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April 15, 2005 Yale University. Survey and Field Research in Finance: Miscalibration and Corporate Actions. Campbell R. Harvey Duke University, Durham, NC USA National Bureau of Economic Research, Cambridge, MA USA. Survey and Field Research Background.
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April 15, 2005 Yale University Survey and Field Research in Finance:Miscalibration and Corporate Actions Campbell R. Harvey Duke University, Durham, NC USA National Bureau of Economic Research, Cambridge, MA USA
Survey and Field ResearchBackground • In 1995, Duke and Financial Executives International make a deal to conduct a quarterly CFO survey • The deal allows for some special ‘academic’ surveys outside of the quarterly survey that would use the FEI e-mail and fax list
Survey and Field ResearchBackground 1. Graham and Harvey conduct a survey on capital structure and project evaluation • “Theory and Practice of Corporate Finance: Evidence from the Field” appears in JFE 2001 2. Brav, Graham, Harvey & Michaely survey on dividend and repurchase policy • “Payout Policy in the 21st Century” forthcoming in JFE 2005
Survey and Field ResearchBackground 3. Graham, Harvey and Rajgopal, survey on corporate financial reporting and disclosure. • “The Economic Implications of Corporate Financial Reporting” 4. Graham and Harvey, quarterly survey on risk premium • “Expectations, Optimism, and Overconfidence”
Survey and Field ResearchPlan • “Methodology” in the true sense of the term • Asset pricing • Measuring expectations (mean, variance, skew), optimism, overconfidence. • Corporate Finance • Understanding corporate financial reporting
Survey and Field Research “Methodology” General goals our research program: • To learn what people say they believe • To examine assumptions • To provide a complement to the usual research methods: archival empirical work and theory
Survey and Field Research“Methodology” Approach sharply contrasts with Friedman’s (1953) “The Methodology of Positive Economics” • Goals of positive science are predictive • Don’t reject theory based on “unrealistic assumptions” • Also, rejects notion that all the predictions of a theory matter to its validity – goal is “narrow predictive success”
Survey and Field Research“Methodology” Alternative view, Daniel Hausman (1992) • “No good way to know what to try when a prediction fails or whether to employ a theory in a new application without judging its assumptions”
Survey and Field ResearchExpectations Key asset pricing theories relate expected returns to “risk” • Expected returns are never observed • Variances and covariances are never observed
Survey and Field ResearchExpectations Many asset pricing theories also postulate the existence of the representative agent, i.e. there is no disagreement • Recent research has made some progress both theoretically (heterogeneous expectations) and empirically (modeling disagreement) • Disagreement proxy of choice is the I/B/E/S standard deviation of analysts’ forecasts
Survey and Field ResearchExpectations Many asset pricing tests rely on a rational expectations argument • Empirical models of expectations • Average returns (unconditional expectations) • Linear projection (conditional expectations) • ARCH/GARCH weighted average of past squared return surprises (which embeds an expectation of the return) • Skewness extremely difficult to measure
Survey and Field ResearchExpectations: Measurement • Survey CFOs every quarter • Q2 2000 through Q1 2005 (20 quarters) • 200+ responses per quarter (4,346 total observations) • We have other data back to Q3 1996 • Why CFOs? • We have access to CFOs • We know from previous surveys and interviews that part of their job is to try to understand both the market and their stock’s performance relative to the market • Should not be biased the way that analyst forecasts might be
Survey and Field ResearchExpectations: Mean Determinants –Persistence of Expectations
Survey and Field ResearchExpectations: Mean Determinants –Persistence of Expectations
Survey and Field ResearchExpectations: Mean Determinants –Extrapolation of Past Returns
Survey and Field ResearchExpectations: Mean Determinants –Extrapolation of Past Returns
Survey and Field ResearchExpectations: Mean Determinants –Extrapolation of Past Returns
Survey and Field ResearchExpectations: Mean Determinants –Expectations of Fundamentals
Survey and Field ResearchExpectations: Mean Determinants –Expectations of Fundamentals
Survey and Field ResearchExpectations: Mean Determinants –Expectations of Risk
Survey and Field ResearchExpectations: Volatility • We measure two components of volatility • Individual volatility • Disagreement among individuals
Survey and Field ResearchExpectations: Volatility • Market volatility Var[r]= E[Var(r|Z)] + Var(E[r|Z]) average vol. + disagreement vol. • Individual volatilities (Davidson and Cooper) Variance = {[r(0.90) - r(0.10)]/2.65}2
Survey and Field ResearchExpectations: Disagreement Volatility
Survey and Field ResearchExpectations: Individual Volatility
Survey and Field ResearchExpectations: Volatility determinants –Persistence of expectations
Survey and Field ResearchExpectations: Volatility determinants –Persistence of expectations
Survey and Field ResearchExpectations: Volatility determinants –Persistence of expectations
Survey and Field ResearchExpectations: Volatility determinants –Influence of past returns (Individual vol)
Survey and Field ResearchExpectations: Volatility determinants –Influence of past returns (Disagreement vol)
Survey and Field ResearchExpectations: Volatility determinants –Influence of past returns (Disagreement vol)
Survey and Field ResearchExpectations: Volatility determinants –Fundamentals (Individual vol)
Survey and Field ResearchExpectations: Volatility determinants –Fundamentals (Disagreement vol)
Survey and Field ResearchExpectations: Volatility determinants –Fundamentals (Total vol)
Survey and Field ResearchExpectations: Volatility determinants –Risk measures (Individual)
Survey and Field ResearchExpectations: Volatility determinants –Risk measures (Disagreement)
Survey and Field ResearchExpectations: Volatility determinants –Risk measures (Total)
Survey and Field ResearchExpectations: Disagreement Skewness
Survey and Field ResearchExpectations: Skewness determinants–Influence of past returns (Disagreement skewness)
Survey and Field ResearchOptimism • Will be measured as the mean difference between the expected returns and the realized returns • Notice that we have no way to calibrate the quality of the expected returns – given the “true” expected return is unobservable • We can only make inference about forecasting ability
Survey and Field ResearchOptimism Returns forecasting ability
Survey and Field ResearchOptimism Returns bias (Average=10% per annum)