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Earnings Announcements and Price Behavior

Earnings Announcements and Price Behavior. Sam Lim. A Little Background. Information Content of Earnings Announcements Beaver 1968 Landsman and L. Maydew 2002 Abnormal volatility Volatility increases around quarterly earnings announcements Kinney et al 2002

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Earnings Announcements and Price Behavior

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  1. Earnings Announcements and Price Behavior Sam Lim

  2. A Little Background • Information Content of Earnings Announcements • Beaver 1968 • Landsman and L. Maydew 2002 • Abnormal volatility • Volatility increases around quarterly earnings announcements • Kinney et al 2002 • “Surprise” materiality in returns • Most surprises and returns are of same sign, but 43 to 45% of firms’ surprises associated with returns of opposite sign • S-shaped surprise return relation • Use HAR-RV as suggested

  3. Summary of last time • HAR-RV • Earnings surprise factor (percentage) • ( EPSactual - EPSestimate ) / EPSactual * 100 • Split-sign regression • Statistically significant positive findings • Surprise correlated with increase in volatility • Not too surprising.

  4. (continued) • Standardize returns, as suggested by Dr. Tauchen • Return divided by square root of RV • Alison Keane finds weekly RV works relatively better than daily or monthly RV, so I follow suit • Mostly same result–surprise often correlated with overnight returns, but not intraday returns. Previously, had a problem—surprise sometimes correlated with intraday returns. Turns out F-statistic is very low in those cases, so cannot reject null hypothesis that surprise does not determine direction of intraday returns. • Price corrections happen fairly quickly, before market open

  5. Not all firms of same interest • E.g. Goldman Sachs • GS • 32 positive surprises, 3 negative surprises, 1 hits estimate (no surprise). Not very interesting. • Positive surprises positively correlated with volatility at .1% level, positively correlated with overnight returns at 1% level, no correlation with intraday returns. • McDonald’s • 14 positive surprises, 10 negative surprises, 19 hits estimate

  6. McDonald’s • 4/9/1997 to 1/7/2009 • 14 positive, 10 negative, 19 no surprise • Did not account for quarters when firm just hits estimate (SURPRISE=0), so generate dummy variable for earnings release with no surprise. • Generate dummy variables for positive and negative days as well, for comparison purposes. • May be better to do anyway?

  7. MCD • HAR-RV regression, omit RV1, RV5, RV22 for simplicity. • All significant at .1% level • Nice results? Fits with theory that negative news has more impact on the market than positive news. • No surprise days also increase volatility! • Why? • Analyst estimates discounted? • Dispersion of estimates? • Hopefully not, but could also be release of other news on same day.

  8. Another look – Merck, UPS, Pepsi • MRK - 17 positive surprises, 7 negative, 19 no surprises • Positive significant at 5% level, negative and no surprise significant at 1% level • UPS - 19 positive, 5 negative, 9 no surprises • All significant at .1% level • PEP – 24 positive, 8 negative, 11 no surprises • Positive and no surprise significant at .1%, negative at 1% • Though positive coefficient is larger…

  9. Accounting for dispersion? • Account for dispersion in analyst estimates, as suggested by Dr. Bollerslev • The less consensus among analysts, the less information the market has (mean estimate has less informative value) • Interaction term created with standard deviation of analyst estimates • No surprise days (using McDonald’s) • No surprise significant at 5%, dispersion at .1%, interaction at 10%

  10. Dispersion, continued • Makes more sense using absolute value of surprise, but this begs the question of whether I should use the surprise value, or the dummy values. • All statistically significant at .1% level.

  11. Another issue: Sub-sampling

  12. Walmart: Importance of sampling rate • 28 positive, 6 negative, 10 no surprise • Sampled at 15 minutes Positive significant at 5%, no surprise significant at 10% • Sampled at 10 minutes Negative significant at 10% • Problematic?

  13. Further work • Have a list of different S&P 100 firms, is there some systematic pattern to results? Industry? • When looking at returns, picture further complicated. • Do announcements of one firm affect another firm’s stock behavior? • Jumps? • Last time, concluded jumps do not occur in higher frequencies on earnings release dates. Perhaps this is not the case? • IBM – 27.9% jumps (BNS test at 5% level) on earnings release dates, 16.3% other days.. Similar numbers for Intel.

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