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DEPARTMENT OF MANAGEMENT ENGINEERING 1 Copyright Daniela Laurel 2011 Socially Responsible Investments in Europe: the effects of screening on risk and the clusters in the fund space DANIELA LAUREL
DEPARTMENT OF MANAGEMENT ENGINEERING 2 Copyright Daniela Laurel 2011 Introduction INTRODUCTION SRI is a must to be able to remain competitive in the capital markets Pension fund requirements HNWI driving the Asset Management industry Consumer trends for sustainable products driving the mutual fund industry Increasing concern for Corporate Social Responsibility among both private and institutional investors Positive performance, particularly evident during the recent crisis SRI is now mainstream rather than niche In Europe, worth €5 trillion at the end of 2009 (85% growth since 2007)* Represents 10% of the total asset management industry in Europe SRI funds were more resilient during the recent financial crisis Institutional Investors represent 92% of all SRI in Europe. *Eurosif, 2010
DEPARTMENT OF MANAGEMENT ENGINEERING 3 Copyright Daniela Laurel 2011 Research Objectives Previous research focus: – Are investors interested in non-financial issues? – Comparison of SRI vs. non-SRI performance RESEARCH OBJECTIVES To determine the effects of screening criteria on returns and risk Fund managers can better understand what screening intensity to use Fund managers can better select which screening criteria to implement To determine the clusters in the current European fund space Identify the dominant strategies in the SRI universe Managerial implications Firms can understand how ESG and CBI practices are rewarded or penalized by the financial markets
DEPARTMENT OF MANAGEMENT ENGINEERING 4 Copyright Daniela Laurel 2011 Key Literature (1/2) The SRI performance debate: “Morals matter but there must be a business case.” (Lewis and Juravle, 2009) The “underperformance hypothesis”: SRI funds suffer a financial loss as compared to non-SRI funds Expected Utility Theory: there is a trade-off between altruistic or ethical behavior and the material well-being of an individual (Smith, 1776) Agency Theory (Jensen and Meckling, 1976); Contract Theory (Bolton and Dewatripont, 2005; Tirole, 2003); Portfolio Theory (Markowitz, 1952) CSR detracts from the bottomline (Friedman, 1970, etc.) SRI funds will underperform due to higher research tasks and additional monitoring
DEPARTMENT OF MANAGEMENT ENGINEERING 5 Copyright Daniela Laurel 2011 Key Literature (2/2) The “overperformance hypothesis”: SRI funds perform better in the long-term as compared to traditional funds. Behavioral Economics and non-financial motives for investment (e.g. Bounded Rationality (Simon, 1955; 1957); Prospect Theory (Kahneman and Tversky, 1979, 1981, 1984); Gao and Schmidt, 2005; Beal et. Al, 2005, etc.) Stakeholder Theory (Freeman et. Al, 2010; Donaldson and Preston, 1995, etc.) Relationship between CSP and CFP: “The virtuous cycle” (Orlitzky et. Al, 2003, etc.) Because of higher monitoring, SRI fund managers have information unavailable to others which will allow them to manage risks better and take better investment decisions. (Renneboog et. al, 2008a) The result of the empirical work is unsurprisingly a neutral one. The two effects generally cancel each other out.
DEPARTMENT OF MANAGEMENT ENGINEERING 6 Copyright Daniela Laurel 2011 Hypotheses (1/3) Barnet and Salomon, 2006 -Find a curvilinear (U-shaped) effect between number of SRI screens and risk- adjusted returns -Using least amount of screens is positive for return -Returns decrease with screening intensity as more good performing assets were eliminated from the investable universe -With increasing screening intensity, the over-performance hypothesis is realized Hypothesis 1: Screening intensity will have a curvilinear (U-shaped) effect on returns.
DEPARTMENT OF MANAGEMENT ENGINEERING 7 Copyright Daniela Laurel 2011 Hypotheses (2/3) Extension to risk: -Risk will be lower for funds with the least amount of screens -The risk will increase as more screens are added -As the fund screens at maximum intensity, new benefits come into play which reduces risk again (stickiness of SRI assets and informational benefits of SRI) Hypothesis 2: Screening intensity will have a curvilinear (inverted U-shaped) effect on risk.
DEPARTMENT OF MANAGEMENT ENGINEERING 8 Copyright Daniela Laurel 2011 Hypotheses (3/3) -Positive relationship between Corporate Governance and return (Gompers et. Al, 2003; Brown and Caylor, 2006; Cremers and Nair, 2005) -“Sin stocks” outperform other stocks (Hong and Kacpercyzk, 2009) Hypothesis 3a: Screening for Corporate Governance will have a positive effect on performance. Hypothesis 3b: Screening for Controversial Business Involvement will have a negative effect on performance.
DEPARTMENT OF MANAGEMENT ENGINEERING 9 Copyright Daniela Laurel 2011 Dataset and Methodology (1/2) 529 SRFs domiciled in Europe (EUROSIF) Final unbalanced panel of 226 funds 24 Screening criteria (Avanzi) Current information (fund structure, domicile, fund age, sector, geography, and securities splits) as of February 2011 (Morningstar) Historical data: Monthly fund returns and Monthly Net Asset Values from the inception date of the oldest fund on April 1980 to February 2011 (Morningstar) Total number of observations for monthly fund returns is 31,083
DEPARTMENT OF MANAGEMENT ENGINEERING 10 Copyright Daniela Laurel 2011 Number of SRI funds per year (sample)
DEPARTMENT OF MANAGEMENT ENGINEERING 11 Copyright Daniela Laurel 2011 Dataset and Methodology (2/2) DEPENDENT VARIABLES Risk-Adjusted Performance (RAP) using CAPM methodology (Sharpe, 1968) Standard deviation of RAP Annualized for 3 years (2008-2010) “crisis period”, 5 years (2006-2010) “medium-term”, and 10 years (2001-2010) “long-term” INDEPENDENT VARIABLES Screening intensity: number of screens from 1-24 Individual and grouped screens (Environmental, Social, Governance, and Controversial Business Involvement) CONTROL VARIABLES Fund age, Fund size, Geographic split, Sector split, Securities split METHODOLOGY: OLS Regression using Stata
DEPARTMENT OF MANAGEMENT ENGINEERING 12 Copyright Daniela Laurel 2011 Screening Criteria
DEPARTMENT OF MANAGEMENT ENGINEERING 13 Copyright Daniela Laurel 2011 Regression Model (1/2) Screening intensity on financial performance (Model 1): RAP it (3, 5, 10 year) = α + β 1* si it + β 2 *F_age it + β 3 *znav it + β 4 *Geo_splitEUR it + β 5 *Sect_info it + β 6 *Sect_serv it + β 7 *Secu_split1 it + ε it Screening intensity on financial performance (Model 2): RAP it (3, 5, 10 year) = α + β 1* si it + β 2 si 2 it + β 3 *F_age it + β 4 *znav it + β 5 *Geo_splitEUR it + β 6 *Sect_info it + β 7 *Sect_serv it + β 8 *Secu_split1 it + ε it Screening intensity on financial risk (Model 1): SD it (3, 5, 10 year) = α + β 1* si it + β 2 *F_age it + β 3 *znav it + β 4 *Geo_splitEUR it + β 5 *Sect_info it + β 6 *Sect_serv it + β 7 *Secu_split1 it + ε it Screening intensity on financial risk (Model 2): SD it (3, 5, 10 year) = α + β 1* si it + β 2 si 2 it + β 3 *F_age it + β 4 *znav it + β 5 *Geo_splitEUR it + β 6 *Sect_info it + β 7 *Sect_serv it + β 8 *Secu_split1 it + ε it
DEPARTMENT OF MANAGEMENT ENGINEERING 14 Copyright Daniela Laurel 2011 Regression Model (2/2) Individual screening criteria on financial return (Model 1): RAP it (3, 5, 10 year) = α + β 1 *F_age it + β 2 *znav it + β 3 *Geo_splitEUR it + β 4 *Sect_info it + β 5 *Sect_serv it + β 6 *Secu_split1 it + β 7 *env_t2 it + β 8 *soc_t2 + β 9 *gov_t2 it + β 3 *cbi_t2 it + ε it Individual screening criteria on financial return (Model 2): RAP it (3, 5, 10 year) = α + β 1 *F_age it + β 2 *znav it + β 3 *Geo_splitEUR it + β 4 *Sect_info it + β 5 *Sect_serv it + β 6 *Secu_split1 it + β 7 *env_tot it + β 8 *soc_tot + β 9 *gov_tot it + β 3 *cbi_tot it + ε it Individual screening criteria on financial risk: SD it (3, 5, 10 year) = α + β 1 *F_age it + β 2 *znav it + β 3 *Geo_splitEUR it + β 4 *Sect_info it + β 5 *Sect_serv it + β 6 *Secu_split1 it + β 7 *env1 it + β 8 *env2 it + β 9 *env3 it + β 10 *env4 it + β 11 *soc1 it + β 12 *soc2 it + β 13 * soc3 it + β 14 *soc4 it + β 15 *soc5 it + β 16 *soc6 it + β 17 *gov1 it + β 18 *gov2 it + β 19 *gov3 it + β 20 *cbi1 it + β 21 *cbi2 it + β 22 *cbi3 it + β 23 *cbi4 it + β 24 *cbi5 it + β 25 *cbi6 it + β 26 *cbi7 it + β 27 *cbi8 it + β 28 *cbi9 it + β 29 *cbi10 it + β 30 *cbi11+ ε it
DEPARTMENT OF MANAGEMENT ENGINEERING 15 Copyright Daniela Laurel 2011 Results and Discussion (1/5) EFFECT OF SCREENING INTENSITY (SI) ON FINANCIAL PERFORMANCE REJECT H1: SI will have a curvilinear (U-shaped) effect on returns. Screening Intensity: No relationship between Screening Intensity and financial performance, neither linear nor curvilinear. Fund age: older funds performed worse than the newer funds in the long-term Fund size: positive size effect increases in significance with longer time period Geography: long-term performance positive for funds invested mostly in Europe Sector: Services sector performed consistently bad Securities: stocks has a significantly negative effect on performance and this effect was much stronger during the crisis period
DEPARTMENT OF MANAGEMENT ENGINEERING 16 Copyright Daniela Laurel 2011 Results and Discussion (2/5) EFFECT OF SCREENING INTENSITY ON FINANCIAL RISK ACCEPT H2: SI will have a curvilinear (inverted U-shaped) effect on risk Individual Screening Intensity (si) and Screening Intensity squared (si 2 ) variables are significant at a 90% confidence level INDIVIDUAL SCREENING CRITERIA EFFECTS ON FINANCIAL RETURN ACCEPT H3a: Screening for Corporate Governance will have a positive effect on performance Finding only for the crisis period ACCEPT H3b: Screening for CBI will have a negative effect on performance Finding only for the long-term period
DEPARTMENT OF MANAGEMENT ENGINEERING 17 Copyright Daniela Laurel 2011 Results and Discussion (3/5) CURVILINEAR EFFECT OF SCREENING INTENSITY ON RISK FOR 3Y AND 5Y PERIODS
DEPARTMENT OF MANAGEMENT ENGINEERING 18 Copyright Daniela Laurel 2011 Results and Discussion (4/5) CURVILINEAR EFFECT OF SCREENING INTENSITY ON RISK FOR 10Y PERIOD
DEPARTMENT OF MANAGEMENT ENGINEERING 19 Copyright Daniela Laurel 2011 Results and Discussion (5/5) ADDITIONAL ANALYSIS: CLUSTERS IN THE EUROPEAN FUND SPACE SRI FUND CLUSTERS IN EUROPE
DEPARTMENT OF MANAGEMENT ENGINEERING 20 Copyright Daniela Laurel 2011 Conclusions and Implications Number of screens implemented by the fund has no significant effect on performance but has a curvilinear “inverted U-shaped” effect on risk Low screening = low risk (diversification) Medium screening = high risk (no benefits) High screening = low risk (informational benefits) Highly screened SRI investments could represent an "insurance" investment during periods of crises due to its lower volatility The market recognizes the following: Good environmental practices = less risky Good Corporate Governance = rewarded during periods of crises Screening on CBI = negative for performance in the long-term At least one Social Screen = increases risk during all time periods European SRI universe can be grouped into 6 clusters based on investment styles
DEPARTMENT OF MANAGEMENT ENGINEERING 21 Copyright Daniela Laurel 2011 Socially Responsible Investments in Europe: the effects of screening on risk and the clusters in the fund space DANIELA LAUREL
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