Andrea Nardon, Fund Manager, Partner. May 2014

Transcription

1 Smart β: Echter Fortschritt oder nur buzz words? Andrea Nardon, Fund Manager, Partner 1

2 Systematic Strategies es Increasing popularity p for systematic strategy Systematic strategies differ from conventional discretionary investment processes as it is the process that dictates the investment decision A series of transparent rules determine the decision to buy/sell securities and as a result of this, Systematic Strategies can be indexed Systematic strategies are precursor to quantitative strategies and differ from the latter as they adopt a less dynamic approach Systematic ti strategies t are designed d to exploit anomalies Systematic strategies are active investment products as they generate a tracking error versus market cap indices recently branded under Smart Beta risk premia and more generally market Investment Strategies designed to exploit a single or multiple sources of return through a transparent and clear rule based process where the discretionary overlay of the fund manager is negligible 2

3 Positioning o Systematic Strategies es in the Active/Passive Space Breaking Down the out-dated binary Active / Passive classification Discretionary Investment Style Active Quant Non- Discretionary Alternative Weighting/Smart β Systematic Market Cap Passive 3

4 Structural Challenges undergoing g th he Asset Management age e industry EQUITY CUMULATIVE FUND FLOWS* (USD BN) AUM (USD bn) Since the fund flows peak in October 2007, active equity funds lost $1.3tn while passive products gained $1.2tn 1500 Smart Beta included in the passive because the strategies are indexed Active Passive All Funds Why are investors considering smart beta solutions? - Active has struggled - it is an expensive proposition - Some alternative indexing methodologies to market cap (developed by the same index providers) have generated superior absolute and risk adjusted returns - Strategies are very transparent and governed by a clear investment process Is Smart β the Holy Grail? Source: EFPR Global, March

5 Smart tββ may not be the Holy oyga Grail but Predictability of Returns Suitable for a Core/Satellite Asset Allocation approach Overcoming market cap inefficiencies e c es Clarity & Transparency Attractive Pricing Building Blocks of Asset Allocation Smart β is a logical solution to market cap inefficiencies and a valid alternative to the discretionary inve estment styles 5

6 Sarasin s experience in managi ing a Smart β solution in Emerging Market Equities 6

7 The Emerging gmarket Franchise - Overview v ew Emerging g Market Franchise () 5 GEM funds*, including SICAV, Swiss and Irish funds for an AUM of $1.15bn. The two reference funds: - EmergingSar Global Retail - Lux SICAV, launched in 1996 in Basel and moved to London in SaraPro Emerging Markets Institutional - Swiss Open-ended fund, launched in 2004 in London The investment objective is to generate superior returns to the MSCI Emerging Market index through h the use of a systematic ti invest tment t strategy t The investment strategy is designed to benefit from the growth of smaller countries while offering a broad portfolio diversification Originally developed to serve a retail clientele, it has become over the years very institutional focused 18yrs after its launch, the Sarasin Systematic EM investment strategy while being kept up to date with the evolution in financial markets it is still faithful to it's original formulation * The franchise includes: EmergingSar Global, SaraPro Emerging Markets, Swiss Institutional Fund, Sarasin Sustainable Emerging Market Equity fund, Sarasin IE Emerging Markets Systematic, EmergingSar New Frontiers. 7

8 Emerging g Market Investment e t Proce ess Equally Weighted Country Allocation Equally Weighted Country Allocation To exploit the small country effect To ensure portfolio diversification Rebalancing Rebalancing To capture the rebalancing premium that co omes from cross-sectional sectional mean-reversion Implementation Impleme Index entation Products Use of Index Products to achieve a perfe ect implementation of country weights Risk monitoring and oversight 8

9 The Equally Weighted Country Allocation o COUNTRY WEIGHTS MSCI Emerging Market Index is invested in 21 countries Portfolio weights (%) Sarasin approach targets all countries unless: 20% 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% MSCI EM Equally Weighted - Lack of liquidity - Limited it accessibility - High trading costs Currently targeting 20 out of 21 countries. Colombia is excluded for accessibility and cost reasons Source: Bloomberg, Sarasin & Partners LLP, COUNTRY WEIGHTS Relative weights (%) 10% 5% 0% -5% -10% -15% Index changes (i.e. new countries coming in or going out) are reflected immediately in the fund Equally weighting improves portfolio diversification: - Single country target weight: 5% (i.e. 1/20) - 5 largest countries (by market cap) represent 2/3 rds of the index (and 3 countries are Asian) - The increase in diversification comes from overweighting smaller countries and underweighting larger countries Source: Bloomberg, Sarasin & Partners LLP,

10 The Size Premium: smaller countries outperform larger countries over the medium-long term SMALL COUNTRY EFFECT (EQUALLY WEIGHTED) Cumulative Returns (USD) Remaining Smaller Countries 5 Largest Countries Source: Bloomberg, Sarasin & Partners LLP, The largest 5 countries by market cap, selected on a monthly basis, have historically underperformed the smaller country portfolio (containing all the all the remaining countries) Historical Performance numbers (Appendix 1) Historical Analysis Return Risk Sharpe Beta Large 5 Countries Smaller Countries SMALL COUNTRY EFFECT (RATIO: SMALL VS. LARGE) Cumulative Relative Returns Motivations: - Convergence Theory (Catch-up effect): poorer economies (GDP per capita) will tend to grow faster than the richer economies and eventually converge - Small Cap bias : a look through of the equally weighted country allocation reveals an overweight position in the small cap stocks (Appendix 2) Source: Bloomberg, Sarasin & Partners LLP,

11 Historical Implementation e HISTORICAL INSTRUMENT ALLOCATION FOR SARAPRO EMERGING MARKETS Portfolio weights (%) 100% 90% 80% 70% 60% 50% 40% 30% Cash Listed Index Products Open Ended Index Swaps Closed End Funds 20% 10% 0% The funds are now pursuing an index implementation but historically investment trusts were a large portion of the fund Source: Sarasin & Partners LLP,

12 An Equally-Weighted country approach in Emerging Markets: Historical i Simulation MSCI EMERGING MARKETS Cumulative Historical Returns (Simulated in USD) 500 Simulated Equally Weighted Strategy 450 MSCI Emerging Market TR An equally-weighted approach shows +497bps p.a. of outperformance on a rolling 3yr basis, for the past 15yrs, with a TE of 5.1% Source: Sarasin & Partners LLP, The historical equally weighted simulation is based on the MSCI single country indices part of the MSCI Emerging g Market index. We used the total returns in USD and focused on the monthly prices fixed at the end of each month. No transaction costs where considered nor management fees. Countries that left (entered) the index have been immediately reflected in the simulation. Please note this analysis contains simulated data and does not represent actual performance of risk characteristics achieved by investors. Past performance is not a guide to future performance and may not be repeated. 12

13 and it can be implemented e in av very cost effective ect way SARASIN INSTITUTIONAL FUND VS. SIMULATION Cumulative Historical Returns (USD) SaraPro Emerging Markets Simulated Equally Weighted Strategy 90 May-10 Nov-10 May-11 Nov-11 May-12 Nov-12 May-13 Nov-13 SARASIN INSTITUTIONAL FUND VS. BENCHMARK Cumulative Historical Returns (USD) MSCI Emerging Market TR SaraPro Emerging Markets 90 May-10 Nov-10 May-11 Nov-11 May-12 Nov-12 May-13 Nov-13 The Sarasin equally-weighted approach addedd +45bps p.a. over the simulated strategy and +217bps p.a. over the M SCI Emerging Market index Source: Sarasin & Partners LLP, The historical equally weighted simulation is based on the MSCI single country indices part of the MSCI Emerging Market index. We used the total returns in USD and focused on the monthly prices fixed at the end of each month. No transaction costs where consideredd nor management fees. Countries that left (entered) the index have been immediately reflected in the simulation. The simulated strategy is compared with the Institutional Emerging market equity fund (SaraPro Emerging Markets Swiss open ended fund), available for distributions only in Switzerland. The fund performance is shows gross of management fee but net of custody fees and transactions costs. Please note this analysis contains simulated data and does not represent actual performance of risk characteristicss achieved by investors. Past performance is not a guide to future performance and may not be repeated. 13

14 SaraPro Emerging Markets Historical Track Record (gross of management tf fees) Calendar Year Performance (%) to SaraPro Emerging g Markets (USD) Benchmark (MSCI EM TR - USD) Relative Annualised Performance (%) to YTD 1 Year 3 Years 5 Years Ann. Vol. (3yr)* Ann. Vol. (5yr)* SaraPro Emerging Markets (USD) Benchmark (MSCI EM TR - USD) Relative * Volatility is computed on the daily TR in USD Source: Sarasin & Partners LLP, All data as at Please remember that you should not base decisions on past performance and that the prices may fluctuate and you may not get back your original investment. Past performance is not a reliable guide to future performance. The fund s Synthetic Risk and Return Indicator is 5 (1 low to 7 high) and further details of the risks can be found in the Prospectus and Key Investor Information document available from Overseas shares and bonds may be affected by currency exchange rates. Performance is calculated on a gross of management tfees basis with gross income reinvested. Source for performance figures: Sarasin & Partners LLP, The source for the annualised volatility measurement is Bloomberg and this measurement is expressed using the standard deviation of the Fund s USD monthly returns over the most recent 36 month period]. 14

15 Applying smart beta approache es to other Asset Classes 15

16 Sarasin s as s (initial) building blocks of Smart Beta Methodology Efficiency Low Volatility Absolute Return Concept The efficient approach is designed to invest in a large number of stocks within a given universe. The selection is based on stock s efficiency levels The investment strategy consists in selecting and weighting stocks based on their respective volatility levels. The sector allocation is also based on the sector s risk (dual-risk parity approach) The investment strategy is designed to exploit irrational short term price dislocations. It combines a long gportfolio of stocks with a short position on the index future. Ideally suited for Investors that believe it is possible to achieve better returns (in absolute and risk adjusted terms) than the market cap index without relying on discretionary stock picking approach Investors that want to extract the low volatility premium in a systematic and diversified way as the resulting portfolio is invested in a la rge number of securities Investors that demand stable and attractive levels of returns over the rate of inflation, avoiding market swings and permanently available (liquid) 16

17 The Efficient Approach: A Focus on US Equities 17

18 How do we measure e Efficiency? cy? Efficiency Methodology Remove noise as much as possible to identify sustained return levels Estimating risk in a very robust way Goals Being ab ble to identify only stocks that deliver the highest efficiency levels over time. Stocks with high volatilities will be disregarded if the level of returns are not sustained The strategy is designed to exploit the three systematic returns in the US equity market Performance Drivers Size Premium (Small vs. Large Cap) Low Volatility Anomaly Momentum Premium 18

19 The Investment Process 250 names are selected according to the highest efficiency ratio Monthly selection Stock Selection Allocation Stocks are equally weighted (i.e. 1/250 = 0.4% in each name) Overweighting small versus large Multiple implementations: Single stocks program trade (2bps). The US market is very liquid Derivatives unfunded index swaps. Such a solution will decrease the operation risks Implementation Rebalancing Monthly portfolio rebalancing Cross sectional meanreversion of the index constituents 19

20 An Efficient ce tallocation ocato for the eus Equities S&P500 Cumulative Historical Returns (USD) S&P500 Market Cap S&P500 Equally Weighted Sarasin's Efficient Approach Historic Data S&P500 Market Cap S&P500 Equally Weighted Sarasin's Efficient S&P Strategy Returns (ann.) Risk (ann.) Sharpe Ratio Tracking Error Rolling Returns (ann.) 12m yr yr yr The efficient strategy has delivered +330bps of outperformance on a rolling 3yr basis, for the past 22yrs, with a TE of 5.9% Source: Sarasin & Partners. The simulation is done using total returns in USD with 2bps of transaction costs. Rebalancing occurs at the beginning of each month. Period considered: Nov 1990 until March Please refer to the appendix for the calendar year returns 20

21 The Sarasin s Low Volatility Approach: A focus on Global Equities 21

22 Overview v ew Low Volatility strategies are gained popularity among investors (not just institutional). A study of DB 1 shows that the AUM of the 30 most popular ETFs that focus on low volatility has risen to c. USD13 billion in just two years (compared to less than USD10 billion for the MSCI USA and S&P500) Low volatility can be achieved in many ways and depends on what risks sources one wants to minimize Index providers offer low volatility indices based on their proprietary methodologies: - S&P select stocks with low volatilities which creates a bias towards the most defensive sectors - MSCI uses the multi-factor Barra Risk Model which is designed to generate diversification Several academic works 2 as well as technical reports published by practitioners have acknowledged and confirmed the Low-Volatility Anomaly for some years now Even though expected returns are usually not playing a crucial role (for achieving low volatility) there is still estimation risk At Sarasin we developed a Dual-Risk Parity methodology that invests in all market sectors inversely-proportionally to their risk levels and in stocks with the lowest volatility 1 Deutsche Bank, Introduction to minimum volatility equity indices, July 13 2 R.Haugen, N.Baker, The Efficient market inefficiency of capitalization-weighted stock portfolios, The Journal of Portfolio Management, 1991 R.Clarke, H.de Silva, St.Thorley, Minimum Variance Portfolios in the U.S. Equity Market, The Journal of Portfolio Management, 2006 D.Blitz, P.Van Vliet, The Volatility Effect: Lower Risk Without t Lower Return, The Journal of Portfolio Management, 2007 M.Baker, B. Bradley, J.Wurgler, Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly, Financial Analyst Journal, 2011 S.Maillard, T.Roncalli, J.Teiletche, On the Properties of Equally-Weighted Risk Contributions Portfolios, The Journal of Portfolio Management,

23 Sarasin s as s Approach to Low Risk Investment Objective Investment Process Lower Absolute risk profile compared to the benchmark Generate supe erior returns to the MSCI Minimum Variance benchmark Enhanced Portfolio Diversification Dual Risk Parity Allocation Sector weights are inversely proportionate to their risk levels Within each sector: Stock Selection based on low risk Alloca ation inversely proportionate to the risk levels Turnover constraint Max exposure constraint Implementation Monthly Portfolio rebalancing Centralised Dealing Desk Execution through program trade Risk monitoring and oversight 23

24 Historical Performance of the Low Risk approach MSCI WORLD Historical Simulation MSCI World MSCI min Var Sarasin Low Vol Historical Data MSCI World TR MSCI World Low Vol Sarasin's Low Volatility Returns (ann.) Risk (ann.) Sharpe Ratio Tracking Error Rolling Returns 12m yr yr The Low Volatility Strategy has outperformed on a rolling 3yr basis the MSCI World by +275bps and the MSCI Low Volatility by +231bps Source: Sarasin & Partners. The simulation is done using total returns in USD with 2bps month. Period considered: June 2008 until April of transaction costs (source Bloomberg). Rebalancing occurs at the beginning of each 24

25 The Sarasin s Systematic Absolute Return Strategy Introduction 25

26 Investment e t Challenges A commonly shared investment goal: - A positive and consistent return above inflation rate - Independent from market cycles - Avoidance of large absolute drawdowns - Permanent accessibility Asset Allocation techniques, deployed for centuries proved to have severe limitations (i.e. the 60/40 model) Major lessons of the last decade: - Yields can become negative - Diversification while improving the volatility profile - Rapid changes in market trends (markets are accessible) - Crowded space for mitigating risks while accessing global trends, of an investment does not remove drawdowns An alternative approach that operates in a less crowded space with focus on drawdowns is needed 26

27 Our Investment e t Philosophy To deliver consistent absolute returns with low drawdowns across multiple market cycles it is necessary to have a short term investment strategy Predicting market directions is very difficult particularly in the short term where macro trends are less effective We believe security returns can be decomposed into multiple factors, some of these are external and others specific to the company itself Our studies show that security prices oscillates around what is explained by the external observable factors and price dislocations tend to correct relatively quickly Diversification - in the sense of benefiting from multiple sources of return - improves the chances of achieving the target return, while controlling the volatility of the overall investment. But in order to decrease the risk of losses, captured by the drawdowns, risks need to be stripped out/hedged 27

28 The Investment e tstrategy Achieving a positive return over a 12month investment cycle while avoiding large drawdowns Long / Short Investment Strategy Long book: portfolio of approximately 40 stocks sele ected among the largest constituents of the S&P500 according to the attractiveness of the mean-reversion of their alphas Short book: mini S&P future. Stocks will not be shorted Daily recalculation and Implementation Exploiting the short term mean-r reverting characteristics of stocks specific alphas, cross-sectionally 28

29 Historical Simulation HISTORICAL SIMULATION Cumulative (Log) returns Historic Data Long/Short Returns (ann.) 16.3 Risk (ann.) 9.8 Sharpe Ratio Positive days (%) 54.2 Positive weeks (%) 61.9 Positive months (%) 74.1 Max DD (%) 11.1 Max DD length (days) Rolling Returns (ann.) 12m yr yr yr 13.6 Net of transaction costs, the simulation achieved over the past 24yrs a Sharpe Ratio of 1.65 Please note this analysis contains simulated data and does not represent actual performa ance of risk characteristics ti achieved dby investors. Past performance is not a guide to future performance and may not be repeated. The strategy is implemented at the close using the official closing and 2bps of transaction costs. No management fee nor performance fee was included in the simulation. Source: Sarasin

30 Historical Simulation: EuroStoxx HISTORICAL SIMULATION Cumulative returns Historic i Data Long/Short Returns (ann.) 9.2 Risk (ann.) 8.9 Sharpe Ratio Positive days (%) 53.1 Positive weeks (%) 58.9 Positive months (%) 69.6 Max DD (%) 9.8 Max DD length (days) Rolling Returns (ann.) 12m yr 9.8 5yr yr 8.3 Net of transaction costs, the simulation achieved over the past 12yrs a Sharpe Ratio of 1.03 Please note this analysis contains simulated data and does not represent actual performa ance of risk characteristics ti achieved dby investors. Past performance is not a guide to future performance and may not be repeated. The strategy is implemented at the close using the official closing and 2bps of transaction costs. No management fee nor performance fee was included in the simulation. Source: Sarasin

31 Historical Simulation: UK HISTORICAL SIMULATION Cumulative returns Historic i Data Long/Short Returns (ann.) 11.5 Risk (ann.) 8.0 Sharpe Ratio Positive days (%) 54.6 Positive weeks (%) 62.4 Positive months (%) 71.9 Max DD (%) 11.8 Max DD length (days) 105 Rolling Returns (ann.) 12m 6.0 3yr 5.5 5yr yr 10.0 Net of transaction costs, the simulation achieved over the past 13yrs a Sharpe Ratio of 1.43 Please note this analysis contains simulated data and does not represent actual performa ance of risk characteristics ti achieved dby investors. Past performance is not a guide to future performance and may not be repeated. The strategy is implemented at the close using the official closing and 2bps of transaction costs. No management fee nor performance fee was included in the simulation. Source: Sarasin

32 Disclaimer This presentation is for investment professionals only and should not be relied upon by private investors This presentation has been approved by Sarasin & Partners LLP of Juxon House, 100 St Paul s Churchyard, London, EC4M 8BU, a limited liability partnership registered in England & Wales with registered number OC which is authorised and regulated by the Financial Conduct Authority with firm reference number and passported under MiFID to provide investment services in Republic of Ireland. The investments of the fund are subject to normal market fluctuations. The value of the investments of the fund and the income from them can fall as well as rise and investors may not get back the amount originally invested. If investing in foreign currencies, the return in the investor s reference currency may increase or decrease as a result of currency fluctuations. Past performance is not a guide to future returns and may not be repeated. There are greater risks associated with the shares in this type of fund due to the potential volatility of the markets into which it invests. You should view any investment as a long term one (i.e. 10 years plus). Frequent political and social unrest in Emerging Markets, and the high inflation and interest rates this tends to encourage, may lead to sharp swings in foreign currency markets and stock markets. There is also an inherent risk in the smaller size of many Emerging gmarkets, especially since this means restricted liquidity. Further risks to bear in mind are restrictions on foreigners making currency transactions or investments. All details in this document are provided for marketing and information purposes only and should not be misinterpreted as investment advice or taxation advice. This document is not an offer or recommendation to buy or sell shares in the fund. You should not act or rely on this document but should seek independent advice and verification in relation to its contents. Sarasin & Partners LLP and/or any other member of Bank J. Safra Sarasin Ltd accepts no liability or responsibility whatsoever for any consequential loss of any kind arising out of the use of this document or any part of its contents. The views expressed in this document are those of Sarasin & Partners LLP and these are subject to change without notice. This document does not explain all the risks involved in investing in the fund and thereforee you should ensure that you read the prospectus and the Key Investor Information document which contain further information including the applicable risk warnings. For your protection, telephone calls may be recorded. Where the data in this document comes partially from third party sources the accuracy, completeness or correctness of the information contained in this publication is not guaranteed, and third party data is provided without any warranties of any kind. Sarasin & Partners LLP shall have no liability in connection with third party data. Persons domiciled in the USA or US nationals are not permitted to hold shares in the fund and shares may not be publicly sold, offered or issued to anyone residing in the USA or to US nationals. This publication is intended for investors in the United Kingdom and Republic of Ireland.. This document can only be distributed or reproduced with permission from Sarasin & Partners LLP. Please contact marketing@sarasin.co.uk. 32

33 Sarasin & Partners LLP Juxon House 100 St. Paul s Churchyard London EC4M 8BU T: +44 (0) F: +44 (0) E: marketing@sarasin.co.uk 33