systematic alpha monthly

ANALYST CERTIFICATIONS AND IMPORTANT DISCLOSURES ARE IN THE DISCLOSURE APPENDIX. FOR OTHER IMPORTANT DISCLOSURES, PLEASE REFER TO https://firesearchdisclosure.credit-suisse.com

07 September 2011Fixed Income Research

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

Systematic Alpha Monthly

September 2011

Research Analysts David Tien

Director 1 212 538 9665

[email protected]

Riad Houry Associate

+44 20 7883 0168 [email protected]

Richard Durand

Director +1 212 538 6445

[email protected]

Meng-Chen Hsieh Associate


Bhaskar Krishnan

Director +1 212 538 5632

[email protected]

Weijian Liang Associate


Yongchu Song

Director +1 212 538 7013

[email protected]

Limin Wang Vice President


.

07 September 2011

Table of Contents

Global Market Overview 3

Performance Review and Recommendations 4

Credit Suisse Alpha Strategies Platform 6

Individual Strategy Performance 7

Research Spotlight: Profiting from the Excess Demand for Tail Risk Hedges 9

Strategy Snapshots 16 Equities ...................................................................................17 Interest Rates..........................................................................22 Foreign Exchange...................................................................27 Commodities ...........................................................................28 Emerging Markets...................................................................30 Tail-Risk Hedging....................................................................31 Hybrid......................................................................................35 Liquid Alternative Beta ............................................................38

Appendix 42 The Extreme Flow Indicator ....................................................43

Systematic Alpha Monthly 2

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Global Market Overview • Economics: While global manufacturing

surveys continue to point to softening economic activity, the downside surprise in US non-farm payrolls underscored the growing concerns about global growth conditions. Ben Bernanke’s long-awaited Jackson Hole speech hinted at some degree of monetary policy intervention, but details will not be announced before the September 21 FOMC statement.

• Market Sentiment: Market sentiment was mostly negative throughout the month, as asset prices across a range of markets were convulsed by a confidence shock. Evidence of the dramatic deterioration in confidence can be seen in the outperformance of gold versus traditional safe haven currencies, such as the Japanese yen and Swiss franc.

In Gold We Trust: Comparing Safe Haven Currencies versus Gold

90100110120130140

Dec-10 Mar-11 May-11 Jul-11

JPY TWI CHF TWIGold (USD/oz.)

Source: Bank of England, the BLOOMBERG PROFESSIONAL™ service, Credit Suisse Note: Data as of 9/6/2011

Italy and Spain 10Yr Yield Spread over Germany, 1990 – 2011

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100

200

300

400

Dec-99 Dec-01 Dec-03 Dec-05 Dec-07 Dec-09

Italy Spain

Source: OECD, the BLOOMBERG PROFESSIONAL™ service Note: Data as of 9/6/2011

Benchmark Performance Benchmark Level MTD YTD VIX 31.6 25.2% 78.1% MSCI World 1211.2 -7.3% -5.4% S&P GSCI 495.5 -1.8% 3.2% S&P 500 1218.9 -5.7% -3.1% JPM Global Bond 312.0 1.9% 4.1% US 10Yr Yield 2.22 -0.57 -1.07 Gold 1825.7 12.2% 28.5% Moody's BAA Sprea d 187.9 27.7% 14.2% Source: the BLOOMBERG PROFESSIONAL™ service Note: Data as of 8/31/2011

• Fixed Income: Bond yields have fallen to historical lows in the US and Germany given demand for safe havens and easy monetary policy. Meanwhile, spreads of Italian and Spanish yields rose drastically in the month.

• Equities: Global equity markets continued to take a beating, ending the month down nearly 6% for the S&P 500 and 14% for Euro Stoxx.

• FX: Most G10 currencies were down for the month led by NZD and AUD, which were coming off the historical highs they reached at the end of July.

• Commodities: Gold generally continued to rally despite a brief respite in the second half of the month, ending over 12% up in August.

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Performance Review and Recommendations lAlpha Strategies Thematic Portfolios The Alpha Strategies team has constructed thematic portfolios of index strategies for investors seeking uncorrelated returns from low-fee, liquid investments that perform in a variety of market conditions.

At the end of each year, we categorize the indices into three broad portfolios, based on their five-year return correlations with the S&P 500. The Growth portfolio is designed to perform when equity markets rally, the Defensive portfolio when the markets are flat to down and the Market-Neutral portfolio irrespective of market conditions. Indices are weighted inversely to their volatility.

Portfolios Constructed Using Historical Correlation between Individual Indices and S&P 500, December 2010

-0.8 -0.4 0.0 0.4 0.8

CSAVI-SPXCSAVI-FX Long Only

CSAMIMOVERS

CSAVI-FX OpportunisticMCI

FX FactorEMCROPCSAVI-IR

HS Market NeutralHS Global Sty le Rotation Equity Hedged

Global Carry SelectorMIDAS

ACEGAINS

RAII HOLTCARES

HS Global Sty le Rotation

5-Year Return Correlation to S&P 500

Grow th Portfolio

Defensive Portfolio

Market Neutral Portfolio

Source: Credit Suisse, the BLOOMBERG PROFESSIONAL™ service

Cumulative Performance of the Index Portfolios from January 2007 to August 2011

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Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10 Jun-11

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Source: Credit Suisse, the BLOOMBERG PROFESSIONAL™ service


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Alpha Strategies Tactical Portfolio Recommendation: Continue to Hold the Growth Index Portfolio Alpha Strategies uses the Extreme Flow Indicator (EFI) to make tactical recommendations for the month ahead (see Appendix for details on the Extreme Flow Indicator). The EFI switched to a risk-on portfolio stance on June 7, 2011, after three months of risk-off recommendations. The EFI is based on net positioning in S&P 500 futures and helps to gauge when risky assets have reached a medium-term peak or trough.

For investors seeking positive absolute returns irrespective of market regime, we recommend holding the Market Neutral Portfolio.

Cumulative Performance of Allocating Between Growth and Defensive Portfolios Based on the Extreme Flow Indicator

EFI Tactical Portfolio Performance Summary See appendix for details on the EFI Tactical Portfolio

100125150175200

Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10 Jun-11

Cum

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Growth Regime Defensive Regime EFI Tactical Portfolio

Jan 2007 – Aug 2011 Annual Return 14.06% Sharpe Ratio 7.73% Maximum Drawdown 1.82 2011 Year-to-Date return 5.01%

Source: Credit Suisse, the BLOOMBERG PROFESSIONAL™ service Note: Data as of 8/31/2011

Source: Credit Suisse, the BLOOMBERG PROFESSIONAL™ service Note: Data as of 8/31/2011

Market Neutral Allocation Portfolio Objective: Generate positive absolute returns irrespective of broad equity market performance

Defensive Allocation Portfolio Objective: Focus on generating significant outperformance in recessionary economic environments

Growth-Oriented Allocation Portfolio Objective: Focus on generating significant outperformance in strong economic growth environments

0% 20% 40% 60% 80% 100%

Equity

Rates

FX

Commodities

EM

Hybrid

Portfolio Weight

0% 20% 40% 60% 80% 100%

Equity

Rates

FX

Commodities

EM

Hybrid

Portfolio Weight

0% 10% 20% 30% 40% 50% 60% 70%

Equity

Rates

FX

Commodities

EM

Hybrid

Portfolio Weight

Source: Credit Suisse Note: Data as of 12/31/2010

Weight Allocation CSAVI-IR 39% CSAVI-SPX 4% ACE 9%Macro Conditions 42% CSAMI 47% HS Global Style Rotation 10%FX Factor 4% Macro Conditions 39% RAII HOLT 13%CSAVI-FX 4% CSAVI-FX 4% GAINS 10%MOVERS 2% CSAVI-FX Long 3% CARES 8%EMCROP 8% MOVERS 2% CSMIDAS 50%Source: Credit Suisse Note: Data as of 12/31/2010

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Credit Suisse Alpha Strategies Platform

Alpha

Equities Commodities Emerging Markets

Foreign Exchange

InterestRates

Hedge Fund Beta

Global Style Rotation EH

Global Style Rotation

HOLT Quality Factor Swap

Global Carry Selector

CSAVI-SPX

HOLT Market Neutral

HOLT Value Factor Swap

GAINS

MOVERS MN

CSAVI-FX

CSAVI-FXLong

ROCI

FX Metrics

FX Factor Momentum

FX FactorCarry

FX Factor Interest Rate Alpha Basket

CSAVI-IR

CSMCI

CSAMI

CSATPI

CSMM

EMSELeCT*

EMCROP

CSGLOBE*

CSMIDAS

CARES

RAII HOLT

Hybrid

MergerArb IndexCSCB CSEMLC

BetaCarryLong/Short

Liquid Index

Multi Alpha

Event Driven Index

MomentumFortinbras

TFMIMOVERS

FX Factor Value

Value

CSAVI-JPY

Volatility

FX Factor EM

* Indices currently under development

Source: Credit Suisse

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Individual Strategy Performance RETURN SHARPE RATIO

Strategy Style Bloomberg Ticker

Inception Date

Current Month Year-to-Date Past 12-

Months Total Return

Since Inception Past 12-Months

Since Inception

Index Portfolios Growth -1.56% 5.13% 22.03% 1.81 -1.56% Defensive -0.08% -0.14% -0.85% -1.19 -0.08% Market Neutral -0.29% 0.16% 0.10% 0.23 -0.29% EFI Tactical Portfolio -1.56% 5.01% 21.56% 2.00 -1.56% Equities ACE Carry CSACE 01/01/2010 -7.10% -5.09% -1.42% -8.62% -0.03 -0.42 HS Global Style Rotation Hybrid HSGSR 10/14/2009 -8.44% -1.57% 18.59% 7.48% 0.99 0.51 HS Market Neutral Value HSGMN 09/01/2007 -0.94% -0.44% 2.88% -1.41% 0.78 -0.21 HS Global Style Rotation Equity Hedged Hybrid HSGSREH 04/01/2010 -1.41% 3.50% 5.48% 4.65% 1.59 1.32 Global Carry Selector Volatility GCSCS 01/02/2009 1.37% 32.26% 49.00% 23.63% 2.41 1.12 Interest Rates Adaptive Volatility Index - IR Volatility CSVIA 03/01/2009 -0.08% 1.19% 0.57% 2.20% 0.70 1.71 Macroeconomic Conditions Index Value CSMCUS20 12/28/2009 -0.31% -0.26% 0.03% -0.04% 0.04 -0.07 Adaptive Momentum Index Momentum CMOIEREU 08/01/2008 0.23% 0.30% 0.33% 0.69% 0.67 1.14 Fortinbras TFMI Momentum CSFNERUS 06/27/2008 1.63% 2.35% 1.96% 4.31% 0.83 1.28 Adaptive Term Premium Index Carry CATPUSEA 01/11/2011 -0.48% 0.38% 0.50% 0.34% 0.27 0.20 Foreign Exchange FX Factor Hybrid FXFTERUS 04/01/2009 -4.64% -9.49% -9.57% -2.40% -1.67 -0.41 Commodities GAINS Value CSGADER 10/15/2008 2.65% 2.41% 29.55% 18.17% 1.47 1.07 MOVERS Value CSMVERS 02/01/2009 0.97% 9.02% 21.84% 1.94% 1.37 0.20 Emerging Markets EMCROP Value EMCPERUS 01/26/2011 -2.14% 0.48% 2.30% -1.00% 0.60 -0.22 Tail-Risk Hedging Advanced Volatility Index - FX Opportunistic Volatility CSVIOEUS 09/01/2009 1.02% -0.30% -4.57% 0.94% -0.77 0.22 Advanced Volatility Index - FX Long Volatility CSVILEUS 09/01/2009 1.67% -0.26% -5.21% -2.99% -0.79 -0.45 Advanced Variance 5% Volatility Index Volatility CSVISPX5 01/07/2011 -3.68% -7.07% -7.07% -10.73% -2.38 -2.38 Equity Tail Hedge Index Tail-Risk Hedging CSEATAIL 07/15/2011 9.45% 5.91% 2.06% 78.55% 0.19 1.44

Source: Credit Suisse Note: Data as of 8/31/2011 Sharpe Ratio: We calculate the Sharpe Ratio as the annualized average excess return divided by the annualized daily volatility of the strategy. For excess return strategies, we simply use the raw strategy returns. For total return strategies, we deduct the 1-month LIBOR for the currency in which the strategy is denominated. For more information please visit us on Bloomberg at IGAT <GO>

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Individual Strategy Performance (cont’d) RETURN SHARPE RATIO

Strategy Style Bloomberg Ticker

Inception Date

Current Month Year-to-Date Past 12-

Months Total Return

Since Inception Past 12-Months

Since Inception

Hybrid CARES Value CSCSTR 05/01/2009 -2.08% 3.52% 29.65% 17.68% 1.13 0.83 RAII HOLT Value RAIIHUST 04/06/2010 3.96% 11.81% 29.71% 17.02% 2.42 1.39 CSMIDAS Hybrid CSMDCEUS 12/31/2009 -0.81% 0.97% 3.40% 1.36% 0.67 0.30 Liquid Alternative Beta Liquid Alternative Beta Hybrid CSLAB 12/31/2009 -3.36% -0.98% 5.22% 4.22% 0.63 0.57 Long/Short Liquid Index Hybrid CSLABLS 04/30/2008 -3.68% -0.38% 9.03% 1.25% 0.79 0.17 Event Driven Liquid Index Hybrid CSLABED 12/31/2009 -4.61% -1.95% 7.12% 6.73% 0.67 0.70 Merger Arbitrage Liquid Index Hybrid CSLABMA 12/31/2009 -0.77% 2.89% 5.29% 6.56% 1.10 1.43

Source: Credit Suisse Note: Data as of 8/31/2011 Sharpe Ratio: We calculate the Sharpe Ratio as the annualized average excess return divided by the annualized daily volatility of the strategy. For excess return strategies, we simply use the raw strategy returns. For total return strategies, we deduct the 1-month LIBOR for the currency in which the strategy is denominated. For more information please visit us on Bloomberg at IGAT <GO>

07 September 2011

Research Spotlight: Profiting from the Excess Demand for Tail Risk Hedges In the aftermath of the global financial crisis in 2008, hedging against sharp drops in risky assets, i.e. tail risk, has been the subject of intense interest among investors. The unsatisfactory performance of traditional, diversified asset allocations has driven investors to search for alternatives to cheaply insure against tail risk. One indicator of how widespread this concern has become is the upward trend in Google searches for ‘Tail Risk’ over the past three and a half years.

Exhibit 1: Google Searches for ‘Tail Risk’ are Trending Higher

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Apr-08 Oct-08 Apr-09 Oct-09 Apr-10 Oct-10 Apr-11

Source: Google Insights for Search

The extent of tail risk hedging can be observed in excess demand for downside protection on equity option markets, which exhibit a higher premium of implied over historical volatility as well as of out-of-the-money puts versus at-the-money equity options as shown below.

Exhibit 2: The Premium of Implied versus Historical Volatility in Equity Markets is Extremely Wide …

Exhibit 3: … As is the Premium of Deep Out-of-the-Money Put versus At-the-Money S&P 500 Options

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Dec-98 Dec-01 Dec-04 Dec-07 Dec-103M A

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Source: Credit Suisse Locus Source: Credit Suisse

The strong demand for insurance against severe downside risk in equity markets creates an opportunity to earn an attractive risk premium by selectively selling equity volatility. Two ways in which investors can capture historically high volatility risk premium are via covered call selling (selling out-of-the-money call options against a core long equity


07 September 2011

position) or by selling volatility. The charts below track the year-to-date performance of the CS Advanced Covered Equity Index, a proprietary covered call selling strategy overlaid on the Euro Stoxx 50, and the Global Carry Selector, a strategy which looks to sell equity variance in major developed market equity indices. Both strategies have performed well despite the recent spike in equity volatility.

Exhibit 4: Covered Call Writing Via CS ACE Has Significantly Outperformed the SX5T Benchmark

Exhibit 5: Selling Volatility via the Global Carry Selector Has Performed Well Despite the Rise in VIX

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31-Dec 28-Feb 30-Apr 30-Jun 31-Aug

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CSACE SX5T

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55

VIX

Inde

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Global Carry Selector (LHS) VIX (RHS)

Source: the BLOOMBERG PROFESSIONAL™ service, Credit Suisse Source: Credit Suisse

Exhibit 6 highlights a similar dynamic in fixed income markets, where short-term rates have declined to historical lows while the difference between implied and realized interest rate volatility is well within historical ranges. This suggests that income-oriented investors should consider ways to earn volatility risk premia in interest rates as yields on traditional fixed income instruments look to remain extremely low for some time.

Exhibit 6: US 1-Month LIBOR is at Historical Lows While Volatility Risk Premium is in its Normal Range

Exhibit 7: CSAVI-IR Has Delivered Stable Performance Despite Heightened Rates Volatility

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LIB

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Imp. - Hist. Rate Vol. (LHS) 1M LIBOR (RHS)

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0

Source: the BLOOMBERG PROFESSIONAL™ service, Credit Suisse Source: the BLOOMBERG PROFESSIONAL™ service, Credit Suisse

Exhibit 7 plots the year-to-date performance of the CS Adaptive Volatility Index – IR (CSAVI-IR), which dynamically sells US interest rate volatility depending on market conditions. CSAVI-IR has delivered stable performance well in excess of the return on most carry-oriented interest rate strategies for the year-to-date despite relatively high volatility across developed bond markets.


07 September 2011

In the sections below, we highlight two strategies that help investors capture volatility risk premia in equity and interest rate markets. Both strategies, the Global Carry Selector and CSAVI-IR, systematically sell volatility in their respective markets in a risk-controlled fashion.

Harvesting Volatility Risk Premia Across Global Equity Markets

The Global Carry Selector Index is an equity volatility arbitrage strategy that extracts equity risk premia embedded in the option prices of four global indices (S&P 500, DJ Euro Stoxx 50, DAX and Nikkei 225). The strategy systematically sells variance swaps and opportunistically buys forward variance as a hedge.

Trading Strategy

Every month, the strategy performs the following steps:

1. Sell risk: The algorithm sells a 1-month variance swap on the SPX, DAX, SX5E or NKY index. A volatility momentum indicator is used to determine which index would bring the best value based on the carry realized over the previous month.

2. Buy protection: The algorithm determines whether to go long protection based on a term structure risk indicator that also selects the index on which protection is to be purchased. The protection is in the form of a forward starting variance swap.

3. Asset allocation: 30% is invested in 1-month Euribor and 70% in variance swaps. The cash cushion prevents full deleveraging in case of drawdown.

Performance

GCSCS has performed well in a variety of market environments, significantly outperforming the equity benchmark. Exhibits 8 and 9 show the performance of GCSCS against the S&P 500 since January 2006.

Exhibit 8: Cumulative Performance, January 2006 – August 2011 The Global Carry Selector index has been live since January 2009

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Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10 Jun-11

GCSCS S&P 500

Source: the BLOOMBERG PROFESSIONAL™ service

GCSCS has generated a Sharpe ratio nearly nine times higher than that of the benchmark with less than half the drawdown.


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Exhibit 9: Performance Statistics, January 2006 – August 2011 GCSCS S&P 500 Annual Excess Return 16.58% 2.53% Annual Volatility 18.75% 24.27% Sharpe Ratio 0.88 0.10 Maximum Drawdown 24.13% 56.78% Source: Credit Suisse

Exhibits 10 and 11 break down return and Sharpe ratio annually. While both GCSCS and the S&P were down in 2008, GCSCS suffered less than a 2% loss when the equity benchmark was down nearly 40%. Importantly, GCSCS has delivered strong performance so far this year despite severe market gyrations over the past few months.

Exhibit 10: Annual Excess Return, January 2006 – August 2011

Exhibit 11: Annual Sharpe Ratio, January 2006 – August 2011

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GCSCS S&P 500

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GCSCS S&P 500

Source: the BLOOMBERG PROFESSIONAL™ service Source: Credit Suisse

Exploiting the Bias Between Implied and Realized Interest Rate Volatility

Deposit rates and bond yields have fallen to historical lows in the developed interest rate markets given demand for safe havens and easy monetary policy. Despite this phenomenon, volatility markets still offer historically average volatility risk premia. In this section, we highlight how investors can capture interest rate volatility risk premia as a way to earn extra income in the current low yield environment.

The Credit Suisse Adaptive Volatility index is a volatility strategy that aims to exploit the bias between implied and realized volatility in the US interest rate swap market. The strategy sells 1-month into 10-year swaption straddles and delta hedges the position until expiry. CSAVI aims to improve risk-adjusted returns by dynamically adjusting its leverage depending on the prevailing volatility environment (various states of richness and cheapness in USD interest rates volatility markets).

Exhibit 12 plots the bias between implied vs. realized volatility in 10Y swap rates one month later. Over the past 15 years, the implied – realized volatility spread has averaged 12 basis points and implied volatility has been higher than realized volatility 70% of the time. As shown in the chart, during severe market disruptions (Fed surprise cuts, Lehman collapse), this bias breaks down. CSAVI dynamically adjusts its risk exposure to mitigate significant losses during distressed market periods as well as to capture outsized risk premia during periods of elevated volatility.


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Exhibit 12: Implied Interest Rate Volatility is Generally Higher than Realized The chart below plots the difference between 1-month into 10-year implied swaption volatility minus realized volatility of 10-year US swap rate changes over rolling 1-month periods.

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0

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Aug-94 Aug-96 Aug-98 Aug-00 Aug-02 Aug-04 Aug-06 Aug-08 Aug-10

bps

Implied Vol 10y - Realized Vol 10y Bias

Fed surprise cut

Fed surprise cut

Lehman collapse

Average = + 12 bps

Source: the BLOOMBERG PROFESSIONAL™ service, Credit Suisse

The strategy uses the steepness of the implied volatility curve to distinguish between four distinct volatility regimes. CSAVI errs on the side of caution in Distressed and Cheap volatility regimes by reducing risk exposures. In both cases, volatility risk premia are likely to be insufficient to compensate for the risk of selling swaption straddles. In Rich and Neutral states, CSAVI varies its risk exposure depending on the magnitude of the opportunity set. When volatility is in a Rich regime, the strategy uses a GARCH-based volatility forecast to determine whether volatility is likely to decline or rise and adjusts its exposures accordingly.

Exhibit 13: CSAVI Risk Allocation and Regimes of Interest Rate Volatility

Source: Credit Suisse


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Performance

Exhibits 14 and 15 show the performance of CSAVI since January 2006.

Exhibit 14: Cumulative Performance, January 2006 – August 2011 CSAVI has been live since March 2009.

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Dec-05 Jun-06 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10 Jun-11

Source: the BLOOMBERG PROFESSIONAL™ service

CSAVI generated a Sharpe ratio of 1.56 over the entire period with a drawdown of 2.43%.

Exhibit 15: Performance Statistics, January 2006 – August 2011 CSAVI-IR Annual Excess Return 2.37% Annual Volatility 1.52% Sharpe Ratio 1.56 Drawdown 2.43% Source: Credit Suisse

Exhibits 16 and 17 break down return and Sharpe ratio annually. CSAVI’s dynamic risk allocation helped the strategy avoid the extreme volatility around the Lehman bankruptcy while reaping significant gains as markets normalized in 2009. 2007 and 2010 were both challenging years for the strategy as rapid shifts in volatility regimes occurred in both years with the initial onset of the subprime crisis in 2007 and the Greek debt crisis in 2010.



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2006 2007 2008 2009 2010 2011 Total

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Combining Equity and Fixed Income Volatility Strategies

Combining the two volatility strategies can provide diversified alpha as a result of the extremely low correlation among the two constituents. Daily return correlation for the two underlying indices is 4.5% for the entire period. The weights of the constituent indices are determined based on their historical volatility: the higher the historical volatility, the lower the weight. The relative weights of the constituents remain constant over time.

Exhibit 18: Performance Statistics, January 2006 – August 2011 GCSCS + CSAVI-IR Annual Excess Return 3.44% Annual Volatility 2.03% Sharpe Ratio 1.69 Drawdown 2.40% Source: Credit Suisse

The combination of the two volatility indices generates a higher Sharpe ratio than the underlying indices, with lower drawdown. This boost in performance is a byproduct of the diversification provided by uncorrelated underlyings. Exhibits 19 and 20 plot return and Sharpe ratio annually; the basket has generated positive returns every year over the whole period.



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2006 2007 2008 2009 2010 2011 Total

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Strategy Snapshots


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Equities ACE Asset Class: Equity / Style: Carry BBG Ticker: CSACE

Historical Performance

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Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10 Jan-11 Jul-11


Performance Summary (Inception date: January 2010)

MTD YTD Last 12-Mo. Since Inception Return -7.10% -5.09% -1.42% -8.62% Volatility 13.90% 17.42% Sharpe Ratio -0.03 -0.42 D rawdown 14.57% 20.70% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

ACE is the Credit Suisse Enhanced Covered Call Equity Index. This index follows an optimal strike covered call strategy on the Euro Stoxx 50 that contains two additional elements: long put positions when the market is expected to fall and a delta hedging program when the market trends up.

H1 2011 Performance Commentary

ACE returned 0.62% for the first six months of the year, after losses in May and June mitigated the gains made between January and April. The index maintained a consistent Long Euro Stoxx 50 call position over the period and hedged using short calls of varying strikes. Rallying markets in the first four months of the year benefitted the strategy, resulting in a 6.94% gain through April. Market uncertainty tied to the Greek crisis and concerns of global slowdown resulted in losses toward the end of the first half.

For more information regarding this index, please contact Alfke Kierspel in Equity Derivatives at [email protected].


mailto:[email protected]

07 September 2011

HS Global Style Rotation

Asset Class: Equity / Style: Hybrid BBG Ticker: HSGSR


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Performance Summary (Inception date: October 2009)

MTD YTD Last 12-Mo. Since Inception Return -8.44% -1.57% 18.59% 7.48% Volatility 18.09% 18.53% Sharpe Ratio 0.99 0.51 D rawdown 19.87% 19.87% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The HS Global Style Rotation Index invests according to investment styles that dominate at each stage of the economic cycle as determined by the Credit Suisse Cycle Clock, an indicator that is a measure of the output gap. The HOLT® framework is used to identify stocks with appropriate characteristics for the relevant economic cycle stage. Expert financial ratios and rules are used to pinpoint these qualities systematically. The HS Global Style Rotation Index is a synthetic price return index calculated in US dollars.


The HS Global Style Rotation Index gained 9.48% over H1 2011, outperforming the MSCI World (TR) Index, which returned 5.62%. The index rebalance in February and increased allocations to America and non-Japan Asia were performance drivers over the first half of the year. The index also captured rallies in the Information Technology, Consumer Staples and Consumer Discretionary sectors after increasing their allocations during the rebalance.




07 September 2011

HS Market Neutral Index Powered by HOLT® Asset Class: Equity / Style: Value BBG Ticker: HSGMN


859095

100105110



Performance Summary (Inception date: September 2007)

MTD YTD Last 12-Mo. Since Inception Return -0.94% -0.44% 2.88% -1.41% Volatility 3.69% 5.76% Sharpe Ratio 0.78 -0.21 D rawdown 4.98% 12.52% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The HS Market Neutral Index Powered by HOLT® uses a strategy popular with hedge funds, where the main aim is to achieve stable returns: the emphasis is on reducing risk rather than maximizing outperformance. Approximately 75 stocks are held on the expectation that their share prices will go up (long position) and the same number of stocks are held on the expectation their share prices will go down (short position). Stocks may belong to any industry either in Europe (selected countries), Japan, Canada or the US, and each exposure on the long side is matched with exposure on the short side, resulting in neutral overall exposure. Companies included typically exhibit strong/weak cash flows, are under-valued/over-valued and experience positive/negative investor sentiment. HOLT® uses expert financial ratios and rules to pinpoint these characteristics systematically. The HS Market Neutral Index is an excess return index calculated in US dollars.


The HS Market Neutral Index was up 1.87% in the first half 2011. The US region and the Consumer Discretionary sectors were consistent positive contributors to performance. The index enjoyed a good start to the year when the US and Japan were driving performance. The index was down in the second quarter as Asia and Europe lost money.




07 September 2011

HS Global Style Rotation Equity Hedged Asset Class: Equity / Style: Hybrid BBG Ticker: HSGSREH


100

110

120

130



Performance Summary (Inception date: April 2010)

MTD YTD Last 12-Mo. Since Inception Return -1.41% 3.50% 5.48% 4.65% Volatility 3.39% 3.49% Sharpe Ratio 1.59 1.32 D rawdown 3.66% 3.66% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The HS Global Style Rotation Equity Hedged Index is a US dollar excess-return index that goes short the MSCI World index against a long position in the HS Global Style Rotation Index to have a net exposure of zero. The index is rebalanced on a quarterly basis.


The HS Global Style Rotation Equity Hedged Index was up 4.86% in the first half of 2011, continuing to exhibit very low volatility over the period. All sectors contributed to performance over the first half, with Consider Discretionary and Health Care being the return drivers.




07 September 2011

Global Carry Selector Asset Class: Equity / Style: Volatility BBG Ticker: GCSCS


80110140170200230




MTD YTD Last 12-Mo. Since Inception Return 1.37% 32.26% 49.00% 23.63% Volatility 17.03% 20.87% Sharpe Ratio 2.41 1.12 D rawdown 13.56% 26.34% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The Credit Suisse Global Carry Selector Index is an equity volatility arbitrage strategy that extracts the equity risk premium embedded in the option prices of four global indices (S&P 500, DJ Euro Stoxx 50, DAX and Nikkei 225) while attempting to deliver a low beta to the equity market. The strategy systematically sells variance swaps and opportunistically buys forward variances as a hedge.


HS Global Carry Selector Index was up 25.67% through June 2011, on top of positive performances every month of the year. The market rally over the first half of the year and decreased market volatility over the period (prior to the Greek crisis and slowdown concerns) drove returns for the strategy. The index was short Nikkei 225 volatility in June and short S&P500 and Euro Stoxx 50 volatility prior to that.




07 September 2011

Interest Rates Adaptive Volatility Index Asset Class: Interest Rates / Style: Volatility BBG Ticker: CSVIA


98

102

106

110



Performance Summary (Inception date: March 2009)


Strategy Overview

CSAVI-IR exploits the bias between implied and realized volatility in the USD interest rate options market by selling 1-month into 10-year swaptions and delta-hedging until expiry. The innovative part of CSAVI is that it identifies various states of richness and cheapness in USD rates volatility markets by employing an advanced formula.


CSAVI was up 1.04% in H1 2011, benefitting from stabilization in US interest rates after a volatile H2 2010. Despite the lack of action on raising the debt ceiling in the US, the slowdown in global economic growth and escalation in the European debt crisis both helped to support the rates market and drive a decline in implied volatility. CSAVI outperformed in Q1 as short-dated implied volatility declined steadily. Returns in Q2 were more muted as volatility generally rose during the quarter.

For more information regarding this index, please contact the Alpha Strategies team at [email protected] or the European Rates Structuring team at [email protected].





07 September 2011

Macro Conditions Index Asset Class: Interest Rates / Style: Value BBG Ticker: CSMCUS20


98

103

108

113



Performance Summary (Inception date: December 2009)

MTD YTD Last 12-Mo. Since Inception Return -0.31% -0.26% 0.03% -0.04% Volatility 0.39% 0.48% Sharpe Ratio 0.04 -0.07 D rawdown 0.50% 0.50% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The Credit Suisse Macro Conditions Index (CSMCI) is an innovative strategy that trades the slope of the US yield curve based on signals extracted from a wide panel of US macroeconomic releases. It aims to benefit from movements in the spread between the 10-year and 2-year rates. Unlike similar curve-trading systematic strategies, CSMCI uses fundamental macroeconomic signals rather than changes in the short rate.


CSMCI registered a gain of 0.15% in H1 2011 as the US yield curve flattened modestly over the course of the year. The strategy has generally had a flattening bias this year as indicators of economic growth began to deteriorate in January.






07 September 2011

Adaptive Momentum Index Asset Class: Interest Rates / Style: Momentum BBG Ticker: CMOIEREU


100

101

102

103



Performance Summary (Inception date: August 2008)


Strategy Overview

CSAMI is a momentum-based strategy that trades interest rate future instruments to provide robust risk-adjusted returns through diverse economic environments. The strategy trades the following futures – CBOT 10Y Note Future; Eurex Bund Future; Euronext.Liffe 3M Euribor Future; CME 3M Eurodollar Future.


CSAMI was up modestly in H1 2011, earning 0.15% as choppy market conditions made for a difficult environment for momentum trading. US rates contributed the bulk of the positive performance as the strategy benefitted from the stability of very short-dated rates, allowing the strategy to profit from the roll down of its long positions. European rates were roughly flat, with gains from Bund futures offset by losses in Euribor futures. The combination of an earlier-than-expected start to the ECB’s tightening cycle coupled with the deterioration in peripheral European bond markets made for a difficult trading environment in European rates.






07 September 2011

Fortinbras Three Factor Model Index Asset Class: Interest Rates / Style: Momentum BBG Ticker: CSFNERUS


95

105

115

125



Performance Summary (Inception date: June 2008)


Strategy Overview

The Fortinbras Three Factor Model Index uses a systematic trend-following strategy to identify and exploit trends in changes in the shape of yield curves. It allocates daily long/short positions in three interest rate swaps (1-, 2-, 5- year) across four different yield curves (USD, EUR, CHF, GBP).


The Fortinbras Three Factor Model was roughly flat in H1 2011, gaining 0.08% in a difficult environment for directional rates trading. The strategy had a challenging start to the year as range trading conditions in the US and an earlier-than-expected start to the ECB's hiking cycle created a difficult environment for momentum trading. In Q2, the model captured the broad decline in US and European rates across the curve as slower growth and debt crises on both sides of the Atlantic sparked an impressive rally in core rates markets.

For more information regarding this index, please contact the European Rates Structuring team at [email protected].



07 September 2011

Adaptive Term Premium Index Asset Class: Interest Rates / Style: Carry BBG Ticker: CATPUSEA


100

105

110

115

Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10 Jan-11 Jul-11




Strategy Overview

The Credit Suisse Adaptive Term Premium Index (CSATPI) systematically exploits the persistent positive bias between implied forward rates and realized rates at the front end of the LIBOR and Euribor yield curves. It identifies situations to go long or short interest rate futures conditioned on the momentum of change in rates, the slope of the yield curve, and volatility in the rates market.


CSATPI was up 1.31% in the first half of the year, after a strong start to the year. It held a short position in Euribor futures, capturing the selloff when Trichet announced a tougher stance on inflation. It was flat in February and March, after switching to a long Euribor position. The index moved to a short position in April, with rising 3M Euribor signaling a selloff. However, rates rallied significantly due to the sovereign debt crisis and the front end of the curve is now flat. The strategy has also been long Eurodollar futures since the beginning of the year, with the future moving in a narrow range around 99.40. The LIBOR component captured the rolldown of the curve and is up 0.86% in the first half, compensating for the underperformance of the Euribor component.

For more information regarding this index, please contact the European Rates Structuring team at [email protected].



07 September 2011

Foreign Exchange FX Factor Asset Class: Interest Rates / Style: Hybrid BBG Ticker: FXFTERUS


95

100

105

110

115





Strategy Overview

The Credit Suisse FX Factor Index tracks the performance of a diversified portfolio of macroeconomic and market-driven foreign exchange trading strategies. Credit Suisse has identified six factors that tend to explain currency performance – Carry, Momentum, Valuation, Growth, Terms of Trade, and Emerging Markets. The index uses these factors to allocate capital efficiently across both G10 and emerging markets currencies. Exposure to the different strategies rebalances monthly as a function of the performance, volatility, and skew of each of the underlying factors.


FX Factor posted a decline of 3.74% in H1 2011, with realized volatility of 5.37%. Momentum in G10 currencies and in Emerging Markets, along with the persistent depreciating trend of the USD, were positive impacts on performance through April. A directionless period over the course of May and June, when markets were weighed by Greek fiscal woes and global slowdown concerns, led to a decline.

For more information regarding this index, please contact the Alpha Strategies team at [email protected] or the FX Structuring team at [email protected].





07 September 2011

Commodities GAINS Asset Class: Commodities / Style: Value BBG Ticker: CSGADER


80100120140160180

Nov-08 Feb-09 May-09 Aug-09 Nov-09 Feb-10 May-10 Aug-10 Nov-10 Feb-11 May-11 Aug-11


Performance Summary (Inception date: October 2008)


Strategy Overview

CS GAINS uses market information from one of the world’s largest commodity traders to dynamically re-weight the allocation of individual commodities in a commodity index. Using ‘votes’ from the commodity trading units, the index determines the adjusted weights based on the commodity trader’s outlook on the physical market for each commodity.


Rises in precious metals and refined oil products prices were outweighed by negative performances in crude oil, natural gas and agricultural products, resulting in a decline of 3.47% for the first half of the year.

For more information regarding this index, please contact Mi-Sonn Kim ([email protected]) and Kamal Naqvi ([email protected]) in Commodities Sales or Mark Harvey in Commodities Structuring ([email protected]).







07 September 2011

MOVERS Asset Class: Commodities / Style: Value BBG Ticker: CSMVERS


80100120140160180200220





Strategy Overview

MOVERS is designed to produce positive absolute returns regardless of the commodity cycle, in contrast to traditional long-only commodity indices. It uses a quantitative approach to generate long/short signals that aim to capitalize on both positive and negative trends in the market. The index is based on the 24 S&P GSCITM sub indices covering all five commodity sectors: Energy, Industrial Metals, Precious Metals, Agriculture and Livestock.


The index retained a bullish stance for the majority of the first half of the year, turning more neutral in June. A strong positive performance from energy, precious metals and grains allocations was partially offset by softs and industrial metals, resulting in an overall rise of 6.90% in the index for the first half of the year.

For more information regarding this index, please contact Mi-Sonn Kim ([email protected]) and Kamal Naqvi ([email protected]) in Commodities Sales or Mark Harvey in Commodities Structuring ([email protected]).







07 September 2011

Emerging Markets EMCROP Asset Class: Emerging Markets / Style: Value BBG Ticker: EMCPERUS


100105110115120125

Jun-09 Sep-09 Dec-09 Mar-10 Jun-10 Sep-10 Dec-10 Mar-11 Jun-11



MTD YTD Last 12-Mo. Since Inception Return -2.14% 0.48% 2.30% -1.00% Volatility 3.99% 4.10% Sharpe Ratio 0.60 -0.22 D rawdown 4.00% 4.00% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The Credit Suisse Emerging Market Credit Opportunities Index (EMCROP) is an investment strategy designed to benefit from mispricing in EM sovereign credit spreads relative to their macroeconomic and credit fundamentals. The strategy sells credit default swap (CDS) protection on up to six EM sovereign credits and rebalances its exposure quarterly. Credit exposure is adjusted according to the Credit Suisse Extreme Flow Indicator, a proprietary medium-term timing indicator. For "risk-on" periods, the strategy invests in the selected CDS contracts; in "risk-off' periods, the strategy stays neutral.


EMCROP generated strong performance in H1 2011, delivering a 2.68% gain as compared to the benchmark CDX.EM index's 0.90% return. While performance did suffer somewhat in Q2 as the European debt crisis escalated, the generally strong credit fundamentals of the EMCROP portfolio insulated the strategy from much of the market volatility in May and June.

For more information regarding this index, please contact the Alpha Strategies team ([email protected]) or Bikram Chaudhury in EM Structuring ([email protected]).




07 September 2011

Tail-Risk HedgingAdvanced Volatility Index Opportunistic Asset Class: Foreign Exchange / Style: Volatility BBG Ticker: CSVIOEUS


90

100

110

120

130




MTD YTD Last 12-Mo. Since Inception Return 1.02% -0.30% -4.57% 0.94% Volatility 5.66% 5.62% Sharpe Ratio -0.77 0.22 D rawdown 7.74% 10.26% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The Credit Suisse Advanced Volatility Index (CSAVI-FX) uses a statistical approach to buy undervalued/sell overvalued FX volatility. Employing a Jump Diffusion model, CSAVI-FX produces daily signals to buy or sell volatility via One-Month Volatility Swaps. The currency portfolio includes 12 of the most liquid G10 currency pairs.


CSAVI-FX experienced a decline of 2.41% in H1 2011, in line with expectations as equity markets rallied ahead of the Greek crisis, concerns of global slowdown and the US debt limit quagmire. While the strategy is down for the year, it has performed significantly better than VXX. CSAVI-FX has been long FX volatility, particularly in USDJPY, EURGBP and GBPUSD, as implied volatility in these currency pairs has been exceptionally low this year. It has also been long volatility in AUDUSD and NZDUSD, currency pairs that are susceptible to jumps in volatility.






07 September 2011

Advanced Volatility Index Opportunistic Long Asset Class: Foreign Exchange / Style: Volatility BBG Ticker: CSVILEUS


90

100

110

120

130




MTD YTD Last 12-Mo. Since Inception Return 1.67% -0.26% -5.21% -2.99% Volatility 6.30% 6.32% Sharpe Ratio -0.79 -0.45 D rawdown 9.30% 14.90% Source: Credit Suisse Note: Data as of 8/31/2011

Strategy Overview

The Credit Suisse Advanced Volatility Index (CSAVI-FX) Long uses a statistical approach to buy undervalued FX volatility. Employing a Jump Diffusion model, CSAVI-FX produces daily signals to buy volatility via One-Month Volatility Swaps. The currency portfolio includes 12 of the most liquid G10 currency pairs.


CSAVI-FX Long experienced a decline of 3.30% in H1 2011 as equity markets rallied ahead of the Greek crisis, concerns of global slowdown and the US debt limit quagmire. While the strategy is down for the year, it has performed significantly better than VXX. CSAVI-FX Long has been long USDJPY, EURGBP and GBPUSD, as implied volatility in these currency pairs has been exceptionally low this year. It has also been long volatility in AUDUSD and NZDUSD, currency pairs that are susceptible to jumps in volatility.






07 September 2011

Credit Suisse Advanced Variance 5% Volatility Weighted Index SPX Asset Class: Equity / Style: Volatility BBG Ticker: CSVISPX5


9092949698

100102

Jan-11 Feb-11 Mar-11 Apr-11 May-11 Jun-11 Jul-11 Aug-11




Strategy Overview

The Credit Suisse Advanced Variance 5% Volatility Weighted Index SPX (CSAVI-SPX) tactically implements long or short exposures in S&P 500 implied variance based on market regime signals from the Extreme Flow Indicator (see Appendix for details on the EFI). The strategy is designed as a tail-risk hedge overlay and rebalances monthly in order to maintain a 5% volatility budget. Its ability to tactically go long or short implied variance significantly mitigates the cost of passively holding long volatility hedges.


The Credit Suisse Advanced Variance 5% Volatility Weighted Index SPX was down 2.14% in the first half of the year. The index was mostly long the VelocityShares SPX Inverse Variance Index (short SPX variance) over the period. This position benefited the index in June and should continue to benefit the index going forward due to increased market volatility and uncertainty.

For more information regarding this index, please contact Christin Hinkle in US Equity Derivatives Structuring at [email protected].



07 September 2011

Credit Suisse Equity Tail Hedge Index Asset Class: Equity / Style: Tail-Risk Hedge BBG Ticker: CSEATAIL


80

100

120

140

160



Performance Summary (Inception date: July 2011)


Strategy Overview

The Credit Suisse Equity Tail Hedge Index is a rules-based algorithm on the Eurostoxx50 Index that achieves long equity tail risk exposure through the monthly systematic purchase of 3-month Ratio Put-Spreads (short 95% strike puts, long 80% strike puts). The options are subsequently delta-hedged, offering long Skew and Gap Risk (i.e., Delta for large moves down) exposure. The positions are determined such that both options have the same vega.


This index has been live since July 2011.




07 September 2011

Hybrid CARES Asset Class: Hybrid / Style: Value BBG Ticker: CSCSTR


80

130

180

230



Performance Summary (Inception date: May 2009)


Strategy Overview

The Credit Suisse CARES Index tracks the performance of an enhanced commodities strategy through allocations to either commodities or the related resource equities in its various components. The Index consists of five component indices, representing different commodity groups – Petroleum, Natural Gas, Industrial Metals, Precious Metals and Agriculture. Each month, the unique switching methodology identifies whether it is more favorable to invest in commodities or the related resource equities for each commodity group. When a commodity group is allocated to commodities, it will be invested in the relevant S&P GSCI sub-indices. When a commodity group is allocated to equities, it will be invested in a basket of stocks related to that commodity group. The weights of each component index in the CARES Index are based on the weights of the relevant commodity group in the S&P GSCI Index.


The index retained a predominant allocation to commodities for the first part of the year, with allocations to equities in metals and natural gas occurring in the second quarter. Strong gains in Brent crude oil and refined oil products prices were partially offset by weakness in WTI crude oil and grains, giving a positive performance of 3.68% for the first half of the year.

For more information regarding this index, please contact Alfke Kierspel in Equity Derivatives at [email protected] or Kamal Naqvi in Commodities Sales at [email protected].




07 September 2011

RAII HOLT: Risk Appetite Investible Index Powered by HOLT® Asset Class: Hybrid / Style: Value BBG Ticker: RAIIHUST


80100120140160180





Strategy Overview

The Credit Suisse Risk Appetite Investable Indices offer investors a rules-based asset allocation between riskier assets (equities) and safer assets (bonds). The objective is to outperform a classic 50:50 balanced portfolio of equities and bonds. The core concept is to use a highly disciplined rule system to reduce risk (decrease equities) when investors are unusually optimistic, and to add risk when investors are unusually pessimistic, as measured by extremes in the long established CS Global Risk Appetite Index (“CS GRAI”). The riskier asset is represented by the HOLT® Long Index Total Return, which reflects the approximately 75 highest-ranking stocks in certain jurisdictions and industry sectors according to HOLT’s proprietary scoring model. RAII Powered by HOLT® Total Return consists of: (1) the Credit Suisse HOLT® Long Index Total Return (HSGMNLTR); and (2) a bond portfolio tracking the Citigroup World Government Bond Index.


RAI HOLT® returned 5.65% in H1 2011, compared with 4.11% for a balanced portfolio. The index had a strong first quarter due to its exposure to equities and started reducing exposure in March due to some triggers. The Index continued to overweight equities through April but increased allocations to bonds due to continued outperformance, particularly US bonds in May. RAII HOLT® was completely allocated to bonds by the end of May. The Risk Appetite sentiment fell further in June and continued weakness could result in an allocation to equities going forward. Expectations for Japan to lead the early stages of a second half recovery were high and returns were strong, but substantially below expectations. The continuing drumbeat of crisis in peripheral Europe was heard through all of this as resolutions on Greece remained uncertain both in timing and type.

For more information regarding this index, please contact Paul Mcginnie in Global Strategy ([email protected]) or Mark Smith in Fund-Linked Products ([email protected]).




07 September 2011

CSMIDAS

Asset Class: Hybrid / Style: Hybrid BBG Ticker: CSMDCEUS


95100105110115120

Sep-07 Mar-08 Sep-08 Mar-09 Sep-09 Mar-10 Sep-10 Mar-11




Strategy Overview

The Credit Suisse Multi-Index Diversified Alternative Strategy (CSMIDAS) is an asset allocation framework based on a multi-asset basket of Credit Suisse alpha indices. It is designed as a source of diversified alpha with tail-risk hedge overlay. CSMDCEUS is a diversified basket of alternative equity, commodity and FX volatility strategies, designed to outperform in a reflationary environment. The basket includes two equity-oriented Liquid Alternative Beta (LAB) strategies, CSLAB Long/Short and CSLAB Merger Arbitrage, a long/short commodity momentum strategy, CSMOVERS, and an FX volatility strategy with the characteristics of a tail-risk hedge, CSAVI-FX.


CSMIDAS generated solid performance in H1 2011, gaining 2.16% on the back of gains in the commodity momentum and Liquid Alternative Beta (LAB) indices. The CSLAB Merger Arbitrage Index outperformed on the back of robust global mergers and acquisitions activity. Both the CSMOVERS and CSLAB Long/Short Index participated in the rally in global risk assets through April but suffered setbacks in May and June as the European debt crisis intensified. The FX volatility component of the basket, CSAVI-FX, experienced a marginal decline due to its bias toward long volatility exposures in H1 2011, in line with expectations during market rallies.

For more information regarding this index, please contact the Alpha Strategies team at [email protected] or Christin Hinkle in US Equity Derivatives Structuring at [email protected].




07 September 2011

Liquid Alternative Beta Liquid Alternative Beta Index Asset Class: Liquid Alternative Beta / Style: Hybrid BBG Ticker: CSLAB


80

90

100

110

120

Apr-07 Oct-07 Apr-08 Oct-08 Apr-09 Oct-09 Apr-10 Oct-10 Apr-11




Strategy Overview

The Credit Suisse Liquid Alternative Beta Index reflects the return of a dynamic basket of liquid, investable market factors selected and weighted in accordance with an algorithm that aims to approximate the aggregate returns of the universe of hedge fund managers as represented by the Dow Jones Credit Suisse Hedge Fund Index. The algorithm has been determined by an index committee taking into consideration extensive quantitative research into alternative beta. It benefits from accurate daily valuations with objective and transparent rules-based construction.


CSLAB was up 3.44% for first half of year, with performance mostly coming from Q1, which was up 3.08%. Hedge funds struggled in Q2 as issues facing Europe and the US debt ceiling created headwinds. The primary contributors to performance in the first half of the year were US equities, merger arbitrage and high yield debt. The DJ/CS Hedge Fund Index was up 1.65% in H1.

For more information regarding this index, please contact Peter Little ([email protected]) or Jordan Drachman ([email protected]) in Credit Suisse Asset Management.





07 September 2011

Long/Short Liquid Index Asset Class: Liquid Alternative Beta / Style: Hybrid BBG Ticker: CSLABLS


708090

100110120





Strategy Overview

The Credit Suisse Long/Short Liquid Index reflects the return of a dynamic basket of liquid, investable market factors selected and weighted in accordance with an algorithm that aims to track the performance of the Dow Jones Credit Suisse Long/Short Equity Hedge Fund Index by allocating weights to non-hedge fund, transparent market factors. The algorithm has been determined by an index committee, taking into consideration extensive quantitative research into systematic ways of achieving certain risk return profiles by using alternative investing techniques. The index is calculated daily by NYSE and benefits from objective and transparent rules-based construction.


The Long/Short Liquid Index was up 5.20% for H1, with 3.58% coming from Q1. The model outperformed long/short equity hedge funds (DJ/CS Index was up 75 bps in H1 after losing 1.49% in Q2), primarily in Q2, when a few big intra-month reversals in equity performance probably saw managers forced to cut risk and miss out on the snapback in the second part of those months, while CSLAB Long/Short maintained more consistent exposures throughout. US Large Caps and long growth vs. short value were the most consistent themes throughout H1 as well as the biggest contributors to performance.






07 September 2011

Event-Driven Liquid Index Asset Class: Liquid Alternative Beta / Style: Hybrid BBG Ticker: CSLABED


8090

100110120130





Strategy Overview

The Credit Suisse Event-Driven Liquid Index reflects the return of a dynamic basket of liquid, investable market factors selected and weighted in accordance with an algorithm that aims to approximate the aggregate returns of the universe of event-driven hedge fund managers. The algorithm has been determined by an index committee, taking into consideration quantitative research into alternative beta. The index benefits from daily valuations with objective and transparent rules-based construction.


The Event-Driven Liquid Index was up 3.95% for H1, after losing 0.42% in Q2. Small cap equities, high yield debt and merger arbitrage were the main contributors and all contributed roughly equal amounts for H1. High yield and small caps were the factors most responsible for the negative performance in Q2. The DJ/CS event-driven Hedge Fund index was up 1.31% in H1.






07 September 2011

Merger Arbitrage Liquid Index Asset Class: Liquid Alternative Beta / Style: Hybrid BBG Ticker: CSLABMA


80

90

100

110

120





Strategy Overview

The Credit Suisse Merger Arbitrage Liquid Index aims to gain broad exposure to the merger arbitrage strategy using a pre-defined quantitative methodology to gain exposure to a liquid, diversified and broadly representative set of announced merger deals in accordance with index rules. The algorithm has been determined by an index committee, taking into consideration quantitative research into alternative beta. The index benefits from daily valuations with objective and transparent rules-based construction.


The Merger Arbitrage index was up 4.48%, with most of the performance coming from Q1 (3.74%). Despite challenging months for the markets in March, May and June, the Merger Arbitrage index only lost money in June, when four of the larger deals experienced some issues. Q1 was characterized by many deals being completed and lots of new deals being added, but the number of eligible deals peaked at the end of February, with the amount of completed deals matching the amount of incoming deals until the end of May when new deal activity started to slow.






07 September 2011

Appendix


07 September 2011

The Extreme Flow Indicator Recent financial market dynamics have exhibited a number of historically extreme features. One of the more puzzling features of the current environment is the high correlation across asset classes. As shown in Exhibit 1, the current average correlation is over 50%, far above the previous high correlation set in 2001, and indicates an extremely high level of co-movement between equity, currency, commodity, and credit indices. The high correlation across asset classes implies that market risk premia are increasingly driven by a single factor and that understanding the dynamics of the aggregate market risk premium has never been more important than it is currently.

Exhibit 1: Average Correlation of US Dollar, Commodities, and Credit with the S&P 500 Average of the rolling 52-week return correlation between the S&P 500 and 1) US Federal Reserve Trade Weighted Major Currency Index, 2) Reuters/Jefferies CRB Commodity Price Index, and 3) the Moody’s Baa/30-yr UST Credit Spread

-0.4

-0.2

0.0

0.2

0.4

0.6

Jan-95 Jan-98 Jan-01 Jan-04 Jan-07 Jan-10

Ave

rage

Rol

ling

52-W

eek

Cor

rela

tion

Source: Credit Suisse, the BLOOMBERG PROFESSIONAL™ service, Moody’s Note: Data as of 8/31/2011

We focus on identifying periods when risk premia are either extremely high or low, i.e., the market is oversold or overbought, by using positioning data in the S&P 500 futures market. Positioning information is relevant for understanding risk premia because risk premia are likely to be low when investors are aggressively buying beta assets and vice versa when investors are actively selling. In particular, we study the relationship between extreme flows in S&P 500 futures contracts and the future performance of risky assets. We focus on the S&P 500 because it is the single most visible, transparent, and liquid risky asset for which we can observe publicly available flow information.

Constructing the Extreme Flow Indicator (EFI) While it is difficult to get timely positioning data, a good public source of this type of information comes from the Commodity Futures Trading Commission’s (CFTC) weekly Commitment of Traders (COT) report 1 . It categorizes long and short positions of respective future market participants into holdings by commercial traders, non-commercial traders and small accounts. Commercials typically represent institutions using futures to hedge their exposure in the underlying spot or cash markets; these participants are usually called hedgers. Non-commercials are typically hedge funds or commodity trading advisors (CTAs) who use futures as a vehicle to speculate in a particular market. We focus on the positioning of commercial traders because, to understand the drivers of risk premia, we believe the activities of large hedgers should be most informative.

1 The Commitment of Traders report is normally released on Friday afternoon EST using data as of Tuesday of the same week.


07 September 2011

We use the net commercial position (long position – short positions) in the S&P 500 e-mini contract to construct the EFI. Since futures volumes and position sizes have grown over time, we need to normalize the data to make consistent historical comparisons. There are two basic steps in calculating the EFI:

1. We normalize the recent history using a statistical approach to map the distribution of net commercial positions into an approximately Normal distribution using recent history; and

2. The EFI is the standard deviation of the latest observation relative to the distribution estimated in step 1.

This process is quite similar to estimating a z-score2 of the net commercial positions, but has the advantage of being more robust in small samples and more responsive to recent changes in the environment. Exhibit 2 below plots the recent history of the EFI versus the S&P 500. Extreme EFI values tend to be generated just after the reversal of the recent market trend in the equity market, reflecting the responsiveness of net positioning as markets rally (sell off) from oversold (overbought) levels. The relatively short history, three months, used to estimate the local distribution of net commercial positioning makes the EFI quite responsive to recent market developments. The apparent ability of the EFI to signal trend reversals makes it a potentially interesting way to time market exposure. We explore this application in the next section.

Exhibit 2: Recent History of the Extreme Flow Indicator and S&P 500

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-1.0

0.0

1.0

2.0

3.0

Jan-07 Jan-08 Jan-09 Jan-10 Jan-11

EFI

600

800

1000

1200

1400

1600 S&

P 500 Index Level

EFI (LHS) S&P 500 Index (RHS)


Using the EFI as a Tool for Timing Market Exposure The responsiveness of the EFI to market trend reversals makes it a natural candidate for use as a timing tool for beta exposures. We test the EFI in two different applications:

1. To time exposures in equity (S&P 500) versus fixed income (BarCap US Aggregate) benchmark indices; and

2. To time exposures between growth and defensive Index portfolios.

While the first application works with raw underlying indices, timing between the index portfolios is potentially much more powerful because the growth and defensive portfolios are essentially enhanced beta portfolios. We employ a simple timing rule to switch between equity (growth portfolio) and fixed income (defensive portfolio): if the EFI exceeds a fixed threshold during the month, we buy equities or the growth portfolio; if the EFI is less than a fixed threshold, we buy fixed income or the defensive portfolio. If the EFI is

2 The z-score of a data point is calculated by subtracting its historical mean and dividing by its historical standard deviation. Z-

scores are a common way to normalize data.


07 September 2011

between the positive and negative thresholds, there is no trade and we hold the same position as the previous month. We use the same absolute threshold for positive and negative breaches. Exhibit 3 below plots the results of the timing strategy applied to the S&P 500 and BarCap US Aggregate indices. EFI timing greatly improves performance relative to a buy-and-hold strategy in the S&P 500, but underperforms the BarCap US aggregate. EFI timing avoided most of the decline in equities prior to 2009 and captured much of the equity market rally from Q2 2009 onward. From January 2007 through August 2011, the EFI generated nine trading signals, or about two signals per year.

Exhibit 3: EFI Timing with Benchmark Indices: S&P 500 and BarCap US Aggregate The returns on both the S&P 500 / BarCap US Aggregate timing strategy and S&P 500 Index are normalized to have the same volatility in the period to facilitate a comparison. We use overnight USD LIBOR as our proxy for the risk-free rate.

859095

100105110115120125130135


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Exc

ess

Ret

urn

S&P 500 / BarCap US Agg S&P 500 Index BarCap US Aggregate


We now apply the same timing strategies to the growth and defensive index portfolios. The performance of the timing strategy improves significantly, as seen in Exhibit 4 below, now outperforming both the fixed income and equity benchmarks through the period. The performance boost relative to the previous test using benchmark indices is a testament to the enhanced beta attributes of both the growth and defensive index portfolios.

Exhibit 4: EFI Timing Using S&P 500 / BarCap US Aggregate and Growth / Defensive Index Portfolios The returns on both the S&P 500 / BarCap US Aggregate and Growth / Defensive timing strategies are normalized to have the same volatility in the period to facilitate a comparison. We use overnight USD LIBOR as our proxy for the risk-free rate.

90

100

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160


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S&P 500 / BarCap US Agg Growth / Defense Portfolios BarCap US Aggregate



07 September 2011


Exhibit 5 presents summary performance statistics on the two EFI timing strategies compared with the benchmark indices; all return series were normalized to have the same volatility over the period to facilitate comparison. Timing with the growth / defensive index portfolios is the best-performing strategy in terms of Sharpe ratio.

Exhibit 5: Summary Performance Statistics, Jan 2007 – August 2011 All return streams are normalized to have the same volatility in the period to facilitate a comparison. We use overnight USD LIBOR as our proxy for the risk-free rate.

Growth / Defensive S&P 500 / BarCap US

Aggregate S&P 500 BarCap US Aggregate Annualized Excess Return 8.93% 4.99% -0.38% 5.37% Annualized Volatility 5.00% 5.00% 5.00% 5.00% Sharpe Ratio 1.79 1.00 -0.08 1.07 M aximum Drawdown 6.72% 5.53% 13.63% 6.74% Source: Credit Suisse Note: Data as of 8/31/2011

Alpha Strategies

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

+1 212 538 6480

NORTH AMERICA Eleven Madison Avenue, New York, NY 10010

Richard Durand, Director +1 212 538 6445 [email protected]

Meng-Chen Hsieh, Ph.D., Associate +1 212 538 1362 [email protected]

Bhaskar Krishnan, Director +1 212 538 5632 [email protected]

Weijian Liang, Ph.D., Associate +1 212 325 9123 [email protected]

Yongchu Song, Ph.D., Director +1 212 538 7013 [email protected]

David Tien, Ph.D., Director +1 212 538 9665 [email protected]

LONDON One Cabot Square, London E14 4QJ, United Kingdom

Riad Houry, Associate +44 20 7883 0168 [email protected]

Limin Wang, Ph.D., Vice President +44 20 7888 6445 [email protected]

Disclosure Appendix

Analyst Certification The analysts identified in this report each certify, with respect to the companies or securities that the individual 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.

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