1. COURSE TITLE: SEMINOR IN FINANCE COURSE CODE: MPH 622
Presentation on
The Cross-Section of Realized Stock
Returns: The Pre-COMPUSTAT
Evidence
Article written by: James L. Davas, Kansas State University, USA
Article published in: Journal of Finance, Vol. XLIXI No. 5 (December 1994),
pp. 1579-1593
3rd March, 2011

2.  Research question
Is there ability of certain variables to explain the cross-sectional
variation in realized stock returns?
 Objectives
To analyze the explanatory power of book-to-market equity, earning
yield, sales growth, firm size, stock price and historical beta with
respect to the cross-section of realized stock returns.
To find the January seasonal explanatory power of these variables.
 Nature and Purpose
Explanatory (to establish the relationship between the variables)
 Methodology : Primary sources
 Approach : Quantitative
 Research Design : Causal correlation and descriptive
Continue….

3. Continue….
 Review of literature & research gap
Relationship between book-to-market equity and
stock returns
Rosenberg, Reid and Lanstein
(1985), De Bondt and Thaler
(1987), Chan, Hamao and
Lakonishok (1991) and Fama
and French (1992)
Relationship between earning yield and stock
returns
Basu (1977), Jaffe, Keim and
Waterfield (1989)
Relationship between cash flow yield and stock
returns
Chan, Hamao and Lakonishok
(1991)
Relationship between historical sales growth and
stock returns
Lakonishok, Shleifer, and
Vishny (1993)
Seasonality is the explanatory power of earnings
yield
Jaffe, Keim and Waterfield
(1989)
January seasonal in the magnitude of the
regression coefficient on book-to-market equity
Fama and French (1992).
To confirm the relationship of the variables on
earlier studies using different time frame and
methodologies
Research gap

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 Hypotheses: (Null hypotheses)
o H1: The correlation between the variables and subsequent returns do
not reflects compensation for bearing risk.
o H2: The variables doe not allow investors to identify stocks that are
mispriced.
o H3: The observed predictive ability is not an artifact of the research
design and database used to conduct the study, and the predictive ability
of certain variables would be reduced or vanish if different
methodology and data were used.
These hypotheses which are based on the study of Fama and French
(1993), Lakonishok, Shleifer, and Vishny (1993) and Kothari, Shanken,
and Sloan (1993) respectively.
H1 & H2 = Explanatory power H3 = Methodologies

5. Continue….
 Limitations
o Includes only the largest firms of NYSE in the top half of the size
spectrum.
o The ratio of book-to-market equity was calculated on the basis of
accounting information rather than market value of equity.
o Use of accounting information for analysis may be affected by the
COMPUSTAT related problems.
But, the survivorship bias in the selection of firms, Davis (1994), Banz
and Breen (1986) and problem of a look-ahead bias, Banz and Breen
(1986) have been eliminated by employing Moody’s Industrial
Manuals. However, Data snooping, Lo and MacKinlay (1990) and short
sample period problems still remains in the study.

6. Continue….
 Sources of data
Two primary sources
Moody Industrial Manuals: for book value earnings, cash flow, and
sales and,
University of Chicago, Center for Research in Security Prices (CRSP):
for stock returns, stock prices and market values of equity.
 Sample
100 firms selected on top half of the June 30 size ranking and listed in
the Moody’s Industrial Manual.
 Study period
From 1940 to the early 1960s
Reasons - first, fairly constant volatility in the stock market compare
with 1930s and availability of the accounting information.

7. Continue….
 Variables
o Book-to-market equity
o Cash flow yield
o Earning yield and
o Historical sales growth use as primary focus.
BETA (historical betas base), Firm size, Share price, LBM, LMV,
E/P, CF/P, GROWTH (five year compound annual average sales
growth rate) and LPRICE as of each June 30 for each firms also
included as secondary variables.
ttl: 13 variables = 4 + 9

8. Continue….
 Procedures of analysis
Ranking
o First, the stocks were ranked by the variables and quintiles were
formed.
o Second, the returns, systematic risk, and other characteristics of these
quintiles were analyzed.
Portfolio
o First portfolio was formed with the top third of the CF yield ranking
and in the bottom third of the sales growth ranking. (top 3 + bottom 3)
o Second portfolio was formed with the bottom third of the CF yield
ranking and in the top third of the sales growth ranking. (bottom 3 +
top 3 )
Cross-sectional regression
o Fama-MacBeth (1973) cross-sectional regression analysis use to
determine the explanatory power of realized returns.
o Monthly regressions were run for whole period and results were
presented for all months, for January only, and for February-December
only.

9.  Empirical results
Portfolio results
i) Ranking on the basis certain variables produces dispersion in
returns.
ii) There are correlations among the variables. (multicollienarity)
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Portfolio sorted by 0 (Neg.) 1 (Low) 5 (High) I Dispersion I
Earning/Price 11.91 13.48 23.04 9.56*
Cash Flow/Price 13.46 12.54 22.07 9.53*
5 Year Sales Growth 15.67 15.58 0.09
Firm Size 18.13 15.03 3.10
Stock Price 20.17 15.42 4.75
Book/Market 14.24 21.06 6.82*
Historical Beta 13.47 18.19 4.72
Cross-sectional correlation
Mean Corr.(E/P, CF/P) 0.83
Multicollinearity
Mean Corr.(CF/P, LBM) 0.66
Mean Corr.(E/P, LBM) 0.50
Mean Corr.(LP, LMV) 0.45
Mean Corr.(LP, LBM) -0.42
Others Mean Corr. <0.32

10. Regression results: (return vs. other variables)
iii) There significant relationship between book-to-market equity and
subsequent returns.
iv) Cash flow yield has explanatory power with respect to subsequent
realized returns when book-to-market equity and historical sales
growth are held constant. (conditional relationship)
v) Earning yield has also explanatory power to predict subsequent
returns.
vi) There is insignificant explanatory power for beta to predict returns.
vii) There is a weak relationship between sales growth and returns.
Beta LBM CF/P+ CFPNEG E/P+ EPNEG GROWTH Avg. Adj R2
0.15 0.029
0.26* 0.020
1.64 0.29 0.021
4.35* 0.52 0.023
-0.46 0.010
1.56 0.43 -0.45 0.031
-0.05 2.55* 0.2 -0.56 0.040
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11. Continue….
Seasonal patterns
viii) There is significance of LBM, E/P+, and CF/P+ with return mostly
in January.
Beta LBM CF/P+ CFPNEG E/P+ EPNEG GROWTH Avg. Adj R2
Panel A:
January Only
(23 obs)
0.20 0.028
1.95* 0.043
15.83* 3.77 0.030
25.54* 4.73 0.033
-4.59 0.014
16.31* 4.45 -4.60 0.043
1.15 9.12* 5.00 -3.41 0.061
Panel B:
Feb-Dec (253
Obs)
0.15 0.029
0.11 0.018
0.35 -0.02 0.020
2.42 0.14 0.022
-0.08 0.010
0.22 0.06 -0.07 0.030
-0.15 1.95 -0.24 -0.30 0.038

12. Conclusions
Book-to-market equity, earning yield, and cash flow yield have
significant explanatory power with respect to the cross-section of realized
stock returns during the study period and,
There is a strong January seasonal in the explanatory power of book-to-
market equity, earning yield and cash flow yield.
 Critical appraisal
This work has found out the relationship between the variables which had
already been identified, thus it is believed that it validates the former.
Contains of the article is quite repetitive.
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13. Thank you.