Post on 19-Oct-2020
Earnings Autocorrelation and the Post-Earnings-Announcement Drift
Josef Finka, Stefan Palana, and Erik Theissenb,a
a Department of Banking and Finance, University of Graz b Business School, University of Mannheim
Austrian Working Group on Banking and Finance | University of Liechtenstein | November 22, 2019
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 1
Eugene Fama
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 1
Eugene Fama Image source: Nyman, B., 2013, accessed : 17.10.2019, https://commons.wikimedia.org/wiki/File:Eugene_Fama_at_Nobel_Prize,_2013.jpg.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 1
Eugene Fama Image source: Nyman, B., 2013, accessed : 17.10.2019, https://commons.wikimedia.org/wiki/File:Eugene_Fama_at_Nobel_Prize,_2013.jpg.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 1
Eugene Fama Image source: Nyman, B., 2013, accessed : 17.10.2019, https://commons.wikimedia.org/wiki/File:Eugene_Fama_at_Nobel_Prize,_2013.jpg.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 1
Eugene Fama Image source: Nyman, B., 2013, accessed : 17.10.2019, https://commons.wikimedia.org/wiki/File:Eugene_Fama_at_Nobel_Prize,_2013.jpg.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 2
Motivation
Ball and Brown (1968):
− Prices drift upward after positive and downward
after negative earnings surprises
− Long duration: up to one year
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 3
View in the literature
− Risk-based explanations cannot explain PEAD (Ball, Kothari and Watts, 1993; Kim and Kim, 2003)
− Multifactor models cannot explain PEAD (Sadka, 2006; Francis et al., 2007; Chordia et al., 2009; Hou, Xue and Zhang,
2015)
− Majority view: PEAD is a mispricing phenomenon (Fama, 1998; Richardson, Tuna and Wysocki, 2010; Hung, Li and
Wang, 2015)
− Economic significance: institutional investors exploit PEAD, earning 22% mean annualized
excess return (Ke and Ramalingegowda, 2005)
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 4
Potential causes
− Misspecified model for forecasting earnings (Bernard and Thomas, 1989; Freeman and Tse, 1989; Bernard and
Thomas, 1990)
− Inattention (Hou, Peng and Xiong, 2009; Hung, Li and Wang, 2015), possibly joint with firm size (Foster, 1977; Bernard
and Thomas, 1989; Bathke et al., 2014)
− Positive serial correlation in quarterly earnings (Bernard and Thomas, 1989; Bernard and Thomas, 1990; Rendleman,
Jones and Latane, 1987; Ball and Bartov, 1996; Rangan and Sloan, 1998; Battalio and Mendenhall, 2005; Bathke, Lorek and Lee Willinger, 2006;
Bathke et al., 2014; Chang et al., 2017; Chung and Hrazdil, 2011)
− Frictions prevent arbitrage (Bernard and Thomas, 1989; Ball, 1992; Ravi Bhushan, 1994; Mendenhall, 2004; Sadka, 2006; Cohen
et al., 2007; Ng, Rusticus and Verdi, 2008; Chordia et al., 2009; Chung and Hrazdil, 2011)
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 5
Contribution
− First study in the experimental lab
− Full control over fundamental value, information, risk, timing …
− Ceterus paribus test of the role of earnings autocorrelation
− Focus on behavioral biases, ruling out confounds
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 6
Experimental design: Markets
− Two firms/stocks: A and B
− Simultaneous continuous double auction markets following NASDAQ rules
(z-Tree, GIMS; Fischbacher, 2007; Palan, 2015)
− Endowments: 900 talers plus 9 shares of A or B
− Short-selling of 9 shares and buying on margin of 900 talers possible
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 7
Experimental design: Assets
− Initially expected earnings per share: 𝐸 = 5 talers, corresponding to 𝐹𝑉0 = 100 talers
− In each announcement, earnings change by Δ𝐸 ∈ {δ− = −0.5, δ+ = 0.5}
− Earnings of firms A and B are perfectly negatively correlated
− Equal numbers of firm A and B shares in the market ⇒ no aggregate risk
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 8
Experimental design: Period structure
− 4 trading periods à 900s
− First earnings announcement
180s after period start
− Consecutive announcements every 180s
− Final announcement at period close
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 9
Treatment BASE
− All transition probabilities equal 0.5
− No earnings autocorrelation: 𝑅Δ𝐸,Δ𝐸𝐵𝑎𝑠𝑒 (𝜏 − 1, 𝜏) = 0
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 10
Treatment CORR
− Positive earnings autocorrelation:
𝑅Δ𝐸,Δ𝐸𝐶𝑜𝑟𝑟 (τ − 1, τ) = 0.5
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 11
Further design details
− Subjects are business and economics students
− 8 (of 10) sessions of BASE, 8 (of 15) sessions of CORR
− 12 traders per session, 190* (298) in total
− Average payoff: €24.90 (sd €3.64)
* Two of the original 16 sessions had only 11 instead of 12 traders due to no-shows.
Results
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 12
Evidence on Post-Earnings-Announcement Drift
− Log return relative to bid-ask midpoint at the
time of the earnings announcement
− Points indicate ending value of 10s windows
− First 10s constitute announcement window
− Dashed lines indicate return levels reached by
the end of the announcement window
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 13
Evidence on Post-Earnings-Announcement Drift
− Separate data for treatments
BASE and CORR
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 14
Evidence on Post-Earnings-Announcement Drift
− Data only from treatment CORR
− Surprise: sign of earnings
change switches compared to
preceding announcement
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 15
Paper returns to PEAD investment
− Mean returns from end of announcement window until end of phase (t-statistics in
parentheses)
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 16
Interim conclusions
− Result 1. There is PEAD following both positive and negative earnings news.
− Result 2. There is PEAD when earnings are not autocorrelated, but PEAD is larger with
autocorrelation.
− Result 3. Announcements of unexpected earnings news are followed by significantly
greater PEAD than announcements confirming expectations.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 17
Trading strategies
Strategy
Following an announcement with
positive earnings news, submit a
limit buy order priced at the bid-ask
price midpoint. If this order gets
executed, hold the position until the
end of the period and earn FV for
each share held. Following an
announcement with negative
earnings news, do the opposite.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 17
Trading strategies
Strategy
Following an announcement with
positive earnings news, submit a
limit buy order priced at the bid-ask
price midpoint. If this order gets
executed, hold the position until the
end of the period and earn FV for
each share held. Following an
announcement with negative
earnings news, do the opposite.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 18
Interim conclusions
− Result 4. There are trading strategies which can profitably exploit the observed PEAD,
net of transaction costs.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 19
Price adjustment
− Percentage adjustment of closing bid-ask midpoint
prices from pre-announcement price levels to pre-
announcement price levels plus change in 𝐹𝑉
− Clear evidence of delayed and incomplete
adjustment
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 20
Price adjustment
− Separate data for treatments BASE and CORR
− Surprising/Unsurprising looks similar to CORR
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 21
Interim conclusions
− Result 5. Prices generally exceed the fundamental value in our markets.
− Result 6. The observed mispricing allows for profitable arbitrage.
− Result 7. Prices adjust slowly and incompletely to changes in fundamental values.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 22
Conclusion
− First experimental examination of Post-Earnings-Announcement drift
− Clear evidence of PEAD even in a simplified lab environment
− Stronger drift in the presence of earnings autocorrelation
− Stronger drift following surprising than unsurprising announcements
− More complete adjustment in CORR than in BASE
− More complete adjustment following Unsurprising than following Surprising
announcements
Earnings Autocorrelation and the Post-Earnings-Announcement Drift (Fink, Palan, Theissen) 23
Outlook
− Impact of algorithmic arbitrage
− Impact of frictions
− Impact of announcement time (during/after trading hours)
− Microstructure of PEAD
This project was funded by the Austrian Science Fund – FWF, Grant no. P 32124-G27.
Earnings Autocorrelation and the Post-Earnings-Announcement Drift
Josef Finka, Stefan Palana, and Erik Theissenb,a
a Department of Banking and Finance, University of Graz b Business School, University of Mannheim
Austrian Working Group on Banking and Finance | University of Liechtenstein | November 22, 2019
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Screenshot trading screen
− Red captions are
translations not visible
during the experiment
Trading strategies
− Figure shows spreads in the 10s
following the announcement, and
at the close of the phase
− Large spreads at both open and
close of the strategy
Mispricing
− Measures of mispricing:
Arbitrage
− Sum of stock A’s and stock B’s values is always 200 talers
− Clear arbitrage opportunity whenever:
− Sum of best bids of
stocks A and B
exceeds 200 talers
− Sum of best asks of
stocks A and B falls
short of 200 talers
Price adjustment
− Separate data for surprising and unsurprising announcements in phases 3-5 of treatment
CORR
−
Spreads
− Spreads around 𝐹𝑉 reflect overpricing
(at least at the beginning of a period)
− Spreads generally decline over time
within a period
− Spreads also decline over time within
phases