Management forecasts disclosure quality and market efficiency
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Management Forecasts, Disclosure Quality, and Market Efficiency. Jeffrey Ng, İrem Tuna, and Rodrigo Verdi. What do we do?. We examine short-term and long-term market reaction to management forecasts We test the effect of disclosure quality on the long-term market reaction. Motivation.

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Management forecasts disclosure quality and market efficiency

Management Forecasts, Disclosure Quality, and Market Efficiency

Jeffrey Ng, İrem Tuna, and Rodrigo Verdi


What do we do
What do we do? Efficiency

  • We examine short-term and long-term market reaction to management forecasts

  • We test the effect of disclosure quality on the long-term market reaction


Motivation
Motivation Efficiency

  • There is substantial evidence of market underreaction to news events e.g.,

    • PEAD (Bernard and Thomas, 1989, 1990)

    • Conservatism theory (Barberis et al., 1998)

    • Rational structural uncertainty (Brav and Heaton, 2002)

  • Is there a post-management-forecast drift?

  • Is underreaction to earnings news a function of perceived credibility of the news (e.g., stronger underreaction to good news)?


Motivation1
Motivation Efficiency

  • Management forecasts constitute an interesting setting to study reaction to news because of credibility concerns (voluntary disclosure)

  • Stronger short-term market reaction for bad news forecasts despite no difference in bias (Rogers and Stocken, 2005)

  • Management forecasts allow us to examine whether disclosure quality affects the market reaction to news


Overview of results
Overview of Results Efficiency

Figure 1a – Annual earnings forecasts




Hypothesis i
Hypothesis I Efficiency

  • PEAD literature provides evidence of underreaction to earnings surprises

  • Both conservatism and rational structural uncertainty can explain an underreaction phenomenon

  • We hypothesize that credibility concerns related to management forecasts can exacerbate underreaction to earnings news

    H1: Future stock returns are positively associated with management forecast news


Hypothesis ii
Hypothesis II Efficiency

  • Larger stock price reaction to bad news forecasts than to good news forecasts (e.g., Hutton et al., 2003)

  • Typical explanation is that bad news forecasts are more credible than good news forecasts

  • No difference in the forecast bias between bad news and good news forecasts (Rogers and Stocken, 2005)

    H2: The magnitude of the future returns is larger for firms forecasting good news


Hypothesis iii
Hypothesis III Efficiency

  • Better disclosure may help investors understand the future cash flow implications of an information signal

  • Prior literature provides evidence that better disclosure mitigates the magnitude of market inefficiency

    • PEAD (Francis et al., 2005; Kimbrough, 2005)

    • Accruals anomaly (Richardson et al., 2005; Levi, 2007)

  • H3: The magnitude of the hedge portfolio returns from the PMFD trading strategy is lower for firms whose forecasts are of higher quality.


Sample description
Sample Description Efficiency

  • Follow Anilowski et al. (2007):

    • 17,184 (14,890) forecasts of annual (quarterly) EPS

    • 6,369 (5,859) annual (quarterly) forecasts that do not overlap with earnings announcements

  • Ordinary shares listed on NYSE / AMEX / NASDAQ from 1996 to 2005


Key variables
Key Variables Efficiency

  • Surprise= (Manag. Forec – Analyst Forec) / Price

  • Abnormal returns:

    • Size-adjusted buy-hold returns

    • Size-BM adjusted buy-hold returns

    • Factor alphas (3-factor, 4-factor, 5-factor)

    • Short-term: 3-day around the forecast

    • Long-term: 12-month subsequent to the forecast month


Short and long term reaction
Short- and long-term reaction Efficiency

Return = β0+ β1 Good News + β2 Surprise +

β3 Surprise x Good News

+ ∑ βj Surprise x Controls + ∑ βm Controls + ε

  • Return is either:

    - AbRet3d (3-day return around forecast)

    - AbRet (future 12-month return)

  • Fama-MacBeth regressions with Newey-West corrected standard errors



Hedge portfolio analyses
Hedge Portfolio Analyses Efficiency

  • We sort the observations into quintiles based on the previous year’s distribution of forecast surprises

  • Hedge portfolio strategy:

    • Buy shares of firms in Q5 (extreme good news)

    • Short shares of firms in Q1 (extreme bad news)

  • Abnormal returns:

    • Size-adjusted and size-BM-adjusted buy-hold returns

    • 3-factor, 4-factor, and 5-factor alphas







Conservatism vs structural uncertainty
Conservatism vs. Structural Uncertainty Efficiency

  • Analyst forecast dispersion

    • Proxy for precision of pre-forecast signals

    • Lower dispersion, greater conservatism

  • Intraday return volatility

    • Proxy for the degree of uncertainty generated by the disclosure signal

    • Higher volatility, more structural uncertainty


Research design
Research Design Efficiency

AbRet = β0+ β1 QSurprise +

β2 QSurprise * Dispersion +

β3 QSurprise * Intraday Vol +

β4 Dispersion + β5 Intraday Vol + ∑ βj Risk Controls

  • Prediction: β2 < 0 and β3 > 0

  • AbRet (future 12-month size-adjusted return)

  • Fama-MacBeth regressions with Newey-West corrected standard errors

  • QSurprise is a quintile variable re-scaled from 0 to 1.

  • Dispersion and IntradayVol are dummy variables based on median.



Disclosure quality h3
Disclosure Quality (H3) Efficiency

  • Accuracy = -1*|Earnt-1 – Man Forecastt-1| / Price

  • Precision: Point versus range forecasts

  • Horizon: # of days between forecast and Fiscal-year end


Research design1
Research Design Efficiency

AbRet = β0+ β1 QSurprise +

∑ βi QSurprise * Disclosure Quality +

∑ βj Disclosure Quality + ∑ βm Risk Controls

  • Prediction:

    • βj < 0 for Accuracy

    • βj < 0 for Precision

    • βj > 0 for Horizon

  • QSurprise is a quintile variable re-scaled from 0 to 1.

  • Disclosure Quality are dummy variables based on median.



Pmfd vs pead
PMFD vs. PEAD Efficiency


Summary of findings
Summary of Findings Efficiency

  • The short-term reaction larger for bad news

  • The future long-term reaction is larger for good news

  • A hedge portfolio earns annual abnormal returns above 25%

  • Both analyst forecast dispersion and intraday volatility explain the cross-sectional variation in the PMFD

  • Hedge returns smaller for firms with higher prior forecast accuracy


Implications
Implications Efficiency

  • Significant underreaction to management forecasts.

  • Results consistent with behavioral theories of conservatism (Barberis et al., 1998) and rational structural uncertainty (Brav and Heaton, 2002)

  • Disclosure quality appears to reduce the market underreaction to management forecasts

  • An unresolved question is why the effect is not arbitraged away

    – As Merton (1987) states:

    “…an anomaly must uncovered and learned before one can arbitrage…even when learned, there are limits to arbitrage…”


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