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Abstract

AAII.com ranks four stock-picking models by Buffet, Graham, Greenblatt, and O’Neil (CAN SLIM) that consistently outperform the S&P 500. Implementing these models requires complicated procedures an average investor might find challenging. Also, the website does not identify the companies comprising each portfolio or provide statistical analyses. We show how an inexpert investor can easily implement these models. Given that AAII.com ranks CAN SLIM the best, coupled with the observed popularity of this model among practitioners and student investment funds, we offer a simpler version of the model, which consistently outperforms the S&P 500.
44
APPLIED FINANCE LETTERS
VOLUME 12, 2023
TOWARDS A SIMPLIFIED CAN SLIM MODEL
MATHEW MAXWELL LUTEY1, TARUN MUKHERJEE2*
1. Indiana University Northwest, USA
2. University of New Orleans, USA
* Corresponding Author: Tarun Mukherjee, Moffett Chair in Financial Economics, University of New Orleans,
USA. ( +00 (504) 606-4139 * tmukherj@uno.edu
Abstract
AAII.com ranks four stock-picking models by Buffet, Graham, Greenblatt, and O'
Neil (CAN SLIM)
that consistently outperform the S&P 500. Implementing these models requires complicated
procedures that an average investor might find challenging. Also, the website does not identify the
companies comprising each portfolio or provide stat
istical analyses. We show how even an
unskilled investor can implement these models. Given that AAII.com ranks CAN SLIM the best,
coupled with the observed popularity of this model among practitioners and student investment
funds, we offer a simpler version of the model, which too consistently outperforms the S&P 500.
1. Introduction
The efficient capital market theory suggests that it is impossible to consistently beat the market
portfolio by picking stocks based on publicly available information: the most obvious implication is that
if one cannot beat the market portfolio, one might as well join it. Despite the market efficiency, a few
"Wizards" have consistently outperformed the market (usually, the S&P 500 Index). Warren Buffet,
Benjamin Graham, Joel Greenblatt, and William O 'Neil (CAN SLIM) fall in this distinguished group. None
of these individuals is privy to the inside information of the firms they hold in their portfolio. So, their
extraordinary success must be owing to their unique stock-picking acumen.
The margins of victory of the models over the S&P 500 have varied from one wizard to another. The
American Association of Individual Investors (AAII.com), among others, has studied the relative
efficiency of the four models. The stock screen on AAII.com gives real-time results of passing
companies and breaks down the criteria from the books published on the famous investor model1.
The website provides the reader with a list of criteria and then displays the results without the ability to
replicate them.2 The first objective of this paper is to show how ordinary investors can use these models
with relative ease to compare their efficiencies.
The CAN SLIM appears to be the best-performing Wizard strategy on the AAII stock screen. Also, the
CAN SLIM system has been widely used among practitioners and student investment funds.3 Despite
1 For example, Jack Schwager, Market Wizards, 1989 New York Institute of Finance.
2 When filtering forward, the screen shows the returns over the last three or five years or one year but does not show the passing
companies and does not allow for statistical analysis.
3 CAN SLIM’s parent company, Investor’s Business Daily, which the Wall Street Journal recently acquired, publishes a list of the
top 50 (IBD 50) following the CAN SLIM criteria. The list has claimed to beat the market over the last several years and has
become so popular that it is now an exchange-traded fund (ETF). Furthermore, student funds have found success using the
model. For example, the College of Business at East Carolina University ran a study using the CAN SLIM system and beat the
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
the popularity of CAN SLIM, an average investor will likely find its execution difficult. Our second
objective is to propose a much friendlier and shorter version of the model, the Adjusted CAN SLIM
method (hereinafter, ACS). Our work will help make implementing these models easier to average
investors, student-managed funds, and smaller institutions using tools for under $100 a month.4
The paper proceeds along the following lines. Section II describes the four Wizard models as well as
the ACS method we propose. We discuss the methodology in Section III and the results in Section IV.
Section V concludes.
2. Details of the Four Models
2.1 CAN SLIM
The CAN SLIM acronym is discussed in the book O 'Neil (2002, 1995). The letters stand for the investing
criteria such as current quarterly earnings (C), annual earnings (A), new products, new management,
new highs (N), supply and demand (S), leader, or laggard (L), institutional sponsorship (I), market
direction (M).
The system breaks down individual criteria for each letter in the acronym and how it should relate to
buying stock. The "C" and "A" letters refer to quarterly and annual growth rates; the higher, the better.
"N" stands for catalysts for growth or momentum. "S" refers to quarterly or annual sales growth (the
higher, the better) or supply and demand, such as buying stocks with high relative strength. "L" stands
for the position of stock within the industry and the industry's position in the market. The goal is to buy
leading stocks in leading industries. "I" stands for institutional sponsorship, large pension fund, and
institutional investing. This would refer to following smart money or large shareholders. "M" stands for
market direction and means to buy when the market is in an uptrend or expansion period. These are
all challenging criteria to screen for and automate, which makes replication and simulation difficult
for academic study. After meeting the above fundamental and checklist criteria, the study also looks
for stocks from O'Neil proper chart bases.
In summary, the CAN SLIM system recommends making investment decisions not purely based on
momentum but focusing on stocks with innovative products, services, and ideas, from properly timed
chart patterns, with explosive growth in earnings and before their price is run up5. According to O'Neil,
no one in their right mind buys stocks that have gone through excessive price increases following
extreme relative strength.
2.2 Graham
Benjamin Graham illustrates the method for value investing initially described in 1949. In addition,
several publications further elaborate on the technique.6 Graham describes buying growth stocks as
stocks with steady track records of increasing earnings per share (EPS) and high earnings per share
well above the norm for common stock. This is related to the CAN SLIM method of investing but is too
market from 1998 to 2005.3 The College of Business at the University of Southern California (USC) also uses the CAN SLIM
method by trading the IBD 50. North Coast Asset Management (northcoast.com) manages a CAN SLIM portfolio which is, to
our knowledge, the only investment fund created around a famous investor strategy.
4 It’s $84/month using portfolio123.com backtest.
5 The hand-collected analysis of CAN SLIM founder Bill O’Neil shows stocks improve 100% or more after meeting the CAN SLIM
criteria.
6 They include the one by Warren Buffet in the 1976 edition of Financial Analyst Journal titled Benjamin Graham.” Further,
Buffet explains investing strategies of Graham and Doddsville in “The Superinvestors of Graham-and-Doddsville.”
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
risky for defensive investing. Graham discusses buying common stock as buying in low markets and
selling in high markets, finding bargain issues, selectively choosing growth stocks, and buying special
situations. This sounds relatable and is similar to CAN SLIM.
The Enterprising Investor model suggested by Graham is more relatable to the CAN SLIM method and
involves buying bargain companies with a long dividend track record and strong earnings stability.
The strategy aims to find low price-earnings (P/E) ratio stocks. This is something the CAN SLIM method
ignores but is critical to Graham. These stocks are considered bargains. Graham also discusses finding
stocks with robust financial conditions. This involves picking stocks with a current ratio of at least 1.5
and long-term debt no higher than 100% of current assets. Graham recommends stocks with at least
a 5-year track record of positive earnings for earnings per share. Lastly, Graham recommends buying
stocks with a Price-to-Book-ratio (P/B) of 120% of tangible book value.
3.3 Buffett
Buffet's methodology is somewhat similar to Graham's. The Buffet factors include a strong uptrend in
earnings per share, high return on equity, high sustainable earnings per share, low debt to assets
compared to the industry, net profit margin and net operating margin better than the industry, and
better return on equity than the industry.
3.4 Greenblatt
Greenblatt is famous for the 'Magic Formula' of investing. The formula is based on two sorts, one for
value and another for quality. The purpose is to find quality companies that are undervalued. Stocks
are selected with the following characteristics: liquid stocks not trading on the over the counter (OTC)
market, a market cap of at least $50 million, no ADR stocks (the U.S. only), no financial companies,
utility companies, or Real Estate Investment Trusts (REITS), and high values of 5-year return on
investment. Appendix I details each strategy, the definition of the variable, and the corresponding
code for replication based on Portfolio123.com.
We make additional efforts to make implementing these models friendlier. First, we remove limiting
factors that would cause the model to hold only a few stocks at a time and give volatile results. For
example, the Buffet model's screening process includes a strong uptrend in earnings per share, high
return on equity, high sustainable earnings per share, low debt to assets compared to the industry,
net profit margin, and net operating margin better than the industry, and better return on equity
than the industry. We modify the Buffet model requirements to a) the stocks being in the top 75% of
earnings per share (EPS) compared to the industry, b) EPS better than the last three years compared
with the last seven, and c) EPS having grown within the past year and past seven years. Appendix II
provides the details of such modifications. Second, to help investors better understand some of the
technical words used in this paper, we provide a list of glossaries in Appendix III.
3. Methodology
3.1 Procedure
Following AAII's back-testing procedure, we scan each month for the list of passing stocks and carry
the portfolio for the next trading day7. We use data from the fact set to screen for the positions and
plug in the criteria for screening through a portfolio management tool from portfolio123.com, which
uses point-in-time data from FactSet. We combine the rules from AAII.com with what is already in
7 We take the positions at the average of the next trading day’s high, low, and 2x close and incur no carrying cost or
transaction costs.
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
portfolio123.com for implementing the four models. We follow the steps prescribed by each 'Wizard'-
Buffet, Graham, O'Neil, and Greenblatt and compare their performances.8
For benchmarking purposes, we select annual return, total return, standard deviation (for risk
measurement), Sharpe ratio (for risk-adjusted returns), and alpha and beta. These are commonly used
benchmarking measures (Neely et al., 2014).
AAII.COM's 'Wizard' model site suggests buying stocks that pass a fundamental filter each month and
dropping stocks from their portfolio that no longer pass the filter. This is known as rebalancing. For each
of our famous investor models, we modify the number of filters to aggregate any difference between
the AAII.com website, the books from the famous investor models, and the screening tool from
portfolio123.com (see Appendix II)9.
According to AAII.com, the CAN SLIM model performs best over the January 1998 March 2023
sample period. We shorten their sample period to match the maximum data available from
Portfolio123.com (January 1999-March2023). Shortening their sample involves recomputing the total
return for each model by downloading the data and recomputing the cumulative return across the
new sample. Doing this leads to a slightly different ranking of the models. For example, their site for the
new sample shows that Graham outperforms the CAN SLIM model. Our sample consistently gives CAN
SLIM the top ranking.
4. Results
We report the results in the two sub-sections below. In the first section, we compare the efficiency of
models relative to each other and the INDEX portfoliothe four models discussed above. The second
section explains the adjusted CAN SLIM model (ACS) and compares its results with the S&P500 index.
For a fee, AAII.com produces a list of the passing stocks from each screen. There are no legal issues
with producing the information on a paid or free document.
4.1 Comparing the Wizards
Figure 1 depicts the models' performances (including the market index) over the period from January
2, 1999, through March 2023. All models begin with an original investment of $100 (000's). All four Wizard
models overwhelmingly outperform the market index. In terms of performance ranking, CAN SLIM is at
the forefront with the ending portfolio value of $16,601.55, with Buffet being the second ($7,173.34)
and the third being nearly tied between Graham ($1,583.81) and Greenblatt ($1,367.08).
Table 1 compares five models, four Wizard models, and the S&P 500 across several performance
measures. In addition to annualized returns, the table provides Sharpe Ratio and alpha and beta; Max
Drawdown is defined as the lowest peak to trough on the equity curve, and Sharpe Ratio stands for
the return from the investment over the treasury bill divided by the investment standard deviation.
CAN SLIM ranks as the best performer among the five models. CAN SLIM has the highest annualized
returns. In addition, it has the highest alpha along with the lowest beta.
Although CAN SLIM ranks the best, the full implementation of the model is still complicated for an
average investor. To simplify the CAN SLIM strategy further, we suggest an adjusted CAN SLIM method
8 Investors that want to implement the screen in real-time would buy the list of passing companies and rebalance monthly.
9 AAII does not consider transaction costs. We do not either.
48
TOWARDS A SIMPLIFIED CAN SLIM MODEL
(ACS) for such investors. We do not expect the ACS model to perform as well as the fully executed
CAN SLIM model. We will consider the ACS model successful if it can beat the S&P 500.
Figure 1: Famous Investor Growth Models
Note: The Figure charts the investment growth of four Wizard models and the S&P 500 from January 2, 1999, to March 30, 2023.
The starting investment in each portfolio is $100.00.
Table 1: Comparing Efficiencies
Buffet
Graham
CAN SLIM
GREENBLATT
Total Return
7273.14%
1683.81%
16550.93%
1472.21%
Annualized Return
19.42%
12.63%
23.50%
12.04%
Max Drawdown
-49.44%
-51.84%
-55.08%
-56.77%
Sharpe
0.60
0.73
0.76
0.63
Std Dev
33.19%
15.94%
30.62%
18.66%
Beta
0.80
0.90
0.69
1.08
Alpha
16.04%
6.46%
20.99%
5.31%
Note: This table compares five models, four Wizard models, and the S&P 500 across several performance measures. Max
Drawdown is the lowest return from peak to trough, and Sharpe Ratio is the excess return divided by the standard deviation.
Alpha and beta are excess return and slope coefficients on the regression of the stock returns explained by the market return.
4.2 The ACS Model
We simplify the CAN SLIM model by using only the factors related to price and earnings per share.
While it seeks to mimic the full-scale CAN SLIM model results, the ACS model relies only on a simple
small-scale version of the key component factors of CAN SLIM (earnings and price). We call it the ACS
model because it is the acronym for adjusted CAN SLIM (A C S). Appendix III provides details of the
ACS model. We do not provide a shortened version of other models, but it would be an interesting
avenue for future work.
49
TOWARDS A SIMPLIFIED CAN SLIM MODEL
Figure 2 portrays the performances of the ACS model versus the S&P 500 and testifies to the consistent
superiority of the ACS model.
Figure 2: Returns on S&P 500 and the ACS Model
Note: The Figure charts the investment growth of the ACS model and the S&P 500 from January 2, 1999, to March 30, 2023. The
starting investment in each portfolio is $100.00.
Table 2 is similar in construction to Table 1 and compares the ACS model with the S&P 500 across
several performance measures. The results show that, from January 1999 through March 2023, the ACS
portfolio earned a 3,558.48% return compared to the S&P 500's 405.10%. Additionally, the ACS portfolio
has a lower beta and higher alpha than the market index. Thus, Figure 2 and Table 2 confirm the
superiority of the ACS model to the market index.
Table 2: Comparing Performances: ACS vs. S&P 500
ACS
S&P 500
Total Return
3558.48%
405.10%
Annualized Return
16.01%
6.91%
Max Drawdown
-47.01%
-55.19%
Sharpe
0.97
0.39
Std Dev
15.04%
15.41%
Beta
0.71
1
Alpha
10.87%
0.00%
Note: This table compares the ACS and S&P 500 models across several performance measures. Max Drawdown is the lowest
return from peak to trough, and Sharpe Ratio is the excess return divided by the standard deviation. Alpha and beta are excess
return and slope coefficients on the regression of the stock returns explained by the market return.
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
4/01/1999
4/01/2000
4/01/2001
4/01/2002
4/01/2003
4/01/2004
4/01/2005
4/01/2006
4/01/2007
4/01/2008
4/01/2009
4/01/2010
4/01/2011
4/01/2012
4/01/2013
4/01/2014
4/01/2015
4/01/2016
4/01/2017
4/01/2018
4/01/2019
4/01/2020
4/01/2021
4/01/2022
4/01/2023
ACS SP500
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
5. Conclusions
The efficient capital market theory suggests that it is not possible to consistently beat the market
portfolio by picking stocks based on publicly available information. However, a few "Wizards" have
consistently outperformed the market (specifically, the S&P 500 Index). Warren Buffet, Benjamin
Graham, Joel Greenblatt, and William O 'Neil fall into this distinguished group. None of these individuals
is privy to the inside information of the firms they hold in their portfolio. So, their extraordinary success
must be owing to their unique stock-picking acumen.
AAII.com, the official website of the American Association of Individual Investors, implements these
models based on the criteria espoused by the wizards and provides real-time results on their
performances (i.e., the last five-, three-, and one-year returns). An average investor is likely to find
replicating these models rather tricky. In addition, the website does not identify the companies
comprising each portfolio or provide statistical analyses. This paper demonstrates how ordinary
investors can use these Wizard models relatively easily.
Upon analyzing the four models, AAII.com places O'Neil's CAN SLIM model at the top. Our analyses of
these models also arrive at the same conclusion. The observed superior performance of CAN SLIM has
contributed to its popularity among practitioners and student investment funds. This model, however,
requires several steps that might be difficult for average investors to execute, thus prompting us to
suggest and implement a shorter and friendlier model, which we call Adjusted CAN SLIM (ACS). We
demonstrate that the ACS model consistently outperforms S&P500. The procedures outlined in this
paper will be helpful for individuals who want to manage their portfolios with limited time, expertise,
and resources.
References
AAII.com, the Website of The American Association of Individual Investors.
Buffett, W. (1976). Benjamin Graham (1894–1976). Financial Analysts Journal 32.6, 19-19.
Buffett, W. (1984). The super investors of Graham-and-Doddsville. Hermes, 4-15.
Graham, B (2005). Intelligent Investor: The Classic Text on Value Investing. Harper Collins
Han, Y., Yang, K., & Zhou, G. (2013). A new anomaly: The cross-sectional profitability of technical
analysis. Journal of Financial and Quantitative Analysis, 48(5), 1433-1461.
Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014). Forecasting the equity risk premium: the role of
technical indicators. Management Science, 60(7), 1772-1791
O'Neil, W. J., & Ryan, C. (2002). How to make money in stocks: A winning system in good times or bad
(p. 266). New York: McGraw-Hill.
O'Neil, W. J. "How to Make Money in Stocks: A Winning System in Good Times or Bad." (1995).
Schwager, J. D. (1989). Market Wizards. New York Institute of Finance.
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
Appendices
Appendix 1. Four Wizards’ Stock Screening Models
MODEL
STEPS DEFINITION OF VARIABLES PORTFOLIO 123.COM
Buffet 1 Stocks in the top 75%
of EPS compared to
the industry.
EPS Excluding Extraordinary Items is
earnings per share, including all-
expense except those deemed
extraordinary.
Frank("EPSExclXorGr%5Y",#industry)>25
2 Annual EPS has been
better in the last three
years than the last 7.
Growth=Earnings Per Share value
taken straight out of the SEC filing with
the most recent three-year and 7-
year values. The 3-year value is the
average growth over the last three
years, and the seven years is t.
EPSExclXor(2,ann)>=EPSExclXor(6,ann)
3 EPS grew over the
past year and the
past seven years.
EPS Growth Last year = % Change in
EPS from the previous year. EPS
Growth in the last Seven years is a
%Change in EPS from 7 years ago.
EPSExclXor(0,ann)>EPSExclXor(1,ann)
4 ROE last 12 months
better than the
industry median
ROE = Return on Equity divided by the
Average Common Equity as a
percentage. Average Common
Equity is the average of the Common
Equity at the beginning and the end
of the period. Median = The trailing
12-month return compared to the
median of the industry
EPSExclXor(0,ann)>EPSExclXor(6,ann)
5 ROE 5 year-average
better than the
industry
Average ROE = each year’s ROE for
the last five years added and divided
by five. The industry is value for each
stock trading in the same industry.
ROE%5YAvg>FMedian("ROE%5YAvg",#
industry)
6
Sustainable growth
rate in the top 15%
compared to industry
peers.
Sustainable Growth = Trailing twelve-
month Retention Rate multiplied by
the trailing twelve-month Return on
Equity, divided by 100.
Frank("SusGr%",#industry)>85
7 Debt to equity lower
than the industry
Debt To Equity = Total Debt divided
by Total Common Equity for the same
period.
DbtTot2EqQ <= DbtTot2EqQInd
8 Net profit margin
higher than the
industry
Net Profit Margin (NPM) = NPM
divided by Total Revenue for the
period expressed as a percentage
above value for industry value
NPMgn%TTM >= NPMgn%TTMInd
9 Operating profit
margin higher than
the industry
Operating Profit Margin = percent of
revenues remaining after paying all
operating expenses. It is calculated
as operating Income divided by Total
Revenue
OpMgn%TTM >= OpMgn%TTMInd
MODEL
STEPS DEFINITION OF VARIABLES PORTFOLIO 123.COM
Graham 1
No thinly traded over-
the-counter (OTC)
stocks. Choose more
liquid stocks.
Over the Counter = Least liquid
stocks. Universe(NOOTC)
2 Current ratio is at
least 1.5
Current Ratio = Total Current Assets
divided by Total Current Liabilities for
the same period.
CurRatioQ>=1.5
3
Long-term debt is less
than 110% of working
capital.
Long-term debt = All debt that is
due more than 12 months after the
date of the latest balance sheet,
DbtLTQ<=(CurAstQ- CurLiabQ)*1.10
4 Last four quarters of
EPS positive Positive EPS = EPS above 0 for each
of the last four quarters
EPSExclXor(0,qtr)>0 and
EPSExclXor(1,qtr)>0 and
EPSExclXor(2,qtr)>0 and
EPSExclXor(3,qtr)>0
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
5 Last five years of EPS
positive Positive EPS = EPS above 0 for each
of the last 5 years.
EPSExclXor(0,ann)>0and
EPSExclXor(1,ann)>0 and
EPSExclXor(2,ann)>0 and
EPSExclXor(3,ann)>0 and
EPSExclXor(4,ann)>0
6
Annual EPS grew over
the past year and
past five years.
EPS Growth = EPS this year above
last year’s and 5 years ago. EPSExclXor(0,ann)>EPSExclXor(1,ann)
andEPSExclXor(0,ann)>EPSExclXor(4,ann)
7
Company has paid
dividends within the
past year
Dividends = Dividends per share in
the previous year. DivPSTTM>0
MODEL
STEPS DEFINITION OF VARIABLES PORTFOLIO 123.COM
CAN SLIM
1 Percentile rank for %
institutional ownership
between 10 and 50
Percentile Rank = Percent of
Institutional Ownership in relation to
other stocks in the universe.
Institutional Ownership is the
number of institutional investors,
including large firms and pension
funds, who buy the stock.
Frank(" Inst%Own",#all,#desc)>=10 and
Frank(" Inst%Own",#all,#desc)<50
2
EPS growth (latest
qtr.) Percentile rank in
top 35%
Percentile Rank = EPS growth within
the top 35% of available stocks Frank(" EPSExclXorGr%PYQ")>=65
3 Share price % gain in
last 240 trading days
ranks in the top 35%
Share Price Gain = Share Price
Percent Gain in the top 35% of
available stocks over roughly last
year.
Frank("Close(0)/Close(240)")>=65
4
Distance between
the current price and
the 12-month high
ranks in top 50%
Distance = Current price is within
the top 50% of stocks trading near
their 12-month high. 5. Frank(" Price/ PriceH")>=50
MODEL
STEPS DEFINITION OF VARIABLES PORTFOLIO 123.COM
Greenblatt 1
Choose liquid stocks
not trading over the
counter (OTC).
Over the Counter = Least liquid
stocks. Universe(NOOTC)
2
Market cap is at least
$50 million.
Market Cap = Share Price x Shares
Outstanding.
MktCap>=50
3 U.S. stocks only, no
ADR
Non-U.S. companies = American
Depository Receipts (foreign
companies trading on a U.S.
exchange)
Universe($ADR)=false
4 No financial or utility
companies or REITs Financial sector, Utility Sector, Real
estate Investment Trusts !GICS(FINANC) and !GICS(UTILIT) and
!GICS(reoper)
5 5-year return on
investment is in the
top 35%
Return on Investment = This value is
the trailing twelve-month Income
After Taxes divided by the average
total long-term debt and
Stockholder’s Equity, expressed as a
percentage.
Frank(" ROI%5YAvg")>=65
MODEL
STEPS DEFINITION OF VARIABLES PORTFOLIO 123.COM
ACS Model
1
EPS growth is above
15% 5-year average,
and EPS growth is
above 25% in the
most recent quarter
compared to the
same quarter one
year prior.
EPS Growth 5-year average is each
year added over the last five years
divided by five, equal to 15% or
more. The most recent quarter is this
quarter’s EPS divided by the same
quarter last year minus one above
25%.
EPSExclXorGr%5Y>=15And
EPSExclXorGr%PQ > 25
2 Price is within 10% of
a new high High is stock price all-time high. The
price is the current price. Price >= 0.9 * PriceH
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TOWARDS A SIMPLIFIED CAN SLIM MODEL
Appendix II. Modification of the filters employed at AAII.com.
MODEL
AAII.COM OUR MODIFICATION
BUFFETT 1 Market capitalization (price * shares outstanding)
of greater than or equal to 1 billion dollars. No minimum cutoff market capitalization
2 Positive operating income for the trailing twelve
months and each of the last seven years Not considered
3 ROE greater than 15% Return on equity over the last 12 months (also
last five years) is better than the industry median.
4 Current operating profit margin greater than the
industry’s current median operating margin The current operating profit margin greater than
that of the industry over the last year.
5 The current net profit margin exceeds the industry’s
median operating profit margin. Net profit margin better than the industry’s
median last year.
6 Low price to free cash flows Not considered
7 EPS growth over the last year and seven years; a
sustainable growth rate within the top 15% of the
industry peers. Not considered
MODEL
AAII.COM OUR MODIFICATION
GRAHAM 1 Price-earnings ratio among the lowest 25% Not considered
2 Firms that intend to pay a dividend next year Firms that paid a dividend last year
3 EPS for the last 12 months is more significant than
the previous five years. EPS growth over the last 12 months and last five
years
MODEL
AAII.COM OUR MODIFICATION
CAN SLIM 1 Buy stocks with earnings per share up at least 20%
in the most recent quarter compared to the same
quarter one year prior.
EPS growth in the latest quarter is in the top 35%
of available stocks
2
Buy stocks with a growth rate in earnings in the
most recent quarter and the same quarter one
year prior greater than the growth rate in earnings
between two quarters ago and the same quarter
one year prior.
Not considered
3 Buy stocks with a growth rate in sales of at least
25% in the most recent quarter compared to the
same quarter one year prior. Not considered
4 Buy stocks with EPS from continuing operations for
the latest quarter greater than zero. Not considered
5
Buy stocks with EPS from operations in the last 12
months greater than earnings per share for the
previous year.
Not considered
6 Buy stocks with earnings per share from continuing
operations for the last year greater than earnings
per share from operations two years ago. Not considered
7 Buy stocks with earnings per share growing more
two years ago than three years ago and earnings
growing three years ago more than four years ago. Not considered
8 By stocks with consensus earnings for the current
year greater than diluted earnings for the last year. Not considered
9 By stocks with a three-year average growth rate
greater than or equal to 25%. Not considered
54
TOWARDS A SIMPLIFIED CAN SLIM MODEL
10 Buy stocks that have relative strength over 52
weeks greater than 80 Not considered
11 Buy firms with at least ten institutional shareholders. Not considered
12
Buy firms where the number of shares purchased
by institutions over the last quarter is greater than
or equal to the number sold over the previous
quarter.
The percentage of institutional ownership is
between 10 and 50 percent.
MODEL
AAII.COM OUR MODIFICATION
GREENBLATT 1 Buy stocks with EBIT/EV above the risk-free rate. The
higher, the better. Not considered
2 The higher the return on invested capital, the
better the investment We buy the top 35% of companies ranked by
return on invested capital.
3
Minimum market cap between 50 million and 5
billion
We use a cutoff of 50 million for the market cap
4 Rank stocks on return on capital (highest to lowest) Not considered
5
Next, rank on the ratio of EBIT to EV (highest to
lowest)
Not considered
6 Buy 20 to 30 stocks by purchasing five to seven
every few months. We buy all passing stocks.
7 Hold for one year We rebalance monthly
Appendix III. Glossary
Term Definition
ADR American Depository Receipts
Backtesting Backtesting involves following the historical buy and sells rules with data as it occurred at that point
in time and recording the performance.
Chart Bases Chart bases include a pattern, such as a trading range breakout, that would signal a low-risk entry
to buy the stock.
Chart Patterns Chart patterns include double bottom and inverse head and shoulders (see Lo et al. 2000).
Double Bottom A chart pattern indicating a reversal in stock prices from a selloff. The pattern involves a decline,
rebound, another decile to a similar level, and a final rebound to end the falling of stock prices.
Equity Curve The equity curve involves the plotting of a real money investment (e.g., growth of $1) from investing
in the fund returns.
High Relative
Strength Stocks that have been advancing by more than the market or have a high accumulation rating or
a large number of funds flowing into the stock.
Index INDEX is the S&P 500 Index and is used as our benchmark for success
Special Situations The payout is independent of stock market factors and is a one-time event.
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Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the predictive ability of technical indicators with that of macroeconomic variables. Technical indicators display statistically and economically significant in-sample and out-of-sample predictive power, matching or exceeding that of macroeconomic variables. Furthermore, technical indicators and macroeconomic variables provide complementary information over the business cycle: technical indicators better detect the typical decline in the equity risk premium near business-cycle peaks, whereas macroeconomic variables more readily pick up the typical rise in the equity risk premium near cyclical troughs. Consistent with this behavior, we show that combining information from both technical indicators and macroeconomic variables significantly improves equity risk premium forecasts versus using either type of information alone. Overall, the substantial countercyclical fluctuations in the equity risk premium appear well captured by the combined information in technical indicators and macroeconomic variables. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1838 . This paper was accepted by Wei Jiang, finance.
How to Make Money in Stocks: A Winning System in Good Times or Bad
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