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 “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

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.

(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

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

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?

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.

RVt Positive Negative No surprise

Coefficient 3.13 4.23 2.12

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…

RVt Positive Negative No surprise

Coefficient 1.06 2.58 1.24

RVt Positive Negative No surprise

Coefficient 2.04 3.54 3.09

RVt Positive Negative No surprise

Coefficient 2.03 1.83 3.45

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%

RVt No surprise

Dispersion

Interaction

Coefficient 1.97 201.5 -183.8

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.

RVt |SURPRISE|

Dispersion

Interaction

Coefficient 1.03 284.35 -103.82

Another issue: Sub-sampling

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?

RVt Positive Negative No surprise

Coefficient 1.03 Not significant

1.24

RVt Positive Negative No surprise

Coefficient Not significant

1.66 Not significant

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.