Asset Management Spotlight

Trends Summer 11 Asset Management Spotlight The structured investment process key to success Dr. Anja Hochberg, CIO Office The most successful way to manage investments is to take an all-encompassing approach to the assets. There are two key ingredients in investment success. 12 Dossier The first is the long-term asset allocation, which is determined with reference to the benchmark. The second is the tactical side of the investment decision. Pronounced economic and political risks and volatile, fast-reacting markets are making it more important than ever to temporarily over or underweight asset classes and sub-classes versus the benchmark. The tactical process, which can be used to boost returns and to manage portfolio risk, is therefore a key component of asset management at Credit Suisse. Chart 1: Structured investment process clear responsibilities Client Requirements Long-term Financial objectives Risk profile Need for liquidity Overall wealth consideration Asset-Liability-Mgmt. Other (succession planning, etc.) Client, Credit Suisse Long Term Assumption 5 years Long-term Asset Allocation (Bi-)annually Best-possible combination of asset and sub-asset classes to reach financial objectives Benchmark definition (neutral weights, bandwidth, reference indices) Risk budget Coordination with personal risk profile Client, Credit Suisse Short Term Assumption 1 3 months Tactical Asset Allocation Monthly / as required Weightings of asset classes and sub-asset classes Country weightings Duration Currencies Credit Suisse, Asset Allocation Committee Global Investment Committee sets the framework The Investment Committee (IC), chaired by Chief Investment Officer (CIO) Stefan Keitel, lays down the framework for investment decisions in asset management. At the IC s meetings, which are held fortnightly or on an ad-hoc basis if required, experienced analysts from Credit Suisse s Research departments Research Manager Selection Strategic Partners Portfolio Engineering Ongoing Equities, bonds, alternatives, derivatives Styles - Value vs. growth - Active vs. indexed Yield curve, credits Open architecture Hedging (if applicable) Credit Suisse, Portfolio Management Reporting & Monitoring Ongoing Risk and return (absolute) Deviation from benchmark (relative) Performance attribution (timing, selection) Adherence to client instructions Process monitoring Risk Management, Reporting, Custody Source: Credit Suisse DossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossier

DossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossier Chart 2: Tactical asset allocation decision process Earnings and valuations Investment Views Optimal Risk Budgeting Tactical Asset Allocation (TAA) Under-/overweight of asset classes Macroeconomics Technical analysis and investment officers from Asset Management discuss the latest developments on the financial markets. The Investment Committee s judgments on the attractiveness of asset classes form the basis for investment recommendations in both advisory business and wealth management. Chief Investment Officer & Asset Allocation Committee Market sentiments Quantitative analysis Region exposure Currency exposure Global investment themes Source: Credit Suisse Turning market assessments into investment decisions The Asset Allocation Committee (AAC), also chaired by the CIO, uses these views to develop its investment tactics for asset management. In addition to the assessment of the macroeconomy and fundamental analysis (e.g. earnings and valuations), technical market factors and sentiment also feed into this fine-tuning. Quantitative investment analysis techniques are also applied. The AAC therefore includes employees with responsibility for each asset class and for central analysis processes from the CIO s office. Regional views from around the world are brought together, enabling the assessments of specialists with in-depth knowledge of local markets to be taken into account. The final stage of the analytical part of the investment decision consists of consistency checks and the amalgamation of all the analyses presented. Only investment ideas in which we truly believe are put forward for optimization in the next stage: Credit Suisse s portfolio allocation system. Trends Summer 11 With a mandate the client profits of our entire analytic and strategic knowhow and can be certain of prompt and consistentapplication of tactical recommendations. Stefan Keitel Chief Investment Officer Dossier 13

Trends Summer 11 Long-term asset allocation the benchmark Martin Hirt, Dr. Georg Stillhart, CIO Office The first level of the asset allocation process is the long-term asset allocation. This division of capital between asset classes is not set in stone; rather, it is the result of extensive analysis of the financial markets and assessments of economic trends over a full economic cycle. We will now outline some of Credit Suisse s fundamental views on which it bases its long-term asset allocation for clients. More emerging markets, increased global diversification. Credit Suisse Research has for some years now homed in on the increasing significance of the emerging markets, where it has identified a megatrend. These markets currently account for around 36% of global GDP, but only around 13% of market capitalization (measured using the MSCI World AC). Our conviction that the emerging markets hold great potential is also reflected in our long-term investment profiles. We have also further reduced the home bias of all investment profiles to ensure the greatest possible global diversification within equities. Expected outperformance of real assets over nominal assets. After years of falling interest rates and with rates now standing at historic lows, there are various indications that higher inflation is on its way (e.g. expansive monetary and fiscal policy, emerging market growth and the associated rise in commodity prices). We therefore favor real assets, such as equities, commodities and real estate, over fixed income. However, bonds of course represent an indispensable element of any multi-asset class portfolio, and a wide variety of different types of instrument are available: in addition to 14 Dossier Chart 3: Current capital market assumptions in CHF 12% Expected Return (5yr) p.a. 10% 8% 6% 4% 2% RE Funds Switzerland Hedge Funds Govt & Corp Bonds CHF Corp Bonds USD Govt Bonds EUR Money Corp Bonds EUR Market CHF Govt Bonds USD HY Bonds USD 0% 0% 5% 10% 15% 20% 25% 30% 35% Expected Volatility (5yr) p.a. government and corporate bonds, these include the likes of inflation-linked, high yield and emerging market bonds and asset-backed securities (ABSs). Foreign currency risk. Investors with long-term exposure to foreign bonds gain little in return for the currency risk entered into. Last year showed that such risks can indeed be massive, with the US dollar and the euro depreciating by 10% and 16% respectively against the Swiss franc, for example. Even over a longer time period a very clear picture emerges: over the past 25 years, a Swiss franc-based investor would have been able to more than halve the risk associated with global bonds, without diminishing returns 1. For this reason, we recommend avoiding, hedging or tactically managing foreign currency risks when investing in bonds. We therefore exclude any foreign currency exposure on bonds from our long-term asset allocation (benchmark). Equities Asia Pacific ex Japan Private Equity Equities USA Equities CH Equities UK Equities World AC Equities Europe HY Bonds EUR Gold Commodities EmMa Bonds RE Europe (listed) Capital market assumptions are not a projection, prognosis or guarantee for future performance. Equities Japan RE USA (listed) Source: Credit Suisse Global Research / CIO Office Credit Suisse s capital market assumptions Equities EmMa RE Asia (listed) Credit Suisse Global Research follows a transparent semi-annual process to produce a consistent set of capital market assumptions for more than 50 main and sub-asset classes. These capture return expectations and estimated volatility and correlations over a five-year horizon. These assumptions form the basis for our analysis and optimization activities. 1 BoA Merrill Lynch Global Bond Index ex Switzerland, Dec. 31, 1985 Apr. 30, 2011: - unhedged: 4.6% return p.a. 8.1% risk p.a. - hedged: 5.2% return p.a. 3.5% risk p.a. Historical returns and analyses are no guarantee for current or future results. DossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossier

DossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossier Tactical asset allocation (TAA) shares the same investment universe as the long-term benchmark mix. The relatively small number of markets and the generally good availability of market data creates an opportunity to optimally combine the market information by way of computer algorithms. In short, TAA is the sweet spot where the impact on the overall performance is large and the volume of available data allows for the optimal combination of information by numerical computation. Credit Suisse has developed a unique algorithmbased system to exploit this opportunity in TAA portfolio construction. The optimal risk budgeting system (ORB) combines active investment views with a internal risk model to create bespoke tactical asset allocations for selective user preferences. The main elements of optimal risk budgeting The objective of the ORB system is the generation of TAA-based outperformance through the calculation of active TAA weights. The calculation is based both on active market views as a measure of asset class attractiveness and on market uncertainties as a proxy for associated market risks. The covariance matrix representing the market uncertainties is estimated using a deterministic risk model (Ledoit and Wolf, 2002). In our investment process, experienced strategists are responsible for the formulation of the active market views that are the main drivers of alpha generation. The views are formulated as pairwise views. Pairwise views are relative statements of conviction that "asset class A" will outperform "asset class B". The structure of a pairwise view is very similar to a trade where the attractive asset is bought and the unattractive asset is sold. This similarity greatly simplifies the portfolio construction, as the view not only suggests the asset class that should receive the active weight, but also the asset class that should provide the funding. Pairwise Trends Summer 11 The case for quantitative Tactical Asset Allocation portfolio construction Ralf Seschek, CIO Office Chart 4: Summary of tactical asset allocation process Client Investment Profile Strategy (e.g. benchmark, risk) Reference Currency Bandwidths Restrictions etc. Optimal risk budgeting model Client-specific Asset Allocation (short term) Switzerland E.M.U. U.K. U.S.A. Canada CHF EUR GBP USD CAD Benchmark 12.03% 0.56% -0.22% 0.06% -0.01% Optimal 17.12% -0.74% 0.00% 0.00% 0.00% Benchmark 32.04% 3.87% 1.04% 0.60% 0.15% Optimal 28.84% 2.58% 0.00% 0.00% 0.00% Benchmark 25.59% 3.83% 2.20% 10.11% 0.98% Short term market expectations = Investment Views Source: Credit Suisse views are a concept that is not unique to the ORB, they are also part of another industry-standard approach to portfolio construction. The standard approach blends the pairwise views linearly into portfolio positions. The ORB, in contrast, goes beyond this concept by optimizing the information represented by the pairwise views and their associated risks. After standardizing the views to a comparable risk level, the ORB seeks out the highest information ratio or entry probability of the view portfolio by varying the weight assigned to any individual view. Once the view portfolio is established, the introduction of bespoke client features such as risk level, benchmark or absolute return focus and individual restrictions allows for tailor made TAA solutions. These solutions take into account both the individual client approach while simultaneously enabling a consistent representation of the strategists investment views. In this manner, we assign the same probability of outperformance to each investment view. In a related manner, intra-bond shifts typically involve larger portfolio allocations than a trade between equity and bonds to achieve the same risk and associated return expectation impact. This is how the name optimal risk budgeting is derived. Each investment decision is able to contribute equally to the overall result, irrespective of the risk level of the underlying asset classes. During optimization, the system makes use of diversification by emphasizing weakly correlated views. Putting it together We ve seen that the system is designed to give all investment views the same chance of outperformance by budgeting Dossier 15

Trends Summer 11 16 Dossier the bets according to their perceived risk level. All else being equal, a low-risk trade is assigned a larger magnitude than a high-risk transaction. We ve also seen that in this optimization step, less weight is put into highly correlated trades to avoid making the same bets twice. Because the investment views are valid for all client portfolios, we are able to split the investment process into two sections. One section deals with the generation of high-conviction investment views. A subsequent section constructs client portfolios based on investment views, the risk model and the client preferences. The TAA portfolio construction system ORB provides the link between the investment view set and the many clientspecific solutions. Because investment projections are laced with uncertainty, a sound investment process should account for the imprecision that arises from investment views. It is possible to reflect the uncertainty in the views by suitably reducing the magnitude of the associated exposure. In the ORB, we have chosen another approach. The ORB calculates trust regions or bandwidths around the optimal TAA weights. The bandwidths are small if the position varies very little with minuscule changes in the investment views. If the position is unstable and small changes in the investment views cause large swings in the resulting position, the associated bandwidths will be large to account for the inherently large uncertainty. It is the responsibility of the portfolio manager to postion the portfolio within the bandwidths. The measurement of the success rates at suitable points complements the investment process. External evaluations by independent experts have yielded very positive reviews (B. Solnik 2004, H. Markowitz 2008). DossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossier

DossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossierDossier Possibilities of implementation Marc Geissmann, Thomas Isenschmid, Portfolio Management Institutional Clients The investment process described above and in particular the optimal risk budgeting (ORB) approach enable us to manage various kinds of multi-asset class portfolios consistently under a single investment process. Asset management mandates can be divided into two main categories according to their investment philosophy: those with traditional benchmarks (i.e. the asset allocation strategy is laid down) and those with a risk budget. The first group consists of portfolios with defined investment strategies and ranges per asset class forming the framework for asset management. Within an active management approach, tracking error which measures the deviation of the tactical allocation from the strategic benchmark is a key management measure. Individual investment strategies are devised on the basis of a defined return objective, which must be consistent with the investor s risk appetite and capacity. In the second group, a volatility-based approach is taken to asset management. This is particularly well-suited to investors who experience a heightened risk or loss aversion and as such are most concerned about the potential for losses during bearish phases. The volatility of the overall portfolio which can be seen as a dynamic risk budget is the key management measure. It is not permitted to exceed a predefined level in any market phase. Even if there is no benchmark to act as the management measure, the objective of the investment process described above still applies in the same way for both categories, i.e. to seek to maximize returns within the investment restrictions laid down. The question can be asked as to why portfolio volatility should be used at all as a budget. Firstly, overall portfolio volatility encompasses both the investment risks associated with the individual securities and those associated with the asset allocation. History shows us that periods of strong price corrections coincide with increased volatility, which serves as an indicator of nervousness among investors or on the market. If volatility goes up in stress phases, the portfolio manager is forced to reduce risks in the portfolio in order to comply with the maximum budget. This means that there is an additional rule on top of the investment process outlined above enforcing disciplined portfolio management in tough market conditions. In particular, this can help get round psychological traps in periods when Chart 5: Reducing risks in periods of stress 0% Risk-based performance Trends Summer 11 markets are fluctuating substantially. If the markets then recover, portfolio volatility decreases again, generally from a high level. This enables the portfolio manager to gradually increase risk again (e.g. via equities), while always observing the maximum permitted risk budget. Both investment philosophies outlined here can be deployed either in mandate form or within an overlay structure (with multiple asset managers/mandates). Performance traditional benchmark During extended stress phases, volatility-oriented mandates can shield themselves to some extent against negative returns. The flipside is that they can be rather slower to enter into risk positions again in recovery phases. Source: Credit Suisse, for illustrative purposes only Dossier 17

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