Technical Analysis Of CAN SLIM Stocks

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Technical Analysis of CAN SLIMStocksA Major Qualifying Project ReportSubmitted to the Faculty ofWorcester Polytechnic InstituteIn Partial Fulfillment of the Requirements for aDegree of Bachelor of SciencebyBelin BeyogluMartin IvanovAdvised byProf. Michael J. RadzickiMay 1, 2008

Table of ContentsTable of Figures . 7Table of Tables. 91.Abstract . 102.Introduction and Statement of the Problem . 113.Background Research . 133.1.Fundamental Analysis . 133.1.1.Earnings per Share (EPS) . 143.1.2.Price-to-Earnings Ratio (P/E) . 143.1.3.Return on Equity (ROE) . 153.2.Technical Analysis . 153.2.1.The Bar Chart . True Range (ATR) . 17CAN SLIM . 183.3.1.C: Current Earnings Growth . 183.3.2.A: Annual Earnings Growth. 193.3.3.N: New Products, New Services, New Management, New Price Highs . 193.3.4.S: Supply and Demand . 193.3.5.L: Leader or Laggard .203.3.6.I: Institutional Sponsorship.203.3.7.M: Market.20Page 2

3.3.8.Our CAN SLIM Stock Selection . 213.4.TradeStation . 223.5.Performance Measurements. 223.5.1.Expectunity and System Quality Measurement . 223.5.2.Monte Carlo Analysis . 234. Complete Trading Strategies . 255.4.1.Set-up . 264.2.Entry . 274.3.Exit with a profit .284.4.Exit with a loss (Money management stop) . 294.5.Money Management . 29Back-Testing using TradeStation .305.1.Overview of the Back-Testing Procedure .305.2.Moving Average Crossover . 315.3.Bollinger Bands . 325.4.Keltner Channel . 335.5.Volume Breakout . 345.6.Donchian Channel 20-Day and 55-Day . 346. Results Attained from Back-testing . 366.1.Bollinger Bands . 366.1.1.TradeStation Settings . 366.1.2.AAPL: Apple Inc. (NASDAQ). 37Page 3

6.1.3.MTL: Mechel OAO (NYSE) . 386.1.4.RIMM: Research in Motion Limited (NASDAQ) . 386.1.5.Equity Curve. 396.1.6.Monte Carlo Simulation Results at a 95% Confidence.406.1.7.Raw System Quality Results .406.2.Volume Breakout . 416.2.1.TradeStation Settings . 416.2.2.AAPL: Apple Inc. (NASDAQ). 426.2.3.MTL: Mechel OAO (NYSE) . 436.2.4.RIMM: Research in Motion Limited (NASDAQ) . 436.2.5.Equity Curve. 446.2.6.Monte Carlo Simulation Results at a 95% Confidence. 456.2.7.Raw System Quality Results . 456.3.Moving Average Crossover . 466.3.1.TradeStation Settings . 466.3.2.AAPL: Apple Inc. (NASDAQ). 476.3.3.MTL: Mechel OAO (NYSE) .486.3.4.RIMM: Research in Motion Limited (NASDAQ) .486.3.5.Equity Curve. 496.3.6.Monte Carlo Simulation Results at a 95% Confidence. 506.3.7.Raw System Quality Results . 506.4.Keltner Channel . 51Page 4

6.4.1.TradeStation Settings . 516.4.2.AAPL: Apple Inc. (NASDAQ). 516.4.3.MTL: Mechel OAO (NYSE) . 526.4.4.RIMM: Research in Motion Limited (NASDAQ) . 536.4.5.Equity Curve. 536.4.6.Monte Carlo Simulation Results at a 95% Confidence. 546.4.7.Raw System Quality Results . 556.5.Donchian Channel 20-day . 556.5.1.TradeStation Settings . 556.5.2.AAPL: Apple Inc. (NASDAQ). 566.5.3.MTL: Mechel OAO (NYSE) . 576.5.4.RIMM: Research in Motion Limited (NASDAQ) . 576.5.5.Equity Curve. 586.5.6.Monte Carlo Simulation Results at a 95% Confidence. 596.5.7.Raw System Quality Results . 596.6.Donchian Channel 55-days .606.6.1.TradeStation Settings .606.6.2.AAPL: Apple Inc. (NASDAQ).606.6.3.MTL: Mechel OAO (NYSE) . 616.6.4.RIMM: Research in Motion Limited (NASDAQ) . 616.6.5.Equity Curve. 626.6.6.Monte Carlo Simulation Results at a 95% Confidence. 63Page 5 System Quality Results . 63Comparison of the Strategies . 647.1.System Quality Comparison . 647.2.Monte Carlo Simulation Comparison . 658. Conclusion . 669. Further Work . 6710.References .6811.Appendixes . 7011.1. Moving Average Crossover Strategy EasyLanguage Code . 7011.2.Donchian Channel Strategy EasyLanguage Code . 7111.3.Keltner Channel Strategy EasyLanguage Code. 7211.4.Bollinger Bands Strategy EasyLanguage Code . 7311.5.Volume Breakout Strategy EasyLanguage Code . 7411.6.CAN SLIM Stock Selection Indicator EasyLanguage Code . 7511.7.CAN SLIM Stock Selection (Symbols) . 79Page 6

Table of FiguresFigure 1: Bar Chart (What Are Charts?) . 17Figure 2- Trades Generated by Bollinger Bands, AAPL . 37Figure 3 - Trades Generated by Bollinger Bands, MTL . 38Figure 4 - Trades Generated by Bollinger Bands, RIMM . 38Figure 5 - Equity Curve Generated by Bollinger Bands. 39Figure 6 - Monte Carlo Results of Bollinger Bands at a 95% Confidence .40Figure 7 - Trades Generated by Volume Breakout, AAPL . 42Figure 8 - Trades Generated by Volume Breakout, MTL . 43Figure 9 - Trades Generated by Volume Breakout, RIMM . 43Figure 10 - Equity Curve Generated by Volume Breakout . 44Figure 11 - Monte Carlo Simulations Results for Volume Breakout at a 95%Confidence .45Figure 12 - Trades Generated by Moving Average Crossover, AAPL . 47Figure 13 – Trades Generated by Moving Average Crossover, MTL .48Figure 14 - Trades Generated by Moving Average Crossover, RIMM .48Figure 15 - Equity Curve Generated by Moving Average Crossover . 49Figure 16 - Monte Carlo Simulation Results for Moving Average Crossover at a 95%Confidence .50Figure 17 - Trades Generated by Keltner Channel, AAPL . 51Figure 18 - Trades Generated by Keltner Channel, MTL . 52Figure 19 - Trades Generated by Keltner Channel, RIMM. 53Figure 20 - Equity Curve Generated by Keltner Channel. 53Figure 21 - Monte Carlo Simulation Results for Keltner Channel at a 95% Confidence. 54Page 7

Figure 22- Trades Generated by Donchian Channel 20-Day, AAPL . 56Figure 23 - Trades Generated by Donchian Channel 20-Day, MTL . 57Figure 24 - Trades Generated by Donchian Channel 20-Day, RIMM . 57Figure 25 - Equity Curve Generated by Donchian Channel 20-Day . 58Figure 26 - Monte Carlo Simulation Results for Donchian Channel 20-Day at a 95%Confidence .59Figure 27 - Trades Generated by Donchian Channel 55-Day, AAPL .60Figure 28 - Trades Generated by Donchian Channel 55-Day, MTL. 61Figure 29 - Trades Generated by Donchian Channel 55-Day, RIMM . 61Figure 30 - Equity Curve Generated by Donchian Channel 55-Day . 62Figure 31 - Monte Carlo Simulation Results for Donchian Channel 55-Day at a 95%Confidence .63Page 8

Table of TablesTable 1 - TradeStation Settings for Bollinger Bands . 36Table 2- System Quality Results for Bollinger Bands .40Table 3 - TradeStation Settings for Volume Breakout. 41Table 4 - System Quality Results for Volume Breakout . 45Table 5 TradeStation Settings for Moving Average Crossover . 46Table 6 - System Quality Results for Moving Average Crossover . 50Table 7 - TradeStation Settings for Keltner Channel . 51Table 8 - System Quality Results for Keltner Channel . 55Table 9 - TradeStation Settings for Donchian Channel 20-day . 56Table 10 - System Quality Results for Donchian Channel 20-Day. 59Table 11 - TradeStation Settings for Donchian Channel 55-Day .60Table 12 - System Quality Results for Donchian Channel 55-Day . 63Table 13 - System Quality Results . 64Table 14 - Monte Carlo Simulation Results . 65Page 9

1. AbstractThis MQP combines fundamental and technical analysis by adding value to theCAN SLIM investment methodology through the concept of complete tradingstrategies. We utilize the TradeStation trading platform to evaluate five set-ups Donchian channel 20-day and 55-day, Keltner channel, Bollinger bands, movingaverage crossover and volume breakouts – by back-testing 559 CAN SLIM stocks for2007. For comparison purposes we employ system quality calculations and MonteCarlo analysis to assess the performance of each set-up.Page 10

2. Introduction and Statement of the Problem 51 trillion. That’s how much the stock market’s value is estimated at, making itabout four times the size of the U.S. economy. Its significance as a part of theAmerican financial system cannot be downplayed. It has provided Americans withimmense profit opportunities, enabling them to buy a new house, send their child toa top-tier university or retire early. These are dreams which each of us have but onlya few know the best path for realizing them. And how else given the seeminglyinfinite number of investment instruments - stocks, bonds, all those exoticderivatives, mutual funds, hedge funds Most people do not have the courage NOTto follow an analyst’s advice after watching CNBC or reading a free investmentnewsletter. They simply do not believe they could have a greater return by investingon their own and beating the average annual return of a mere 7.84% of the S&P 500for the past 50 years. (Moneychimp) And in part, they are right. To be a successfultrader, you need to be disciplined, to learn to disregard all the headlines and analysts’comments, taking emotions out of the game. You need to adhere to your own rulesunder any circumstances. You need to decide what you trade, when you trade, howyou enter a position and how you exit it, when you take profits and when you stopyour losses.The purpose of this MQP is to show individual investors a way to implement allthe above rules by introducing them to the development of complete tradingstrategies. As with many other stock trading strategies, ours incorporatesfundamental and technical analysis. We have decided that the former has alreadybeen perfected trough the CAN SLIM methodology created by William O’Neil (O'Neil,2002) and offered by Investor’s Business Daily (IBD). That’s why we do not intend tospend any more time deciding which stock has the necessary fundamentalPage 11

characteristics but concentrate on the latter part of the equation. Bill O’Neil and IBDprovide the individual investor with a list of CAN SLIM stocks but they offer onlylimited advice on when and how to buy or sell them. In our MQP we solve this issueby using the TradeStation trading platform which allows for the testing of varioustechnical indicators on the CAN SLIM stocks.In the first part of this report we will introduce you to the essence of fundamentaland technical analysis. We will cover those concepts we deem to be pertinent to thisMQP. After that we will guide you through the world of CAN SLIM stocks – whatthey are, where you can find them and how we are going to use them. Then we willintroduce you to the complete trading strategies and their five steps – set-up, entry,exit with a profit, exit with a loss and money management. In the end we will analyzethe CAN SLIM stocks for 2007 using TradeStation by testing five set-ups whilekeeping the other aspects of the complete trading strategy constant. To compare theperformance of each set-up we will use system quality calculations and Monte Carloanalysis which will allow us to differentiate between the strengths and weaknesses ofeach strategy. Finally, we reach the conclusion that the trend-following movingaverage crossover strategy combines the best out of the six strategies we back-testwith the CAN SLIM characteristics.Page 12

3. Background Research3.1.Fundamental AnalysisFundamental analysis is a method used to determine the value of a stock byanalyzing the financial data essential to the company with the goal of projectingfuture price movements. Investors examine the company’s financials and operationsby looking at sales, earnings, dividends, growth potential, assets, debt, management,products and competition, in order to verify if a stock should be bought or sold. Animportant characteristic of fundamental analysis is that it focuses exclusively onthose variables that are directly related to the company. The general market and thebehavioral variables in its methodology are in secondary focus.There are two different fundamental analysis methodologies. Value investorsassign a fair value to stocks by using a methodology that was developed by Grahamand Dodd (Value Investing). If this fair value is not equal to the actual market priceof the stock, fundamental analysts believe that the stock is under- or overvalued andthat it will settle towards the fair value.On the other hand, growth investors buy stocks at any given price and hope to sellit even higher. Although a stock might have a high price, indicated by a high price toearnings ratio, investors purchase the stock because of its potential high growth.Growth investing is considered riskier; however it is appealing to investors becauseof the high returns it promises.Generally, a follower of the fundamental analysis approach would initially startlooking at the overall economy and work their way down from industry groups toindividual companies. When the economy expands, most companies tend to benefitfrom this and grow, while most companies usually suffer when the economy declines.Page 13

Certain industry groups are prone to gain a better advantage relative to others inan expanding economy. The investor should determine those groups that will be bestaffected by the current economic environment. In determining this, importantfactors to be considered are the overall growth rate, market size, and the importanceof the group to the economy.When a certain industry group is selected, the investor should select a list ofcompanies before going on with a more detailed analysis. It is important to find theleaders and the innovators within the group. In this selection process, the investorshould consider the company’s business plan, management and sensible financials.By understanding the company’s business, traders can better position themselves tocategorize stocks within their relevant industry group.Quantitative analysis is the biggest part of fundamental analysis. This engageslooking at past data to forecast future earnings. Some of the variables used forfundamental analysis that are relevant to CAN SLIM Stocks are explained below.3.1.1. Earnings per Share (EPS)Earning per Share indicates the profitability of a company.Calculated as: Earnings per ShareEarnings per Share is a key ratio used in share valuations. It shows how much ofthe company’s profits, after tax, each shareholder owns.3.1.2. Price-to-Earnings Ratio (P/E)Although Earnings per Share is a great way to compare earnings acrosscompanies, it lacks in notifying the investor anything about how the market valuesthe stock.Page 14

Calculated as: Price to Earnings RatioThe P/E ratio is one way for investors to obtain an idea about how much themarket is willing to pay for a company’s earnings.3.1.3. Return on Equity (ROE)Return on Equity is an indicator of a company’s efficiency.Calculated as: Return on EquityIt shows how much profit a company is able to generate given the resourcesprovided by its stockholders. Companies with high and growing ROE are said to havegreat potential.3.2.Technical AnalysisWhile fundamental analysis focuses on determining the fair value of a stock bylooking at its financials, technical analysis considers the past price movements of astock to determine its future actions. Technical analysis is often described as an artwhich requires experience, skills and dedication in order to be mastered. Due to thenature of this short-term project, we will use the TradeStation platform to catch-upto the level of an experienced and skilled trader and apply technical analysis to theCAN SLIM stocks. Technical analysis is a versatile tool that can be applied to stocks,bonds, futures, options, commodities and other securities whose price is set by theforces of supply and demand. (Technical Analysis) Furthermore, technical analysismakes an extensive use of charts – e.g. bar charts, candlesticks charts, point andPage 15

figure charts. It can also be applied to different time frames depending on the tradingpreferences of the investor – intra-day, daily, weekly, monthly and even yearly.Technical analysis has been developed at the beginning of the century on thebasis of the Dow Theory – a theory pieced together from the writings of Charles Dowby William P. Hamilton, Robert Rhea and E. George Schaefer. Three importantassumptions can be derived from the Dow Theory: Price reflects all information available Prices trend and their movements exhibit certain patterns Price is what interests investors and not how it is arrived atThe first assumption states that price embodies all information available tothe public. Here technical analysis differs strongly from fundamental analysis as theformer assumes that price is the fair value of a stock while the latter uses all kinds ofrelevant data to come up with it.Technical analysts (also called technicians) believe that each stock has anunderlying trend or that at least not all of the stock movements are random. Onceidentified, the trend is used by technicians to capitalize on the future price movementof the stock.The third assumption runs again technical analysis counter to fundamentalanalysis by emphasizing the final price of a stock rather than any other fundamentalcharacteristics or finding out why the price is what it is. Much effort is directedtoward .predicting the future price direction so according to technical analysts it onlymakes sense to look at past price movements.Price movements are best observed when plotted on a chart. Thus, charts havebecome the technicians’ main tool to assess the current state of a stock, where it iscoming from and where it is heading to.Page 16

The next subsections will guide you through some terms and techniques whichare relevant to technical analysis and which we use in this MQP.3.2.1. The Bar ChartOne of the most widely used charts is the bar chart. For the formation of a barchart you need the close, high and low values of the price of a stock.Figure 1: Bar Chart (What Are Charts?)As you can see in Figure 1 the top and bottom of the bar represent the highest andlowest points reached by the price of the stock during the time period. The horizontalline is the closing price of the stock. Depending on the trading horizon, the close,high and low values could refer to minutes, hours, days, weeks or even months. Barcharts offer a great way to analyze the closing price relative to the high and low. If thestock closes higher in value relative to the open, then the bar is usually shaded black.If the bar is shaded red then the close is lower than the open.3.2.2. Average True Range (ATR)The Average True Range is a technical indicator developed by J. Welles Wilderand is a measure of the stock’s volatility. (Average True Range) To derive the ATRWilder started with the concept of the True Range which is defined as the greatest ofthe following: Current high less the current lowPage 17

The absolute value of the current high less the previous close The absolute value of the current low less the previous closeThe ATR is simply the moving average of the True Range over a specified timeperiod. For example, a more volatile stock will have a higher ATR (e.g., ATR of 4)than a stock experiencing lower level of volatility (e.g., ATR of 2).3.3.CAN SLIMCAN SLIM is a formula created by William J. O'Neil and represents a growthstock investment strategy that combines fundamental and technical analysis. BillO’Neil is the founder of the Investor's Business Daily (IBD), author of the book “Howto Make Money in Stocks” and a highly successful trader whose approach helps bothindividual and institutional investors improve their returns. CAN SLIM is a checklistfor seven common characteristics all great performing stocks have before their majorprice increase. In the next subsections we will walk you through each part of the CANSLIM stock selection process.3.3.1. C: Current Earnings GrowthThe first and foremost indicator of a stock’s performance has been shown byIBD’s research to be the current earnings growth of the company. The “C” rule saysthat stocks must show a major percentage increase in their current quarterlyearnings per share when compared to the same quarter one year ago. The generalrule of thumb is the higher the EPS growth, the better. However, those increasesshould be at least 25% and, preferably, they should be accelerating in at least thethree most recent quarters.Page 18

3.3.2. A: Annual Earnings GrowthIn addition to the strong quarterly earnings results a stock should also show amajor and consistent increase in its annual earnings growth for the past three years.A CAN SLIM stock should exhibit at least a 25% increase in its annual earnings pershare in each of the last three years. It is considered an even better indication if thereturn on equity is higher than 17%.3.3.3. N: New Products, New Services, New Management, NewPrice HighsIBD’s research shows that all great performing stocks are characterized by a novelevent that triggers the major increase in their stock prices. Often that could be ashakeup at the top management level that will change the strategic path the companypursues. This could also be a pioneering product or service that increases thecompany’s market share and improves its competitive advantage. O’Neil’sinvestment strategy views the price of each stock as its quality measure. Thus, stocksreaching new