Reasoning in doubt: the singularity of low volatility investing

Transcription

1 Reasoning in doubt: the singularity of low volatility investing Intended for professional clients as defined by the MiFID directive AN EXPERTISE OF

2

3 # 5 Quantitative Research White Papers SEEYOND Seeyond is the structured product and volatility management investment division of Natixis Asset Management. In order to offer investments that combine performance generation with risk reduction, Seeyond applies investment strategies that go beyond conventional active management. In order to turn uncertainty into opportunity, Seeyond develops a complete range of funds in three areas of expertise: structured and active protected management, flexible asset allocation and active volatility management, model-driven global and European equity strategies. The portfolio management team is daily supported by a quantitative research platform. With 31 employees, Seeyond has e14.4 billion in assets under management as of 30/09/

4 Quantitative Research White Papers # 5 CONTENTS Introduction 3 The mispricing of equity risk 4 Does low-volatility investing lead to sector biases? 8 The persistence issue 9 Diversification benefits 10 Conclusion 13 2

5 # 5 Quantitative Research White Papers INTRODUCTION Equity investors have been cognizant for decades of a number of risk factors that help explain the behavior of equity markets. We believe the recent past has drawn out into the light an additional factor that investors should look to integrate into their analysis, which is low volatility. The low-volatility factor runs counter to traditional portfolio theory which stipulates that an investor should be rewarded in proportion with the risk taken. In this paper, we attempt to elucidate equity risk mispricing, continue to comment on whether this is a structural phenomenon, and conclude by explaining how investors may best position themselves in the context of a diversified portfolio. 3

6 Quantitative Research White Papers # 5 THE MISPRICING OF EQUITY RISK Market participants, by and large, expect to be compensated for taking risk. A simplistic analysis shown below supports the claim that riskier asset classes command a higher required return. CHART 1: ANNUALIZED RISK AND RETURN ACROSS ASSET CLASSES 25% 20% 15% 10% 5% 0% Citigroup 1 Month Treas Bill Citi USBIG Treasury/Govt Citi USBIG Corporate Index Citi High-Yield Market Index MSCI USA MSCI USA SMALL CAP Performance Standard deviation Source : Seeyond Observation period: January, 31st 1995 to September, 30th Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. Delving a bit deeper into the equity markets we do not find evidence t hat higher risk necessarily commands a higher return. The chart below separates the global equity market into quintiles of risk and then measures the associated level of return. As observed there is not necessarily a positive relationship between risk and return. CHART 2 - ANNUALIZED RISK AND RETURN FOR LOW RISK STOCKS (QUINTILE 1) VERSUS HIGH RISK STOCKS (QUINTILE 5) 25% 20% 15% 10% 5% 0% Q1 Least Volatile Stocks Q2 Q3 Q4 Q5 Most Volatile Stocks Return Standard deviation Source: Seeyond Observation period: January, 31st 1995 to September, 30th Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. Q1 (lowest quintile) represents low risk stocks based on standard deviation (volatility). Q5 (highest quintile) represents high risk stocks based on volatility. Based on returns of stocks included in the MSCI ACWI NR USD index. Stocks are equal weighted and quintiles are rebalanced on a quarterly basis. 4

7 # 5 Quantitative Research White Papers A positive relationship between risk and return is predicted by the Capital Asset Pricing Model (CAPM), while several empirical studies find the actual relation to be flat or even negative. This pattern known as the low volatility bias is now recognized as a new determinant of the cross section of the stock market return (Ang et al., 2006), specifically in uncertain market environments. Although the empirical evidence of the low volatility factor is largely established in the literature, there appears to be no consensus on the reasons behind it. A wide range of explanations have been proposed 1. For instance, Karceski (2002) ascribes this anomaly to the fact that investors want to outperform the market during bull markets but are more oblivious of their portfolios during bear markets. This therefore increases the irrational demand for so-called high-risk equities. Baker and al. (2011) meanwhile explain that some investors do not take advantage of this anomaly because they do not want to stray too far from capitalization weighted indices due to the constraints imposed by investment policies. In summary, we believe both behavioral biases 2 (lottery effect, overconfidence, representativeness) and structural factors (leverage, risk and return measurement, agency effects) have the potential to provide the basis for such an anomaly. However, as shown in a recent study by Garcia-Feijoo et al (2015), the low-volatility factor may interact with other equity risk-factors, specifically momentum and value which can be considered interacting factors 3 themselves. In order to figure out how the low-volatility factor is linked to other factors, we constructed two hypothetical low-volatility portfolios (hereinafter our hypothetical low-volatility portfolios ), applying the analysis to both the US and European equity markets. Our analysis, summarized in tables 1 and 2, shows the measure of the low-volatility portfolios exposure to other factors 4 over the period from January, 3rd 2000 to October, 1st 2015 based on the average rank of the portfolios stocks according to a criterion of interest (ex: for the dividend factor the ranking criterion is the 12-month trailing dividend yield). 1. See Blitz et al. (2014) for a summary. 2. Lottery effect - preference for small chance of big gain. Overconfidence - Underestimation of margin of error when making forecasts. Representativeness - Tendency to remember success and dismiss failures. 3. See Asness (1997) and Asness, Moskowitz & Pedersen (2009) for further details. 5

8 Quantitative Research White Papers # 5 The figures below measure our hypothetical low-volatility US and European portfolios exposure to other factors. Exposure score is normalized and ranges from 0 to 1. A high score (above 0.5) signifies that the portfolio is concentrated in stocks with high factor value 4. TABLE 1. FACTOR EXPOSURE OF THE HYPOTHETICAL US LOW VOLATILITY PORTFOLIO MEAN MIN MAX DIVIDEND SIZE VALUE QUALITY MOMENTUM Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. The index used is the MSCI US Index. TABLE 2. FACTOR EXPOSURE OF THE HYPOTHETICAL EUROPE LOW VOLATILITY PORTFOLIO MEAN MIN MAX DIVIDEND SIZE VALUE QUALITY MOMENTUM Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. The index used is the MSCI Europe Index. As we can see from the figures in Tables 1 and 2 above, on average, our hypothetical low volatility portfolios are biased towards the dividend factor in the US market, while exposed to size and quality in the European market. However if we consider the range of exposure over the whole sample (i.e. Min and Max figures for both US and Europe), low-volatility stocks can be strongly associated with high/low momentum stocks and high quality and high dividend-paying stocks. 4. Factor construction methodology: Our hypothetical low-volatility portfolios low-volatility portfolios are constructed using equally-weighted stock baskets. Each portfolio is rebalanced quarterly. We narrow our focus to the decile (10%) of stocks with the lowest volatility. We further narrow by removing the quintile (20%) of stocks with the lowest 3-month trading volume. Volatility is estimated using 12-month daily returns. Momentum is based on 12-month stock returns. Value is based on a score combining Price-to-Book, Sales-to-Price and Earning-to-Price ratios. Quality is estimated based on a combination of ROE, 5-year ROE volatility and the Gearing (i.e. debt-to-equity ratio). Dividend yield is computed as the 12-month trailing dividend-to-price ratio. Size is based on the market capitalization. 6

9 # 5 Quantitative Research White Papers The analysis illustrated in charts 3 and 4 below focuses on the evolution of exposures to the dividend and momentum factors. At first sight, there seems to be a strong dividend tilt in our hypothetical low-volatility portfolios, specifically in the US. This link seems to vanish during periods of high economic uncertainty such as the 2009 great recession and 2011 Euro zone debt crisis. Moreover, the relationship to momentum appears to be strongly cyclical, with weak exposure during favorable economic cycles (i.e. potential phases of optimism and high risk-appetite leading to higher demand for high-volatility and strong momentum stocks) and high exposure during economic downturns (i.e. potential phases of pessimism). CHART 3 - HYPOTHETICAL LOW VOLATILITY EXPOSURE TO THE DIVIDEND FACTOR Exposure to Dividends Exposure score US Europe Median CHART 4 - HYPOTHETICAL LOW VOLATILITY EXPOSURE TO THE MOMENTUM FACTOR Exposure to Momentum Exposure score US Europe Median Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. 7

10 Quantitative Research White Papers # 5 DOES LOW-VOLATILITY INVESTING LEAD TO SECTOR BIASES? We believe low-volatility portfolios display time-varying exposure towards other risk factors, which leads to implicit concentration around these factors. Now the question is whether low-volatility investing encompasses sector biases. To address this question we performed the sector exposure analyses represented in charts 5 and 6. The plot figures represent the breakdown of major sector weights within our hypothetical low-volatility portfolios. They mainly show that there are time-varying exposures to some sectors in the US and Europe including financials, utilities and consumer staples. CHART 5 SECTOR EXPOSURE FOR A HYPOTHETICAL US LOW VOLATILITY PORTFOLIO US sector exposure Cumulative weights 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Industrials Cons. Staples Financials Utilities Health Care Cons. Directionnary CHART 6 SECTOR EXPOSURE FOR A HYPOTHETICAL EUROPE LOW VOLATILITY PORTFOLIO Cumulative weights 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2000 Europe sector exposure Industrials Cons. Staples Financials Utilities Health Care Cons. Directionnary Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. 8

11 # 5 Quantitative Research White Papers The analysis reported in charts 7 and 8 aims to separate sector performance contributions from the residual alpha 5 of our hypothetical low volatility portfolios. Sector contributions have a positive contribution to cumulative alpha (almost one third of the alpha is due to this bias on average) specifically in the US. CHART 7 ALPHA OF A HYPOTHETICAL US LOW VOLATILITY PORTFOLIO Cumulative alpha (100 basis) US Low volatility alpha Total Alpha effect Sector effect CHART 8 ALPHA OF A HYPOTHETICAL EUROPE LOW VOLATILITY PORTFOLIO Cumulative alpha (100 basis) Europe Low volatility alpha Total Alpha effect Sector effect Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. THE PERSISTENCE ISSUE One of the major concerns raised by investors with low-volatility stocks is the persistence of the underlying premium in the long run. This problem, sometimes referred to as the crowding dilemma, has fueled a debate. For instance, as pointed out by Baker et al. (2011), the historical persistence of the low-volatility premium results from the tradition of indexing portfolios to benchmarks weighted by market capitalization. This feeds the excessive and irrational demand for high beta stocks and therefore limits the opportunities for investors to arbitrage the volatility anomaly. According to these authors, removing this bias would require a paradigm change in benchmarking policies using cap-weighted indices and, more importantly, an incentive for investors to move away from budgeting risk in relative terms. 5. Alpha is computed as the cumulative residual of an Ordinary Least Squares (OLS)-regression against the specified market indices based on a 260-day rolling window. We use daily returns. These comparisons of alpha are done versus the respective benchmarks, US: MSCI US and Europe: MSCI Europe. 9

12 Quantitative Research White Papers # 5 We believe a base case approach for gauging the crowdedness of the low-volatility premium is to track the relative cheapness of low-volatility stocks. The figures represented in chart 9 illustrate the spread between the value factor exposure scores of our hypothetical low-volatility portfolios and those of the related market at large. The value exposure score is determined as previously described (see footnote 4, pg. 7). The decreasing patterns in both geographical areas (US and Europe) are indicative of an increasing expensiveness of low-volatility stocks since 2000, which could possibly reflect increasing demand for these stocks over the period. However, European low-volatility stocks have become significantly more expensive than the broad market, specifically following years of great crisis, while US low-volatility stocks exhibit almost similar expensiveness as the broad market since the 2008 market collapse. CHART 9 RELATIVE CHEAPNESS OF THE HYPOTHETICAL LOW VOLATILITY PORTFOLIO COMPARED TO THE BROAD MARKET Value exposure score spread 0,5 0,4 0,3 0,2 0,1 0-0,1-0,2-0,3-0,4-0, Europe US Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. These comparisons of relative cheapness are done versus the respective benchmarks, US: MSCI US and Europe: MSCI Europe. DIVERSIFICATION BENEFITS Due to their interesting risk/reward features, we believe low-volatility stocks are worth considering for investors seeking to enhance the risk/return profile of a diversified equity portfolio, or simply to enhance the diversification 6 of a global portfolio. Charts 8 and 9 highlight the potential for low-volatility stocks to improve the risk/return profile of an equity portfolio over a 3-year holding period. The dynamic analysis reported herein shows that the hypothetical low-volatility portfolios (we constructed) may have the potential to exhibit more consistent risk/return profiles compared to the broad market. These portfolios may have the opportunity to lower numbers of negative returns and therefore, reduce the time necessary to recover from losses. We believe, this makes for an attractive trade-off between drawdown size/duration and return. 6. Diversification does not guarantee a profit or protect against a loss. 10

13 # 3 Quantitative Research White Papers Finally, beyond the scope of equity investing, we believe low-volatility strategies could be considered to enhance a globally diversified portfolio. Charts 10 and 11 summarize a static analysis of portfolio risk/return efficiency. CHART 10 RISK AND RETURN OF A HYPOTHETICAL US LOW VOLATILITY PORTFOLIO Year Return Year Volatility Low volatility Broad market CHART 11 RISK AND RETURN OF A HYPOTHETICAL EUROPE LOW VOLATILITY PORTFOLIO Year Return Year Volatility Low volatility Broad market Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. The broad market refers to the respective benchmarks, US: MSCI US and Europe: MSCI Europe We compare several hypothetical portfolios: the first one is represented by P0% and made up of 50% global bonds (T-notes or Bunds) and 50% equities (the respective MSCI market benchmark); and the others labelled P10% to P50% introduce gradually low-volatility stocks up to 50% equities without changing the bond allocation. The first conclusion is that the introduction of low-volatility stocks enhances the risk-reward profile of the portfolio in the sense that it significantly improves the return-to-max drawdown ratio. Let us take the example of the US P50% portfolio which is comprised of 50% T-notes, 50% of US low-volatility stocks. The return-to-max drawdown ratio of this portfolio is 0.58 compared to 0.19 for portfolio P0%, hence an improvement of almost 40 points. Furthermore, low volatility stocks-t-notes mix (P50%) turns out to be more efficient than the Benchmark-Tnotes mix. Indeed, adding T-notes to the low-volatility portfolio labelled LV reduces the max-drawdown (65% contraction) to a greater extent than mixing T-notes and the broad market (54% contraction), which leads in turn to improved diversification. 11

14 Quantitative Research White Papers # 3 CHART 12 DIVERSIFICATION BENEFITS OF A HYPOTHETICAL US LOW VOLATILITY PORTFOLIO 1-year return 12% 10% 8% 6% 4% 2% 0% P0% P10% P20% Max drawdown (R) P30% P40% CAGR (L) P50% Equity market Low volatility Government bonds Max Draw Down CHART 13 DIVERSIFICATION BENEFITS OF A HYPOTHETICAL EUROPE LOW VOLATILITY PORTFOLIO 1-year return 12% 10% 8% 6% 4% 2% 0% P0% P10% P20% Max drawdown (R) P30% P40% CAGR (L) P50% Equity market Low volatility Government bonds Max Draw Down Source: Seeyond All data is based on monthly observations between January, 3rd 2000 and October, 1st Performance data shown represents past performance and is no guarantee of, and not necessarily indicative of, future results. These results are based on classifications that are designed with the benefit of hindsight, are hypothetical in nature, for illustrative purposes and do not represent an actual strategy or portfolio. Please see the disclosure page for additional important information. The broad market refers to the respective benchmarks, US: MSCI US and Europe: MSCI Europe 12

15 # 5 Quantitative Research White Papers CONCLUSION We believe low-volatility stocks exhibit attractive features related to their dynamic interaction with other common risk factors, their sector exposure and their risk-reward profile. Beyond diversification benefits to equity portfolios, low-volatility stocks could potentially supplant other less effective diversification channels within global portfolios specifically when combined with government bonds. The persistence of these features is subject however to persistence of the low-volatility factor in the long run. As pointed out by many authors, a real paradigm change in benchmarking policies using cap-weighted indices and, more importantly, an incentive for investors to move away from budgeting risk in relative terms are required for the low-volatility factor to vanish. We believe such a change in behavior is clearly not on the agenda. Compounded with the impact of investor behavioral biases, the risk premium associated with low-volatility investing looks like more of an equity market feature than an equity market fad. We strongly believe that continuously challenging traditional financial theory may help provide greater insight into the seemingly irrational behavior of equity market participants. As a wise man once said your trust in rationality makes you irrational. 13

16 Quantitative Research White Papers # 5 REFERENCES Ang A., Hodrick R., Xing Y. et Zhang X. (2006), The cross-section of volatility and expected returns, The Journal of Finance, 61, pp ASNESS, C. S. (1997), The interaction of value and momentum strategies. Financial Analyst Journal, 53, ASNESS, C. S., MOSKOWITZ, T. J. and PEDERSEN, L. H. (2009), Value and Momentum Everywhere. The Journal of Finance, 68, Baker M., Bradley B. et Wurgler J. (2011), Benchmarks as limits to arbitrage: understanding the low-volatility anomaly, Financial Analysts Journal, 67, Blitz D., Falkenstein E., and van Vliet P. (2014), Explanations for the Volatility Effect: An Overview Based on the CAPM Assumptions, Journal Of Portfolio Management, 40, Garcia-Feijoo L., Kochard L., Sullivan, R.,N., and Wang P. (2015), Low-volatility cycles: The influence of valuation and Momentum on Low-volatility portfolios, Financial Analysts Journal, 71, Karceski J. (2002), Returns-chasing behaviour, mutual fund and beta s death, The Journal of Financial and Quantitative Analysis, 37, pp

17 # 5 Quantitative Research White Papers NOTES 15

18 Quantitative Research White Papers # 5 DISCLAIMER This document is intended for professional clients only. IMPORTANT INFORMATION All data presented in Tables 1 and 2 and Charts 1 through 13 is related to two hypothetical portfolios that Seeyond created for illustrative purposes. The methodology for all data herein is described in the relative sections. The performance information presented is backtested performance based on combined simulated index data and live equity results for the periods shown, using the strategy of buy and hold and rebalancing quarterly. Back-tested performance is hypothetical and is provided for informational purposes only to indicate historical performance had the hypothetical portfolios been available over the relevant time period. Back-tested performance is calculated using Bloomberg data. The hypothetical back-tested data and performance was derived from the retroactive application of this methodology developed with the benefit of hindsight. There are inherent limitations of the data derived from retroactive application of such methodology. Economic and market factors may impact an adviser s decision-making when actually using such methodology to manage funds. Backtested performance does not reflect the deduction of any advisory or other fees. Performance would be different if such fees were included. The MSCI ACWI, MSCI US and MSCI Europe Indices are free float-adjusted market capitalization weighted indices that are designed to measure the equity market performance of respective markets. Performance data is shown with net dividends. Net total return indices reinvest dividends after the deduction of withholding taxes, using (for international indexes) a tax rate applicable to nonresident institutional investors who do not benefit from double taxation treaties. Neither Natixis AM nor Natixis Global AM provide tax or legal advice. Please consult with a tax or legal professional prior to making any investment decisions. This publication may not be used for any purpose other than that for which it was intended and may not be reproduced, disseminated or disclosed to third parties, whether in part or in whole, without prior written consent from Natixis Asset Management. No information contained in this document may be interpreted as being contractual in any way. This document has been produced purely for informational purposes. It consists of a presentation created and prepared by Natixis Asset Management based on sources it considers to be reliable. Natixis Asset Management reserves the right to modify the information presented in this document at any time without notice. Natixis Asset Management will not be held liable for any decision taken or not taken on the basis of the information in this document, nor for any use that a third party might make of the information. Figures mentioned refer to previous years. Past performance does not guarantee future results. The analyses and opinions referenced herein represent the subjective views of the author(s) as referenced, are as of the date shown and are subject to change. There can be no assurance that developments will transpire as may be forecasted in this material. This material is provided only to investment service providers or other Professional Clients or Qualified Investors and, when required by local regulation, only at their written request. In the EU (ex UK): This material is provided by NGAM S.A. or one of its branch offices listed below. NGAM S.A. is a Luxembourg management company that is authorized by the Commission de Surveillance du Secteur Financier and is incorporated under Luxembourg laws and registered under n. B Registered office of NGAM S.A.: 2, rue Jean Monnet, L-2180 Luxembourg, Grand Duchy of Luxembourg. France: NGAM Distribution (n RCS Paris). Registered office: 21 quai d'austerlitz, Paris. Italy: NGAM S.A., Succursale Italiana (Bank of Italy Register of Italian Asset Management Companies no ). Registered office: Via Larga, , Milan, Italy. Germany: NGAM S.A., Zweigniederlassung Deutschland (Registration number: HRB 88541). Registered office: Im Trutz Frankfurt 55, Westend Carrée, 7. Floor, Frankfurt am Main 60322, Germany. Netherlands: NGAM, Nederlands filiaal (Registration number ). Registered office: World Trade Center Amsterdam, Strawinskylaan 1259, D-Tower, Floor 12, 1077 XX Amsterdam, the Netherlands. Sweden: NGAM, Nordics Filial (Registration number Swedish Companies Registration Office). Registered office: Kungsgatan 48 5tr, Stockholm , Sweden. Spain: NGAM, Sucursal en España. Registered office: Torre Colon II - Plaza Colon, Madrid, Spain. In Switzerland: Provided by NGAM, Switzerland Sàrl, Rue du Vieux Collège 10, 1204 Geneva, Switzerland or its representative office in Zurich, Schweizergasse 6, 8001 Zürich. In the UK: Approved for use by NGAM UK Limited, authorized and regulated by the Financial Conduct Authority (register no ). Registered Office: NGAM UK Limited, One Carter Lane, London, EC4V 5ER. In the DIFC: Distributed in and from the DIFC financial district to Professional Clients only by NGAM Middle East, a branch of NGAM UK Limited, which is regulated by the DFSA. Related financial products or services are only available to persons who have sufficient financial experience and understanding to participate in financial markets within the DIFC, and qualify as Professional Clients as defined by the DFSA. Registered office: Office Level 6, Currency House Tower 2, PO Box , DIFC, Dubai, United Arab Emirates. In Singapore: Provided by NGAM Singapore (name registration no D), a division of Natixis Asset Management Asia Limited (company registration no D). Registered address of NGAM Singapore: 10 Collyer Quay, #14-07/08 Ocean Financial Centre, Singapore In Taiwan: This material is provided by NGAM Securities Investment Consulting Co., Ltd., a Securities Investment Consulting Enterprise regulated by the Financial Supervisory Commission of the R.O.C. Registered address: 16F-1, No. 76, Section 2, Tun Hwa South Road, Taipei, Taiwan, Da-An District, 106 (Ruentex Financial Building I), R.O.C., license number 2012 FSC SICE No. 039, Tel In Japan: Provided by Natixis Asset Management Japan Co., Registration No.: Director-General of the Kanto Local Financial Bureau (kinsho) No Content of Business: The Company conducts discretionary asset management business and investment advisory and agency business as a Financial Instruments Business Operator. Registered address: Uchisaiwaicho, Chiyoda-ku, Tokyo. In Hong Kong: This document is issued by NGAM Hong Kong Limited and is provided solely for general information only and does not constitute a solicitation to buy or an offer to sell any financial products or services. In Australia: This document is issued by NGAM Australia Pty Limited (NGAM Aust) (ABN ) (AFSL No ) and is intended for the general information of financial advisers and wholesale clients only. In New Zealand: This document is intended for the general information of New Zealand wholesale investors only and does not constitute financial advice. This is not a regulated offer for the purposes of the Financial Markets Conduct Act 2013 (FMCA) and is only available to New Zealand investors who have certified that they meet the requirements in the FMCA for wholesale investors. NGAM Australia Pty Limited is not a registered financial service provider in New Zealand. In Latin America: This material is provided by NGAM S.A. In Mexico: This material is provided by NGAM Mexico, S. de R.L. de C.V., which is not a regulated financial entity with the Comisión Nacional Bancaria y de Valores or any other Mexican authority. This material should not be considered an offer of securities or investment advice or any regulated financial activity. Any products, services or investments referred to herein are rendered exclusively outside of Mexico. In Uruguay: This material is provided by NGAM Uruguay S.A., a duly registered investment advisor, authorised and supervised by the Central Bank of Uruguay. Registered office: WTC Luis Alberto de Herrera 1248, Torre 3, Piso 4, Oficina 474, Montevideo, Uruguay, CP In Colombia: This material is provided by NGAM S.A. Oficina de Representación (Colombia) to professional clients for informational purposes only as permitted under Decree 2555 of Any products, services or investments referred to herein are rendered exclusively outside of Colombia. The above referenced entities are business development units of Natixis Global Asset Management, S.A., the holding company of a diverse line-up of specialised investment management and distribution entities worldwide. The investment management subsidiaries of Natixis Global Asset Management conduct any regulated activities only in and from the jurisdictions in which they are licensed or authorised. Their services and the products they manage are not available to all investors in all jurisdictions. In Canada: NGAM Distribution, L.P. ( NGAM Distribution ), with its principal office located in Boston, MA, is not registered in Canada and any dealings with prospective clients or clients in Canada are in reliance upon an exemption from the dealer registration requirement in National Instrument Registration Requirements, Exemptions and Ongoing Registrant Obligations. There may be difficulty enforcing legal rights against NGAM Distribution because it is resident outside of Canada and all or substantially all of its assets may be situated outside of Canada. The agent for service of process in Alberta is Borden Ladner Gervais LLP (Jonathan Doll), located at Centennial Place, East Tower, 1900, 520 3rd Avenue SW, Calgary, Alberta T2P 0R3. The agent for service of process in British Columbia is Borden Ladner Gervais LLP (Jason Brooks), located at 1200 Waterfront Centre, 200 Burrard Street, P.O. Box 48600, Vancouver, BC V7X 1T2. The agent for service of process in Ontario is Borden Ladner Gervais LLP (John E. Hall), located at Scotia Plaza, 40 King St. W, Toronto, ON M5H 3Y4. The agent for service of process in Quebec is Borden Ladner Gervais LLP (Christian Faribault), located at 1000 de La Gauchetiere St. W, Suite 900, Montreal, QC H3B 5H4. In the United States: Provided by NGAM Distribution L.P. 399 Boylston St. Boston, MA Natixis Global Asset Management consists of Natixis Global Asset Management, S.A., NGAM Distribution, L.P., NGAM Advisors, L.P., NGAM S.A., and NGAM S.A. s business development units across the globe, each of which is an affiliate of Natixis Global Asset Management, S.A. The affiliated investment managers and distribution companies are each an affiliate of Natixis Global Asset Management, S.A. This material should not be considered a solicitation to buy or an offer to sell any product or service to any person in any jurisdiction where such activity would be unlawful. Investors should consider the investment objectives, risks and expenses of any investment carefully before investing. Document written on January Natixis Asset Management Limited liability company - Share capital 50,434, Regulated by AMF under no. GP RCS Paris n Registered Office: 21 quai d Austerlitz Paris Cedex 13 Tel Seeyond is a brand of Natixis Asset Management 16

19

20