RESEARCH & INNOVATION in RESPONSIBLE INVESTMENT ANDREAS G. F. HOEPNER
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1 RESEARCH & INNOVATION in RESPONSIBLE INVESTMENT ANDREAS G. F. HOEPNER
2 A personal introduction ANDREAS G. F. HOEPNER Associate Professor of Finance, ICMA Centre, Henley Business School Senior Academic Fellow, PRI Managing Director, Sociovestix Labs Social Enterprise President, ReFine Research Charity Full list of affiliations on LinkedIn
3 Agenda Presentation: Part A: ESG integration into Equities Part B: ESG integration into Fixed Income Appendix: Part C: ESG within Financial Data Science Part D: DynamicESG: Responsible, especially when it matters ESG ~ Environmental, Social and/or Governance information
4 ESG integration into Equities ANDREAS G. F. HOEPNER
5 Some ESG Alpha findings ESG integration strategies can lead to sizable abnormal returns (Alphas): Corporate Governance (Bebchuk et al., 2009, Gompers et al., 2003, 2011) ESG Engagement (Becht et al. 2009) Eco-efficiency (Derwall et al., 2005) Employee Relations (Statman and Glushkov, 2009; Edmans, 2011) Community Relations (Kempf and Osthoff, 2007, Statman and Glushkov, 2009; Borgers et al. 2013) Green Real Estate (Eichholtz, Kok and Quigley, 2010) Best in class strategies (Kempf and Osthoff, 2007; Statman and Glushkov, 2009; Borgers et al. 2013) Successful ESG investment requires specific skills (Gil-Bazo et al., 2009) Financial institutions with more ESG appeal are found to realise better competitive outcome in mortgage and deposit markets (Callado-Muñoz & Utrero-Gonzalez, 2011) have more loyal clients (Bollen, 2007).
6 Integration across ESG criteria Kempf and Osthoff, 2007 The authors analysed the performance of a long-short investment strategy backing the top 5% and shorting the bottom 5% stocks in an ESG criteria over the period 1991 to 2003 for the US market % 7.50% 6.22% 8.70% 7.59% 5.00% 4.29% 4.09% 2.50% 2.54% 0.46% 0.00% -2.50% Community Best-In-Class (BIC) Diversity BIC Employee Relations BIC Environment BIC Human Right BIC -1.13% Product BIC All criteria BIC All criteria BIC with Negative Screening Light and dark blue indicate the 1%, 5% and 10% significance level, respectively. Grey bars represent statistically insignifiicant estimations
7 ESG integration in 10 GICS industries We analysed the performance of investing in the Global 100 most (likely) sustainable companies in the year before (left bar) and after (right bar) the companies from each Global Industry Classification Standard (GICS) industry received the annual award at the World Economic Forum from % 10.80% 9.00% 6.00% 3.00% 7.20% 4.08% 4.92% 3.48% 3.48% 1.80% 0.96% 7.20% 6.96% 6.48% 3.12% 3.84% 9.00% 6.72% 0.00% -3.00% -0.84% -0.72% -2.04% -0.72% -6.00% Consumer Discretionary Consumer Staples -3.84% Energy Financials Health Care Industrials IT Materials Telecom. Services Utilities Light and dark blue indicate the 1%, 5% and 10% significance level, respectively. Grey bars represent statistically insignifiicant estimations [Based on a research project with P.S. Yu]
8 Analysing the materiality of ESG factors Synthetic Portfolio Construction [Based on a research project with M. Rezec]
9 ESG: Barely related to volatility (standard deviation) Sample: FTSE All World (Hoepner, Rezec & Siegl, 2013) [Based on a research project with M. Rezec and S. Siegl]
10 ESG: Reducing Downside Risk Sample: FTSE All World (Hoepner, Rezec & Siegl, 2013) [Based on a research project with M. Rezec and S. Siegl]
11 ESG: Strongly Reducing Extreme Downside Risk Sample: FTSE All World (Hoepner, Rezec & Siegl, 2013) [Based on a research project with M. Rezec and S. Siegl]
12 ESG: Very Strongly Reducing Worst Case Risk Sample: FTSE All World (Hoepner, Rezec & Siegl, 2013) Portfolios rated most responsible (shown in blue) have over 100 basis points lower worst case risk than less responsible portfolios (shown in red). [Based on a research project with M. Rezec and S. Siegl]
13 ESG integration into Fixed Income ANDREAS G. F. HOEPNER
14 ESG, Risk Reduction, and fixed income Companies with high ESG scores are found to have less company specific risk (Bouslah et al., 2012; Boutin-Dufresne and Savaria, 2004; Lee and Faff, 2009; Bauer, Derwall and Hann, 2009; Oikonomou et al., 2012) Corporations with better ESG ratings are found to have lower cost of debt and cost of capital and higher credit ratings (Bauer et al., 2009; Bauer and Hann, 2011; Chava, 2013; Oikonomou et al. 2011) ESG criteria are found to provide an insurance like protection for firms in legitimacy crisis (Godfrey, Merrill and Hansen, 2009)
15 Fixed Income Funds & ESG Engagement Performance influencing characterisitcs 3.00% 2.00% 1.00% Engagement Policy Shareholder Activism Voting Policy Voting Policy: ESG issues Approach: Good Signed PRI 2.55% *** 1.33% *** 1.45% *** 1.21% *** 0.96% *** 1.09% *** 0.00% -1.00% -2.00% -3.00% -1.07% *** -1.19% *** -1.19% *** -0.84% *** -2.02% * -0.96% ** Yes No Difference Study of 122 ESG integrating Fixed Income funds from 17 countries Statistical model explains up to 98.3% of funds return variation ESG engagement related characteristics of asset management firm explain up to 450 basis points performance differential [Based on a research project with M. Nilsson]
16 ESG & Sovereigns: Seeing Greece coming Moodys Fitch S&P Oekom s environmental, social and governance (ESG) sovereign rating sensed deterioration in Greece as sovereign much earlier than the Big 3 [Based on a research project with K.B.H. Bouslah, J.M. Linares-Zegarra and A.L. Neher]
17 ESG: Protection against Portugal ESG sovereign ratings also much earlier warning signals than Moodys and Fitch re Portugal Similar results for Ireland, Italy and Spain [Based on a research project with K.B.H. Bouslah, J.M. Linares-Zegarra and A.L. Neher]
18 ESG & Sovereigns: statistical results for short term sovereign debt CONTROL VARIABLES oekom totalrating (4) 3M, WITH COUNTRY & YEAR DUMMIES (5) 6M, WITH COUNTRY & YEAR DUMMIES (6) 12M, WITH COUNTRY & YEAR DUMMIES * * * GDP p.c. (%) ** * Inflation rate (%) Current Account Balance Rate (%) External Debt (%) * Trade Rate (%) S&P long term, orthogonalised (%) * ** * Constant ** *** * No. observations R-squared Significant relationship between short-, and mediumterm government bond rates and ESGrating Stronger relationship in case of 12Mmatuarity than 3M-, and 6M-matuarity [Based on a research project with K.B.H. Bouslah, J.M. Linares-Zegarra and A.L. Neher]
19 ESG & Sovereigns: statistical results for longer term sovereign debt CONTROL VARIABLES oekom totalrating (7) 3YR, WITH COUNTRY & YEAR DUMMIES (8) 5YR, WITH COUNTRY & YEAR DUMMIES (9) 10YR, WITH COUNTRY & YEAR DUMMIES ** *** *** GDP p.c. (%) *** Inflation rate (%) Current Account Balance Rate (%) External Debt (%) ** Trade Rate (%) * S&P long term, orthogonalised (%) ** *** *** Constant ** *** *** No. observations R-squared Highly significant relationship between long-term government bond rates and ESG-rating Strongest relationship in case of long-term government bond yields [Based on a research project with K.B.H. Bouslah, J.M. Linares-Zegarra and A.L. Neher]
20 Thank you for your attention ANDREAS G. F. HOEPNER Sustainability Advisory Board, Bank J. Safra Sarasin Senior Academic Fellow, PRI Associate Professor of Finance, ICMA Centre, Henley Business School Director, Sociovestix Labs Social Enterprise President, ReFine Research Charity Full list of affiliations on LinkedIn
21 APPENDIX to STATE of ACADEMIC RESEARCH Equities & Fixed Income ANDREAS G. F. HOEPNER
22 ESG within Financial Data Science ANDREAS G. F. HOEPNER
23 Price vs. Return Current tools (i.e. DCF) to find abnormal return opportunities originate from Corporate Finance not Asset Management Returns are often confused with Price: Is there a correct, true firm value, if thousands of market participants are arguing about the market valuation every minute? What is more relevant for the investor? The expected price or the expected change in price? Many ESG factors are hard to monetarise and hence difficult to integrate into Price estimates. They can, however, easily be identified as driver of differential return, as long as firms can be separated on their ESG practices.
24 Uncertainty vs. Risk Current tools (i.e. DCF) to find abnormal return opportunities originate from Corporate Finance not Asset Management Risk is commonly understood as probability of negative events, however: current finance practice defines it commonly as probability of deviation from expectation, downwards and upwards (i.e. standard deviation, tracking error) Firms with more ESG conscious business practices have a lower probability of ESG related negative events but are not necessarily harmed in any positive events Hence: measuring risk accurately as probability of negative events is essential to highlight ESG s competitive advantage in terms of risk adjusted materiality (i.e. semi-standard deviation instead of standard deviation)
25 Is standard deviation always risky? 3.00% 30 day rolling standard deviation 2.50% 2.00% 1.50% 1.00% 0.50% 0.00%
26 How about pure downside deviation? 3.00% 30 day rolling standard deviation / Lower Partial Moment (Benchmark: 0) 2.50% 2.00% 1.50% 1.00% 0.50% 0.00%
27 Return/Risk ratios in Bull vs. Bear markets Low Risk Asset High Risk Asset Bull market Bear market Bull market Bear market Return 3% -3% 3% -3% Risk 1% 1% 10% 10% Sharpe Ratio
28 Detailed background on diversification ANDREAS G. F. HOEPNER
29 The 3 drivers of Portfolio Diversification n n j 1 w 2 j 2 j n n w j i iw j 1 1 i, j i j ij i j i, j i i j Variance term diversified away with number of stocks (1st driver) Covariance matrix crucial (Covariance a,b = Correlation a,b * Standard Deviation a * Standard Deviation b ) Weighted average correlation between assets (2nd driver) Weighted average specific risk of assets (3rd driver) Tradeoff between 2nd & 3rd driver: In a single covariance term, a reduction of the correlation by 10% has the same effect on portfolio risk than reducing the average standard deviation by 5.13%
30 Portfolio Diversification and ESG Criteria: A simple theoretical model (-) Number of Assets in Portfolio (+) Environmental, Social or Governance (ESG) Criteria (+) (-) Weighted Average Correlation of Portfolio s Asset Returns Portfolio Diversification (-) (-) Weighted Average Specific Risk of Portfolio s Assets
31 DynamicESG: Responsible, especially when it matters ANDREAS G. F. HOEPNER
32 Challenge to Status Quo The Corporate Monologue Paradigm: ESG information currently focuses on the behaviour of (listed) corporations It is adjusted to country or industry of the corporations It is updated when corporate behaviour changes though this is challenging to observe at a high frequency It often suffers from self-reporting biases. But isn t there some dialogue between corporations and society? What about societal responsiveness to ESG issues?
33 Challenge to the Status Quo Can societal perceptions change without a change in company behaviour?
34 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Nov-11 Jan-12 Trust in major German savings banks Overall Brand Index (10 days moving average) Commerzbank Sparkasse [Based on a research project with M. Barnett, C. Palstring and Yougov]
35 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Nov-11 Jan-12 Trust in major German savings & commercial banks Overall Brand Index (10 days moving average) Commerzbank Deutsche Bank Volks- und Raiffeisenbank Sparkasse [Based on a research project with M. Barnett, C. Palstring and Yougov]
36 Challenge to the Status Quo Do societal perceptions vary across cultures?
37 Trust in industries by country United States % 80.00% 60.00% 40.00% 20.00% 0.00% Automotive Banks Insurance Mainstream Media [Based on a research project with M. Barnett, I. Timofeeva and Edelmann]
38 Trust in industries by country United States United Kingdom % 80.00% Automotive % 80.00% Automotive 60.00% Banks 60.00% Banks 40.00% 20.00% 0.00% Insurance Mainstream Media 40.00% 20.00% 0.00% Insurance Mainstream Media [Based on a research project with M. Barnett, I. Timofeeva and Edelmann]
39 Trust in industries by country United States United Kingdom % 80.00% Automotive % 80.00% Automotive 60.00% Banks 60.00% Banks 40.00% 20.00% 0.00% Insurance Mainstream Media 40.00% 20.00% 0.00% Insurance Mainstream Media Germany % 80.00% 60.00% 40.00% 20.00% Automotive Banks Insurance Mainstream Media 0.00% [Based on a research project with M. Barnett, I. Timofeeva and Edelmann]
40 Trust in industries by country United States United Kingdom % 80.00% Automotive % 80.00% Automotive 60.00% Banks 60.00% Banks 40.00% 20.00% 0.00% Insurance Mainstream Media 40.00% 20.00% 0.00% Insurance Mainstream Media China Germany % 80.00% 60.00% 40.00% Automotive Banks Insurance % 80.00% 60.00% 40.00% Automotive Banks Insurance 20.00% 0.00% Mainstream Media 20.00% 0.00% Mainstream Media [Based on a research project with M. Barnett, I. Timofeeva and Edelmann]
41 Climate Change Conference [Based on a research project of Sociovestix Labs]
42 Challenger to Status Quo: Dynamic ESG Dynamic ESG recognises the continuous dialogue between corporations and society Therefore, it conditions individual ESG criteria on the relevance which these criteria have within a society (or country) at a certain point in time In other words, Dynamic ESG allows to integrate individual ESG criteria into investment processes especially when and where it really matters Societal relevance can be measured via mainstream media, social media or government preferences
43 Dynamic ESG The case of Chinese A-shares: Over 1,600 firms RepRisk negative news data from thousands of sources Text-mining of about 80,000 Chinese government statements to measure societal relevance Statistical Model explains up to 93.4% of the variation in the return data
44 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Portfolio Value Government Interests Index Societal Relevance of Corporate Governance Government Interests Dynamic ESG [Based on a research project with Q. Li] Please note, the Beijing Olympics took place between August 8 th and 24 th 2014
45 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Portfolio Value Government Interests Index Corporate Governance Index performance & societal relevance Government Interests Anti-ESG ESG [Based on a research project with Q. Li] Please note, the Beijing Olympics took place between August 8 th and 24 th 2014
46 May-07 Jul-07 Sep-07 Nov-07 Jan-08 Mar-08 May-08 Jul-08 Sep-08 Nov-08 Jan-09 Mar-09 May-09 Jul-09 Sep-09 Nov-09 Jan-10 Mar-10 May-10 Jul-10 Sep-10 Nov-10 Jan-11 Mar-11 May-11 Jul-11 Sep-11 Portfolio Value Government Interests Index Corporate Governance Government Interests Dynamic Anti-ESG Anti-ESG ESG Dynamic ESG [Based on a research project with Q. Li] Please note, the Beijing Olympics took place between August 8 th and 24 th 2014
47 Feb-07 Apr-07 Jun-07 Aug-07 Oct-07 Dec-07 Feb-08 Apr-08 Jun-08 Aug-08 Oct-08 Dec-08 Feb-09 Apr-09 Jun-09 Aug-09 Oct-09 Dec-09 Feb-10 Apr-10 Jun-10 Aug-10 Oct-10 Dec-10 Feb-11 Apr-11 Jun-11 Aug-11 Portfolio Value Government Interests Index Corporate Environmental Responsibility Government Interests Dynamic Anti-ESG Anti-ESG ESG Dynamic ESG [Based on a research project with Q. Li]
48 Feb-07 Apr-07 Jun-07 Aug-07 Oct-07 Dec-07 Feb-08 Apr-08 Jun-08 Aug-08 Oct-08 Dec-08 Feb-09 Apr-09 Jun-09 Aug-09 Oct-09 Dec-09 Feb-10 Apr-10 Jun-10 Aug-10 Oct-10 Dec-10 Feb-11 Apr-11 Jun-11 Aug-11 Portfolio Value Government Interests Index Corporate Social Responsibility Government Interests Dynamic 2-Sigma Anti-ESG Dynamic Anti-ESG Anti-ESG ESG Dynamic ESG Dynamic 2-Sigma ESG [Based on a research project with Q. Li]
49 Feb-07 Apr-07 Jun-07 Aug-07 Oct-07 Dec-07 Feb-08 Apr-08 Jun-08 Aug-08 Oct-08 Dec-08 Feb-09 Apr-09 Jun-09 Aug-09 Oct-09 Dec-09 Feb-10 Apr-10 Jun-10 Aug-10 Oct-10 Dec-10 Feb-11 Apr-11 Jun-11 Aug-11 Portfolio Value Government Interests Index 350 Corporate Legal Responsibility Government Interests Dynamic 2-Sigma Anti-ESG Dynamic Anti-ESG Anti-ESG ESG Dynamic ESG Dynamic 2-Sigma ESG [Based on a research project with Q. Li]
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