Sustainable competitive advantage and stock performance: the case for wide moat stocks

Abstract

‘In business, I look for economic castles protected by unbreachable “Moats”’. Warren Buffett Companies that have sustainable competitive advantages should be able to create a barrier (Moat) to prevent or lessen competition from other firms. The wider the Moat the greater the barrier and the more secure the company’s profitability. Using the Morningstar classification of ‘Wide Moat’ stocks, we construct annually rebalanced equal- and value-weighted portfolios to analyse their performance in order to determine if they deliver superior performance relative to standard benchmark portfolios. The period for our analysis extends from June 2002 through May 2014. We find that the ‘Wide Moat’ portfolios outperform both the S&P 500 and Russell 3000 indices generating higher average monthly and annualized returns, Sharpe Ratio, Sortino Ratio, Treynor Ratio, Omega Ratio, Upside Potential Ratio, M2, M2 Alpha, and cumulative returns. When we compute alpha using Carhart four-factor and Fama–French five-factor models, we find that ‘Wide Moat’ portfolios had significantly positive risk-adjusted alphas with both the models. ‘Wide Moat’ portfolios also lost less value during the 2007–2009 financial crisis compared to both S&P 500 and Russell 3000. In conclusion, we find that ‘Wide Moat’ stocks have created significant value for their investors over the course of our study.

Full text

Full Terms & Conditions of access and use can be found at
https://www.tandfonline.com/action/journalInformation?journalCode=raec20
Applied Economics
ISSN: 0003-6846 (Print) 1466-4283 (Online) Journal homepage: https://www.tandfonline.com/loi/raec20
Sustainable competitive advantage and stock
performance: the case for wide moat stocks
Srinidhi Kanuri & Robert W. McLeod
To cite this article: Srinidhi Kanuri & Robert W. McLeod (2016) Sustainable competitive advantage
and stock performance: the case for wide moat stocks, Applied Economics, 48:52, 5117-5127, DOI:
10.1080/00036846.2016.1170938
To link to this article: https://doi.org/10.1080/00036846.2016.1170938
Published online: 13 May 2016.
Submit your article to this journal
Article views: 276
View Crossmark data

Sustainable competitive advantage and stock performance: the case for wide
moat stocks
Srinidhi Kanuri
a
and Robert W. McLeod
b
a
Department of Finance, Real Estate, and Business Law, College of Business, University of Southern Mississippi, Hattiesburg, MS, USA;
b
Department of Economics, Finance, and Legal Studies, Culverhouse College of Commerce, University of Alabama, Tuscaloosa, AL, USA
ABSTRACT
‘In business, I look for economic castles protected by unbreachable “Moats”’. Warren Buffett
Companies that have sustainable competitive advantages should be able to create a barrier
(Moat) to prevent or lessen competition from other firms. The wider the Moat the greater the
barrier and the more secure the company’s profitability. Using the Morningstar classification of
‘Wide Moat’stocks, we construct annually rebalanced equal- and value-weighted portfolios to
analyse their performance in order to determine if they deliver superior performance relative to
standard benchmark portfolios. The period for our analysis extends from June 2002 through May
2014. We find that the ‘Wide Moat’portfolios outperform both the S&P 500 and Russell 3000
indices generating higher average monthly and annualized returns, Sharpe Ratio, Sortino Ratio,
Treynor Ratio, Omega Ratio, Upside Potential Ratio, M
2
,M
2
Alpha, and cumulative returns. When
we compute alpha using Carhart four-factor and Fama–French five-factor models, we find that
‘Wide Moat’portfolios had significantly positive risk-adjusted alphas with both the models. ‘Wide
Moat’portfolios also lost less value during the 2007–2009 financial crisis compared to both S&P
500 and Russell 3000. In conclusion, we find that ‘Wide Moat’stocks have created significant
value for their investors over the course of our study.
KEYWORDS
Competitive advantage;
performance; risk-adjusted
returns
JEL CLASSIFICATIONS
G11; G12; G14
I. Introduction
The importance to a company of establishing and
maintaining a competitive advantage is well estab-
lished. Porter (1985) developed the five forces model
to provide a framework to assist companies in eval-
uating the competitiveness of a particular market
and for strategy development. The forces described
in his model were centred on the rivalry among
existing competitors in the industry. The degree of
rivalry was determined by the other forces, which
include bargaining power of suppliers; bargaining
power of customers; threat of new entrants; and
threat of substitutes.
1
Having a competitive advan-
tage enhances the ability of a company to generate
superior performance relative to its competitors.
According to Alber (2013), these competitive advan-
tages could be comparative or differential. He
describes comparative advantage as the ‘. . . firm’s
ability to produce its products at a lower cost than
its competitors while differential advantage focuses
on firm’s ability to produce at a better quality com-
pared with its competitors’.
McGrath (2013) supports the position that com-
panies should move beyond the concept of a sustain-
able competitive advantage and focus on increasing
their ability to rapidly identify, capture, and exploit
new opportunities and move on before they run
their course. Her position is based on the premise
that competitive advantages are transient. Other
seminal works by Deming (1982) and Juran (1982)
support the notion that quality is integral to estab-
lishing and maintaining competitive advantages.
Companies with sustainable competitive advantages
are referred to as ‘Wide Moat’stocks.
In this article, we utilize the Morningstar classifi-
cation of ‘Wide Moat’stocks to construct annually
rebalanced portfolios by deleting companies that
have lost their wide Moat status and adding those
companies that achieved wide Moat status. Our ana-
lysis begins in June 2002 and ends in May 2014. We
analyse the performance of the wide Moat portfolios
CONTACT Robert W. McLeod rmcleod@cba.ua.edu
1
Porter’s five forces were later expanded to six with the inclusion of the impact of complimentary products.
APPLIED ECONOMICS, 2016
VOL. 48, NO. 52, 5117–5127
http://dx.doi.org/10.1080/00036846.2016.1170938
© 2016 Informa UK Limited, trading as Taylor & Francis Group

relative to common stock market benchmarks. Using
multiple models, we find that the ‘Wide Moat’port-
folios deliver superior performance relative to the
benchmark portfolios.
The remainder of this article is organized as fol-
lows: Section II gives a comprehensive literature
review; Section III provides information on the
source of the data used in our study and the selec-
tion process for the Wide Moat stocks; Section IV
explains the research methodology and results;
Section V concludes the article.
II. Literature review
Other papers, which look at risk-adjusted perfor-
mance (RAP) of a portfolio of firms and compare
them to benchmark indices are as follows: Anderson
and Smith (2006) look at the stock performance of
the companies identified each year by Fortune maga-
zine as the most admired companies in the United
States for 1983 through 2004. A portfolio of these
stocks outperformed the market by a substantial and
statistically significant margin, which contradicts the
efficient market hypothesis. Fabozzi, Ma, and
Oliphant (2008) look at the RAP of stocks associated
with sin activities (such as consumption of alcohol,
adult services, gaming, tobacco, weapons, and bio-
tech alterations) in 21 countries from 1970 to 2007
and compare them to their respective national
benchmark indices. The sin portfolio produced an
annual return of 19%, outperforming common
benchmarks in terms of both magnitude and fre-
quency. Goenner (2008) looks at the performance
of Fortune’s‘100 Best Companies to Work for in
America’based on their superior employer-
employee relations. His results indicate that portfo-
lios, consisting of firms on the list, offer higher risk-
adjusted returns than the S&P 500 over the period
1998–2005. Anginer and Statman (2010) look at
Fortune Magazine’s annual list of ‘America’s Most
Admired’companies from April 1983 to December
2007. They find that stocks of admired companies
had lower returns, on average, compared to stocks to
spurned companies. They also find that increase in
admiration, on average lead to lower returns.
Edmans (2011) looks at the relation between
Employee Satisfaction and long run stock returns.
A value-weighted portfolio of the ‘100 Best
Companies to Work For in America’earned an
annual four-factor alpha of 3.5% from 1984 to
2009, and 2.1% above industry benchmarks. Kenny,
Johnson, and Kunkel (2013) look at the RAP of
Morningstar Tortoise and the Hare portfolios with
the stocks included in each portfolio published and
updated in the Morningstar Stock Investor monthly
newsletter. Results examining the Tortoise and Hare
portfolios indicate both portfolios outperform the
market when using the Sharpe, Treynor and
Sortino ratios; however, neither portfolio shows sta-
tistically significant abnormal returns when evalu-
ated using the CAPM and Carhart four-factor
model. They also look at a third portfolio which is
created by using equal weights of the Tortoise and
Hare portfolios. This combined portfolio exhibits a
significant abnormal return of 3.6% per year even
after accounting for systematic risk, small-firm
effect, book-to-market effect and the momentum
effect. Sum (2014) looks at the RAP of equally
weighted portfolio of best companies to work for in
the United States from 1998 to 2011. His results
show that an equal-weighted portfolio of the best
companies to work for exhibits positive average
risk premiums and average risk-adjusted excess
returns majority of the times. This is the first article
to look at the RAP of Wide Moat firms and compare
them to benchmark indices (S&P 500 and Russell
3000).
III. Data
The list of Wide Moat stocks for each year in our
study has been obtained from the Morningstar
Direct stock database. In order to identify companies
with sustainable competitive advantages,
Morningstar begins its classification of stocks by
comparing each company’s return on invested capi-
tal (ROIC) to its cost of capital. If the ROIC has
exceeded the cost of capital, this ‘excess return’
should create value for its shareholders.
For those companies that exhibit a positive excess
return in the past, the next step is to determine if
those returns are expected to continue. This stage of
the analysis attempts to identify a clear competitive
advantage using five economic sources. The first
economic source is ‘High Switching Costs’, which
equate time with money to switch to a competitor.
The second is ‘Cost Advantage’, which allows the
company to sell at the same price, but generate
5118 S.KANURIANDR.W.MCLEOD

higher profits (or have the option to gain market
share by pricing below the competition). The third is
‘Intangible Assets’such as patents, trade secrets,
licensing agreement, etc. The fourth is ‘Efficient
Scale’where the market is dominated by one or a
small number of companies. The fifth is ‘Network
Effect’, which reflects the increase in value of a
service as the number of users increases.
2
Once it has been determined by a selection review
committee that the company has one or more of the
identifiable competitive advantages and that there is
confidence that these advantages will result in excess
returns that will persist for at least 20 years, it will be
rated as a ‘Wide Moat’stock. According to
Morningstar, only approximately 10% of the stocks
reviewed receive this rating. Moats are not expected
to remain constant and change with time.
3
For example, a paper by Ellis and Sinegal
(Forthcoming) analysed data over a 10-year period
to determine the factors or actions that resulted in a
company improving its Moat. Their findings suggest
that in about 50% of the companies that had a Moat
upgrade were due to one or more of the following
factors:
(1) Restructuring (e.g. to concentrate on profit-
able lines of business and divest of less profit-
able ones).
(2) Consolidation (e.g. to achieve economies of
scale through mergers and acquisitions).
(3) Paradigm shift (e.g. a significant change in the
business model of the industry).
(4) Innovation (e.g. a new patent or process).
Ellis and Sinegal (Forthcoming) conclude that man-
agement action is the common element that results
in an increase in a company’s Moat.
Each portfolio year, stocks which have Wide Moat
status in June of the year (from 2002) were chosen and
a Wide Moat portfolio is formed. Wide Moat stocks
returns, market cap, Russell industry and sector clas-
sifications and S&P 500 and Russell 3000 monthly
returns were also obtained from Morningstar Direct
database. Monthly risk-free rates, the momentum fac-
tor (for the Carhart four-factor model), and the
Fama–French five factors (Fama–French five-factor
model) have been obtained from the Professor
Kenneth French’swebsite.
4
Descriptive statistics
Based on market cap, the Wide Moat companies are
classified as large cap (>$10 Billion), mid cap ($2–
$10 Billion) and small cap ($300 Million–$2 Billion)
every year.
5
Table 1 shows the number of Wide
Moat stocks in each classification for each portfolio
year. The majority of Wide Moat stocks for each
year are classified as large cap.
Since companies sometimes lose their Wide Moat
status, we also provide data on firms that have lost
this status. Table 2 shows a comparison of the num-
ber of Wide Moat firms for each portfolio year that
maintained their status relative to those that lost their
Table 1. The number of stocks classified as Wide Moat by
Morningstar and their capitalization. Large Cap (>$10 Billion),
Mid Cap ($2–$10 Billion) and Small Cap ($300 Million–$2
Billion). There were no Micro Cap ($0–$300 Million) Wide
Moat companies during the period of our analysis.
Time period # Wide Moat companies Large Mid Small
June 2002–May 2003 75 52 20 3
June 2003–May 2004 78 58 18 2
June 2004–May 2005 115 72 32 11
June 2005–May 2006 121 80 31 10
June 2006–May 2007 129 81 39 9
June 2007–May 2008 140 92 44 4
June 2008–May 2009 151 82 51 18
June 2009–May 2010 138 84 45 9
June 2010–May 2011 139 90 40 9
June 2011–May 2012 135 88 38 9
June 2013–May 2013 136 95 36 5
June 2012–May 2014 136 103 31 2
Table 2. The number of firms that maintained and lost their
Wide Moat status by the end of the portfolio year.
Time period
# Wide moat
companies
Maintain
status
Loose
status
June 2002–May 2003 75 56 19
June 2003–May 2004 78 78 0
June 2004–May 2005 115 107 8
June 2005–May 2006 121 120 1
June 2006–May 2007 129 122 7
June 2007–May 2008 140 134 6
June 2008–May 2009 151 133 18
June 2009–May 2010 138 132 6
June 2010–May 2011 139 135 4
June 2011–May 2012 135 121 14
June 2012–May 2013 136 127 9
June 2013–May 2014 136 129 7
2
Morningstar (2012). See also Appendix 1 for type of Moats. Appendix 2 presents firm characteristics that do not necessarily represent and economic Moat.
3
Appendix 3 gives a good summary of why Moats expand or shrink with time.
4
http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html
5
There were no microcap ($0–$300 Million) Wide Moat companies during the period of our study.
APPLIED ECONOMICS 5119

Wide Moat status by end of portfolio year. The num-
ber of firms that lost Wide Moat status varies con-
siderably from year to year with the greatest losses
occurring during market downturns (2002 and 2009).
Table 3 shows Wide Moat firms classified by
Russell sectors each portfolio year. As can be seen,
the financial services sector consistently had the
highest percentage of Wide Moat stocks during our
study period. The percentages, however, ranged
from less than 20% (2012–2013 and 2013–2014) to
as high over 36% in the period leading up to the
financial crisis (2007–2008).
IV. Methodology
Morningstar started classif
yingstocksasWide,Narrow
and No Moat in June 2002, which is the starting point
of our analysis.
6
Following Anderson and Smith (2006)
and Anginer and Statman (2010), we form annual
portfolios of Wide Moat stocks. We construct both
equal- and value-weighted portfolios for Wide Moat
stocks each year. Wide Moat (E) and Wide Moat (V)
represent equal-weighted and value-weighted portfo-
lios, respectively. To be included in a portfolio the
stock must be classified as a Wide Moat stock in June
of that portfolio year. The portfolio is dissolved in May
of the following year and a new Wide Moat portfolio is
again formed in June, i.e. the portfolio is again reba-
lanced after 12 months at the beginning of June 2003
and a new portfolio is formed for the period June
2003–May 2004. The same process is repeated and 12
equal-and value-weighted portfolios were created based
on annual rebalancing from June 2002 to May 2014.
7
These portfolios will then be evaluated using a
number of measures of risk, return, and RAP. We
will then analyse the performance for the Wide Moat
Portfolios using factor models. Finally, we will exam-
ine the performance of Wide Moat stock portfolios
during the financial crisis.
RAP
In order to evaluate the performance of the wide
Moat portfolios we compute various measures of
risk and return. In Table 4, we report the average
monthly returns, median monthly returns and stan-
dard deviation of monthly returns for Wide Moat
portfolio (both equal- and value-weighted), S&P 500
and Russell 3000 for the entire period of our study
from June 2002 to May 2014.
As can be seen, the Wide Moat portfolio (both
equal-weighted and value-weighted) had higher
Table 3. Shows Wide Moat firms classified by Russell sectors each portfolio year.
Year
Financial
services
Consumer
discretionary
Consumer
staples
Producer
durables Healthcare Technology Energy Utilities
Materials and
processing Total
June 2002–May 2003 21 11 7 10 8 10 2 6 0 75
28.00% 14.67% 9.33% 13.33% 10.67% 13.33% 2.67% 8.00% 0.00% 100.00%
June 2003–May 2004 23 12 8 6 14 11 2 2 0 78
29.49% 15.38% 10.26% 7.69% 17.95% 14.10% 2.56% 2.56% 0.00% 100.00%
June 2004–May 2005 40 16 9 14 14 13 8 1 0 115
34.78% 13.91% 7.83% 12.17% 12.17% 11.30% 6.96% 0.87% 0.00% 100.00%
June 2005–May 2006 42 16 11 15 15 15 6 1 0 121
34.71% 13.22% 9.09% 12.40% 12.40% 12.40% 4.96% 0.83% 0.00% 100.00%
June 2006–May 2007 43 18 12 14 16 16 8 1 1 129
33.33% 13.95% 9.30% 10.85% 12.40% 12.40% 6.20% 0.78% 0.78% 100.00%
June 2007–May 2008 51 24 9 19 16 13 6 1 1 140
36.43% 17.14% 6.43% 13.57% 11.43% 9.29% 4.29% 0.71% 0.71% 100.00%
June 2008–May 2009 48 23 11 22 15 15 9 2 6 151
31.79% 15.23% 7.28% 14.57% 9.93% 9.93% 5.96% 1.32% 3.97% 100.00%
June 2009–May 2010 35 23 11 21 18 14 8 2 6 138
25.36% 16.67% 7.97% 15.22% 13.04% 10.14% 5.80% 1.45% 4.35% 100.00%
June 2010–May 2011 36 20 14 21 18 13 8 2 7 139
25.90% 14.39% 10.07% 15.11% 12.95% 9.35% 5.76% 1.44% 5.04% 100.00%
June 2011–May 2012 35 18 12 21 19 13 9 2 6 135
25.93% 13.33% 8.89% 15.56% 14.07% 9.63% 6.67% 1.48% 4.44% 100.00%
June 2012–May 2013 27 16 14 21 20 17 12 3 6 136
19.85% 11.76% 10.29% 15.44% 14.71% 12.50% 8.82% 2.21% 4.41% 100.00%
June 2013–May 2014 20 13 18 21 21 15 19 2 7 136
14.71% 9.56% 13.24% 15.44% 15.44% 11.03% 13.97% 1.47% 5.15% 100.00%
6
In addition to identifying ‘Wide Moat’stocks, Morningstar analysts also introduced its ‘Tortoise and Hare’portfolios in 2001 with the goal of identifying
undervalued stocks. For an analysis of the performance of these portfolios see Kenny, Johnson, and Kunkel (2013).
7
The portfolios include the universe of Wide Moat stocks. We considered analysing multiple portfolios but given the relatively small number of Wide Moat
stocks a random selection process could lead to unintentional under or overweightings in certain sectors.
5120 S.KANURIANDR.W.MCLEOD

average monthly returns compared to both S&P 500
and Russell 3000 over the period of our study with
equivalent or lower standard deviations.
To adjust for risk differentials, we compute a
number of RAP measures, such as Sharpe Ratio,
Sortino Ratio, Treynor Ratio, Omega Ratio, Upside
Potential Ratio, and M
2
and M
2
Alpha for the Wide
Moat portfolio (both value- and equal-weighted),
S&P 500 and Russell 3000. A description of each of
these measures follows:
The Sharpe Ratio (1966) is calculated as:
Sharpe Ratio ¼RpRf

Rf
(1)
The second measure of RAP is the Sortino Ratio
(1991) expressed as
Sortino Ratio ¼RpRf

σd
(2)
The third measure we use is the Treynor Ratio
(1965), which is expressed as
Treynor Ratio ¼RpRf

βp
(3)
Where:
R
p
denotes the monthly returns on the portfolio.
R
f
is the monthly risk-free rate.
σ
p
is the standard deviation of portfolio’sexcess
returns.
σ
d
is the standard deviation of portfolio’s negative
returns.
β
p
is the systematic risk of the portfolio computed
with respect to CRSP value-weighted index, which
is value-weighted portfolio of all stocks from
NYSE, AMEX and NASDAQ.
The Sharpe Ratio evaluates how well an invest-
ment compensates its investor for each unit of
risk incurred. The higher the Sharpe Ratio, the
better is the performance of the investment. The
Sortino Ratio differentiates between good and bad
volatility in the Sharpe Ratio. The differentiation
of upward and downward volatility allows the
calculation of the risk-adjusted return to provide
a performance measure of an investment without
penalizing it for positive returns. A large Sortino
Ratio indicates low risk of large losses occurring.
Similar to the Sharpe Ratio, the higher the Sortino
and Treynor Ratios, the better is the performance
of a portfolio
The next RAP measure that we compute is the
Omega Ratio, which was introduced by Keating and
Shadwick (2002). This measure is a way of analysing
the performance of financial assets based on the level
of returns they offer in return for the risk of invest-
ing in them. It is a ratio of weighted gains to
weighted losses. The measure divides expected
returns into two parts –gains and losses, or returns
above the expected rate (the upside) and those below
it (the downside). Therefore, in simple terms, con-
sider omega as the ratio of upside returns (good)
relative to downside returns (bad). While the Sharpe
Ratio covers only the first two moments of return
distribution (means and variance), Omega Ratio
covers all moments of return distribution or the
Omega ratio is an alternative measure of asset per-
formance that gives the investor the information the
Sharpe Ratio discards:
Ω¼ðb
r
ð1FðxÞÞdx
ðr
a
FðxÞdx
(4)
Where:
F(x) is the cumulative probability distribution (i.e.
the probability that a return will be less than x);
ris a threshold value selected by the investor and
a,bare the investment intervals. It is effectively
equal to the probability weighted gains divided by
the probability-weighted losses after a threshold.
Table 4. The average monthly returns, median monthly returns
and standard deviation of monthly returns for Wide Moat
portfolio (both equal- and value-weighted), S&P 500 and
Russell 3000 for the period of our study (June 2002–May
2014). The Wide Moat portfolios are formed in June of each
calendar year and dissolved in May of the following year and
new portfolio is formed based on their Wide Moat rating in
June of the following year.
June 2002–May
2014
Average
monthly
returns (%)
Median
monthly
returns (%)
Standard
deviation of
returns (%)
P-value of
average
returns
Wide Moat
portfolio (E)
0.87 1.42 4.37 <0.01
Wide Moat
portfolio (V)
0.88 1.24 3.94 <0.01
S&P 500 0.68 1.32 4.35 <0.01
Russell 3000 0.72 1.36 4.48 <0.01
APPLIED ECONOMICS 5121

We also compute the Upside Potential Ratio which
was introduced by Sortino, Van Der Meer, and
Plantinga (1999). The Upside Potential Ratio mea-
sures upside potential relative to the downside var-
iance. This favours investments with stable growth
above a minimum acceptable return. It is defined by
UPR ¼Pþ1
MAR RMARðÞPr
PMAR
1 MAR RðÞPr

1
2
(5)
Where:
MAR is the minimum acceptable return, and is
chosen to match the investor’s goals.
Rare the empirical investment returns.
P
r
is the probability of making that return.
The numerator of the UPR is the first order
higher partial moment and the denominator is the
square root of the second order lower partial
moment.
As a final analysis of RAP, we compute two mea-
sures developed by Modigliani and Modigliani
(1997). Their measure expresses an investment’s per-
formance relative to the market in percentage terms,
which they believe the average investor would find
easier to understand. They called it the RAP or M
2
.
A related measure is Risk Adjusted Performance
Alpha (RAPA) or M
2
Alpha, which is defined as
RAP minus the risk-free rate.
M2or RAP ¼SRIσB
ðÞþRf(6)
M2Alpha or RAPA ¼SRIσB
ðÞ(7)
Where:
SR
I
is the Sharpe Ratio of the investment.
σ
B
is the standard deviation of CRSP value-
weighted index and R
f
is average risk-free rate
for the period of the analysis.
Table 5 shows that both equal- and value-
weighted Wide Moat portfolios had better RAP
compared to S&P 500 and Russell 3000, i.e. higher
Sharpe Ratio, Sortino Ratio, Treynor Ratio, Omega
Ratio, Upside Potential Ratio, M
2
and M
2
Alpha.
To present the wealth effects for a hypothetical
investor, we computed a Cumulative Wealth Index
(CWI) (following Woolridge 2004). Table 6 shows
the annualized returns and CWI for the equal- and
value-weighted Wide Moat portfolios, the S&P 500
and the Russell 3000 every year. CWI measures the
outcome of investing $1000 in each portfolio at the
beginning of June 2002, presuming reinvestment of
dividends.
Both equal- and value-weighted Wide Moat port-
folios outperformed both S&P 500 and Russell 3000
indices with higher average annualized returns (both
arithmetic and geometric), lower standard deviation
of returns and higher cumulative returns over the
entire period. Cumulative returns over the 12-year
period for equal- and value-weighted Wide Moat
portfolios, S&P 500 and Russell 3000 were 202.77%,
216.75%, 129.91% and 142.29%, respectively. As also
shown in Table 6 and Figure 1, the CWI over
12 years for the Wide Moat portfolio (E), Wide
Moat portfolio (V), S&P 500 and Russell 3000 were
$3027.69, $3167.46, $2299.09 and $2422.94,
respectively.
Results from Tables 4–6indicate that Wide Moat
portfolio had much better absolute and risk-adjusted
performance over both the indices.
Factor models
Performance (α) for wide Moat portfolio is also
computed using the following three models:
Carhart four-factor model (1997)
According to Elton, Gruber, and Blake (2011) the
most frequently used multi-factor model for measur-
ing portfolio performance is the three-factor model
Table 5. Risk-adjusted measures of performance –Sharpe Ratio, Sortino Ratio, Treynor Ratio, Omega Ratio, Upside Potential Ratio,
M
2
and M
2
Alpha for Wide Moat portfolio, S&P 500 and Russell 3000 index for the period of our study (June 2002–May 2014).
June 2002–May 2014 Sharpe Ratio Sortino Ratio Treynor Ratio Omega Ratio Upside Potential Ratio Kappa 3 ratio M2 (%) M2 Alpha (%)
Wide Moat portfolio (E) 0.17 0.26 0.008 1.57 0.70 0.079 0.88 0.76
Wide Moat portfolio (V) 0.19 0.30 0.011 1.67 0.75 0.088 0.98 0.86
S&P 500 0.13 0.18 0.006 1.40 0.63 0.056 0.69% 0.57%
Russell 3000 0.13 0.19 0.006 1.42 0.64 0.059 0.71% 0.59%
5122 S.KANURIANDR.W.MCLEOD

developed by Fama and French (1993). The Carhart
four factor (1997) model is similar to the Fama–
French three-factor model, but it includes an addi-
tional factor for momentum (MOM), which is the
return difference between a portfolio of past 12-
month winners and a portfolio of past 12-month
losers. The four-factor model is consistent with a
model of market equilibrium with four risk factors.
For each portfolio, monthly returns are used to
estimate the following regression:
RWMP;tRf;t¼αiþβiRm;tRf;t

þβsSMBtþβvHMLt
þβmMOM þεi:t(8)
Where:
R
WMP,t
= Wide Moat portfolio monthly returns
for month t.
R
f,t
= UST-bill rate for month t.
R
m
,
t
=returnonCRSPvalue-weightedindexfor
month t.
SMB
t
= realization on capitalization factor (small-
cap return minus large-cap return) for month t.
HML
t
= realization on value factor (value return
minus growth return) for month t.
MOM = Return difference between past 12-
month winners and 12-month losers.
ε
i
,
t
= an error term.
Table 6. The annualized returns and Cumulative Wealth Index (CWI) for each portfolio year. CWI measures the outcome of investing
$1000 in each portfolio at the beginning of June 2002, presuming reinvestment of dividends. Figure 1 shows increase in $1000
invested in each portfolio.
Time period
Wide
Moat
portfolio
(E) (%)
Wide
Moat
portfolio
(V) (%)
S&P
500
(%)
Russell
3000
(%)
CWI Wide Moat (E)
(initial wealth $1000
in June 2002)
CWI Wide Moat (V)
(initial wealth $1000
in June 2002)
CWI S&P 500
(initial wealth
$1000 in June
2002)
CWI Russell 3000
(initial wealth
$1000 in June
2002)
June 2002–May 2003 −2.01 −2.05 −8.06 −7.73 $979.92 $979.47 $919.38 $922.68
June 2003–May 2004 22.31 18.49 18.33 19.71 $1198.55 $1160.60 $1087.88 $1104.51
June 2004–May 2005 9.09 5.53 8.24 9.44 $1307.45 $1224.83 $1177.50 $1208.75
June 2005–May 2006 9.02 6.22 8.64 10.13 $1425.34 $1301.00 $1279.20 $1331.18
June 2006–May 2007 23.09 22.47 22.79 22.58 $1754.51 $1593.37 $1570.75 $1631.71
June 2007–May 2008 −6.14 −7.10 −6.70 −6.61 $1646.74 $1480.21 $1465.55 $1523.78
June 2008–May 2009 −23.99 −16.77 −32.57 −32.85 $1251.72 $1232.05 $988.24 $1023.18
June 2009–May 2010 23.84 19.39 20.99 23.20 $1550.13 $1470.89 $1195.68 $1260.53
June 2010–May 2011 26.24 29.93 25.95 27.04 $1956.92 $1911.13 $1505.95 $1601.36
June 2011–May 2012 0.29 5.51 −0.41 −1.87 $1962.66 $2016.43 $1499.73 $1571.43
June 2012–May 2013 29.31 29.91 27.28 27.88 $2537.90 $2619.56 $1908.79 $2009.54
June 2013–May 2014 19.30 20.92 20.45 20.57 $3027.69 $3167.46 $2299.09 $2422.94
Arithmetic average 10.86 11.04 8.74 9.29
Geometric average 9.67 10.08 7.18 7.65
Standard deviation 16.19 14.85 17.91 18.37
Cumulative returns 202.77% 216.75% 129.91% 142.29%
$0.00
$500.00
$1,000.00
$1,500.00
$2,000.00
$2,500.00
$3,000.00
$3,500.00
Wide Moat (E)
Wide Moat (V)
S&P 500
Russell 3000
Figure 1. The CWI, i.e. growth of $1000 invested in June 2002 in Wide Moat portfolio, S&P 500 and Russell 3000 index, presuming
reinvestment of dividends.
APPLIED ECONOMICS 5123

Here, a positive alpha would indicate superior
performance, whereas a negative alpha would indi-
cate underperformance, compared to the four-factor
model.
Fama–French five-factor model (2013)
Novy-Marx (2012), Titman, Wei, and Xie (2004) and
others say that Fama–French three-factor model is
an incomplete model for expected returns because
its three factors miss much of the variation in aver-
age returns related to profitability and investment.
Therefore, Fama and French (2013) add profitability
and investment factors to the three-factor model.
RWMP;tRf;t¼αiþβiRm;tRf;t

þβsSMBtþβvHMLt
þβpRMWtþβInvCMAt
þεi:t(9)
Where:
RMW
t
is the difference between the returns on
diversified portfolios of stocks
with robust and weak profitability and
CMA
t
is the difference between the returns on
diversified portfolios of the stocks of low and
high investment firms, which Fama–French call
conservative and aggressive.
As a robustness test, we also compute alpha for
equal- and value-weighted Wide Moat portfolios by
combining Fama–French five factors and momen-
tum factor.
RWMP;tRf;t¼αiþβiRm;tRf;t

þβsSMBtþβvHMLt
þβpRMWtþβInvCMAt
þβmMOM þεi:t(10)
As shown in Table 7, the Wide Moat portfolio
had significantly positive alphas with all the three
models. In the case of both equal- and value-
weighted Wide Moat portfolios, alpha is positive
and significant at least at 5% with all the three
models. These results indicate that Wide Moat port-
folio has created significant value for their investors
during the period of our study.
Performance during the 2007–2009 financial crisis
As a robustness test, we also look at the performance
of Wide Moat portfolios (both equal- and value-
weighted) during the recent major financial crisis
and compare them to S&P 500 and Russell 3000.
According to the Wall Street Journal, the most
recent bear market in US stocks (2007–2009) was
declared in June 2008 the Dow Jones Industrial
Average had fallen 20% from its 11 October 2007
high. The bear market reversed course during March
2009. Our analysis covers this financial crisis period
from October 2007 to March 2009 (Tables 8 and 9).
Table 7. The net alphas (for Carhart four-factor model and Fama–French five-factor model) for the Wide-Moat portfolio from June
2002 to May 2014. Reported are the estimates for equal- and value-weighted Wide Moat portfolio. All alphas have been annualized.
Standard errors are heteroscedasticity-consistent. T-stats are in brackets.
Wide Moat (E)
Annualized
Alpha (%)
Monthly
Alpha
(%) KSMB HML MOM RMW CMA R
2
Carhart four-factor
model
2.08 0.172** 0.9267682*** 0.0012678 0.0193119 −0.0748003*** 0.9647
[2.51] [44.59] [0.04] [0.66] [−3.63]
Fama–French five-
factor model
1.94 0.16** 0.9647375*** −0.0058968 0.0507269 0.0090668 −0.0682905 0.9593
[2.02] [39.97] [−0.15] [1.26] [0.19] [−0.91]
Fama–French five-
factors plus
momentum factor
1.84 0.152** 0.9410757*** 0.0262706 0.0169605 −0.0837045*** 0.0805668 −0.0571237 0.9661
[2.04] [42.33] [0.78] [0.49] [−5.22] [1.66] [−0.82]
Wide Moat (V)
Carhart four-factor
model
3.66 0.30*** 0.8715328 *** −0.274527*** −0.0206607 −0.044043 * 0.9072
[2.81] [20.38] [−4.84] [−0.28] [−1.94]
Fama–French five-
factor model
2.99 0.246** 0.9111079*** −0.2793186*** −0.0432918 0.0842697 0.14069* 0.9069
[2.23] [22.95] [−4.79] [−0.59] [1.39] [1.66]
Fama–French five-
factors plus
momentum factor
2.93 0.241** 0.8959565*** −0.2587207*** −0.0649136 −0.0535989** 0.1300536** 0.1478405 * 0.9103
[2.20] [21.36] [−4.56] [−0.89] [−2.53] [2.17] [1.77]
***Significant at 1%.
**Significant at 5%.
*Significant at 10%.
5124 S.KANURIANDR.W.MCLEOD

Our results indicate that the Wide Moat portfolio
performed better/lost less value than both S&P 500
and Russell 3000 indices during the 2007–2009
financial crisis as Wide Moat portfolios (both
equal- and value-weighted) had better absolute and
RAP returns over both the indices.
V. Conclusion
In this article, we study the performance of portfo-
lios of Wide Moat stocks which are companies that
have sustainable competitive advantages. Our results
indicate that Wide Moat stocks have created signifi-
cant value for their investors. An equal- and value-
weighted portfolio of these companies rebalanced
annually has outperformed both the S&P 500 and
Russell 3000 indices over the period of our study
(June 2002–May 2014) as evidenced by higher aver-
age monthly and annualized returns, Sharpe Ratio,
Sortino Ratio, Treynor Ratio, Omega Ratio, Upside
Potential Ratio, M
2
and M
2
Alpha.
WeprovideevidencethattheWideMoatport-
folio (both equal- and value-weighted) would
have created greater wealth for investors as mea-
sured by the CWI and also would have generated
significantly positive alphas over our sample per-
iod. Finally, when we compared the performance
of the Wide Moat portfolio with both the bench-
mark indices during the 2007 financial crisis
(October 2007–March 2009), the Wide Moat
portfolio lost less value compared to benchmark
indices. In summary, it is our conclusion that
investors who would have constructed portfolios
of stocks that have Wide Moats would have
experienced superior performance relative to con-
ventional benchmarks using multiple models of
risk, return and RAP.
Disclosure statement
No potential conflict of interest was reported by the authors.
References
Alber, N. 2013.“Competitive Advantages and Performance of
Stock Market: The Case of Egypt.”International Journal of
Economics and Finance 5(11).doi:10.5539/ijef.v5n11p133.
Anderson, J., and G. Smith. 2006.“A Great Company Can Be
A Great Investment.”Financial Analysts Journal 62: 86–
93. doi:10.2469/faj.v62.n4.4189.
Anginer, D., and M. Statman. 2010.“Stocks of Admired and
Spurned Companies.”The Journal of Portfolio Management
36 (3): 71–77. doi:10.3905/jpm.2010.36.3.071.
Carhart, M. M. 1997.“On Persistence in Mutual Fund
Performance.”The Journal of Finance 52 (1): 57–82.
doi:10.1111/j.1540-6261.1997.tb03808.x.
Deming, W. 1982.Quality, Productivity and Competitive
Position. Cambridge, MA: MIT Press.
Edmans, A. 2011.“Does the Stock Market Fully Value
Intangibles? Employee Satisfaction and Equity Prices.”
Journal of Financial Economics 101 (3): 621–640.
doi:10.1016/j.jfineco.2011.03.021.
Ellis, S., and J. Sinegal. Forthcoming.“How a Company
Increases Its Moat.”Morningstar, February/march 52–53.
Elton,E.J.,M.J.Gruber,andC.R.Blake.2011.“Holdings Data,
Security Returns, and the Selection of Superior Mutual
Funds.”Journal of Financial and Quantitative Analysis 46
(2): 341–367. doi:10.1017/S0022109011000019.
Table 8. The absolute and risk-adjusted performance (RAP) of Wide Moat portfolio (both equal- and value-weighted), S&P 500 and
Russell 3000 during the 2007–2009 financial crisis (October 2007–March 2009).
October 2007–March
2009
Average monthly
returns (%)
Median monthly
returns (%)
Standard deviation of monthly
returns (%)
Cumulative returns
(%)
P-value of average
returns
Wide Moat portfolio
(E)
−2.62 −2.88 6.79 −40.55 <0.05
Wide Moat portfolio
(V)
−2.37 −2.35 5.56 −36.84 <0.05
S&P 500 −3.15 −3.25 6.24 −45.08 <0.05
Russell 3000 −3.15 −1.95 6.50 −45.95 <0.05
Table 9. The absolute and RAP of Wide Moat portfolio (both equal- and value-weighted), S&P 500 and Russell 3000 during the
2007–2009 financial crisis (October 2007–March 2009).
October 2007–March 2009 Sharpe Ratio Sortino Ratio Treynor Ratio Omega Ratio Upside Potential Ratio Kappa 3 ratio M
2
(%) M
2
Alpha (%)
Wide Moat portfolio (E) −0.41 −0.44 −0.027 0.35 0.23 −0.174 −2.46 −2.60
Wide Moat portfolio (V) −0.45 −0.47 −0.031 0.30 0.21 −0.168 −2.74 −2.88
S&P 500 −0.53 −0.51 −0.034 0.23 0.16 −0.204 −3.23 −3.37
Russell 3000 −0.51 −0.49 −0.032 0.26 0.17 −0.200 −3.09 −3.23
APPLIED ECONOMICS 5125

Fabozzi, F. J., K. C. Ma, and B. J. Oliphant. 2008.“Sin Stock
Returns.”The Journal of Portfolio Management 35 (1): 82–
94. doi:10.3905/JPM.2008.35.1.82.
Fama,E.F.,andK.R.French.1993.“Common Risk
FactorsintheReturnsonStocksandBonds.”Journal
of Financial Economics 33 (1): 3–56. doi:10.1016/0304-
405X(93)90023-5.
Fama, E. F., and K. R. French 2013.“A Five-Factor Asset
Pricing Model.”Fama-Miller working paper, University of
Chicago, Dartmouth College and NBER.
Goenner, C. 2008.“Investing in Fortune’s 100 Best Companies
to Work for in America.”Journal of Economics 34 (1): 20.
Juran, J. 1982.Juran on Quality Improvement. New York:
Juran Institute.
Keating, C., and W. F. Shadwick. 2002.“AUniversal
Performance Measure.”Journal of Performance
Measurement 6(3):59–84.
Kenny, P., D. Johnson, and R. Kunkel. 2013.“Achieving
Superior Performance with the Morningstar’s Tortoise
and Hare Portfolios.”Applied Financial Economics 23
(24): 1865–1870. doi:10.1080/09603107.2013.856999.
McGrath, R. 2013.The End of Competitive Advantage: How
to Keep Your Strategy Moving as Fast as Your Business.
Boston: Harvard Business Review.
Modigliani, F., and L. Modigliani. 1997.“Risk-Adjusted
Performance.”The Journal of Portfolio Management 23
(2): 45–54. doi:10.3905/jpm.23.2.45.
Morningstar. 2012.“Construction Rules for Morningstar
Wide moat Focus Index.”Version 1.5. June 25.
Novy-Marx, R. 2012.“Is Momentum Really Momentum?”
Journal of Financial Economics 103 (3): 429–453.
doi:10.1016/j.jfineco.2011.05.003.
Porter, M. 1985.Competitive Strategy. New York: Free
Press.
Sharpe, W. F. 1966.“Mutual Fund Performance.”The Journal
of Business 39: 119–138. doi:10.1086/jb.1966.39.issue-S1.
Sortino, F., R. Van Der Meer, and A. Plantinga. 1999.“The
Upside Potential Ratio.”Journal of Performance
Measurement 4 (1): 10–15.
Sortino, F. A., and R. Van Der Meer. 1991.“Downside Risk.”
The Journal of Portfolio Management 17 (4): 27–31.
doi:10.3905/jpm.1991.409343.
Sum, V. 2014.“Why Should You Invest in the Best
Companies to Work For?”The Journal of Investing 23
(2): 69–73. doi:10.3905/joi.2014.23.2.069.
Titman, S., K. C. Wei, and F. Xie. 2004.“Capital
Investments and Stock Returns.”Journal of Financial
and Quantitative Analysis 39 (4): 677–700. doi:10.1017/
S0022109000003173.
Treynor, J. L. 1965.“How to Rate Management of Investment
Funds.”Harvard Business Review 43 (1): 63–75.
Woolridge, R. J. 2004.“Performance of Stocks Recommended
by Brokerages.”The Journal of Investing 13 (1): 23–34.
doi:10.3905/joi.2004.391039.
Appendices
Appendix 1. Appendix shows the type of Moat, its description, and example of companies which possesses it
Number Source of Moat Description Example
1 High switching
cost
High cost to switch to a competitor Oracle
2 Cost advantage Allows firm to sell at the price as competitors while earning profit/undercutting
competitors
Wal-Mart
3 Intangible assets Things that block competition/ cause competitors to cost more Coca-Cola, Pfizer
4 Efficient scale Market of limited size is served effectively by a small number of companies Lockheed Martin
5 Network effect The value of a network grows as more people use it Visa, MasterCard, eBay, Apple,
Amazon
5126 S.KANURIANDR.W.MCLEOD

Appendix 2. What’s not a Moat?
Source Reason Example
Size/dominant market High market share does not give company a moat. GM, Compaq
Technology What one smart engineer can invent, another engineer can make even better. Motorola
Hot products Can generate high returns on capital for a short period of time, but sustainable returns are
what make a moat.
Krispy Crème KKD, Crocs CROX
Process Can be imitated with time. Dell
Management CEOs can create (or destroy) a moat, but management is not a moat by itself Alcoa
http://www.webcastgroup.com/slideshow/webcast_5876/pdf.pdf and authors.
Appendix 3. Why Moats expand or shrink with time
Reason Example
Changes in competitive landscape Groupon
The firm’s investment strategy or business mix Pitney Bowes
Changes in consumer behaviour or preferences Chipotle
Changes in technological landscape Intuitive Surgical
Changes in regulatory/political landscape Medtronic
Demographics Covidien
http://www.webcastgroup.com/slideshow/webcast_5876/pdf.pdf
APPLIED ECONOMICS 5127