Cho Et Al (2012) - The Value of a Two-Dimensional Value Investment Strategy

8/18/2019 Cho Et Al (2012) - The Value of a Two-Dimensional Value Investment Strategy

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Emerging Markets Finance & Trade / July–August 2012, Vol. 48, Supplement 2, pp. 58–81.Copyright © 2012 M.E. Sharpe, Inc. All rights reserved. Permissions: www.copyright.comISSN 1540-496X (print)/ISSN 1558-0938 (online)DOI: 10.2753/REE1540-496X48S204

The Value of a Two-Dimensional Value Investment

Strategy: Evidence from the Korean Stock Market

Seong-Soon Cho, Jung-Soon Shin, and Jinho Byun

ABSTRACT: This paper examines whether the two-dimensional value investment strategy

that incorporates both the value investment strategy and financial statement information

can earn excess returns in the Korean stock market. The two-dimensional value invest-

ment strategy yields a return of 27.9 percent, which is 8.97 percent higher than the

return provided by the simple value investment strategy. Thus, the result shows that the

two-dimensional strategy is not only effective in the U.S. stock market, but also effective

in emerging markets such as the Korean stock market. Furthermore, the two-dimensional

value investment strategy shows that the higher return during a bear market demonstrates

the strategy’s protective ability.

KEY WORDS: book-to-market ratio, FSCORE, glamor stocks, value investment, value stocks.

Investors have found that market anomaly, in contrast to market efficiency, can gener-

ate abnormal return, and various strategies incorporating this phenomenon have been

consistently developed.

The value investment strategy1 is one such strategy and consists of a long position in

value stocks and a short position in glamor stocks, using the valuation ratio to earn excess

return. Basu (1977, 1983) examined the validity of using earnings-to-price (EP) ratio to

assess the valuation ratios of firms. Subsequent studies have extended the variables to

evaluate a firm’s valuation to size, book-to-market (BM) ratio, and cash flow-to-price(CP) ratio (Chan et al. 1991; Jaffe et al. 1989; Rosenberg et al. 1985) and to analyze the

reason for the excess returns earned by the value investment strategy (Fama and French

1992; Lakonishok et al. 1994; La Porta 1996; La Porta et al. 1997).

The two predominant theories of value premium are the risk compensation hypothesis

(Fama and French 1993) and the missed expectations hypothesis (Lakonishok et al. 1994).

Through the use of the book-to-market ratio, Fama and French explain that the excess

return on value stocks reflects compensation for a risk. Extending their 1993 results,

Fama and French (1995) analyze accounting earnings using both size and book-to-market

ratio, and obtain results consistent with rational pricing: a high book-to-market ratio

signals persistent poor earnings, and a low book-to-market ratio signals strong earnings.

Lakonishok et al. (1994), however, explain that the excess return on value stocks results

from the price correction of the initial mispricing: investors are overly optimistic (pes-

simistic) about the future performance of glamor (value) firms, and thus the expectation

errors cause a reversal in their returns.

Seong-Soon Cho ([email protected]) is a Ph.D. candidate at the Ewha School of Busi-

ness, Ewha Womans University, Korea. Jung-Soon Shin ([email protected]) is an assistant pro-

fessor of finance in the Ewha School of Business, Ewha Womans University, Korea. Jinho Byun

([email protected]), corresponding author, is an associate professor of finance in the Ewha School

of Business, Ewha Womans University, Korea. The authors thank two anonymous referees and

the editor, Ali M. Kutan, for their helpful comments. The authors also thank Sungtae Kim for his

excellent assistance.


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July–August 2012 Supplement 59

Lakonishok et al. (1994) present the missed expectations hypothesis when examin-

ing the gap between the expected growth rate and the realized growth rate; however, the

article fails to provide a complete explanation for the missed expectations hypothesis.

In response, Piotroski (2000) suggests the usefulness of financial information to explain

the mispricing hypothesis and composes the FSCORE as a proxy for recent changes inthe financial performance of firms. Piotroski also claims that the excess returns provided

by the simple value investment strategy might be due to a few blue-chip firms and shows

that using the information from financial statements can increase the accuracy of the

strategy. In addition, Frankel and Lee (1998) use the earnings expectations of financial

analysts to separate value stocks from glamor stocks and show that such a value invest-

ment strategy generates positive return. This result confirms the usefulness of historical

financial statements.

Bartov and Kim (2004) measure the performance of two-dimensional value investment

strategies using additional accounting accruals as financial information to find expecta-

tion errors in the value investment strategy. They find that annual returns on a strategy

of investing in mispriced portfolios formed by buying stocks with high book-to-market

ratio and low accruals and selling stocks with low book-to-market ratio and high accru-

als outperform those on the book-to-market classification or the accruals classification

alone, with no evidence of increased risk.

Piotroski and So (2011) also argue that a two-dimensional investment strategy that

incorporates financial statement analysis and value ratios generates higher returns than

a one-dimensional investment strategy that consists only of value ratio. Based on their

studies, this paper examines whether various simple value ratios and the composite value

(CV) ratio also apply to the Korean stock market and analyzes the validity of the two-

dimensional value investment strategy using FSCORE.

Previous studies have mostly dealt with developed markets; few have focused onemerging markets, including the Korean market. In the case of emerging markets, the

stock price may only partially reflect financial information because earnings reports or

disclosures may be less accurate and the market’s regulatory system may be less developed.

For example, Wang and Xie (2010) find evidence of overreaction and the profitability

of a contrarian strategy on the Chinese stock market; Lai et al. (2010) show the asym-

metric market responses to technical buy and sell signals on the Taiwan stock market;

and Kim and Byun (2010) provide evidence that investor sentiment have the power to

predict the buy-and-hold returns on the Korean stock market. In addition, the limited

role of institutional investors in emerging markets might generate a chance of getting

abnormal returns from using financial information. Specifically in Korea, the proportion of

individual investors’ trading volume in 2010 was about 92 percent (64 percent in trading

amount). Bartov and Kim (2004) indicate that mispricing may be more prominent in the

stocks of unsophisticated investors. Because individual investors use financial information

less frequently than institutional investors do, it would be a useful investment strategy to

use missed expectations on stock pricing in order to obtain abnormal returns in Korean

markets, in which there is a heavy amount of trading done by individual investors. In

addition, by showing the varying results of value investment strategies according to

market conditions, this paper will demonstrate how strategies can be applied differently

according to such conditions. In order to examine whether the abnormal returns of two-

dimensional strategy comes from reward-to-risk or expectation errors, we employed the

Fama–French three-factor and four-factor models, with turnover as the liquidity factor,and still found that the two-dimensional value investment strategy was valid.


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60 Emerging Markets Finance & Trade

Some studies on the Korean stock market suggested the presence of a value premium

(Chang and Kim 2003; Gam 1999; Kim and Lee 2006; Song 1999). This paper general-

izes the effectiveness of the value investment strategy by expanding the sample period to

recent years. Chang and Kim (2003) also analyzed the validity of the two-dimensional

value investment strategy using financial conditions. However, they concentrated onprofitability data such as gross margin rate, return on invested capital, and interest cover-

age ratio to measure financial conditions, and thus failed to use the financial statement

holistically. This paper makes use of FSCORE, which measures not only a firm’s profit-

ability, but also the changes in financial leverage and liquidity, and changing operational

efficiency. Unlike previous studies, in which abnormal return calculations were based

on a market index, this study, like that of Piotroski and So (2011), uses size, which is a

market anomaly, to measure the effect of value investments more accurately. By using

a size-adjusted portfolio when calculating abnormal returns, this paper supplements the

shortcomings of previous studies.

The result shows that a value premium also exists in the Korean stock market. In

particular, a one-dimensional investment strategy using composite value (CV) yields an

18.93 percent return, which is higher than the return from any other one-dimensional

value investment strategy using individual value ratios. This indicates that using various

proxies for relative value is more effective than utilizing a single valuation proxy in an

investment strategy. Moreover, a two-dimensional value investment strategy that incor-

porates information from financial statements and value ratios generates higher returns

than a one-dimensional value investment strategy does. Buying value stocks with good

financial conditions and selling glamor stocks with bad financial conditions can generate

at most a 27.9 percent, size-adjusted buy-and-hold abnormal return, which is 8.97 percent

higher than the return from a one-dimensional value investment strategy. As Piotroski

and So (2011) showed, this study shows that the value effect resides in portfolios withhigh expectation errors.

A comparison of the returns during bear and bull markets using value investment

strategies revealed that a value premium exists in both conditions. In addition, consistent

with the results of the full sample, in both bear and bull markets the two-dimensional

value investment strategy generates a higher return than does the one-dimensional value

investment strategy. Furthermore, this paper shows that both one-dimensional and two-

dimensional value investment strategies generate higher profits during the downturn of

the stock market, proving their protective ability. In bear markets, the two-dimensional

value investment strategy using share turnover has higher returns than that which involves

using the composite value, a fact that implies that liquidity is important in the bear market

condition. After controlling for liquidity in our multivariate analysis, we find additional

returns from the two-dimensional value investment strategy.

Research Design

Value/Glamor Classification

Like Piotroski and So (2011), we use a multidimensional approach and a composite

approach to classify value stocks and glamor stocks. Proxies such as book-to-market

(BM), earnings-to-price (EP), cash-flow-to-price (CP), sales growth (SG), and equity

share turnover (ST) are used for relative value. Among these values, BM, EP, and CP arebased on the stock price to identify value stocks and glamor stocks. In other words, since


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pricing multiples provide information about firms with prices that do not fully reflect

their fundamental values, higher values of BM, EP, and CP indicate deep value stocks.

On the contrary, lower values of SG and ST indicate deep value stocks.

BM is calculated by dividing the total equity at the end of the fiscal year2 t – 1 by

the market capitalization at the end of the fiscal year t – 1. EP is calculated by dividingthe net income per share by adjusted stock price at the end of the fiscal year t – 1. CP

is calculated by dividing cash flow per share by adjusted stock price at the end of the

fiscal year t – 1. SG is calculated by dividing the difference between sales at year t – 1

and year t – 2 by the sales at year t – 2. ST is calculated by adjusting the average daily

trading volume from July of year t – 1 (the year before the portfolio formation) until the

end of June of year t to the average number of shares.

To formulate a value/glamor stock portfolio every year, each dimension of relative

values is divided into the top 30 percent, the middle 40 percent, and the bottom 30 percent.

Firms in the top 30 percent and bottom 30 percent are value stocks (glamor stocks if low

SG and ST) and glamor stocks (value stocks if high SG and ST), respectively.

The average of the decile rank of each value proxy is used to calculate the composite

measure of values, or CV. However, the decile ranks of SG and ST are multiplied by –1

because their values are reversed.

CVDecile BM Decile CP Decile EP Decile SG Decile ST

=

( )+ ( )+ ( )+ ( )+ ( )5

..

Korean Stock Market Liquidity and K-IFRS

The liquidity of the Korean stock market is relatively high because the proportion of indi-

vidual investors who tend to frequently trade is high. According to the Korean Digital Times,in 2011 the share turnover of the Korea Stock Exchange ranked at third in the world after

the Nasdaq OMX and the Shenzhen Stock Exchange in China. Measuring liquidity, we

use the turnover ratio, which is the trading volume adjusted to the number of outstanding

shares, as has been done in previous studies (Brennan and Subrahmanyam 1995; Chordia et

al. 2001; Rouwenhorst 1999). We included a liquidity variable as a risk factor in our four-

factor model to measure risk-adjusted returns based on Yun et al. (2009), who show that

liquidity has more explanatory power than book-to-market ratio in Korea. Kim and Byun

(2011) present a summary of behavioral finance literature in the Korean market.

At the end of 2007, the Korean International Financial Reporting Standards (K-IFRS)

were released. The K-IFRS are a word-for-word translation of the full IFRS issued by the

International Accounting Standards Board (IASB) and have been mandatory for Koreanlisted companies with assets over 2 trillion won since 2011 (voluntary early adoption

became possible in 2009 for all companies except financial institutions). However, com-

panies with assets of less than 2 trillion won are allowed to keep their current accounting

systems until 2013.

One of the main changes incurred by introducing IFRS is that unlike K-GAAP, K-IFRS

generally use historical cost, but intangible assets, property, plant, and equipment (PPE),

and investment property may be revalued to fair value. Derivatives and certain other

financial instruments and biological assets are also revalued to fair value. Because of

these changes, if revaluation engenders profits, companies can expect a decrease in li-

abilities. Therefore, companies owning many fine tangible assets are expected to benefitfrom adopting IFRS, which will make their books more attractive.


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FSCORE Classification

Like Piotroski (2000), we compose the FSCORE to classify firms based on the recent

financial performance trend. The FSCORE is the sum of nine financial signals: four

variables measure profitability, three measure change in financial leverage/liquidity, andtwo measure change in operational efficiency. Signal realization is divided into good and

bad implications for future profitability and cash flow. An indicator variable with good

signal realization equals 1, and an indicator variable with bad signal realization equals

0. The FSCORE measures the overall financial condition of a firm.

Out of the nine signals, return on assets (ROA), cash flow from operations (CFO),

change in net income (NI), and ACCRUAL look into a firm’s profitability. ROA is

calculated as net income during year t scaled by total assets at the beginning of the year.

The indicator variable F_ROA receives one point if ROA is positive and zero points if it

is negative. CFO is calculated as cash flow from operations during year t scaled by total

assets at the beginning of the year. The indicator variable F_CFO receives one point if

CFO is greater than 0 and zero points if it is less than 0. NI, change in net income, iscalculated as the current year’s net income minus the prior year’s net income realization.

The indicator variable F_NI receives one point if NI is positive, and zero points if it is

negative. ACCRUAL is calculated as the current year’s net income minus cash flow from

operations, scaled by average total assets. The indicator variable F_ACCRUAL receives

one point if ACCRUAL is lower than 0 and zero points if it is higher than 0.

The following variables are designed to measure the firm’s capital structure and ability

to pay future debt service obligations. Change in long-term leverage (LEVER) is the

change in the ratio of long-term debt to total assets. The indicator variable F_LEVER

receives one point if LEVER decreases and zero points if it increases. A high leverage

ratio indicates a firm’s high financial risk. Change in current ratio (

LIQUID) is the ratioof current assets to current liabilities at the end of a fiscal year compared to the prior year’s

ratio. The indicator variable F_LIQUID receives one point if LIQUID increases and zero

points if it decreases. ISSUANCE checks if a firm is raising external equity capital. The

indicator variable F_ISSUANCE receives zero points if a firm’s change in capital stock

is positive between year t and year t – 1, and one point otherwise. A firm raising external

equity capital displays its inability to raise internal capital to pay for future debts. As

explained in Piotroski (2000), external debt and equity issuance are possible responses to

a positive NPV (net present value) investment opportunity, but prior empirical research

proves that such events negatively affect a firm’s stock price.3

The last two signals measure a firm’s operating efficiency. Change in the gross margin

(MARGIN) is the difference between a firm’s current gross margin ratio and the previousyear’s. Since a positive change in the gross margin ratio signals a firm’s improved condition,

the indicator variable F_MARGIN receives one point if MARGIN is positive and zero

points if it is negative. Change in asset turnover (TURN) is calculated as the firm’s current

asset turnover ratio minus the prior year’s asset turnover ratio. Asset turnover is defined as

total sales scaled by average total assets. The indicator variable F_TURN receives one

point ifTURN is positive and zero points if it is negative. An increase in a firm’s turnover

ratio indicates a firm’s efficiency in generating more sales revenue with its assets.

The FSCORE, which measures a firm’s recent financial performance, is calculated

by adding up the points of the nine individual signals, with a score ranging from zero to

nine. A high FSCORE indicates a firm with strong recent financial performance, and alow FSCORE indicates a firm with weak recent financial performance.


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FSCORE = F_ROA + F_CFO + F_NI + F_ACCRUAL + F_LEVER

+ F_LIQUID + F_ISSUANCE + F_MARGIN + F_TURN.

We will conduct an empirical analysis to see whether FSCORE can identify expecta-

tion errors in value firms and glamor firms more precisely.

Two-Dimensional Value Investment Strategy

The fact that less than 44 percent of high book-to-market firms earn positive returns for

two consecutive years supports the presence of heterogeneity even within a value portfo-

lio (Piotroski 2000). Thus, this paper tests if including both valuation ratio and financial

fundamentals in the portfolio generates greater returns than using a one-dimensional

investment strategy does.

This study’s two-dimensional value investment strategy is based upon the character-

istics of CV and FSCORE, which are calculated according to the method of Piotroski

and So (2011). If the prices of glamor firms demonstrate overly optimistic expectationsand prices of value firms demonstrate overly pessimistic expectations, the value/glamor

strategy should identify overvalued firms in the glamor portfolio and undervalued firms

in the value portfolio. The FSCORE should be able to accurately identify firms with sig-

nificant expectation errors within the value/glamor portfolios. If the FSCORE does not

point in the same direction as the value dimension, there will be significant expectation

errors. Expectation errors should mainly appear in firms whose fundamentals as reflected

in the FSCORE differ the most from those reflected in the value ratios.

According to the mispricing hypothesis, expectation errors should be more significant

in value firms with a high FSCORE and glamor firms with a low FSCORE, as shown

in Figure 1. The incongruent investment strategy, using two portfolios with significant

expectation errors, consists of a long position in value firms with a high FSCORE and

a short position in glamor firms with a low FSCORE. This strategy means that long the

portfolio with a high potential for being undervalued and short the portfolio with a high

potential for being overvalued. As a result, the highest return can be expected using an

incongruent investment strategy when a price reversal occurs to correct the expectation

error. Inversely, the congruent investment strategy, using two diagonal portfolios with

small expectation errors, consists of a long position in value firms with a low FSCORE

and a short position in glamor firms with a high FSCORE.

Size Benchmark Portfolio Formation and Calculations of

Abnormal Returns

We present annual, size-adjusted, equally weighted buy-and-hold returns for most of our

results. To adjust for size, following Fama and French (1992), we construct a size decile

benchmark portfolio during the portfolio formation time by using all the stocks (except

those of financial firms) listed on the Korea Composite Stock Price Index (KOSPI) market.

Each year, we reconstruct a benchmark portfolio using market capitalization at the end

of June in year t . Assuming an annual buy-and-hold strategy, the annual size-adjusted

equally weighted buy-and-hold return on a firm is computed as the return on that firm

minus the buy-and-hold return on the size benchmark portfolio.

If the firm delists prior to the end of the twelve-month compounding period, the delist-

ing return is replaced by the average return of the size benchmark portfolio.


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Results

Data

The research period for this paper is from January 1981 to June 2011. The sample consists

of companies listed on the KOSPI market4 with a December fiscal year-end; it excludes

firms from the finance industry. Since the two previous years of financial statements arerequired, the financial statements from 1981 to 2009 are used in the formation of the

portfolio for the investment strategy. Portfolio performance is based on the returns for

twenty-seven years, from July 1984 to June 2011. The sample includes 11,810 firm-years.

Financial statements and stock information used to compose the FSCORE and calculate

the value ratio are taken from FnGuide (Korean financial database).

Table 1 represents descriptive statistics of the five CV and nine FSCORE components.

With the exception of change in gross margin (MARGIN) and change in asset turnover

(TURN), all FSCORE components have positive indicators of more than 50 percent.

One-Dimensional Investment Strategy: Value Investment Strategy Table 2 represents the annual size-adjusted buy-and-hold returns of the simple value

investment strategy. The value investment strategy consists of a long position in value

firms and a short position in glamor firms. When using the valuation ratios, all but sales

growth (SG) prove the existence of a value premium (significant at the 1 percent level).

These results are congruent with previous research and signify that a value premium

exists in the Korean stock market.

Specifically, among the investment strategies that utilize individual valuation proxies,

the investment strategy using cash-flow-to-price (CP) generates a 15.06 percent annual

buy-and-hold return, and the strategy using share turnover (ST) generates the highest

annual buy-and-hold return: 18.64 percent. However, the value investment strategy us-ing CV, which is composed of five individual valuation ratios, earns an 18.93 percent

Low CV Firms

“Glamor”

High CV Firms

“Value”

Low FSCORE

High Potential forOvervalued Firms

Significant ExpectationErrors

Low Potential forUndervalued Firms

Small ExpectationErrors

High FSCORE

Low Potential forOvervalued Firms

Small ExpectationErrors

High Potential forUndervalued Firms

Significant ExpectationErrors

Figure 1. Value/glamor and FSCORE matrix

Notes: Firms with high potential for overvaluation and undervaluation are concentrated in off-diagonalportfolios that have significant expectation errors. But firms with low potential for overvaluation and

undervaluation are concentrated in diagonal portfolios that have small expectation errors.


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T a b l e

1 . D e s c r i p t i v e s t a t i s t i c s o f c

o m p o s i t e v a l u e ( C V ) a n d F S C

O R E c o m p o n e n t s

I t e m s

M e a n

M i n

2 5 t h

p e r c e n t i l e

M e d i a n

7 5 t h

p e r c e n t i l e

M a x

S t a n d a r d

d e v i a t i o n

P e r c e n t o f

I

n d i c a t o r = 1

C V c o m p o n e n t s

B M

( b o o k - t o - m a r k e t )

1 . 7

1

0 . 1

6

0 . 7

5

1 . 2

2

2 . 1

4

8 . 7

0

1 . 5

1

E P

( e a r n i n g s - t o - p r i c e )

0 . 1

9

– 4 . 6

8

0 . 0

1

0 . 0

8

0 . 2

3

4 . 7

2

0 . 9

8

C P

( c a s h - fl o w - t o - p r i c e )

0 . 6

3

– 2 . 7

1

0 . 0

6

0 . 1

9

0 . 5

3

8 . 5

3

1 . 4

9

S G

( s a l e s g r o w t h )

0 . 1

1

– 0 . 5

7

- 0 . 0

1

0 . 0

9

0 . 2

0

1 . 1

2

0 . 2

4

S T ( s h a r e t u r n o v e r )

0 . 0

1

0 . 0

0

0 . 0

0

0 . 0

1

0 . 0

1

0 . 1

0

0 . 0

2

F S C O R E c o m p o n e n t s

R O A

0 . 0

3

– 0 . 3

1

0 . 0

1

0 . 0

3

0 . 0

6

0 . 2

6

0 . 0

8

8 3 . 4

0

C F O

0 . 0

5

– 0 . 2

9

– 0 . 0

1

0 . 0

5

0 . 1

1

0 . 3

6

0 . 1

1

7 1 . 9

6

∆ N I ( m i l l i o n K R W )

2 , 4

4 9

– 2 3 2 , 4

0 3

– 2 , 1

5 3

1 7 5

3 , 0

3 5

3 0 1 , 9

1 1

5 0 , 7

2 0

5 5 . 5

9

A C C R U A L

– 0 . 0

2

– 0 . 3

1

– 0 . 0

8

– 0 . 0

2

0 . 0

3

0 . 2

9

0 . 1

0

6 3 . 2

0

∆ L E V E R

– 0 . 0

1

– 0 . 2

9

– 0 . 0

4

0 . 0

0

0 . 0

3

0 . 2

5

0 . 0

8

5 4 . 9

6

C_ L

I Q U I D

0 . 0

3

– 2 . 2

3

– 0 . 1

7

0 . 0

0

0 . 1

9

2 . 9

2

0 . 6

2

5 0 . 6

9

I S S

U A N C E ( m i l l i o n K R W )

3 , 1

1 1

– 1 5 , 6

6 7

—

—

1 , 4

0 0

8 2 , 4

5 0

1 1 , 2

4 5

6 1 . 9

9

∆ M

A R G I N

0 . 0

0

– 0 . 1

7

– 0 . 0

2

0 . 0

0

0 . 0

2

0 . 2

1

0 . 0

5

4 8 . 3

7

∆ T U R N

– 0 . 0

3

– 0 . 8

2

– 0 . 1

2

– 0 . 0

2

0 . 0

7

0 . 6

5

0 . 2

1

4 4 . 7

4

N o t e : V a r i a b l e s a r e w i n s o r i z e d a t t h e t o p a n

d b o t t o m 1 p e r c e n t .


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T a b l e 2 . A n n u a l b u y - a n d - h o l d r e t u r n s u s i n g a v a l u e i n v e s t m e n t s t

r a t e g y

M e a n

1 0 t h

p e r c e n

t i l e

2 5 t h

p e r c e n t i l e

M e d i a n

7 5 t h

p e r c e n t i l e

9 0 t h

p e r c e n t i l e

S t a n d a r d

d e v i a t i o n

S k e w n e s s

K u r t o s i s

P e r c e n t

p o s i t i v e

N

A l l fi r m s

– 0 . 0

1 2 8

– 0 . 5

2 1

5

– 0 . 2

9 2 4

– 0 . 0

7 9 5

0

. 1 5 5 5

0 . 5

3 8 3

0 . 8

1 5 1

5 . 6

8 8 4

9 8 . 4

2 7 3

3 9 . 5 7

1 1 , 8

1 0

B o o k - t o - m

a r k e t ( B M )

V a l u e H i g h

_ B M

0 . 0

5 6 7

– 0 . 4

7 1

4

– 0 . 2

4 7 7

– 0 . 0

3 9 8

0

. 2 3 3 4

0 . 7

1 9 3

0 . 9

0 5 8

4 . 8

0 3 4

7 7 . 3

1 5 5

4 4 . 9 4

3 , 5

3 6

M i d_ B

M

– 0 . 0

2 0 3

– 0 . 4

9 6

3

– 0 . 2

8 8 1

– 0 . 0

8 3 3

0

. 1 4 6 8

0 . 4

9 1 1

0 . 7

8 4 0

6 . 6

0 2 6

1 3 5 . 2

7 2 5

3 9 . 0 5

4 , 7

3 8

G l a m o r

L o w_ B

M

– 0 . 0

7 2 2

– 0 . 6

0 7

9

– 0 . 3

4 8 1

– 0 . 1

1 9 9

0

. 0 9 6 5

0 . 4

4 1 3

0 . 7

5 2 9

5 . 6

4 4 7

7 5 . 7

7 2 5

3 4 . 9 0

3 , 5

3 6

D i f f e r e n c e

V a l u e – g l a m o r

0 . 1

2 8 9

0 . 1

3 6

5

0 . 1

0 0 4

0 . 0

8 0 1

0

. 1 3 6 9

0 . 2

7 8 0

0 . 1

5 2 9

– 0 . 8

4 1 3

1 . 5

4 3 0

1 0 . 0 4

p - o r Z - v a l u e

0 . 0

0 0 0

* * *

0 . 0

0 0 0

* * *

E a r n i n g s - t o - p r i c e ( E P )

V a l u e H i g h

_ E P

0 . 0

3 7 9

– 0 . 4

4 5

6

– 0 . 2

4 1 1

– 0 . 0

3 7 2

0

. 1 9 7 2

0 . 5

7 1 1

0 . 7

0 5 9

4 . 0

0 7 5

4 1 . 4

6 0 2

4 4 . 9 9

3 , 5

4 1

M i d_ E

P

– 0 . 0

1 7 2

– 0 . 4

6 1

9

– 0 . 2

6 7 0

– 0 . 0

7 5 5

0

. 1 4 1 0

0 . 4

6 3 8

0 . 6

4 2 2

3 . 8

2 8 9

4 9 . 3

3 8 3

3 9 . 0 4

4 , 7

2 9

G l a m o r

L o w_ E

P

– 0 . 0

5 7 7

– 0 . 6

8 3

4

– 0 . 3

8 2 7

– 0 . 1

4 2 3

0

. 1 1 7 2

0 . 6

1 6 1

1 . 0

7 8 4

6 . 0

6 5 2

9 1 . 4

3 5 2

3 4 . 8 6

3 , 5

4 0

D i f f e r e n c e


0 . 0

9 5 6

0 . 2

3 7

8

0 . 1

4 1 6

0 . 1

0 5 1

0

. 0 8 0 0

– 0 . 0

4 5 0

– 0 . 3

7 2 5

– 2 . 0

5 7 7

– 4 9 . 9

7 5 0

1 0 . 1 3


0 . 0

0 0 0

* * *

0 . 0

0 0 0

* * *

C a s h - fl o w

- t o - p r i c e

V a l u e H i g h

_ C P

0 . 0

6 2 1

– 0 . 4

5 1

8

– 0 . 2

3 8 3

– 0 . 0

2 8 3

0

. 2 2 0 1

0 . 6

5 3 0

0 . 8

0 6 3

5 . 9

3 1 1

8 5 . 6

2 9 3

4 5 . 8 6

3 , 5

3 7

M i d_ C

P

– 0 . 0

1 2 3

– 0 . 4

5 6

5

– 0 . 2

6 3 4

– 0 . 0

7 0 2

0

. 1 4 4 4

0 . 4

8 1 4

0 . 6

1 6 2

2 . 5

3 2 6

2 6 . 1

3 7 1

4 0 . 0 6

4 , 7

3 5

G l a m o r

L o w_ C

P

– 0 . 0

8 8 5

– 0 . 6

8 6

4

– 0 . 3

9 0 1

– 0 . 1

5 8 8

0

. 0 8 7 8

0 . 5

1 1 9

1 . 0

2 4 0

6 . 0

3 2 9

9 4 . 7

9 9 6

3 2 . 6 2

3 , 5

3 8


10/24


D i f f e r e n c e


0 . 1

5 0 6

0 . 2

3 4

6

0 . 1

5 1 8

0 . 1

3 0 5

0

. 1 3 2 3

0 . 1

4 1 1

– 0 . 2

1 7 7

– 0 . 1

0 1 8

– 9 . 1

7 0 3

1 3 . 2 4


0 . 0

0 0 0

* * *

0 . 0

0 0 0

* * *

S a l e s g r o w t h ( S G )

G l a m o r

H i g h

_ S G

– 0 . 0

3 4 4

– 0 . 5

2 4

6

– 0 . 3

0 3 9

– 0 . 0

9 7 4

0

. 1 3 1 5

0 . 5

1 4 6

0 . 7

5 9 1

3 . 8

0 0 8

4 7 . 7

8 7 6

3 7 . 6 3

3 , 5

2 4

M i d_ S

G

0 . 0

0 6 5

– 0 . 4

7 0

0

– 0 . 2

5 9 4

– 0 . 0

6 1 0

0

. 1 6 5 2

0 . 5

2 4 3

0 . 7

4 3 0

4 . 4

7 2 1

7 0 . 3

5 1 7

4 1 . 2 7

4 , 7

4 9

V a l u e L o w_ S

G

– 0 . 0

1 7 3

– 0 . 6

1 4

9

– 0 . 3

2 6 7

– 0 . 0

9 2 3

0

. 1 6 5 1

0 . 5

9 5 5

0 . 9

4 9 9

7 . 2

0 7 0

1 2 3 . 3

8 6 6

3 9 . 2 1

3 , 5

3 7

D i f f e r e n c e


0 . 0

1 7 1

– 0 . 0

9 0

3

– 0 . 0

2 2 8

0 . 0

0 5 1

0

. 0 3 3 6

0 . 0

8 0 9

0 . 1

9 0 8

3 . 4

0 6 2

7 5 . 5

9 9 0

1 . 5 9


0 . 4

0 5 2

0 . 8

2 0 2

S h a r e t u r n o v e r ( S T )

G l a m o r

H i g h

_ S T

– 0 . 1

2 9 8

– 0 . 7

0 9

6

– 0 . 3

9 7 2

– 0 . 1

6 8 3

0

. 0 8 1 9

0 . 4

9 6 4

0 . 8

1 1 3

3 . 2

9 9 4

5 1 . 3

7 2 5

3 1 . 8 9

3 , 5

2 8

M i d_ S

T

0 . 0

2 2 5

– 0 . 4

7 4

7

– 0 . 2

6 5 3

– 0 . 0

6 1 9

0

. 1 7 0 6

0 . 5

5 7 3

0 . 8

4 5 2

7 . 4

9 9 0

1 3 8 . 1

6 0 6

4 1 . 2 8

4 , 7

6 0

V a l u e L o w_ S

T

0 . 0

5 6 6

– 0 . 4

2 5

9

– 0 . 2

3 1 6

– 0 . 0

3 2 8

0

. 1 9 2 2

0 . 5

6 0 6

0 . 7

6 3 5

5 . 5

2 0 5

8 0 . 8

3 5 7

4 4 . 9 5

3 , 5

2 2

D i f f e r e n c e


0 . 1

8 6 4

0 . 2

8 3

7

0 . 1

6 5 6

0 . 1

3 5 5

0

. 1 1 0 3

0 . 0

6 4 2

– 0 . 0

4 7 8

2 . 2

2 1 1

2 9 . 4

6 3 2

1 3 . 0 6


0 . 0

0 0 0

* * *

0 . 0

0 0 0

* * *

C o m p o s i t e v a l u e ( C V )

V a l u e

( c o n t i n u e s )


11/24


M e a n

1 0 t h

p e r c e n

t i l e

2 5 t h

p e r c e n t i l e

M e d i a n

7 5 t h

p e r c e n t i l e

9 0 t h

p e r c e n t i l e

S t a n d a r d

d e v i a t i o n

S k e w n e s s

K u r t o s i s

P e r c e n t

p o s i t i v e

N

H i g h

_ C V

0 . 0

7 6 9

– 0 . 4

1 1

0

– 0 . 2

1 4 3

– 0 . 0

1 9 8

0

. 2 3 0 4

0 . 6

2 8 1

0 . 7

4 8 1

5 . 9

4 2 7

9 4 . 1

9 5 7

4 6 . 7 5

3 , 5

2 7

M i d_ C

V

– 0 . 0

0 5 2

– 0 . 4

8 2

7

– 0 . 2

7 7 2

– 0 . 0

7 2 6

0

. 1 5 2 5

0 . 5

1 9 8

0 . 8

2 0 4

6 . 9

9 9 6

1 4 0 . 1

5 7 4

4 0 . 6 1

4 , 7

4 3

G l a m o r

L o w_ C

V

– 0 . 1

1 2 4

– 0 . 6

8 3

7

– 0 . 3

9 0 9

– 0 . 1

6 1 9

0

. 0 6 8 3

0 . 4

6 0 2

0 . 8

5 9 8

4 . 2

0 6 1

5 5 . 9

5 7 6

3 1 . 0 2

3 , 5

4 0

D i f f e r e n c e


0 . 1

8 9 3

0 . 2

7 2

7

0 . 1

7 6 6

0 . 1

4 2 1

0

. 1 6 2 1

0 . 1

6 7 9

– 0 . 1

1 1 7

1 . 7

3 6 6

3 8 . 2

3 8 1

1 5 . 7 4


0 . 0

0 0 0

* * *

0 . 0

0 0 0

* * *

R a w c o m p o s i t e v a l u e

( r a w C V )

V a l u e H i g h

_ R a w C V

0 . 0

7 2 6

– 0 . 4

1 3

0

– 0 . 2

1 6 6

– 0 . 0

2 0 5

0

. 2 2 5 7

0 . 6

2 8 1

0 . 7

4 6 5

5 . 8

7 2 9

9 3 . 7

6 6 1

4 6 . 7 2

3 , 5

7 9

M i d_ R

a w C V

– 0 . 0

0 7 1

– 0 . 4

7 9

3

– 0 . 2

7 5 0

– 0 . 0

7 3 2

0

. 1 5 0 7

0 . 5

1 0 1

0 . 7

7 5 1

6 . 5

4 2 5

1 3 7 . 3

1 9 8

4 0 . 3 1

4 , 7

8 5

G l a m o r

L o w_ R

a w C V

– 0 . 1

0 9 4

– 0 . 6

9 7

7

– 0 . 3

9 6 3

– 0 . 1

6 6 8

0

. 0 7 0 9

0 . 4

6 9 6

0 . 9

2 0 4

4 . 9

7 1 7

7 0 . 1

6 7 2

3 1 . 1 1

3 , 4

4 6

D i f f e r e n c e


0 . 1

8 2 0

0 . 2

8 4

7

0 . 1

7 9 7

0 . 1

4 6 3

0

. 1 5 4 8

0 . 1

5 8 5

– 0 . 1

7 3 9

0 . 9

0 1 2

2 3 . 5

9 8 9

1 5 . 6 1


0 . 0

0 0 0

* * *

0 . 0

0 0 0

* * *

N o t e s : E a c h J u n e , a l l t h e fi r m s a r e c l a s s i fi e d i n t o t h r e e p o r t f o l i o s a c c o r d i n g t o b o o k - t o - m a r k e t r a t i o ( B M ) , e a r n i n g s - t o - p r i c e r a t i o ( E P ) , c a s h - fl o w - t o - p r i c e r a t i o ( C P ) , s a l e s

g r o w t h ( S G ) , s h a r e t u r n o v e r ( S T ) , a n d c o m p o s i t e v a l u e ( C V ) . “ G l a m o r , ” “ M i d d l e , ” a n d “ V a l u e ” c o n s i s t o f fi r m - y e a r s w i t h a n a v e r a g e r a n k b e l o w t h e 3 0 t h p e r c e n t i l e , b e -

t w e e n t h e

3 0 t h a n d 7 0 t h p e r c e n t i l e s , a n d a b o v e

t h e 7 0 t h p e r c e n t i l e , r e s p e c t i v e l y . S i z e - a d j u s t e d e q u a l l y w e i g h t e d r e t u r n s a

r e c a l c u l a t e d b y s u b t r a c t i n g K O S P I - m

a t c h e d s i z e

d e c i l e p o r

t f o l i o r e t u r n s f r o m t h e c o r r e s p o n d i n g

r a w r e t u r n s . R e t u r n c o m p o u n d i n g b e

g i n s a t t h e s t a r t o f J u l y o f e a c h y e a r .

p - v a l u e s a r e r e p o r t e d i n p a r e n t h e s e s .

* , * * , a n d

* * * t w o - t a i l e d s i g n i fi c a n c e a t t h e 1 0 p e r c e n t , 5

p e r c e n t , a n d 1 p e r c e n t l e v e l s , r e s p e c t i v e l y .

T a b l e 2 . C o n t i n u e d


12/24


13/24


T a b l e

3 . A n n u a l b u y - a n d - h o l d r e t u

r n s u s i n g a n F S C O R E i n v e s t m e n t s t r a t e g y

P a n e l

A ; S i z e - a d j u s t e d b u y - a n d - h o l d r e t u r n s b y F S C O R E

M e a n

1 0 t h

p e r c e n t i l e

2 5 t h

p e r c e n t i l e

M e d i a n

7 5 t h

p e r c e n t i l e

9 0 t h

p e r c e n t i l e

S t a n d a r d

d e v i a t i o n

S k e w n e s s

K u r t o s i s

P e r c e n t

p o s i t i v e

N

A l l fi r m s

– 0 . 0

1 2 8

– 0 . 5

2 1 5

– 0 . 2

9 2 4

– 0 . 0

7 9 5

0

. 1 5 5 5

0 . 5

3 8 3

0 . 8

1 5 1

5 . 6

8 8 4

9 8 . 4

2 7 3

3 9 . 5 7

1 1 , 8

1 0

F S C O R E

0

– 0 . 2

7 3 7

– 0 . 7

9 1 5

– 0 . 4

2 0 1

– 0 . 1

7 2 4

– 0

. 0 0 7 6

0 . 2

6 7 0

0 . 7

4 4 5

– 1 . 6

6 7 7

5 . 7

2 1 6

2 2 . 9 2

4 8

1

– 0 . 1

2 2 7

– 0 . 6

9 9 8

– 0 . 3

8 6 5

– 0 . 1

2 8 7

0

. 0 2 3 6

0 . 5

3 6 9

1 . 2

2 2 6

3 . 8

5 0 4

4 0 . 0

4 3 5

2 8 . 5 7

3 2 2

2

– 0 . 1

3 8 4

– 0 . 6

9 1 8

– 0 . 3

6 4 7

– 0 . 1

6 6 5

0

. 0 6 3 1

0 . 3

9 9 0

0 . 9

3 5 1

2 . 8

2 1 4

3 5 . 2

9 6 8

3 0 . 9 0

8 0 9

3

– 0 . 0

7 2 2

– 0 . 6

0 9 2

– 0 . 3

3 5 4

– 0 . 1

2 9 4

0

. 1 0 0 9

0 . 4

8 9 1

1 . 0

0 7 7

5 . 7

8 3 2

8 7 . 6

9 3 5

3 5 . 1 9

1 , 2

2 2

4

0 . 0

1 3 0

– 0 . 5

8 2 8

– 0 . 3

1 9 6

– 0 . 0

8 5 6

0

. 1 5 1 3

0 . 5

6 1 2

1 . 0

6 1 7

8 . 8

9 5 5

1 4 3 . 5

6 1 5

3 8 . 5 9

1 , 5

3 4

5

0 . 0

1 3 1

– 0 . 5

4 6 4

– 0 . 2

8 1 7

– 0 . 0

6 5 8

0

. 1 6 6 8

0 . 5

8 1 1

0 . 7

8 5 3

3 . 4

9 5 9

3 1 . 3

8 7 7

4 0 . 5 7

2 , 1

9 6

6

– 0 . 0

0 8 9

– 0 . 4

7 2 7

– 0 . 2

5 9 8

– 0 . 0

6 8 6

0

. 1 5 8 4

0 . 5

3 0 9

0 . 6

1 1 8

1 . 2

9 3 7

2 0 . 5

2 1 0

4 0 . 7 3

2 , 2

9 8

7

0 . 0

2 1 0

– 0 . 4

4 5 8

– 0 . 2

6 0 8

– 0 . 0

5 1 9

0

. 1 8 0 2

0 . 5

5 0 0

0 . 6

2 4 8

5 . 7

3 8 5

8 3 . 4

2 2 0

4 3 . 4 7

1 , 9

9 2

8

0 . 0

2 7 6

– 0 . 4

8 6 4

– 0 . 2

7 0 8

– 0 . 0

6 0 6

0

. 1 8 9 1

0 . 5

7 7 7

0 . 7

1 4 5

4 . 5

5 9 8

4 6 . 5

7 9 1

4 3 . 4 0

1 , 1

3 6

9

0 . 0

0 0 3

– 0 . 4

4 3 2

– 0 . 2

6 2 5

– 0 . 0

3 5 4

0

. 2 0 2 6

0 . 5

5 2 5

0 . 5

0 3 3

– 0 . 3

9 6 3

6 . 6

8 9 6

4 4 . 2 7

2 5 3

L o w ( 0 – 3

)

– 0 . 1

0 5 3

– 0 . 6

5 1 5

– 0 . 3

5 4 0

– 0 . 1

4 3 2

0

. 0 8 1 1

0 . 4

5 6 8

1 . 0

1 1 6

4 . 5

5 2 8

6 4 . 0

7 2 2

3 2 . 6 1

2 , 4

0 1

M i d ( 4

– 6 )

0 . 0

0 4 7

– 0 . 5

2 0 8

– 0 . 2

8 0 5

– 0 . 0

7 1 4

0

. 1 5 9 5

0 . 5

5 8 0

0 . 8

0 8 8

6 . 5

0 5 6

1 2 1 . 6

9 5 6

4 0 . 1 3

6 , 0

2 8

H i g h ( 7 – 9

)

0 . 0

2 1 7

– 0 . 4

5 7 7

– 0 . 2

6 5 2

– 0 . 0

5 2 2

0

. 1 8 5 6

0 . 5

5 7 3

0 . 6

4 8 3

5 . 0

6 2 8

6 5 . 6

5 6 9

4 3 . 5 1

3 , 3

8 1

H i g h - l o w

0 . 1

2 7 0

0 . 1

9 3 8

0 . 0

8 8 8

0 . 0

9 1 0

0

. 1 0 4 5

0 . 1

0 0 5

– 0 . 3

6 3 3

0 . 5

1 0 0

1 . 5

8 4 7

3 . 3 8


0 . 0

0 0 0 * * *

0 . 0

0 0 0 * * *


14/24


P a n e l

B : S i z e - a d j u s t e d b u y - a n d - h o l d r e t u r n s b y F S C O R E c o m p o n e n t

R O A

C F O

∆ N I

A C C R U

A L

∆ L E V E R

C_

L I Q U I D

I S S U A N C E

∆ M A R G I N

∆ T U R N

L o w ( 0 – 3

)

– 0 . 0

1 1 5

– 0 . 0 5

2 6

– 0 . 0

0 4 7

– 0 . 0

7 9 8

– 0 . 0

0 2 0

– 0 . 0

3 6 0

– 0 . 0

6 8 1

– 0 . 0

0 8 6

– 0 . 0

2 5 3

M i d ( 4

– 6 )

– 0 . 0

0 2 1

0 . 0 1

5 4

– 0 . 0

4 6 7

0 . 0

1 6 5

– 0 . 0

0 4 1

0 . 0

3 1 9

0 . 0

1 3 1

– 0 . 0

0 9 3

– 0 . 0

0 0 2

H i g h ( 7 – 9

)

– 0 . 0

2 5 4

0 . 0 1

7 8

0 . 0

1 0 7

0 . 0

1 9 9

– 0 . 0

2 6 9

– 0 . 0

2 6 8

0 . 0

0 4 4

– 0 . 0

2 2 2

– 0 . 0

0 8 9

H i g h - l o w

– 0 . 0

1 3 9

0 . 0 7

0 4

0 . 0

1 5 4

0 . 0

9 9 7

– 0 . 0

2 4 9

0 . 0

0 9 2

0 . 0

7 2 5

– 0 . 0

1 3 6

0 . 0

1 6 4


0 . 4

4 3 8

0 . 0 0

0 0 * * *

0 . 4

1 4 2

0 . 0

0 0 0 * * *

0 . 1

9 1 8

0 . 6

1 7 9

0 . 0

0 0 0 * * *

0 . 4

6 1 8

0 . 3

8 8 8

N o t e s :

T h e F S C O R E i n v e s t m e n t s t r a t e g y c o n s i s t s o f a l o n g p o s i t i o n i n h i g h F S C

O R E fi r m s a n d a s h o r t p o s i t i o n i n l o w

F S C O R E fi r m s . “ L o w F S C O R E , ” “

M i d d l e

F S C O R E , ” a n d “ H i g h F S C O R E ” c o n s i s t o f

fi r m - y e a r s w i t h a n F S C O R E l e s s t h a

n o r e q u a l t o 3 , b e t w e e n 4 a n d 6 , a n d

g r e a t e r t h a n o r e q u a l t o 7 , r e s p e c t i v e l y . p - v a l u e a n d

Z - v a l u

e f o r d i f f e r e n c e s i n m e a n a n d m e d i a n

r e t u r n s b e t w e e n h i g h a n d l o w F S C O

R E p o r t f o l i o s a r e f r o m t - t e s t s o f m e a

n s a n d s i g n - r a n k e d W i l c o x o n t e s t s , r e s p e c t i v e l y .

* , * * , a n d * * * t w o - t a i l e d s i g n i fi c a n c e a t t h e

1 0 p e r c e n t , 5 p e r c e n t , a n d 1 p e r c e n t

l e v e l s , r e s p e c t i v e l y .


15/24


T a b l e

4 . A n n u a l b u y - a n d - h o l d r e t u

r n s u s i n g a t w o - d i m e n s i o n a l

v a l u e i n v e s t m e n t s t r a t e g y

B o o k - t o - m a r k e t

E a r n i n g s - t o - p r i c e

G l a m o r

V a l u e

V a l u e -

g l a m o r

G l a m o r

V a l u e

V a l u e -

g l a m o r

L o w_

B M

M i d_

B M

H i g h_

B M

L o w_

E P

M i d_

E P

H i g h_

E P

A l l F i r

m s

– 0 . 0

7 2 2

– 0

. 0 2 0 3

0 . 0

5 6 7

0

. 1 2 8 9

( 0

. 0 0 0 0 ) * * *

– 0 . 0

5 7 7

– 0 . 0

1 7 2

0 . 0

3 7 9

0 . 0

9 5 6

( 0 . 0

0 0 0 ) * * *

F S C O R E

L o w

( 0 – 3

)

– 0 . 0

7 1 2

– 0

. 1 3 5 9

– 0 . 0

9 8 0

– 0

. 0 2 6 8

( 0

. 6 2 8 0 )

– 0 . 1

3 8 1

– 0 . 0

7 6 4

– 0 . 0

6 0 8

0 . 0

7 7 3

( 0 . 0

9 7 0 ) *

M i d

( 4 –

6 )

– 0 . 0

8 4 7

0

. 0 1 7 6

0 . 0

7 3 6

0

. 1 5 8 3

( 0

. 0 0 0 0 ) * * *

– 0 . 0

0 6 3

– 0 . 0

1 9 1

0 . 0

4 7 1

0 . 0

5 3 4

( 0 . 0

8 5 4 ) *

H i g

h ( 7 – 9

)

– 0 . 0

5 2 2

– 0

. 0 0 7 1

0 . 1

5 0 2

0

. 2 0 2 4

( 0

. 0 0 0 0 ) * * *

– 0 . 0

4 3 3

0 . 0

1 6 7

0 . 0

5 4 7

0 . 0

9 8 0

( 0 . 0

0 1 4 ) * * *

H i g

h - l o w

0 . 0

1 9 0

( 0 . 6

5 5 8 )

0

. 1 2 8 8

( 0

. 0 0 0 0 ) * * *

0 . 2

4 8 2

( 0 . 0

0 0 0 ) * * *

0 . 0

9 4 8

( 0 . 0

2 5 7 ) * *

0 . 0

9 3 1

( 0 . 0

0 3 5 ) * * *

0 . 1

1 5 5

( 0 . 0

0 1 4 ) * * *

R e t u r n s u s i n g

i n c o n g r u e n t

s t r a

t e g y

0 . 2

2 1 4

( 0 . 0

0 0 0 ) * * *

0 . 1

9 2 8

( 0 . 0

0 0 0 ) * * *

R e t u r n s u s i n g

c o n

g r u e n t

s t r a

t e g y

– 0 . 0

4 5 8

( 0 . 3

0 9 7 )

– 0 . 0

1 7 5

( 0 . 6

5 0 9 )

N L o w ( 0 – 3

)

6 9 1

9 4 8

7 6 2

1 , 2

2 3

7 8 4

3 9 4

M i d ( 4

– 6 )

1 , 7

7 5

2 , 4

0 4

1 , 8

4 9

1 , 7

5 8

2 , 4

4 7

1 , 8

2 3

H i g h ( 7 – 9

)

1 , 0

7 0

1 , 3

8 6

9 2 5

5 5 9

1 , 4

9 8

1 , 3

2 4


16/24


C a s h - fl o w - t o - p r i c e

S a l e s g r o w t h

G l a m o r

V a l u e

V a l u e -

g l a m o r

V a l u e

G l a m o r

V a l u e -

g l a m o r

L o w_

C P

M i d_

C P

H i g h_

C P

L o w_

S G

M i d_

S G

H i g h_

S G

A l l fi r m s

– 0 . 0

8 8 5

– 0

. 0 1 2 3

0 . 0

6 2 1

0

. 1 5 0 6

( 0

. 0 0 0 0 ) * * *

– 0 . 0

1 7 3

0 . 0

0 6 5

– 0 . 0

3 4 4

0 . 0

1 7 1

( 0 . 4

0 5 2 )

F S C O R E

L o w

( 0 – 3

)

– 0 . 1

4 4 5

– 0

. 0 7 1 0

– 0 . 0

5 0 2

0

. 0 9 4 3

( 0

. 0 5 8 8 ) *

– 0 . 0

9 0 1

–

0 . 1

0 5 2

– 0 . 1

3 1

0 . 0

4 0 9

( 0 . 4

0�

Cho Et Al (2012) - The Value of a Two-Dimensional Value Investment Strategy

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Transcript of Cho Et Al (2012) - The Value of a Two-Dimensional Value Investment Strategy