The EDHEC European ETF and Smart Beta Survey Felix Goltz Head of Applied Research, EDHEC-Risk Institute, and Research Director, ERI Scientific Beta This research has been carried out as part of the Amundi research chair at EDHEC-Risk Institute on ETF, Indexing and Smart Beta Investment Strategies 8 June 2017
Introduction ETF industry has undergone rapid growth since the first European ETF was traded in 2000. Assets under management of the 1,560 ETFs amounted to $552 billion at the end of December 2016 (ETFGI, 2016). Nowadays, growing demand for indices as investment vehicles has led to innovations including new weighting schemes and alternative definitions of sub-segments. European smart beta ETFs AUM reach 27.4 bn at the end of 2016 and accounted for 12% of the total assets (Lyxor, 2017). The aim of the survey is to analyse investor motivations for investing in those products and the issues investors are facing.
Outline The Survey: A Unique Source of Insights How do investors select and use ETFs? What are the key objectives driving smart beta strategies? Future developments
The Survey: A Unique Source of Insights How do investors select and use ETFs? What are the key objectives driving smart beta strategies? Future developments
Potential for Unique Insights (I) Access to differentiated information from investors: The dominant purposes of ETF usage How do investors select ETFs What are the motivations for investing in smart beta strategies How do investors implement smart beta strategies (replication vs discretionary) Do investors have the necessary information to implement smart beta strategies What requirements have investors for selecting factors in factor-based strategies?
Potential for Unique Insights (II) The survey allows obtaining forward-looking information: ETF future growth drivers Growth prospects for smart beta What are investors expectations for further developments for ETF products Expectations on future developments for smart beta products
Scope of the Survey Conducted among investment professionals from December 2016 to February 2017 by online questionnaire The 211 respondents together have at least 3.7 trillions of AUM 1. 61% of respondents have AUM > 1bn 39% of respondents have AUM > 10bn Respondents span 27 European countries 19% are from the UK, 16% from Switzerland, 60% from European Union members and 5% from other countries outside EU. 1. To be compared with a total AUM of 22.8 trillions in Europe at the end of December 2016 (EFAMA, 2017).
Main Activity of Respondents Institution Main focus on institutional investment management
Function of Survey Respondents Main focus on investment decision makers
The Survey: A Unique Source of Insights How do investors select and use ETFs? What are the key objectives driving smart beta strategies? Future developments
Current usage of ETFs Broad market exposure Long-term/buy-and-hold investment Specific sub-segment exposure (sector, style) Short-term/dynamic investment Dominated by passive investment approach Broad market exposure is the main focus Tactical bets Management of cash flows (e.g., cash equitisation) Neutralisation of factor exposures of other investments Dynamic portfolio insurance strategies (e.g., CPPI) Access to tax advantage Arbitrage transactions to benefit from mispricing of other assets relative to the ETF 4% 2% 11% 8% 18% 40% 40% 48% 71% 63% 92% 96% 98% 82% 89% 60% 60% 52% 29% 37% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Frequently Rarely
Preference for broad market exposure Equity Investments Broad market ETFs Sector ETFs Style ETFs Broad market ETFs Market segment ETFs Inflation-protected bond ETFs Broad market ETFs ETFs by credit rating segment Maturity segment ETFs Sector ETFs 35% 55% 95% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Government Bond Investments 57% 52% 82% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Corporate Bond Investments 11% 37% 51% 87% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Satisfaction rates with ETFs 100% 90% 80% 70% 60% 50% 40% 93% 89% 86% 85% 84% 83% 79% 72% 71% 65% 62% 45% 33% 30% 20% 10% 0% High satisfaction with ETFs in traditional asset classes More reserved about ETFs for alternative asset classes
Positive outlook on future use of ETFs 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2006 2008 2009 2010 2011 2012 2013 2014 2015 2016 Increase Stay the same Decrease In 2016, 63% of respondents plan to increase their use of ETFs; 3% plan to decrease it.
Motivations for increasing the use of ETFs 100% 90% 80% 70% 60% 50% 40% 87% 80% 70% 58% 50% 45% 55% 45% 46% 47% 38% 37% 30% 20% 10% 0% Lowering costs in the main motivation for future adoption of ETFs. 7% 3% 1% Costs Performance Liquidity Transparency Non response 2014 2015 2016
80% 70% ETFs as a substitute for active and passive management 74% 64% 64% 68% 60% 50% 40% 42% 49% 30% 20% 10% 0% A substitute to the use of other index products A substitute to the use of active managers Non response 2014 2015 2016 Increasing the use of ETFs will serve not only to replace active managers, but also to replace other passive investing products. 8% 3% 1%
Criteria for selecting ETFs Costs 89% Quality of replication 77% Long-term commitment of the provider Broadness of the range 38% 38% Innovation 24% Complement with active offering of the provider 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Costs and quality of replication are the main criteria to select ETFs.
The Survey: A Unique Source of Insights How do investors select and use ETFs? What are the key objectives driving smart beta strategies? Future developments
Motivations for using smart beta strategies Improve performance 3.67 Manage risk Manage exposure to macro risk factors Lower cost Increase transparency 3.18 3.12 2.80 2.75 Address regulatory constraints 1.59 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 On a scale from 0 (no motivation) to 5 (strong motivation). The quest for outperformance is the main driver for smart beta strategies.
Current use of smart beta strategies My organisation is investing in such products 28% 44% My organisation is considering investment in such products in the near future 29% My organisation is not investing and not considering investment in such products in the near future
Early stage of implementation (I) 80% 70% 67% 60% 50% 40% 30% 20% 10% 0% 23% 3% 6% 1% <20% 20%-40% 40%-60% 60%-80% 80%-100% Two-thirds of respondents invest less than 20% in smart beta strategies. Only 10% invest more than 40% of their total investment in smart beta strategies.
Early stage of implementation (II) 9% 6% Decrease 48% 37% Less than 10% of increase Between 10% and 50% of increase More than 50% of increase 57% of respondents plan an increase of more than 10% of their smart beta investment in terms of assets over the near future. Only 6% plan a decrease.
Discretionary versus replication of smart beta strategies 80% 70% 60% 50% 70% 68% 64% 65% 67% 68% 65% 66% 61% 57% 54% 54% 51% 47% 68% 68% 40% 30% 20% 10% 0% Mitigating possible conflict of interest provider vs. Investor Broadness of the available solutions Costs Transparency of methodology Discretionary smart beta strategies Ease of use as building blocks in portfolio allocation Availability of information for assessing strategies Replication of smart beta strategies Possibility to create alignment with investment beliefs Ease to change portfolio allocation over time The biggest advantage of replicating indices is costs. Slight advantage of discretionary smart beta strategies in terms of breadth of available products and for the possibility to account for specific investment beliefs.
Use of smart beta / factor-based exposure Strategic use to harvest long term premia 3.06 Dynamic use based on variations in factor risk Tactical use based on macro economic regimes Tactical use based on short term return expectations for factors 1.93 1.72 2.18 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 On a scale from 0 (no use) to 5 (highly frequent use). The most frequent use is a strategic use to harvest long term premia. The least frequent use is a tactical use based on short term return expectations for factors.
Information about smart beta strategies 7% 4% 43% 46% Strongly agree Agree Disagree Strongly disagree 89% of respondents declare that smart beta indices require full transparency on methodology and risk analytics
Information regarded as important is not considered to be easily available Long term performance and risk (over 30 years and more) Recent performance and risk (over past 10 years ) Sensitivity of performance to market conditions Transparency on portfolio holdings over backtest period Datamining risk Factor exposures Sensitivity of performance to strategy specification choices Transaction costs Index construction methodology Liquidity and capacity 2.06 2.34 2.58 2.39 2.55 2.95 2.80 3.12 3.07 3.01 2.99 3.14 3.56 3.57 3.59 3.74 3.75 3.84 3.85 4.00 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 Information considered as easily available Information considered to be important for assessing smart beta products On a scale from 0 (difficult to obtain) to 5 (easy to obtain) and on a scale from 0 (not important) to 5 (crucial), respectively.
Gap between investors requirements and accessibility of information Datamining risk 1.53 Liquidity and capacity Sensitivity of performance to strategy specification choices Transparency on portfolio holdings over backtest period Sensitivity of performance to market conditions Transaction costs Factor exposures Index construction methodology Long term performance and risk (over 30 years and more) Recent performance and risk (over past 10 years ) -0.05 1.20 1.20 1.18 0.98 0.85 0.73 0.71 0.61-0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 The gap is computed as the difference between the score of information importance and the score of information accessibility.
Requirements for factors Factor premium should be documented in extensive empirical literature Factor premium should be related to rational risk premium, i.e. explained by a substantial risk that the factor pays off badly in bad times Factors should be easy to implement with low turnover and transaction costs Factors should be straightforward (simple factor definitions) Factors should be related to firm fundamentals Factor premium has been explained as an "anomaly" allowing rational agents to profit from irrationality of others Factors should be related to macroeconomic variables Factors must be orthogonal 3.64 3.61 3.60 3.21 2.81 2.80 2.63 2.53 Factors should be proprietary or novel On a scale from 0 (not important) to 5 (absolutely crucial). 2.01 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00
The Survey: A Unique Source of Insights How do investors select and use ETFs? What are the key objectives driving smart beta strategies? Future developments
Future developments for ETFs Emerging market equity ETFs ETFs based on multi- factor indices ETFs based on smart beta indices ETFs based on single factor indices 34% 33% 33% 33% ETFs based on smart bond indices 30% Actively managed equity ETFs 14% 0% 5% 10% 15% 20% 25% 30% 35% 54% of respondents want further developments in at least one of the three categories of advanced forms of equity indices (single factor, multi-factor, smart beta).
Future developments for smart beta strategies Fixed income smart beta strategies Smart beta strategies in alternative asset classes (currencies, commodities, etc) Solutions addressing specific investor objectives Integration of ESG into smart beta strategies Long/short equity strategies Products offering exposure to novel factors 3.46 3.03 2.84 2.82 2.71 2.65 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 On a scale from 0 (not required) to 5 (strong priority). Further developments are mainly required in the area of fixed income and alternatives.
References EFAMA. 2017. Challenges ahead for the European Fund Industry. ETFGI. 2016. ETFGI monthly newsletter December 2016. Available at www.etfgi.com. Lyxor ETF Research. 2017. European Smart Beta ETF Market Trends. Q4 2016 in brief.