure: 1) Run a regression on CF against (unexpected) St.
2) Check statistical significance of regression coeff’s.
Example: IBM’s EE.
Now, using the IBM data, we run the regression:
IBMrett =  + ß st + t
R2 = 0.003102
Standard Error = 0.09462
Observations = 169
Coefficients
Intercept (α)
0.016283
Changes in St (β) -0.20322
Standard Error
0.007297
0.2819
t-Stat
2.231439
-0.72089
P-value
0.026983
0.471986
Analysis:
We cannot reject H0, since |tβ = -0.72| < 1.96 (not significantly different
than zero).
Again, the R2 is very low. (The variability of st explains less than 0.3%
of the variability of IBM’s returns.) ¶
Example: Kellogg’s EE.
Now, using the data from the previous example, we run the regression:
Krett =  + ß st + t
R2 = 0.030847
Standard Error = 0.05944
Observations = 169
Coefficients
Intercept (α)
0.005991
Changes in St (β) 0.512062
Standard Error
0.003273
0.165815
t-Stat
1.83075
3.08815
P-value
0.671001
0.002014
Analysis:
We reject H0, since |tβ = 3.09| > 1.96 (significantly different than zero).
Note, however, that the R2 is very low! (The variability of st explains less
than 2.4% of the variability of Kellogg’s returns.) ¶
• Returns are not only influenced st. We should use a multivariate
regression to test for EE; say, including not only sUSD/TWC,t, but also the
FF factors: excess market returns over T-bill rates, (Rm-Rf)t, Size (SMB)
and Book-to-Market (HML):
Example (continuation): Kellogg’s EE.
Now, we estimate a multivariate regression with the 3 FF factors:
K-rett = .0040 + 0.3005 sUSD/TWC,t + .0032 (Rm-Rf)t - .0006 SMBt + .0019 HMLt
(1.83) (1.77)
(3.84)
(0.53)
(2.15)
R2 = .0903 (a higher value driven mainly by the market factor). But,
looking at EE, we observe that the t-stat is now 1.77, that is, the
significance of changes in the value of the USD drops to 7.8%. Thus, at
the 5%, we cannot reject the H0: No EE economic exposure. ¶
Evidence: For large companies (MNCs, Fortune 500),  is not
significantly different than zero. We cannot reject Ho: No EE.
EE: Evidence
The above regression (done for Kellogg) has been done repeatedly for
firms around the world.
Recent paper by Ivanova (2014):
- Mean β equal to 0.57 (a 1% USD depreciation increases returns by
0.57%).
- But, only 40% of the EE are statistically significant at the 5% level.
- For large firms (MNCs), EE is small –an average β=0.063– and not
significant at the 5% level.
- 52% of the EEs come from U.S. firms that have no international
transactions (a higher St “protects” these domestic firms).
Summary: On average, large companies (MNCs, Fortune 500) are not
EE. EE is a problem of small and medium, undiversified firms.
Managing Economic Exposure
Definition: EE measures how changes in FX rates affect CFs
Understanding EE: Cash flows from subsidiary
Revenue: Price in FC x Quantity = PQ
Cost: Variable (α PQ) + Fixed Cost
(0<α< 1, with α=αFC +αDC)
Gross profits: (1- α) PQ - FC
EBT = [(1- α) PQ - FC] - IE
(IE: Interest Expense)
EAT = [(1- α) PQ – FC - IE] (1-t)
(t: tax rate)
Costs & IE have two components: a FC & a DC. Say, for VC: αFC &
αDC., and for IE: IEFC & IEDC.
Managing Economic Exposure
EE: How changes in St affect CFs of the firm (say, EAT)?
A first derivative answer this question:
EAT 
PQ IEFC 
 (1   FC )

(1  t )
St
St
St 

If the first derivative is 0, that menas, EAT = constant, independent of
the FC, there is no EE.
=> The better the match, between Revenue and Costs in FC, the smaller
the EE. That is, a company can play with αFC & IEFC to reduce EE.
Managing Economic Exposure
• Matching Inflows and Outflows
Q: How can a firm get a good match? Play with αFC to establish a
manageable EE. For example, if FC and IE are small relative to
variable, then, the bigger αFC, the smaller the exposed CF (EAT) to
changes in St.
When a firm restructures operations (shift expenses to FC, by increasing
αFC) to reduce EE, we say a firm is doing an operational hedge.
Case Study: Laker Airways (Skytrain) (1977-1982)
After a long legal battle in the U.S. and the U.K, Sir Freddie Laker was
allow to let his low cost carrier, no-frills
airline to fly from LON to NY (1977). Big
success. Rapid expansion, financed with debt.
Situation: Rapid expansion: Laker buys planes
from MD, financed in USD.
• Cost
(i) fuel, typically paid for in USD
(ii) operating costs incurred in GBP, but with a small USD cost
component (advertising and booking in the U.S.)
(iii) financing costs from the purchase of aircraft, denominated in USD.
• Revenue
Sale of airfare (probably, evenly divided between GBP and USD), plus
other GBP revenue.
Currency mismatch (gap):
Revenues
mainly GBP, USD
Payables
mainly USD, GBP
• What happened to St?
USD/GBP Exchange Rate
3
2.5
2
1.5
1
0.5
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Ju
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n82
Ju
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0
1977-1981: Big USD depreciation.
1981-1982: Big USD appreciation.
1982: Laker Airlines bankrupt.
Q: Can we solve Laker Airways problem (economic exposure)
• Solutions to Laker Airways problem (economic exposure):
- Increase sales in US
- Increase IE in GBP (borrow more in the UK)
- Transfer cost out to GBP/Shift expenses to GBP (αFC↑ /αDC ↓)
- Diversification
• Severe problems show up when there is a currency gap (= inflows in
FC - ouflows in FC).
• Very simple approach to managing EE: Minimize currency gaps.
=> match inflows in FC and outflows in FC as much as possible.
• European and Japanese car makers have been matching inflows and
outflows by moving production to the U.S. But, not all companies can
avoid currency gaps: Importing and Exporting companies will always be
operationally exposed.
Q: Why Operational Hedging?
- Financial hedging –i.e., with FX derivative instruments- is inexpensive,
but tends to be short-term, liquid only for short-term maturities.
- Operational hedging is more expensive (increasing αFC by building a
plant, expansion of offices, etc.) but a long-term instrument.
A different view: Financial hedging only covers FX risk (St through P),
but not the risk associated with sales in the foreign country (Q-risk). For
example, if the foreign country enters into a recession, Q will go down,
but not necessarily St. An operational hedge works better to cover Q-risk.
From this view, financial hedging does not work very well if the
correlation between price in FC (P) and quantity sold (Q) is low.
On the other hand, if Corr(P,Q) is high, financial hedging will be OK.
Example: A U.S. firm exports to the European Union. Two different FX
scenarios:
(1) St = 1.00 USD/EUR
Sales in US USD 10M
in EU EUR 15M
Cost of goods in US USD 5M
in EU EUR 8M
(2) St = 1.10 USD/EUR
Sales in US USD 11M
in EU EUR 20M
Cost of goods in US USD 5.5M
in EU EUR 10M
Taxes: US
30%
EU
40%
Interest:
US
USD 4M
EU
EUR 1M
Example (continuation):
CFs under the Different Scenarios (in USD)
St=1 USD/EUR
St=1.1 USD/EUR
Sales
10M+15M=25M
11M+22M=33M
CGS
5M+8M= 13M
5.5M+11M=16.5M
Gross profit 5M+7M=12M
5.5M+11M=16.5M
Int
4M+1M=5M
4M+1.1M=5.1M
EBT
7M
11.4M
Tax
0.3M+2.4M=2.7M 0.45M+3.96M=4.41M
EAT
4.3M
6.99M
Q: Is the change in EAT significant?
Elasticity: For a 10% depreciation of the USD, EAT increases by 63%
(probably very significant!). That is, this company benefits by an
appreciation of the Euro against the USD. The firm faces economic
exposure. ¶
Example (continuation):
Q: How can the US exporting firm avoid economic exposure? (match!)
- Increase US sales
- Borrow more in Euros (increase outflows in EUR)
- Increase purchases of inputs from Europe (increase CGS in EUR)
(A) US firm increases US sales by 25% (unrealistic!)
EAT (St=1 USD/EUR) = USD 6.05M
EAT (St=1.1 USD/EUR) = USD 8.915M
=> a 10% depreciation of the USD, EAT increases by only 47%.
(B) US firm borrows only in EUR: EUR 5M
EAT (St=1 USD/EUR) = USD 4.7M
EAT (St=1.1 USD/EUR) = USD 7.15M
=> a 10% depreciation of the USD, EAT increases by 52%.
Example (continuation):
(C) US firm increases EU purchases by 30% (decreasing US purchases
by 30%)
EAT (St=1 USD/EUR) = USD 3.91M
EAT (St=1.1 USD/EUR) = USD 6.165M
=> a 10% depreciation of the USD, EAT increases by 58%.
(D) US firm does (A), (B) and (C) together
EAT (St=1 USD/EUR) = USD 6.06M
EAT (St=1.1 USD/EUR) = USD 8.25M
=> a 10% depreciation of the USD, EAT increases by 36%. ¶
Note: Some firms will always be exposed!
• International Diversification
For the firms that cannot do matching. They still have a very good FX
risk management tool: Diversifying internationally the firm. (Portfolio
approach.)
True international diversification means to diversify:
Location of production, sales, input sources, borrowing of funds, etc.
• In general, the variability of CF is reduced by diversification:
St is likely to increase the firm's competitiveness in some
markets while reducing it in others.
 EE should be low.
• Not surprisingly big MNF do not have EE.
• Case Study: Walt Disney Co.
Four divisions (in 2006): Media Networks Entertainment; Theme Parks
and Resorts; Studios; and Consumer Products.
Total Inflows (2006) - Revenue USD 34.3B, Operating income: USD
6.49B, EPS: USD 2.06:
Media (ABC, ESPN, Lifetime, A&E, etc. Low). Rev: 14.75B, OI: 3.61B
Amusement Parks (Cruise Line & 10 parks: Euro Disney, Tokyo
Disney + HK park, etc. Medium). Rev: 9.95B, OI: 1.53B
Studios (Disney, Pixar, Touchstone, etc. High). Rev: 7.2B, OI: 0.73B
Consumer products (Licensing, Publishing, Disney store (Europe).
Medium) Rev: USD 2.4B, OI: 0.62B
Outflows (2006) – around 80% in USD
SDec 06 = 106.53 TWC/USD (TWC = Trade-weighted currency index)
PriceDec 06 = USD 34.19
• Case Study: Walt Disney Co.
UPDATE (2006-2013):
- DIS bought Marvel for USD 4B in 2009 and Lucasfilm for USD 4B in
2012.
- DIS introduced a new division: Interactive Media (Kaboosee.com,
BabyZone.com, Playdom (social gaming), etc.)
- DIS ordered two new cruises with 50% more capacity each in 2011.
- Shangai theme park to be opened in 2016.
Q: Economic Exposure? Yes. Probably: Medium
• Check intuition: Calculate a pseudo-elasticity to check EE. We need
data. Let’s use 2013 data:
Inflows (Revenue USD 45.04B, OI: USD 10.72B, EPS: USD 3.38):
S 13 = 101.923 TWC/USD
(USD depreciated by 5.73% against TWC)
Price13 = USD 65.30.
• Case Study: Walt Disney Co.
Summary:
2006 (in USD)
Revenue
Operating
Income
Media
Theme Parks
Studios
Consumer Products
Interactive Media
Total
14.75B
9.95B
7.2B
2.4B
34.3B
3.61B
1.53B
0.73B
0.62B
6.49B
2013 (in USD)
Revenue
Operating
Income
20.35B
14.09B
5.98B
3.56B
1.06B
45.04B
6.82B
2.22B
0.66B
1.11B
-0.09B
10.72B
13-06 Change in Revenue = USD 10.74B (31.31%)
13-06 Change in OI = USD 4.23B (65.18%)
13-06 DIS Stock Return = 111.32%
13-06 ef,t = - 0.05725 (or 5.73% depreciation of the USD)
=> Pseudo-elasticity = % Change in OI / ef,t = .6518/-.05725 = -11.385
• Case Study: Walt Disney Co.
=> Pseudo-elasticity = % Change in OI / ef,t = .6518/-.05725 = -11.385
(Interpretation: a 1% depreciation of the USD, EAT increases by 11.4%)
If stock market numbers are more trusted, recalculate pseudo-elasticity:
=> Pseudo-elasticity = DIS Stock Return/ef,t = 1.1132/-.05725 = -19.45
• According to these elasticities, DIS behaves like a net exporter, a
depreciation of the USD increases cash flows.
• Q: Is this pseudo-elasticity informative? Is St the only variable changing
from 2006 to 2013?
A: No! For example, DIS added assets, then more revenue and OI is
expected. We need to be careful with these numbers. We need to
“control” for these changes, to isolate the effect of ef,t.
• Case Study: Walt Disney Co.
A multivariate regression will probably be more informative, where we
can include other independent (“control”) variables (income growth,
inflation, sales growth, assets growth, etc.), not just ef,t as determinants of
the change in OI (or DIS stock return). Say:
DIS Returnt = α + β ef,t + δ GDP growtht + γ S&P Returnst +
+ θ Assetst + ... + εt
• Managing Disney’s EC
1. Increase expenses in FC
- Make movies elsewhere
- Move production abroad
- Borrow abroad
2. Diversify revenue stream
- Build more parks abroad
- New businesses
• Observation taken from Bloomberg.com (November 20, 2007)
(Dollar Will Weather the Whines, Jeers and Jokes: John M. Berry)
[...] As for jokes, one attempt really wasn't very funny. A cartoon by
Mike Luckovich of the Atlanta Journal-Constitution reprinted in the
Nov. 18 New York Times showed Treasury Secretary Henry Paulson, in
the Oval Office with President George W. Bush, asking, ``Can I get paid
in euros?'‘
Paying in Euros
Actually, Zodiac SA, Europe's biggest maker of airplane seats, would
like to get paid in euros.
Zodiac sells both to Boeing Co. and its European competitor Airbus
SAS, the world's two largest manufacturers of commercial aircraft. It's
hardly surprising that Boeing insists on paying its suppliers in dollars.
However, so does Airbus because so many of its own sales are priced in
dollars.
Should a Firm Hedge?
• Fundamental question: Does hedging add value to a firm?
There are two views:
(1) Modigliani-Miller Theorem (MMT):
(2) MMT assumptions are violated
 hedging adds no value.
 hedging adds value.
The MMT depends on a set of assumptions:
MM requires that a firm operates in perfect markets.
•Hedging is Irrelevant: The MMT
Intuition: What is the value of your car?
Example 1: You bought a last year car using a bank loan.
Q: Is the value of your car affected by the loan you took to pay for it?
• MMT provides a similar story to value a firm.
- Firms make money if they make good investments.
- The financing source of those good investments is irrelevant.
- Different mechanisms of financing will determine how the cash
flows are divided among shareholders or bondholders.
• Hedging works like insurance.
Example 2: You bought insurance for your car.
Q: Is the value of your car affected by the insurance you took?
• MMT's hedging implications.
If the methods of financing and the character of financial risks do not
matter, managing them is not important:
 Hedging should not add any value to a firm.
• Hedging increases the portfolio of the firm. But, hedging is not free:
 Hedging might reduce the value of a firm.
• Another result: Investors can hedge (diversify) by themselves.
Example: Ms. Sternin holds shares of a U.S. exporting firm and shares
of a U.S. importing firm. Ms. Sternin's portfolio is hedged.
A USD depreciation will negatively affect the importing firm and will
positively affect the exporting firm.
Hedging at the firm level -since it is not free- will negatively affect the
value of Ms. Sternin portfolio. ¶
• Hedging Adds Value
Key: MMT assumptions are violated in the "real-world.“
(1) Investors might not be able to replicate an optimal hedge
Sometimes firms can do a better job at hedging than individuals.
Example: Investors might not
be big enough
have enough information
(2) Hedging as a tool to reduce the risk of bankruptcy
If cash flows are very volatile, a firm might be faced with the problem of
needing cash to meet its debt obligations.
Conclusion: Firms with little debt or with good access to credit have no
need to hedge.
Note: Under this view, large corporations may be wasting their capital.
(3) Hedging as a tool to reduce investment uncertainty
Firms should hedge to ensure they always have sufficient cash flow to
fund their planned investment plan.
For example, an exporting firm might have cash flows problems in
periods when the USD appreciates.
Example: Merk, a U.S. pharmaceutical firm, has used derivatives to
ensure that investment (R&D) plans can always be financed. ¶
(4) Stable CFs to get bank financing.
(5) Herding: “Everybody else is hedging. I should hedge too; otherwise, I
may not look good.”
• Do U.S. Firms Hedge?
From a survey of the largest 250 U.S. MNCs, taken in (2001):
(1) Most of the MNCs in the survey understood
translation, transactions, and economic exposure
completely or substantially.
(2) A large percentage (32% - 44%) hedged
themselves substantially or partially. However, a
larger percentage did not cover themselves at all
against transactions and economic exposure.
(3) A significant percentage of the firms' hedging decisions depended on
future FX fluctuations.
(4) Over 25% of firms indicated that they used the forward hedge.
(5) The majority of the firms surveyed have a better understanding of
transactions and translation exposure than of economic exposure.
• Canadian Evidence
The Bank of Canada conducts an annual survey
of FX hedging. The main findings from the 2011
survey are:
• Companies hedge approximately 50% of their FX risk.
• Usually, hedging is for maturities of six months or less.
• Use of FX options is relatively low, mainly because of accounting rules
and restrictions imposed by treasury mandate, rules or policies.
• Growing tendency for banks to pass down the cost of credit (credit
valuation adjustment) to their clients.
• Exporters were reluctant to hedge because they were anticipating that
the CAD would depreciate. On the other hand, importers increased
both their hedging ratio and duration.
Joke: Talking About Accounting
Never trust your Accountant or Stockbroker - The Franciscan
The Godfather, accompanied by his stockbroker, walks into a room to meet with his
accountant. The Godfather asks the accountant, “Where’s the three million bucks you
embezzled from me?” The accountant doesn’t answer. The Godfather asks again,
“Where’s the three million bucks you embezzled from me?”
The stockbroker interrupts, “Sir, the man is a deaf-mute and cannot understand you, but
I can interpret for you.” The Godfather says, “Well, ask him where the @#!* money is.”
The stockbroker, using sign language, asks the accountant where the three million
dollars is. The accountant signs back, “I don’t know what you’re talking about.” The
stockbroker interprets to the Godfather, “He doesn’t know what you’re talking about.”
The Godfather pulls out a pistol, puts it to the temple of the accountant, cocks the
trigger and says, “Ask him again where the @#!* money is!”
The stockbroker signs to the accountant, “He wants to know where it is!” The
accountant signs back, “Okay! Okay! The money’s hidden in a suitcase behind the shed
in my backyard!”
The Godfather says, “Well, what did he say?” The stockbroker interprets to the
Godfather, “He says that you don’t have the guts to pull the trigger.”