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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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survey and field research in finance miscalibration and corporate actions
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
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 research background1
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 research background2
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 research plan
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 methodology1
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 methodology2
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 methodology3
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 research expectations
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 research expectations1
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 research expectations2
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 research expectations measurement
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 research expectations volatility
Survey and Field ResearchExpectations: Volatility
  • We measure two components of volatility
      • Individual volatility
      • Disagreement among individuals
survey and field research expectations volatility1
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 research expectations volatility determinants persistence of expectations
Survey and Field ResearchExpectations: Volatility determinants –Persistence of expectations
survey and field research expectations volatility determinants persistence of expectations1
Survey and Field ResearchExpectations: Volatility determinants –Persistence of expectations
survey and field research expectations volatility determinants persistence of expectations2
Survey and Field ResearchExpectations: Volatility determinants –Persistence of expectations
slide34
Survey and Field ResearchExpectations: Volatility determinants –Influence of past returns (Individual vol)
slide35
Survey and Field ResearchExpectations: Volatility determinants –Influence of past returns (Disagreement vol)
slide36
Survey and Field ResearchExpectations: Volatility determinants –Influence of past returns (Disagreement vol)
survey and field research expectations volatility determinants fundamentals individual vol
Survey and Field ResearchExpectations: Volatility determinants –Fundamentals (Individual vol)
survey and field research expectations volatility determinants fundamentals disagreement vol
Survey and Field ResearchExpectations: Volatility determinants –Fundamentals (Disagreement vol)
survey and field research expectations volatility determinants fundamentals total vol
Survey and Field ResearchExpectations: Volatility determinants –Fundamentals (Total vol)
survey and field research expectations volatility determinants risk measures individual
Survey and Field ResearchExpectations: Volatility determinants –Risk measures (Individual)
survey and field research expectations volatility determinants risk measures disagreement
Survey and Field ResearchExpectations: Volatility determinants –Risk measures (Disagreement)
survey and field research expectations volatility determinants risk measures total
Survey and Field ResearchExpectations: Volatility determinants –Risk measures (Total)
slide45
Survey and Field ResearchExpectations: Skewness determinants–Influence of past returns (Disagreement skewness)
survey and field research optimism
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
slide74
Survey and Field ResearchOverconfidence
  • In the psychology literature, overconfidence can mean either believing that the distribution of your knowledge is tighter than it actually is or believing that your mean skill is higher than it actually is
    • We will focus on the subjective probability being tighter than true probability following other finance papers such as Odean (1998), Gervais and Odean (2001)
slide75
Survey and Field ResearchOverconfidence:% of time realized returns fall outside 80% confidence range
slide76
Survey and Field ResearchOverconfidence:% of time realized returns fall outside 80% confidence range
slide77
Survey and Field ResearchOverconfidence:Number of standard deviations realized return from forecasts
slide79
Survey and Field ResearchLink to Corporate Actions
  • Corporate decisions
    • IPO/SEO
    • Capital structure
    • Payout policy
    • Investment decisions
    • Mergers/acquisitions
    • Corporate financial reporting
  • Our data is aggregate so we can only study economy-wide variation
survey and field research corporate financial reporting
Survey and Field ResearchCorporate Financial Reporting

Insight on following issues:

  • Importance of reported earnings and earnings benchmarks
  • Are earnings managed? How? Why?
    • Real versus accounting earnings management
    • Does missing consensus indicate deeper problems?
  • Consequences of missing earnings targets
  • Importance of earnings paths
  • Why make voluntary disclosures?
survey and field research strengths and limitations
Survey and Field ResearchStrengths and limitations

Strengths:

  • Surveys enable us to ask decision-makers specific qualitative questions about motivations
  • Less of a variable specification problem
  • Complements large sample analyses
  • A unique angle to confront theories with data

Limitations:

  • Questions may be misunderstood
  • Truthful responses?
  • Non-response bias
  • Friedman (1953)
survey and field research method
Survey and Field ResearchMethod

Survey and Interview Design

  • Draft survey instrument “refereed” by both finance and accounting researchers as well as experts in survey design
  • Interviewed structured to adhere to best scientific practices of interviews, e.g. Sudman and Bradburn (1983)
  • IRB certification for human subject research
survey and field research sample
Survey and Field ResearchSample
  • 401 usable survey responses
    • response rate of 10.4%
      • 25% response rate at a practitioner conference
      • 8% response rate to Internet survey
  • Interview 20 CFOs
    • 40-90 minutes in length
    • More give and take than in the survey
    • Interviewed firms are much larger, more levered and more profitable than the average Compustat firm.
  • Relative to Compustat firms
    • Surveyed firms are larger, more levered, greater dividend-yield, fewer firms report negative earnings
    • Similar B/M and positive P/E
survey and field research sample1
Survey and Field ResearchSample

Firm characteristics (self reported)

  • Agency
    • CEO age, tenure, education
    • Inside ownership
  • Size
    • Revenues
    • Number of employees
  • Growth opportunities
    • P/E
    • Growth in earnings
survey and field research sample2
Survey and Field ResearchSample

Firm characteristics (self reported)

  • Free cash flow effects
    • Profitability
    • Leverage
  • Informational effects
    • Public/private
    • Which stock exchange
  • Industry
  • Credit rating
survey and field research sample3
Survey and Field ResearchSample

Firm characteristics (self reported)

  • Financial reporting practices
    • Number of analysts
    • Do they give “guidance”?
  • Ticker symbol!

Demographic correlations in Table 1

    • Note positive relation between whether you give guidance and number of analysts (Lang and Lundholm TAR 1996)
slide88
Corporate Financial Reporting

Performance measurements

(earnings, cash flows): Sec 3.1,Table 2

Voluntary disclosure

Timing

Sec 6.3

Table 13

Why disclose?

Sec 6.1,Table 11

Earnings

benchmarks

Sec 3.2, Table 3

Earnings trends:

Why not disclose?

Sec 6.2, Table 12

Why meet benchmarks?

Sec 3.3, Table 4

What if miss benchmarks?

Sec 3.4, Table 5

Why smooth earnings?

Sec 5.1, Table 8

How to meet benchmarks:

Sec 4.1, Table 6

Value sacrifice to meet benchmarks:

Sec 4.2, Table 7

Value sacrifice for smooth earnings

Sec 5.2, Table 9

Fig. 1 Flowchart depicting the outline of the paper

slide89
Corporate Financial Reporting

Performance measurements

(earnings, cash flows): Sec 3.1,Table 2

Voluntary disclosure

Timing

Sec 6.3

Table 13

Why disclose?

Sec 6.1,Table 11

Earnings

benchmarks

Sec 3.2, Table 3

Earnings trends:

Why not disclose?

Sec 6.2, Table 12

Why meet benchmarks?

Sec 3.3, Table 4

What if miss benchmarks?

Sec 3.4, Table 5

Why smooth earnings?

Sec 5.1, Table 8

How to meet benchmarks:

Sec 4.1, Table 6

Value sacrifice to meet benchmarks:

Sec 4.2, Table 7

Value sacrifice for smooth earnings

Sec 5.2, Table 9

Fig. 1 Flowchart depicting the outline of the paper

slide90
Graham/Harvey/Rajgopal: Corporate ReportingMotivation

DeGeorge, Patel, Zeckhauser, JB 1999

slide91
Corporate Financial Reporting

Performance measurements

(earnings, cash flows): Sec 3.1,Table 2

Voluntary disclosure

Timing

Sec 6.3

Table 13

Why disclose?

Sec 6.1,Table 11

Earnings

benchmarks

Sec 3.2, Table 3

Earnings trends:

Why not disclose?

Sec 6.2, Table 12

Why meet benchmarks?

Sec 3.3, Table 4

What if miss benchmarks?

Sec 3.4, Table 5

Why smooth earnings?

Sec 5.1, Table 8

How to meet benchmarks:

Sec 4.1, Table 6

Value sacrifice to meet benchmarks:

Sec 4.2, Table 7

Value sacrifice for smooth earnings

Sec 5.2, Table 9

Fig. 1 Flowchart depicting the outline of the paper

slide92
Graham/Harvey/Rajgopal: Corporate ReportingWhy meet earnings benchmarks?

Responses to the statement: “Meeting earnings benchmarks helps …”

based on a survey of 401 financial executives.

slide93
Graham/Harvey/Rajgopal: Corporate ReportingConsequences of missing benchmarks

Responses to the statement: “Failing to meet benchmarks…” based on

a survey of 401 financial executives.

slide94
Graham/Harvey/Rajgopal: Corporate ReportingConsequences of missing benchmarks

Cockroach problem

  • “You have to start with the premise that everyone manages earnings”
  • If you can’t come up with a few cents, there must be some previously unknown serious problems at the firm
  • “If you see one cockroach, you immediately assume there are hundreds behind the walls, even though you have no proof that this is the case”
slide95
Corporate Financial Reporting

Performance measurements

(earnings, cash flows): Sec 3.1,Table 2

Voluntary disclosure

Timing

Sec 6.3

Table 13

Why disclose?

Sec 6.1,Table 11

Earnings

benchmarks

Sec 3.2, Table 3

Earnings trends:

Why not disclose?

Sec 6.2, Table 12

Why meet benchmarks?

Sec 3.3, Table 4

What if miss benchmarks?

Sec 3.4, Table 5

Why smooth earnings?

Sec 5.1, Table 8

How to meet benchmarks:

Sec 4.1, Table 6

Value sacrifice to meet benchmarks:

Sec 4.2, Table 7

Value sacrifice for smooth earnings

Sec 5.2, Table 9

Fig. 1 Flowchart depicting the outline of the paper

slide96
Graham/Harvey/Rajgopal: Corporate ReportingActions taken to meet benchmarks

“Near the end of the quarter, it looks like your company might come in below the desired earnings target. Within what is permitted by GAAP, which of the following choices might your company make?”

slide97
Graham/Harvey/Rajgopal: Corporate ReportingSacrificing long-term value

Hypothetical scenario: Your company’s cost of capital is 12%. Near the end of the quarter, a new opportunity arises that offers a 16% internal rate of return and the same risk as the firm. The analyst consensus EPS estimate is $1.90. What is the probability that your company will pursue this project in each of the following scenarios?

slide98
Graham/Harvey/Rajgopal: Corporate ReportingSacrificing long-term value

Probability of accepting project

slide99
Graham/Harvey/Rajgopal: Corporate ReportingSacrificing long-term value

Only 45% would take the project for sure – even if they are projected

to meet consensus

[Table 7]

slide100
Graham/Harvey/Rajgopal: Corporate ReportingSacrificing long-term value

Reminiscent of Brav, Graham, Harvey and Michaely

  • Sacrifice positive NPV projects before cutting dividends
slide101
Graham/Harvey/Rajgopal: Corporate ReportingOther insights on meeting benchmarks

Interviews

  • 18/20 interview mentioned trade off of short-run earnings and long-term optimal decisions
  • Investment banks offer products that create accounting income with negative cash flow consequences
slide102
Graham/Harvey/Rajgopal: Corporate ReportingOther insights on meeting benchmarks

Guidance

  • Goal of guidance is to meet or exceed consensus every quarter
  • Analysts complicit in game of always meeting or exceeding
  • Large positive surprises lead to “ratchet-up effect”
  • Asymmetric
slide103
Graham/Harvey/Rajgopal: Corporate ReportingOther insights on meeting benchmarks

Break out of the game

  • Why not declare that you will not play the earnings management game?
slide104
Corporate Financial Reporting

Performance measurements

(earnings, cash flows): Sec 3.1,Table 2

Voluntary disclosure

Timing

Sec 6.3

Table 13

Why disclose?

Sec 6.1,Table 11

Earnings

benchmarks

Sec 3.2, Table 3

Earnings trends:

Why not disclose?

Sec 6.2, Table 12

Why meet benchmarks?

Sec 3.3, Table 4

What if miss benchmarks?

Sec 3.4, Table 5

Why smooth earnings?

Sec 5.1, Table 8

How to meet benchmarks:

Sec 4.1, Table 6

Value sacrifice to meet benchmarks:

Sec 4.2, Table 7

Value sacrifice for smooth earnings

Sec 5.2, Table 9

Fig. 1 Flowchart depicting the outline of the paper

slide105
Graham/Harvey/Rajgopal: Corporate ReportingSmoothing

96.9% and 20/20 interviews prefer smooth earnings over more volatile holding cash flows constant

slide106
Graham/Harvey/Rajgopal: Corporate ReportingSmoothing

Responses to the question: “Do the following factors contribute to your

company preferring a smooth earnings path?”

slide107
Graham/Harvey/Rajgopal: Corporate ReportingSmoothing

Reasons

  • Lowers “risk”; increased predictability; lower “risk” premium
  • Clear from survey and interviews that CFOs believe that this risk is priced
  • Possible link to literature on: estimation error, disagreement in asset pricing, information risk premium, and behavioral literature on risk versus uncertainty
slide108
Graham/Harvey/Rajgopal: Corporate ReportingSacrificing value for smoothing

Responses to the question: “How large a sacrifice in value would your firm

make to avoid a bumpy earnings path?”

slide109
Graham/Harvey/Rajgopal: Corporate ReportingOther insights on smoothing

Interviews

  • Volatile earnings will create trading incentives for speculators, hedge funds and legal vultures
  • Volatile earnings mean that you will have a number of misses – which CFOs want to avoid

Smoothing example

slide110
Graham/Harvey/Rajgopal: Corporate ReportingConclusions
  • Consensus earnings factors into decisions
  • Cash secondary to accounting earnings
  • Strong desire to meet benchmarks – cockroach problem
  • It is routine to sacrifice long-term value to meet these benchmarks
  • Meeting benchmarks is important both for the firm’s stock price and managers reputation and mobility
  • Agents optimizing over short-term horizon
slide111
Graham/Harvey/Rajgopal: Corporate ReportingConclusions
  • Having predictable smooth earnings is thought to both reduce the cost of capital and enhance manager reputation
  • Voluntary disclosure is an important tool in manager’s arsenal
  • Disclosure can potentially reduce information risk and enhance a manager’s reputation
slide112
Graham/Harvey/Rajgopal: Corporate ReportingFuture research

Last survey instrument!

  • We are thinking of administering the identical survey before it is published to non-management members of Boards of Directors.

Also…

  • “Detection of Financial Earnings Management”
  • “Detection of Real Earnings Management”

We have the tickers for 107 firms many of which admit to both financial and real earnings management

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