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Are Swiss Pension Fund Managers overconfident?

Are Swiss Pension Fund Managers overconfident?. Christoph Gort, Mei Wang, Michael Siegrist Target Journal:Journal of Behavioral Finance March 26, 2007. Agenda. Introduction Hypotheses Sample and questionnaire Are Swiss pension fund managers miscalibrated?

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Are Swiss Pension Fund Managers overconfident?

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  1. Are Swiss Pension Fund Managers overconfident? Christoph Gort, Mei Wang, Michael Siegrist Target Journal:Journal of Behavioral Finance March 26, 2007

  2. Agenda • Introduction • Hypotheses • Sample and questionnaire • Are Swiss pension fund managers miscalibrated? • Individual characteristics and miscalibration • Conclusions • Facts about pension plan investments • Policy Implications University of Zurich, March 26, 2007

  3. Introduction 1-2 • Students and private investors are overconfident (Odean (1998)) but what about managers of Swiss pension plans? • Overconfidence in the domain of financial markets • Facets of overconfidence (see Glaser and Weber (2003)) • Miscalibration • Better-than-average-effect • Illusion of Control • Overoptimism • Focus on differences across individuals. Evidence on miscalibration on average provides not enough information University of Zurich, March 26, 2007

  4. Introduction 2-2 • Impacts of overconfidence • Underestimation of risk (De Long et al (1991)) • Increased risk taking after success (Gervais and Odean (2001)) • Lower expected utility but higher risks in theoretical models (De Long et al (1991)) • Lower performance on financial markets (Odean (1999)) • Lower performance on experimental markets (Biais et al (2002)) • Over- and underreaction to news in the market (Daniel et al (1998)) • Higher trading volumes (Barber and Odean (2001)) • More active management despite unsuccessful track record (Lakonishok et al (1992)) University of Zurich, March 26, 2007

  5. Hypotheses • Practitioners of Swiss pension funds are miscalibrated... • They provide too narrow confidence intervals for estimates of historical returns • as well as for return forecasts on financial markets • ...more overconfident than a convenience sample • Individual characteristics determine overconfidence • Education (4 categories) • Experience (3 categories) • Age • … University of Zurich, March 26, 2007

  6. Sample • Professional sample with practitioners in Swiss pension funds • 108 professionals • Response rate of 22.6% • Managers and investment committee members • Large differences across educations, experiences and ages • Not enough data to study gender differences • Laymen sample with employees from the City of Zurich • 104 participants • Response rate not available • Pretty heterogenous sample University of Zurich, March 26, 2007

  7. Questionnaire • Tasks in questionnaire • Individual characteristics • 90% confidence intervals for return forecasts in different asset classes. Upper and lower boundaries • 90% confidence intervals for historical annual returns in different asset classes. Upper and lower boundaries • Roughly 20 minutes to complete (too long) • Surveymonkey and hardcopies to distribute questionnaire • Roughly 3 months of data collection • SPSS 13 for data analysis University of Zurich, March 26, 2007

  8. Evidence for historical return confidence intervals University of Zurich, March 26, 2007

  9. Evidence for future return confidence intervals University of Zurich, March 26, 2007

  10. Key findings from 90% confidence intervals • Intervals for historical returns are too narrow • Not 90% but only about 70% are included • Underestimation of upside as well as downside • Intervals for future returns are even narrower • Very low implied volatility • Well informed about relative risks of asset classes • Laymen are more miscalibrated than Swiss pension plan managers University of Zurich, March 26, 2007

  11. Individual characteristics and miscalibration 1-3 University of Zurich, March 26, 2007

  12. Individual characteristics and miscalibration 2-3 University of Zurich, March 26, 2007

  13. Individual characteristics and miscalibration 3-3 • Key findings • Education from university (especially general) reduces miscalibration • More experience reduces miscalibration • Age increases miscalibration • Financial education from university is related to more accurate confidence intervals • Level of significance varies across the different asset classes and across the professional and the laymen samples but the effects are all in line with each other University of Zurich, March 26, 2007

  14. Conclusions • The practitioners of Swiss pension funds are miscalibrated • Laymen are more miscalibrated than professionals of Swiss pension plans • Miscalibration is pretty stable across individuals in different estimation and forecasting tasks • Miscalibration is (partly) determined by individual characteristics like education, experience and age • Younger people with an education from university and also some experience finance are the least miscalibrated University of Zurich, March 26, 2007

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