Creditsuisse Jpy Vol.

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Volatility in a Low Rate Environment: Lessons from JapanUS Interest Rate Strategy

• As US yields drift lower, the behavior of the US swaption volatility market has almost eerily begun to resemble the Japanese volatility markets during the lost decade. Our core rates outlook remains unchanged yields lower for longer. Our core economic outlook remains confined to weak or weaker outcomes for the economy; there are no good outcomes in the foreseeable future.

• We explore the impact on the US swaption volatility market if the US economy should undergo a protracted balance sheet recession similar to the one in Japan.

15 November 2011Fixed Income Research

http://www.credit-suisse.com/researchandanalytics

Research Analysts Michael Chang

+1 212 325 1962 [email protected]

George Oomman +1 212 325 7361

[email protected]

• Our main conclusions are:

o ATM Implied Volatility – The zero floor on yields is going to imply a fatter right-tailed distribution for yields than a normal distribution would imply.

o MBS Durations – MBS are going to have higher negative convexity as reflected by higher pass-through durations and less negative IO durations in a sell-off scenario.

o The Term Structure of ATM Implied Volatility – This should steepen out significantly as the market prices for increasing terminal variance to longer horizons. Furthermore, long-dated forward rates on long underlying swap maturities are going to have greater delivered volatility as the front end remains anchored due to the Fed on hold.

o Risk Premium Embedded in Gamma Volatility – Post the global financial crises of 2008, selling risk premium has been less profitable as an alpha strategy on a terminal basis.

o Skew – We expect the slope of the skew to steepen further with payer’s skew richening relative to receiver’s skew.

• Based on our structural view for a protracted low rate environment with tail risks of sharply higher long-end rates much later down the road, our core trade recommendations are:

o Long implied volatility on 30-year swaps against implied volatility on 10-year swaps.

o Buy long-dated high rate protection with proceeds from selling short-dated high rate protection on 10-year swaps.

o Sell long-dated payer skew on 10-year tails.

.

15 November 2011

A Brief Macro Primer and the Case for Persistently Low Rates Unemployment is currently running at 9.1% and is not likely to decline in the foreseeable future. That is because if the inverse relationship between unemployment and leverage in the economy (change in private debt normalized by GDP) highlighted in Exhibit continues to hold going forward, unemployment is likely to remain sticky. Prior to the global financial crises of 2008, the economy was running at maximum leverage (black line in Exhibit 1) and unemployment was at the low end of its past 40-year range. Post crises, as the private sector has deleveraged, unemployment has soared. With no imminent signs of a reversal in the current deleveraging process it is difficult to see how unemployment falls sharply from current elevated levels.

1

Exhibit 1: The surge in unemployment has been associated with unprecedented private sector deleveraging

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Jan-70 Jul-75 Jan-81 Jun-86 Dec-91 Jun-97 Nov-02 May-08 Nov-13

Cha

nge

in P

rivat

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ebt a

s a

% o

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(%)

Change in Private Debt as a % of GDPUnemployment (rhs, inverted)Unemployment Forecast

Source: Flow of Funds, Haver Analytics

With no imminent signs of a reversal

in the current deleveraging

process it is difficult to see how

unemployment falls sharply from current

elevated levels

The private sector deleveraging process can be seen in terms of both sector surplus/deficit analysis (Exhibit 2) as well as the absence of credit growth (Exhibit ). Exhibit 2 shows that the private sector (both households and business) is a now a net saver, leaving the government as the only potential borrower, as was the case in Japan. However, given the current fiscally constrained environment, it is unclear whether the US government has the will or means to fill the void left by the private sector. In fact Exhibit shows that from a credit growth perspective, the supply of government debt has been just sufficient to offset the decline in supply of private sector debt but the recent declining trend in private sector debt flows remains a cause for concern from an unemployment perspective as highlighted in Exhibit 1.

4

4

Volatility in a Low Rate Environment: Lessons from Japan 2

15 November 2011

Exhibit 2: An increase in private sector and household saving implies all the spending has to come from the government

-12%

-10%

-8%

-6%

-4%

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0%

2%

4%

6%

8%

10%

1960. 1963. 1966. 1969. 1972. 1975. 1978. 1981. 1984. 1987. 1990. 1993. 1996. 1999. 2002. 2005. 2008. 2011

US

Fund

Sur

plus

as

a %

of G

DP

Government/GDP Businesses/GDPHouseholds/GDP Rest of World/GDP ?

?

Source: Flow of Funds, Haver Analytics, Economic Report of the President

Exhibit 3: … as it played out in Japan

(50)

(40)

(30)

(20)

(10)

0

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1999/1Q 2001/1Q 2003/1Q 2005/1Q 2007/1Q 2009/1Q 2011/1Q

(Tril

lion

Yen

)

General GovernmentsPrivate Non-Financial CorporationsHouseholdsOverseas

Source: Flow of Funds, Haver Analytics, Economic Report of the President


15 November 2011

Exhibit 4: The increase in federal borrowing has not been able to sustain the decline in private borrowing, resulting in flat net supply of debt securities

(3,000)

(2,000)

(1,000)

-

1,000

2,000

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6,000

'99 '00 '01 '02 '03 '04 '05 '06 '07 '08 '09 '10 '11

Qua

rter

ly F

low

(SA

AR

$B

)

Non-Federal Borrow ing

Federal Gov't Borrow ing

Total Borrow ing

Source: Flow of Funds, Haver Analytics

The scarcity of debt is reflected through historically narrow term premiums that are being priced by the market as highlighted in Exhibit 5 – the term premium represents the ex-ante excess return that investors get paid for receiving fixed in a swap versus rolling a Libor deposit quarterly to the maturity date of the swap. Note that this term premium is not a market observable and needs to be extracted out of the market data using a model. Current term premiums in the 30-year swap rate are running at negative levels in contrast to average historical levels of about 98 bps, which is reflected in the overall depressed levels of yields.

Exhibit 5: Term premium, implied by CS Affine Yield Curve model, across the US swap curve collapsed post Lehman and has remained depressed since then due to the scarcity of net supply of debt

Source: Credit Suisse Locus

The risks to term premium declining further because of deflationary headwinds out of Europe are highlighted in Exhibit 6. Any default will likely result in a net reduction in the outstanding supply of duration, which should spill over into US rates markets through a flight-to-quality bid, driving both the term premium and overall rates lower.


15 November 2011

Exhibit 6: Deflationary headwinds out of Europe are only likely to drive US yields lower


Based on the macroeconomic backdrop, rates are not likely to increase materially from current levels over the foreseeable future; in fact, risk further declines due to a combination of persistent weak growth domestically and insolvency stress out of Europe. There are just no good outcomes in sight which require a tightening in monetary policy resulting in higher rates. In fact the shadow overnight rate (the shadow overnight rate represents the market-implied overnight rate; intuitively, it is extrapolated from the long-run neutral rate and the slope of the yield curve, derived from the Credit Suisse Affine Yield curve model) shows that the Fed remains too restrictive even with policy rates barely above zero (Exhibit 7). At the long end, sell-offs are not likely to be sustainable as inflationary pressures remain contained due to the massive capacity slack in the economy, although a stagflationary shock, albeit unlikely, cannot be ruled out.

The market-implied overnight rate

suggests that the Fed is still too restrictive despite target funds

close to zero


15 November 2011

Exhibit 7: The market-implied overnight rate (shadow overnight rate) shows that the Fed remains too restrictive even with the target funds just above zero


Exhibit 8: The future?


Outlook for ATM Implied Volatility Should the US economy undergo a protracted balance sheet recession similar to the one in Japan as highlighted above, the extreme low levels of rates should drive US ATM swaption volatility lower. Our analysis suggests that as rates approach the real world zero bound floor, the swaption volatility market is likely to behave more lognormally rather than normally, implying a fatter right-tailed distribution for rates.

As shown in Exhibit 9, for an unchanged level of normal volatility, the left tail of the implied rate distribution would eventually fall into the negative region as the outright level of rates approach zero. Since negative nominal rate is impossible in the real world, the market should eventually price for a distribution with a fatter right tail, which assigns higher probabilities to increases in rates than a normal distribution. An example of such a distribution is the lognormal distribution.

As nominal rates approach the zero bound

floor, the swaption volatility market should

imply a fatter right tail


15 November 2011

Exhibit 9: The zero floor on rates by definition implies higher ATM log volatility and a fatter right tail at lower yields for the same normal volatility

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-4.00 -2.00 0.00 2.00 4.00 6.00 8.00 10.00 12.001y10y Forward Swap Rate

Normal at 6%Lognormal at 6%Normal at 1%Lognormal at 1%

Source: Credit Suisse

Intuitively ATM implied normal volatility should decline as rates approach the zero bound because of the extreme asymmetrical nature of the distribution of rates going forward. Additionally lower outright rate levels would by definition result in lower delivered basis-point volatility, which would also weigh on implied normal volatility. The scatter plot in Exhibit 10 shows that this relationship has been demonstrated in the Japanese rates market where the directionality between rates and implied normal volatility became especially strong as rates approached the zero bound.

Exhibit 10: In JPY, normal volatility decreased as rates declined due to both the zero floor and lower delivered volatility


In the US rates market, the directionality between rates and implied normal volatility is already observable for two-year and five-year swaps now that both are well below 2%. However, this relationship has not yet played out for 10-year and 30-year swaps. The scatter plots in Exhibit 12 show that there has been no clear correlation between the forward rates and short-dated implied vol on 10-year and 30-year swaps.


15 November 2011

Exhibit 11: This has already happened on 2-year and 5-year tails in the US

Source: Credit Suisse Locus Source: Credit Suisse Locus

Exhibit 12: … but has yet to play out in 10-year and 30-year tails in the US


The CEV model is a broad framework that

describes the dynamics of the forward rate

Exhibit 13 below models forward-rate dynamics within a broader framework known as constant elasticity of variance (CEV). In this framework, the normal basis point volatility is assumed to be proportional to the power (the beta parameter) of the forward rate. Note that this framework is sufficiently broad to encompass both the normal (beta parameter set to 0.0) and the lognormal (beta parameter set to 1.00) as special cases.

The forward rate dynamics in the third equation of Exhibit 13 can be used to estimate the beta parameter and infer an empirical relationship between implied vol and the forward rate. A beta of 1.00 points to strong dependency of rate changes to the level of the forward rate (lognormal model), whereas beta of 0.0 means there is no tie at all between forward rate changes and the level of rates (normal model). Put differently, a beta of 1.0 points to ATM lognormal volatility insensitive to rate levels and a normal volatility positively correlated to rate levels. Similarly a beta of 0.0 points to an ATM normal volatility insensitive to levels of forward rates and a lognormal volatility inversely correlated to rate levels. Note that this empirical relationship between volatility and the forward rate can also be characterized as being super lognormal (beta > 1.0); i.e., lognormal volatility increasing with rate levels and super normal (beta < 0.0); i.e., normal volatility declining with rate levels.

The CEV framework can be used to estimate the

empirical relationship between implied volatility and the

underlying forward rate

We acknowledge the modeling input of Stephen Prajna and the Fid Quantitative Strategy Rates team to this report.


15 November 2011


Exhibit 13: CEV model assumes non-stochastic vol dynamics of forward rate. Estimate dependency of absolute changes in forward rate on level of the forward rate


Using the past six months of historical data, we estimated the betas across the entire vol surface as shown in Exhibit 14 based on the relationship in Exhibit 13 . Note that the upper left of the grid (short-dated expiries on short tails) is close to lognormal and super lognormal, whereas the long tails are closer to super normal. The betas in the grid are consistent with scatter plots from above that showed strong directionality of normal volatility with forward rates for two-year and five-year swaps and a lack of directionality for 10-year and 30-year swaps.

Exhibit 14: Estimates of the beta parameter using past 6m of history. The upper left is closer to lognormal (beta = 1) and super lognormal (beta > 1) and long tails are closer to super normal (beta < 0)


While the estimated betas above can inform the choice of the appropriate model to use, (lognormal, normal, or hybrid), ultimately the choice of the model should be determined by hedge effectiveness. One of the obvious questions that arises is in the event the market is trading lognormally, then how ineffective does it render the hedges implied by a normal model that has been closer to the industry standard for several years. Towards this end we ran the following hedge simulation; we sold daily 100MM 3m2y and 10y10y straddles and delta hedged on day one and unwound both the next day over the course of the past year. To calculate the delta for the hedge notional, we used a normal black model with and without a volatility adjustment to the delta. This volatility adjustment takes into account the directionality of ATM normal volatility with levels of rates assuming the market is trading lognormally. (The sensitivity of normal volatility to rate levels can be calculated exactly by assuming constant log normal volatility.) If the market is trading lognormally, then we would expect the volatility adjustment to the delta to improve the effectiveness of the hedge.

15 November 2011


For 3m2y straddles, delta hedging with vol adjustment has produced better P&L results (as reflected by the lower variance of unhedged vega P&L) than delta hedging without vol adjustment to the delta. In contrast for the 10y10y straddles, delta hedging without vol adjustment has produced better P&L results (lower variance) than delta hedging with vol adjustment. The analysis shows that volatility adjustment to the delta can improve hedging effectiveness significantly when the market trades lognormally, as is the case for 3m2y straddles, but actually introduces more noise into the hedged P&L when the market trades normally, as is the case for 10y10y straddles.

Exhibit 15: Volatility adjustment to the delta can make a significant difference if market trades lognormal Delta hedge with vol adjustment has lower variance Delta hedge without vol adjustment has lower variance

Source: Credit Suisse Source: Credit Suisse

Outlook for MBS Durations We analyzed the impact lognormal/normal models would have on MBS durations. We find that MBS should have higher negative convexity, which impacts durations differently depending on if the security is a pass-through or an IO.

Under a lognormal model, a move up in rates will proportionally increase the absolute volatility. As the embedded prepayment option is proportional to absolute volatility, assuming a constant OAS, an up shift rate scenario will decrease the price of the MBS more than in the case of the normal model. This implies longer effective durations for TBA under lognormal assumptions.

Similarly, under lognormal model assumptions IOs will increase less in value in an up rate scenario than under normal assumptions. This is because the decrease in price due to callability/short vega exposure dominates the increase in price due to a higher mortgage rate resulting from a wider mortgage/swap basis. This implies less negative durations for IOs under lognormal assumptions.

Ultimately, the choice of model

should be determined by

hedge effectiveness

MBS should have higher negative

convexity, which impacts durations

differently depending on if the

security is a pass-through or an IO

We acknowledge the modeling input of David Zhang and the Mortgage Modeling team to this report.

15 November 2011

Exhibit 16: Normal to Lognormal: TBA durations should increase more in a sell-off; extension risk should increase

30-year 4.0% TBA: DV01 versus Profile

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-150 -100 -50 0 50 100 150 200 250

Relative Coupon in bps (4.00-CC)

lognormal dur$

Production dur$

Source: Credit Suisse Mortgage Strategy

Exhibit 17: Normal to Lognormal: IO durations should become less negative in a sell-off as increase in callability risk dominates slower prepayments due to a higher mortgage rate from a wider basis

IOS 400 2009: DV01 vs Relative Coupon Profile

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Relative Coupon (4.00-CC)

Production dur$

lognormal dur$

Source: Credit Suisse Mortgage Strategy

Term Structure of Implied Volatility The vol term structure for

a fixed tail should steepen as the market prices for

increasing terminal variance combined with

higher delivered volatility for longer-dated forwards

In the scenario where the US rates market continues to drift sideways or lower for a prolonged period similar to the Japanese experience, we expect the term structure of ATM implied volatility to steepen out significantly rather than to return to a “normal” hump-shaped curve. We believe an eventual steepening of the implied volatility term structure is likely as the market prices for increasing terminal variance to longer horizons. In addition, with the front end anchored as the Fed remains on hold for an extended period, longer-dated forward rates for a fixed underlying swap should have greater delivered volatility. In fact this is currently the case in Japan as is highlighted in Exhibit 18. A reshaping of term structure of this sort would be consistent with the Japanese volatility markets where the term structures are completely upward sloping on all swap tenors other than the 30-year tail.


15 November 2011

Exhibit 18: For a fixed underlying swap rate, past 6m delivered volatility is an increasing function of the forward settlement date in JPY


That said the adjustment process towards a steeper volatility term structure could be drawn out as persistent event risk continues to support short-dated expiries, resulting in the currently inverted term structure of volatility.

Prior to the current global financial crisis, the term structure of implied US swaption volatility was humped shape on average, reflecting the embedded mean reversion of rates. The term structures shown in Exhibit 19 are constructed from the simple averages of implied volatilities from 1994 to 2008. Although the peaks occurred at different expirations for different swap tenors, the term structures were hump shaped, with the market pricing for possible market turbulence over the near to medium term but an eventual return to a range over the long term.

Exhibit 19: Pre-crises, the term structure of volatility was hump shaped on average, reflecting the mean reversion embedded in interest rates


After the start of the financial crisis, however, the term structure of volatility has been inverted on average (from 2008 to present) on all swap tenors other than 2s, reflecting elevated levels of near-term event risk. The volatility term structure on two-year swaps has not inverted on average because short-dated volatility quickly collapsed as the two-year swap rate approached the zero bound (as noted earlier) because of its high correlation to policy rates.


15 November 2011

Exhibit 20: Post crises, the term structure of volatility has been inverted on average for long tails, reflecting elevated levels of event risk since 2008


Going forward, we expect the volatility term structure to disinvert if the respective swap rates continue to grind lower and approach the zero bound. Not only should the volatility term structure disinvert, it should become steeply upward sloping, with the peak of the curve eventually pushed farther out as the market prices for increasing terminal variance to longer horizons. Exhibit shows that the volatility term structure in the US should ultimately resemble the Japanese volatility term structure if the prolonged low rate scenario is realized.

21

Exhibit 21: As yields decline, the term structure of volatility should be steeply upward sloping as the market prices for increasing terminal variance to longer horizons


If the yield curve reshapes as expected with shorter maturity rates grinding to the zero bound ahead of longer maturity rates, implied volatility on 30s should continue to richen relative to implied volatility on all other tails. The directionality between rates and volatility (highlighted earlier) is likely to manifest in 10s first, rather than 30s, as rate declines since 10s are likely to approach the zero bound before 30s.


15 November 2011

Additionally dealer hedging flow of Bermudan callable swaps is likely to be supportive of volatility on 30-year tails as rates decline. Borrowers will issue fixed rate debt (30+ years maturity) with Bermudan call back features (on multiple but discrete exercise dates) but usually swap the call options (Bermudan receiver swaptions) to dealers that then hedge these long volatility exposures by shorting European style volatility (single expiration) on 30-year swap rates.

Dealer hedging should richen

30-year tails versus 10-year tails

If rates decline significantly and the call options are exercised, dealers would be left with the short volatility hedges that would need to be covered, causing implied volatility on 30-year tails to richen. This negative rate versus vol correlation dynamic for 30-year tails sharply contrasts with the positive rate/vol correlation observable on other swap tenors, which could magnify the potential richness of volatility on 30s to 10s in a low rate scenario. Exhibit 22 shows that over the past two years, implied 6m30y basis-point vol tends to richen relative to 6m10y basis-point vol as rates decline and tends to cheapen as rates increase.

Exhibit 22: Implied vol on 30s tends to richen relative to implied vol on 10s as rates decline and tends to cheapen as rates increase

Dec 30, 09 Jul 1, 10 Dec 30, 10 Jul 1, 11

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ap ra

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6m30y bp vol - 6m1oy bp vol 10yr Swap Rate (rhs, inverted)


Risk Premium in Implied Volatility Selling volatility is

likely to be less profitable as an

alpha strategy in a post-crises world

As with other markets, implied volatility also trades with a risk premium because of supply/demand imbalances, elevated event risk, and the increased presence of actual or perceived unhedgeable risk factors that result in greater liquidity risk. Exhibit 23 highlights one indicator for risk premium in the implied volatility market – the vol momentum ratio, which is the rolling three-month change in the ratio of 1y10y vol to 3m10y vol. When momentum is in deep negative territory as it was recently, then 3m10y volatility has richened sharply over the past three months relative to 1y10y and represents an increase in risk premium in short-dated expiries. Similarly, when this ratio is in deep positive territory, 3m10y volatility tended to cheapen sharply relative to 1y10y over the past three months.


15 November 2011

Exhibit 23: Vol momentum ratio


This begs the larger question of whether the market has priced this risk premium fairly. The answer to this question is dependent on the time period in the study. Prior to September 2008, as highlighted in Exhibit 24 when short-dated expirations richened sharply, the market appears to have overpriced risk premium based on our analysis; the observed volatility in the 10-year swap rate about its forward over the following three months from the time when a rich signal was observed is markedly lower (blue histogram) than looking at the distribution of the 10-year swap rate around its forward without any filtering on the momentum ratio (red histogram). On the other hand, after September 2008, it appears based on our analysis, in Exhibit 25, that the market is now pricing risk premium fair to cheap whenever the rich signal was observed, as reflected by the pronounced bi-modal distribution relative to the distribution without filtering. The investment implications are that pre-crises, selling short-dated straddles on the 10-year swap rate represented a valid alpha strategy as the risk rich premium could be harvested profitably. This is less likely to be the case going forward if elevated event risk becomes endemic to the global economy.

Exhibit 24: Pre-crises, gamma vol has had excess risk premium that could be harvested by selling straddles

Exhibit 25: Post crises, the risk premium has been insufficient on a terminal basis as shown by fatter tails



15 November 2011

Indeed, Exhibit 26 highlights the risk to being short volatility in a low yield environment. During the summer of 2003 yields were at generational lows in Japan and expected to remain depressed for the foreseeable future against the back drop of the Bank of Japan’s commitment to keeping policy rates low for a well defined duration. However, a burst of strong economic data globally led to a significant sell-off in most rates markets, including Japan, resulting in an unprecedented spike in implied volatility. The US rates market looks like it is setting up for a similar environment with the Fed’s commitment this past August to keep zero policy rates up to mid-2013.

Exhibit 26: Short volatility can be a risky strategy in a low rate environment


Skew The implied volatility skew represents a current snapshot of implied volatility (or spread to ATM volatility) as a function of strike. There are many reasons for the existence of a skew; anticipated dynamics of both implied volatility and forward rates and their mutual interaction, supply and demand imbalances for strikes away from ATM, and variations in liquidity away from the ATM strike. All of these drivers imply deviation from normality away from the ATM strike.

Exhibit highlights a scatter plot of ATM 3m2y normal volatility versus the level of its respective forward rate. Superimposed on the scatter is the implied volatility skew from different regimes. What jumps out is that the shape of the skew has changed dramatically as front-end rates have approached the zero floor. In a high rate environment, the skew was negative with low strike receivers commanding a premium over high strike payers. In the current low rate regime, the skew has now turned sharply positive with high strike payers commanding a substantial premium over low strike receivers. The economics of this pricing structure can be explained by the lack of demand for low strike receivers on the 2-year swap rate given historically low levels of interest rates. Exhibit 28 shows that the upper left of the volatility surface also has the largest payer skew stemming from the strong directionality between normal volatility and rates in this sector. Exhibit 29 shows that the payer skew on long tails (long underlying swap rates) is the least because deviation from normality is minimal for these tails as established empirically in Exhibit .

27The shape of the skew has changed

dramatically as front-end rates have

approached the zero floor

14


15 November 2011

Exhibit 27: The skew for the upper left has become sharply positive in the current low rate environment compared to a negative skew in a high rate environment


Exhibit 28: The upper left (short-dated expirations on short tails) has the largest payer skew because deviation from normality is the most pronounced


Exhibit 29: The lower right (long-dated expirations on long tails) has the least payer skew because deviations from normality are minimal



15 November 2011

Based on the Japanese experience, the slope of the US skew should steepen further if rates continue to decline and the curve flattens.

Exhibit 30: The slope of the skew should steepen further as yields decline


Current Dislocations and Core Recommendations Based on our structural view for a protracted low rate environment with tail risks of sharply higher long-end rates much later down the road, our core trade recommendations after accounting for current market dislocations are:

• Long implied volatility on 30-year swaps against implied volatility on 10-year swaps. • Buy long-dated high rate protection with proceeds from selling short-dated high rate

protection on 10-year swaps. • Sell long-dated payer skew on the 10-year tails.

Long Implied Volatility on 30s Against Implied Volatility on 10s As we have highlighted earlier, implied volatility on 30s should continue to richen relative to implied volatility on all other tails if shorter maturity rates continue to grind toward the zero bound ahead of longer maturity rates. Dealer hedging flow of Bermudan callable swaps is also likely to be supportive of volatility on 30-year tails as rates decline. Based on this view, we favor being long implied volatility on 30s against implied volatility on 10s.

Exhibit 31: Carry attribution analysis 3-month 6-month

Time Decay 63,921 122,117

Rate (32,862) (66,205)

Vol 153,081 292,563

Total 184,140 348,476 Source: Credit Suisse Locus

Specifically, we favor selling ATM 5y10y straddles and buying ATM 5y30y straddles with vega neutral weighting. The trade carries positively with the net positive rolldown along the volatility surface, outweighing the net negative rolldown along the rate curve. The net positive time decay also contributes to the overall carry as shown in Exhibit 31. As noted earlier in Exhibit 22, the trade has a bullish bias given that implied vol on 30s tends to richen relative to implied vol on 10s, as rates decline and tends to cheapen as rates increase. The main risk to this trade is if implied vol on 10s richens at a faster pace than implied vol on 30s.


15 November 2011

Exhibit 32: Buying 100MM ATM 5y30y straddles versus selling 223MM ATM 5y10y straddles B/S NPA Instrument Premium ($) Strike ATMF Spot Vega ($) Gamma ($) Sell 223MM ATM 5y10y Straddles 33,450,00 3.424 3.424 2.228 -314,990 -1,069 Buy 100MM ATM 5y30y Straddles 31,200,00 3.310 3.310 2.866 314,556 1,215 2,250,000 -432 146 Source: Credit Suisse

Buy Long-Dated High Rate Protection and Sell Short-Dated High Rate Protection Our structural view for a protracted low rate environment remains unchanged. Thus for investors who wish to buy protection for an eventual rise in rates, we suggest looking at OTM payers with longer rather shorter expirations. Additionally, we recommend offsetting the cost of the long expiration payers by selling short expiration payers that are likely to expire worthless, in our view.

Specifically, we favor selling $245mm of 67 bps OTM 1y10y payers and buying $100mm of 100 bps OTM 5y10y payers at zero cost. The notionals are chosen so that the trade is close to being vega neutral and the 1y10y strike is adjusted so that this trade is also zero cost when it is initiated. The payer calendar spread carries positively and offers a generous sell-off breakeven cushion of approximately 135 bps from spot over the next year. Even if rates do rise sharply and the 10-year swap rate reaches the OTM strike on the short-dated payer where it would be exercised, investors would essentially be receiving duration at a level that we perceive to be attractive. The main risk to this trade is if the market sells off sharply beyond the breakeven shown below by the trade’s expiration.

Exhibit 33: Buying 100MM 100bps OTM 5y10y payer versus selling 245MM 67bps OTM 1y10y payer for zero cost B/S NPA Instrument Expiry Tenor Strike ATMF Spot Delta ($) Vega ($) Gamma ($) Sell 245MM 67 bps OTM Payer 1y 10y 3.194 2.524 2.228 -47,331 -82,087 -586 Buy 100MM 100 bps OTM Payer 5y 10y 4.424 3.424 2.228 16,019 71,693 144 -31,312 -10,394 -442 Source: Credit Suisse

Exhibit 34: P&L profile



15 November 2011


Sell Long-Dated Payer Skew on 10-year Tails: Buy 100 bps OTM 5y10y Payers Against Equal Notional of 200 bps OTM 5y10y Payers The current shape of the vol skew allows investors who are bearish on rates to monetize the still relatively rich payer skew through payer spreads. Rather than buying long-dated payers outright, we recommend establishing 1x1 payer spreads to reduce part of the cost by selling high strike OTM payers. Specifically, we favor buying 100 bps OTM 5y10y payers and selling an equal notional of 200 bps OTM 5y10y payers. Exhibit 35 shows that although the vol spread that is to be monetized is off from its recent peak, it remains relatively elevated and can help to reduce the upfront premium paid. The maximum terminal P&L is approximately 4x the premium paid. The downside risk to this trade is limited to the upfront premium paid in the scenario where rates don’t rise enough by the trade’s expiration.

Exhibit 35: Current shape of the vol skew allows investors who are bearish on rates to monetize the still relatively rich payer skew through payer spreads


Exhibit 36: Buying 100MM 100bps OTM 5y10y payer versus selling 100MM 200bps OTM 5y10y payer B/S NPA Instrument Premium (bps) Strike ATMF Spot Delta ($) Vega ($) Gamma ($) Buy 100MM 100bps OTM 5y10y Payer 467 4.424 3.424 2.228 16,019 71,693 144 Sell 100MM 200bps OTM 5y10y Payer 289 5.424 3.424 2.228 -7,202 -61,862 -95 178 8,818 9,831 49 Source: Credit Suisse

Exhibit 37: P&L profile


INTEREST RATE STRATEGY

Eric Miller, Managing Director Global Head of Fixed Income and Economic Research

+1 212 538 6480 [email protected]

US RATES EUROPEAN RATES US DERIVATIVES Carl Lantz, Director US Head +1 212 538 5081 [email protected]

Helen Haworth, CFA, Director European Head +44 20 7888 0757 [email protected]

George Oomman, Managing Director Derivatives Head +1 212 325 7361 [email protected]

Ira Jersey, Director +1 212 325 4674 [email protected]

Michelle Bradley, Director +44 20 7888 5468 [email protected]

Scott Sherman, Vice President +1 212 325 3586 [email protected]

Douglas Huggins, Director +44 20 7883 2337 [email protected]

Michael Chang, Vice President +1 212 325 1962 [email protected]

Sabine Winkler, Director +44 20 7883 9398 [email protected]

Carlos Pro, Associate +1 212 538 1863 [email protected]

Panos Giannopoulos, Vice President +44 20 7883 6947 [email protected]

Eric Van Nostrand, Analyst +1 212 538 6631 [email protected]

Thushka Maharaj, Vice President +44 20 7883 0211 [email protected]

TECHNICAL ANALYSIS

David Sneddon, Managing Director +44 20 7888 7173 [email protected]

Steve Miley, Director +44 20 7888 7172 [email protected]

Christopher Hine, Vice President +1 212 538 5727 [email protected]

Pamela McCloskey, Vice President +44 20 7888 7175 [email protected]

Cilline Bain, Associate +44 20 7888 7174 [email protected]

Marion Pelata, Analyst +44 20 7883 1333 [email protected]

LOCUS ANALYTICS (US AND EUROPE)

Jennifer Drag, Director Locus Analytics Specialist +1 212 538 4303 [email protected]

PARIS SINGAPORE TOKYO

Giovanni Zanni, Director European Economics – Paris +33 1 70 39 0132 [email protected]

Jarrod Kerr, Director +65 6212 2078 [email protected]

Kenro Kawano, Director Japan Head +81 3 4550 9498 [email protected]

Shinji Ebihara, Vice President +81 3 4550 9619 [email protected]

Disclosure Appendix

Analyst Certification Michael Chang and George Oomman each certify, with respect to the companies or securities that he or she analyzes, that (1) the views expressed in this report accurately reflect his or her personal views about all of the subject companies and securities and (2) no part of his or her compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this report.

Important Disclosures Credit Suisse's policy is only to publish investment research that is impartial, independent, clear, fair and not misleading. For more detail, please refer to Credit Suisse's Policies for Managing Conflicts of Interest in connection with Investment Research: http://www.csfb.com/research-and-analytics/disclaimer/managing_conflicts_disclaimer.html Credit Suisse’s policy is to publish research reports as it deems appropriate, based on developments with the subject issuer, the sector or the market that may have a material impact on the research views or opinions stated herein. The analyst(s) involved in the preparation of this research report received compensation that is based upon various factors, including Credit Suisse's total revenues, a portion of which are generated by Credit Suisse's Investment Banking and Fixed Income Divisions. Credit Suisse may trade as principal in the securities or derivatives of the issuers that are the subject of this report. At any point in time, Credit Suisse is likely to have significant holdings in the securities mentioned in this report. As at the date of this report, Credit Suisse acts as a market maker or liquidity provider in the debt securities of the subject issuer(s) mentioned in this report. For important disclosure information on securities recommended in this report, please visit the website at https://firesearchdisclosure.credit-suisse.com or call +1-212-538-7625. For the history of any relative value trade ideas suggested by the Fixed Income research department as well as fundamental recommendations provided by the Emerging Markets Sovereign Strategy Group over the previous 12 months, please view the document at http://research-and-analytics.csfb.com/docpopup.asp?ctbdocid=330703_1_en. Credit Suisse clients with access to the Locus website may refer to http://www.credit-suisse.com/locus. For the history of recommendations provided by Technical Analysis, please visit the website at http://www.credit-suisse.com/techanalysis. Credit Suisse does not provide any tax advice. Any statement herein regarding any US federal tax is not intended or written to be used, and cannot be used, by any taxpayer for the purposes of avoiding any penalties.

Emerging Markets Bond Recommendation Definitions Buy: Indicates a recommended buy on our expectation that the issue will deliver a return higher than the risk-free rate. Sell: Indicates a recommended sell on our expectation that the issue will deliver a return lower than the risk-free rate.

Corporate Bond Fundamental Recommendation Definitions Buy: Indicates a recommended buy on our expectation that the issue will be a top performer in its sector. Outperform: Indicates an above-average total return performer within its sector. Bonds in this category have stable or improving credit profiles and are undervalued, or they may be weaker credits that, we believe, are cheap relative to the sector and are expected to outperform on a total-return basis. These bonds may possess price risk in a volatile environment. Market Perform: Indicates a bond that is expected to return average performance in its sector. Underperform: Indicates a below-average total-return performer within its sector. Bonds in this category have weak or worsening credit trends, or they may be stable credits that, we believe, are overvalued or rich relative to the sector. Sell: Indicates a recommended sell on the expectation that the issue will be among the poor performers in its sector. Restricted: In certain circumstances, Credit Suisse policy and/or applicable law and regulations preclude certain types of communications, including an investment recommendation, during the course of Credit Suisse's engagement in an investment banking transaction and in certain other circumstances. Not Rated: Credit Suisse Global Credit Research or Global Leveraged Finance Research covers the issuer but currently does not offer an investment view on the subject issue. Not Covered: Neither Credit Suisse Global Credit Research nor Global Leveraged Finance Research covers the issuer or offers an investment view on the issuer or any securities related to it. Any communication from Research on securities or companies that Credit Suisse does not cover is factual or a reasonable, non-material deduction based on an analysis of publicly available information.

Corporate Bond Risk Category Definitions In addition to the recommendation, each issue may have a risk category indicating that it is an appropriate holding for an "average" high yield investor, designated as Market, or that it has a higher or lower risk profile, designated as Speculative and Conservative, respectively.

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