Managing Risks in a Multi-Asset, Multi-Manager Portfolio

Transcription

1 Managing Risks in a Multi-Asset, Multi-Manager Portfolio Presented by: Mary Jane Bobyock, CFA, Director, Advisory Team Rob Ludwig, Managing Director, Risk Management Group

2 Risk management at multiple levels Client Strategic Risk Management FUNDS MANAGERS SECURITIES 2

3 Risk management analysis at multiple levels Manager Level Analysis Metric Description Frequency Security Level Holdings Analysis Access to portfolio holdings Daily Tracking error Aggregates risk from all active exposures relative to a benchmark Weekly Manager contribution to risk Measures how the active risk budget is allocated Weekly Manager risk-adjusted return Provides an objective measure of manager alpha Monthly Portfolio Level Analysis Metric Description Frequency VaR model integrity Compare manager return forecast with results Daily Portfolio benchmark-relative Controls tracking error by setting limits on relative exposures Daily exposure guidelines Counterparty risk Monitors exposure to dealers from OTC derivative transactions Daily Relative value at risk Identifies excessive risk-taking relative to benchmark Daily Cover Measures the amount of capital in excess of the liabilities created Daily by derivative exposures Tracking error Aggregates risk from all active exposures relative to a benchmark Weekly Stress testing Uses stress scenarios to identify non-linear behavior Monthly This chart illustrates the type and frequency of reports and analysis that SEI has available to monitor risk at the manager and portfolio level. Specific risk management protocols may vary depending on the manager or portfolio and may be customized for particular clients. 3

4 Portfolio design: Strategic alpha source allocation Manager/portfolio Target Weight Tracking error Manager 1 30% 5.0% Alpha source Risk Premium Target risk contribution 25% Manager 2 35% 4.0% Selection 25% Manager 3 15% 8.5% Momentum 25% Manager 4 20% 6.5% Macro 25% Portfolio 100% 3.0% 100% 100% SEI establishes relative return and risk expectations for the portfolio over the medium and long term in a Portfolio Thesis The Thesis identifies which alpha sources will be included and their long-term strategic allocation Through allocations to differentiated managers, SEI seeks to construct portfolios with lower relative risk than the individual underlying investment managers Alpha is additive while volatility (tracking error) can be dampened through diversification (lowly correlated alpha sources) Strategic allocations provide a framework for active manager allocation or sizing For illustrative purposes only 4

5 Manager contribution to risk Prevent one manager s performance from dominating fund performance Control fund level risk by limiting manager percentage contribution to total risk Manager risk contribution determined by volatility and correlation to other managers Risk Limit For illustrative purposes only. 5

6 Internal oversight and state-of-the-art risk management tools provide continuous management of risks at all levels Risk Management SEI Investment Management Unit Investment Strategy Oversight Committee (ISO) Investment Strategy Portfolio Strategy Equities Income Alternatives Our ISO Committee provides independent review and oversight of all investment decisions We have made a significant investment in an enterprise risk management system to proactively monitor risk across asset classes and the total client portfolio Well-defined policies and procedures enforce discipline to defined risk parameters Processes prevent a single manager from dominating the risk of a multi-manager portfolio Stress testing is used to reveal non-linear behavior from large changes to risk factor 6

7 Risk management for multi-asset portfolios Asset allocation strategy is designed to achieve long-term client objectives Uses long-term risk, return and correlation forecasts Asset allocation is relatively static Implementation with active management seeks to add excess return or lower risk over shorter-term horizons Active security selection creates dynamic exposures Dynamic asset allocation creates deviations from long-term policy Asset class correlations are not static Risk management monitors that the active implementation supports the long-term asset allocation strategy 7

8 Risk model explains the variability of individual security returns in terms of systematic factors Equity Factors Market risk Country Industry Style factors Fundamental factors Income Factors Yield curve (by country) Credit spreads (by country, industry) Foreign exchange Inflation Over 2,000 risk factors Factor model creates an intuitive view of risk Alternatives Factors Hedge Funds Real Estate Private Equity Equity market risk Property type Deal type Equity sectors Leverage Size Country Geography Stage Yield curve Vintage Credit Concentration Commodities Geography Currency Style Factor model reduces the number of parameter estimates and improves robustness 8

9 Correlation matrix of risk factors Multi-asset risk management system provides an integrated view across equities, fixed income and alternatives Risk Factors Equities Risk Factors Income Alternatives 9

10 Correlation matrix of risk factors Multi-asset risk management system provides an integrated view across equities, fixed income and alternatives Risk Factors Equities Equities Risk Factors Equities Income Alternatives 10

11 Correlation matrix of risk factors Multi-asset risk management system provides an integrated view across equities, fixed income and alternatives Risk Factors Equities Equities Risk Factors Equities Income Alternatives Alternatives Alternatives 11

12 Correlation matrix of risk factors Multi-asset risk management system provides an integrated view across equities, fixed income and alternatives Risk Factors Equities Equities Equities Alternatives Risk Factors Equities Income Alternatives Equities Alternatives Alternatives Alternatives 12

13 Calculating portfolio risk with a factor model Contribution to risk of each security is determined by: Weight of each security in the portfolio Exposure of each security to each risk factor Covariance matrix of the risk factors We can aggregate securities to calculate: Contribution to risk from each factor Contribution to risk from each manager Contribution to risk from each asset class Total portfolio risk Tracking error relative to benchmark 13

14 U.S. Managed Volatility Strategy: Contribution to risk by factor Risk Group Risk Contribution (%) Equity Risk 9.41 Market Risk Volatility Momentum Size 0.11 Value 0.10 Liquidity 0.17 Growth 0.03 Dividend Yield Other Factors Foreign Exchange 0.06 Total 9.47% Information as of 4/30/

15 Risk decomposition of moderate volatility hedge fund Spread Risk Decomposition Risk Group Total Risk Decomposition Risk Contribution (%) Hedge Fund Equity 3.47 Hedge Fund Spreads 1.29 Hedge Fund Rates 0.11 Hedge Fund Style 0.07 Total 4.94% Risk Group Hedge Fund - Spreads Risk Contribution (%) ABS 0.01 Commercial Mortgage 0.13 Corporate Credit 0.45 Residential Mortgage 0.36 Capital Structure Loans 0.0 U.S. Credit 0.34 Total 1.29% Information as of 4/30/

16 Actual portfolio implementation reflects active view and current market conditions Strategic asset allocation for a sample client portfolio Asset Class Allocation (%) Global Equities 40 Income 26 Inflation-Sensitive 9 Hedge Funds 10 Real Assets 10 Dynamic Allocation 5 Expected Risk 12.5% Risk decomposition of a sample client portfolio implementation Risk Group Risk Contribution (%) Equity 4.84 Alternative 1.34 Foreign Exchange 0.31 Spreads 0.30 Inflation 0.02 Rates Total Risk 6.8% 16

17 Current environment: Volatility is low 17

18 Total portfolio exposures to higher yielding fixed income sectors in sample client portfolio High Yield Corporate Bank Loans Non-Agency Mortgages CMBS CDO / CLO 0% 2% 4% 6% Portfolio Exposure 18

19 Stress testing exposures to higher yielding fixed income sectors in sample client portfolio One Sigma Shock to High Yield Credit Spreads* Factor Shock High yield spreads +70 bps U.S. Treasury 10 year rate -31 bps Investment grade spreads +20 bps VIX +6.4% S&P % World equity ex-u.s. -9.3% *Implied shocks to other risk factors based on correlation matrix. 19

20 Stress test results for high yield credit shock on sample client portfolio Total Return Impact Equity Market Exposure Alternatives / Credit Return Impact (%) 20

21 Portfolio comparison Barclays Aggregate 20.0% 80/20 Passive Portfolio Core Prop 7.0% Diversified Portfolio Private Assets 5.0% Structured Credit 5.0% Large Cap 9.0% S&P 500 Index 7.0% Extended Markets Index 3.0% Special Sits 8.0% Small Cap 2.0% MARR 8.0% World Equity ex-us 12.0% S&P 500 Index 80.0% Oppt Income 3.0% Barclays Aggregate 0 US Core 10.0% EM Debt 6.0% DAA 5.0% High Yield 7.0% EM Equity 3.0% 80/20 Passive Portfolio Diversified Portfolio Compound Return 6.6% 8.0% Risk 15.6% 12.5% Sharpe Ratio Poor Scenario Return -15.9% -10.6% *Gross of Fees Illustrations shown are based on capital market assumptions; see disclosure at end of presentation for additional details 21

22 VAR Analysis of $100 million portfolio May 31, 2014 Undiversified Risk Diversified Risk Alternative Inflation FX Interest Rates Spread Equity $5,000, $- $(5,000,000.00) $(10,000,000.00) $(15,000,000.00) $(20,000,000.00) $(25,000,000.00) $- $1,000, $2,000, $3,000, $4,000, $5,000, $6,000, $7,000, $8,000, $9,000, $10,000, % 10 Yr Treas Hypothetical Inflation Fed Tapering Tech Bubble -10% Equity VIX jumps to 35 Source: Blackrock Portfolio Risk Tools, SEI Investment Management Unit. Risk defined as standard deviation. 80/20 Passive Portfolio Diversified Portfolio 22

23 Don t try this at home 23

24 Important Information This presentation is provided by SEI Investments Management Corporation (SIMC), a registered investment adviser and wholly owned subsidiary of SEI Investments Company. The material included herein is based on the views of SIMC. Statements that are not factual in nature, including opinions, projections and estimates, assume certain economic conditions and industry developments and constitute only current opinions that are subject to change without notice. Nothing herein is intended to be a forecast of future events, or a guarantee of future results. This presentation should not be relied upon by the reader as research or investment advice (unless SIMC has otherwise separately entered into a written agreement for the provision of investment advice). There are risks involved with investing including loss of principal. There is no assurance that the objectives of any strategy or fund will be achieved or will be successful. No investment strategy, including diversification, can protect against market risk or loss. Current and future portfolio holdings are subject to risk. Past performance does not guarantee future results. For those SEI funds which employ a multi-manager structure, SIMC is responsible for overseeing the sub-advisers and recommending their hiring, termination, and replacement. References to specific securities, if any, are provided solely to illustrate SIMC s investment advisory services and do not constitute an offer or recommendation to buy, sell or hold such securities. Certain economic and market information contained herein has been obtained from published sources prepared by other parties, which in certain cases have not been updated through the date hereof. While such sources are believed to be reliable, neither SEI nor its affiliates assumes any responsibility for the accuracy or completeness of such information and such information has not been independently verified by SEI. 24

25 Important Information SIMC develops forward-looking, long-term capital market assumptions for risk, return, and correlations for a variety of global asset classes, interest rates, and inflation. These assumptions are created using a combination of historical analysis, current market environment assessment and by applying our own judgment. In certain cases, alpha and tracking error estimates for a particular asset class are also factored into the assumptions. We believe this approach is less biased than using pure historical data, which is often biased by a particular time period or event. The asset class assumptions are aggregated into a diversified portfolio, so that each portfolio can then be simulated through time using a monte-carlo simulation approach. This approach enables us to develop scenarios across a wide variety of market environments so that we can educate our clients with regard to the potential impact of market variability over time. Ultimately, the value of these assumptions is not in their accuracy as point estimates, but in their ability to capture relevant relationships and changes in those relationships as a function of economic and market influences. The projections or other scenarios in this presentation are purely hypothetical and do not represent all possible outcomes. They do not reflect actual investment results and are not guarantees of future results. All opinions and estimates provided herein, including forecast of returns, reflect our judgment on the date of this report and are subject to change without notice. These opinions and analyses involve a number of assumptions which may not prove valid. The performance numbers are not necessarily indicative of the results you would obtain as a client of SIMC. We believe our approach enables our clients to make more informed decisions related to the selection of their investment strategies. For more information on how SIMC develops capital market assumptions, please refer to the SEI paper entitled Executive Summary: Developing Capital Market Assumptions for Asset Allocation Modeling. If you would like further information on the actual assumptions utilized, you may request them from your SEI representative. Prepared for use at the SEI 2014 Nonprofit Client Symposium, June 19-20,