The 31-year performance graph from inception of our weekly Leaders and Laggards Institutional Service is shown in this chapter. It proves what is potentially possible over a long period if you concentrate on innovative new entrepreneurial leaders that have a unique new product that’s better, faster, or cheaper than others in their field … and you face up to and eliminate your laggards and possible mistakes before they are allowed to deteriorate into huge losses.
Here are 10 charts of many of the better performers with annotations showing key facts known at the time each stock was first added to our service in, around, and following the general market follow-through of the March 12, 2009 market bottom.
You’ll note, half of these stocks, after the third or fourth worst market collapse in 100 years, had an average P/E ratio over 45, 6 of these innovators had an average return on equity of 45%, and all 10 averaged having their IPO in just the last 12 years.
Most averaged earnings up 40% in their latest quarter plus powerful earnings growth in the prior two or three years. All had unique industry leading products. So, you see … the winner’s secret is to always insist on and combine outstanding fundamentals together with sound chart patterns under accumulation during an uptrending general market.
The 2008 bear market was twice as long and deep as typical bears. The S&P 500 fell 58% in 17 months. Nearly all stocks were therefore coming up off the bottom of 50% to 80% or 90% declines. So, Amazon, Vistaprint, Priceline, Baidu, and Ctrip were all “potential deep cup-with-handle bases,” just starting up the right side of a cup, somewhat like Xerox in June 1962.
In 1929, the public was heavily involved in stocks, speculating with 10% cash and 90% margin. This is one reason why so many people got hurt when the market collapsed … they had too much debt.
However, margin debt as a percentage of market capitalization of NYSE stocks also reached an extreme level at the end of March 2000.
Banks in 1929 also had huge mortgage debt. This time around, banks had lower-quality mortgage debt. However, this subprime debt was strongly mandated and pursued by our key politicians in government from 1995 on, something they don’t want to admit as they investigate and blame everyone else rather than take responsibility for their major role in creating the subprime loan 2008 financial crisis. Great government intention—catastrophic results.
The first product we developed for institutional investors was the O’Neil Database Datagraph books, which contain extremely detailed charts on thousands of publicly traded companies. They were the first of their kind and represented an innovation in the institutional investment world.
We were able to produce these books at timely weekly intervals, updating them at market close every Friday. These comprehensive books were delivered to institutional money managers over the weekend in time for Monday’s market open. This quick turnaround (for its time) was achieved not only because of the equity database we compiled and maintained on a daily basis, but also because of our high-speed microfilm plotting equipment. In 1964, this costly computer machinery was so new no one knew how to get a graph out of it. Once this barrier was cleared, it was possible to turn out complex, updated graphs through an automated process, at the rate of one per second.
Today, the technology has advanced so far that we can generate the most complex stock datagraphs with hardly a second thought, and the O’Neil Database books became a mainstay at many leading mutual funds around the globe. Initially, each Datagraph displayed price and volume information, along with a few technical and fundamental data items. Today, each Data-graph displays 96 fundamental and 26 technical items, and these are available for more than 8,000 stocks in 197 proprietary industry groups. This means an analyst or portfolio manager can quickly compare any company to any other, either in the same industry or in the entire database.
We still offer the O’Neil Database books, with their 600 pages of Data-graphs, to our institutional clients as part of our overall institutional investment business. With the advent of the Internet and highly sophisticated computer technology, however, these old-technology, hard-copy books are being replaced by our most innovative flagship service, WONDA. WONDA stands for William O’Neil Direct Access, and it provides institutional clients with a direct interface to the O’Neil Database. The O’Neil Database now contains more than 3,000 technical and fundamental data items on more than 8,000 U.S. stocks, and WONDA allows users to screen and monitor the database using any combination of these data items.
We originally developed WONDA as an in-house system to manage our own money. In the 1990s, after years of real-time use and refinement, the service was rolled out as the newest William O’Neil + Co. service, available to the professional and institutional community.
Because WONDA was conceived and created by our in-house portfolio managers and computer programmers, the service was designed with the serious institutional money manager in mind. Institutional money managers must frequently make rapid decisions while under pressure, and WONDA offers a wide range of features that allows instantaneous access to and monitoring of crucial stock data and related information as the market is moving.
Some of our institutional clients who use WONDA say they can “practically print money” with the system. These clients run the gamut from very conservative value-type managers to hedge fund managers. Clearly, no computer system can print money, but that type of comment from some of our biggest and best institutional clients points out the functionality and effectiveness of WONDA.
The accompanying Datagraph of Dome Petroleum is marked up to highlight a few of the ways we interpret and use this display of fundamanetal and technical information. We suggested Dome to institutions in November 1977 at $48. Fund managers didn’t like the idea, so we bought the stock ourselves. Dome became one of our biggest winners at that time. This and the following case studies are real-life examples of how it’s actually done.
In July 1977, we suggested a stock no institution would touch: Pic ‘N’ Save. Most money managers felt the company was entirely too small because it traded only 500 shares a day, so we began purchasing it several months later. We had successful historical computer models of Kmart in 1962, when it traded only 1,000 shares a day, and Jack Eckerd Drug in April 1967, when it traded 500 shares a day, so we knew, based on its excellent fundamentals, Pic ‘N’ Save could become a real winner.
Precedent was with us. Both Kmart and Eckerd had become big winners after they were discovered. Average daily volume increased steadily. The same thing occurred with Pic ‘N’ Save. This little, unknown company, headquartered in Carson, California, turned in a steady and remarkable performance for seven or eight years. In fact, Pic ‘N’ Save’s pretax margins, return on equity, annual earnings growth rate, and debt-to-equity ratio were at that time superior to those of other, more widely accepted institutional growth favorites—such as Wal-Mart Stores—that we had also suggested.
I’ve always thought of finding an outstanding stock and buying it every point on the way up. That’s almost what happened with Pic ‘N’ Save. We bought it almost every point or two for several years. I liked the company because it gave a way for families of meager means to buy the necessities of life at exceptionally low prices. All told, we bought Pic ‘N’ Save on 285 different days and held it for 7½ years. When we finally sold it, while it was still advancing, our sale did not affect the market. Early purchases showed more than a 10-fold gain.
We first uncovered Tandy Corp. in 1967, but we were able to convince only two institutions to buy the stock. Among the reasons given for not buying it were that it didn’t pay a dividend and Charles Tandy was just a promoter. (Qualcomm was another stock considered to be too promotional from 1996 to 1998. We picked it up straight off the weekly chart in late 1998. It became the leading winner of 1999, advancing 20-fold.)
When I met Tandy in his office in downtown Fort Worth, Texas, my reaction was very positive. He was a brilliant financial man who also happened to be an outstanding salesman. He had innovative incentives, departmental financial statements, and highly detailed daily computer reports on sales of every item in every store by merchandise type, price, and category. His automated inventory and financial controls were almost unbelievable for that time.
After the stock tripled, Wall Street analysts started to acknowledge its existence. There were even a few research reports noting Tandy as an undervalued situation. Isn’t it strange how far some stocks have to go up before they begin to look cheap to everyone?
Many institutions think size is a problem. Because they manage billions of dollars, there never seem to be enough big-capitalization stocks they can buy.
Let’s face it: size is definitely an obstacle. It’s easier to manage $10 million than $100 million; it’s easier to manage $100 million than $1 billion; and $1 billion is a piece of cake compared to running $20 billion or $30 billion. The size handicap simply means it’s harder to buy or get rid of a huge stock holding in a small- or medium-sized company.
However, I believe it’s a mistake for institutions to restrict their investments solely to large-cap companies. In the first place, there definitely aren’t enough outstanding ones to invest in at any given time. Why buy a slow-performing stock just because you can easily acquire a lot of it? Why buy big-caps with earnings growing only 10% to 12% a year?
From 1981 to 1987, in the Reagan years, more than 3,000 dynamic, up-and-coming companies incorporated or had initial public offerings. This was a first, and was due mainly to several cuts in the capital gains tax during the early 1980s. Many small- to mid-sized entrepreneurial concerns became enormous market leaders that drove the unprecedented technology boom and expansion of new jobs in the 1980s and 1990s. Most were small, unknown companies, but you’ll recognize them now as some of the greatest winning companies of that period. Here is a partial list of the thousands of ingenious innovators that reignited growth in America until the March 2000 market top.
Adobe Systems, Altera, America Online, American Power Conversion, Amgen, Charles Schwab, Cisco Systems, Clear Channel Communications, Compaq Computer, Comverse Technology, Costco, Dell Computer, Digital Switch, EMC, Emulex, Franklin Resources, Home Depot, International Game Technology, Linear Technology, Maxim Integrated Products, Micron Technology, Microsoft, Novell, Novellus Systems, Oracle, PeopleSoft, PMC-Sierra, Qualcomm, Sun Microsystems, UnitedHealth Group, US Healthcare, Veritas Computer, Vitesse Semiconductor, Xilinx.
As mentioned earlier, our government should lower the capital gains tax again and shorten the holding period to six months to help fuel a new cycle of entrepreneurial start-up companies and jobs.
Today’s markets are more liquid than past markets, with volume of many medium-sized stocks averaging 500,000 to 5,000,000 shares a day. In addition, significant block crossing between institutions also aids liquidity. The institutional manager handling billions of dollars would be best advised to broaden his prospects to the 4,000 or more innovative companies available. This is better than restricting activities to the same few hundred large, well-known, or legal-list-type companies. And today, a huge number of international entrepreneurial stocks are available.
A sizable institution would probably be better off owning 500 companies of all sizes than 100 large, mature, slow-moving companies. Pension funds can address size problems of their own by spreading their money among several different managers with different investment styles. However, size isn’t the number one problem for institutional investors. Frequently, it’s their investment philosophies and methods that keep them from fully capitalizing on the potential of the market. Superior performance comes from fresh ideas, not from the same old overused, stale names or last cycle’s favorites. For example, the super tech leaders of 1998 and 1999 will probably be replaced by many new consumer leaders in the twenty-first century.
Many institutions buy stocks on the way down, but bottom fishing isn’t always the best way to achieve superior performance. It can place decision makers in the position of buying stocks slowly deteriorating or whose growth is decelerating.
Other money management groups use valuation models that restrict investments to stocks in the lower end of their historical P/E ranges. This approach works for a number of unusually capable, conservative professionals, but over time, it rarely produces superior results. Several major Midwest banks that use this approach have lagged in performance.
Too many analysts have a P/E hang-up. They want to sell a stock with a P/E that’s up and buy one if its P/E is down. Fifty years of models of the most successful stocks show low or “reasonable” P/Es do not cause huge increases in price. Those who buy low P/Es probably missed every big stock market winner of the last half century.
Most of those who concentrate on the undervalued theory of stock selection may lag today’s better managers. Sometimes these undervalued situations get more undervalued or lag the market for a long time. In the market free-fall in late 2008 and early 2009, I noticed several value funds that were down about as much as some of the growth funds, which is unusual.
Over the previous 12 business cycles, it’s been my experience the best money managers during a cycle produced average annual compounded total returns of 25% to, in a few rare cases, 30%. This small group consisted of either growth-stock managers or managers whose most successful investments were in growth stocks plus a few turnaround situations.
The best undervalued-type managers in the same period averaged only 15% to 20%. A few had gains of over 20%. Most typical investors haven’t prepared themselves enough to average 25% or more per year, regardless of the method used.
Value funds will do better in down or poor market periods. Their stocks typically haven’t gone up a large amount during the prior bull market periods, and so they will correct less. Therefore, people who want to prove the value case will pick a market top as the beginning point of a 10-year period to compare value with growth investing. This is an unfair comparison in which value investing may “prove” more successful than growth-stock investing. The reality is if you look at the situation fairly, growth-stock investing usually outperforms value investing over most periods. I am also not convinced over- and under-weighting relative to the S&P 500 Index is as wise as some managers believe.
Another widely used expensive and ineffective practice is to hire a large number of analysts and divvy up coverage by industry.
The typical securities research department has an auto analyst, an electronics analyst, an oil analyst, a retail analyst, a drug analyst, and on and on. But this setup is not efficient and tends to perpetuate mediocre performance. What does an analyst who is assigned two or three out-of-favor groups do? Recommend the least bad of all the poor stocks she follows?
On the other hand, the analyst who happens to follow the year’s best-performing group may recommend only two or three winners, missing many others. When the oil stocks boomed in 1979 and 1980, all of them doubled or tripled. The best shot up five times or more.
The theory behind dividing up research is to allow them to be an expert on an industry. In fact, Wall Street firms may hire a chemist from a chemical company to be their chemical analyst and a Detroit auto specialist to be their auto analyst. These individuals may know the nuts and bolts of their industries, but in many cases, have little understanding of the general market and what makes leading stocks go up and down. Maybe this explains why virtually every analyst appearing on CNBC after September 2000 continued to recommend buying high-tech stocks on their way to 80% to 90% declines. People lost a lot of money if they followed this free advice on TV. A similar repeat performance occurred in 2008, when some fundamental analysts recommended buying oils and banks on their way down since they looked cheap. They then got a lot cheaper. An analyst’s job should be to make money for clients.
Firms like to advertise they have more analysts, the largest department, or more top-ranked “all-star” analysts. I’d rather have five good analysts who are generalists than 60 or 70 who are confined to limited specialties. What are your chances of finding 60 or more analysts who are outstanding at making money in the market or finding moneymaking ideas?
The shortcomings of Wall Street analysts were never made plainer to investors than during the 2000 bear market. While the market continued to sell off and become the worst bear market since 1929, and former high-flying tech and Internet stocks were being decimated, Wall Street analysts continued to issue “buy” or “strong buy” recommendations on these stocks.
In October 2000, one major Wall Street firm ran full-page ads calling the market “One of the Ten Best Times to Own Stocks” in history. As we now know, the market continued to plummet well into 2001 and 2002, making that period one of the worst times in history to own stocks! It was not until many of the tech and Internet high-flyers were down 90% or more from their peaks that these analysts finally changed their tune—many days and many dollars late!
A December 31, 2000, New York Times article on analysts’ recommendations quoted Zacks Investment Research as follows: “Of the 8,000 recommendations made by analysts covering companies in the Standard & Poor’s 500 Index, only 29 now are sells.” In the same article, Arthur Levitt, chairman of the Securities and Exchange Commission, stated: “The competition for investing banking business is so keen that analysts’ sell recommendations on stocks of banking clients are very rare.” A mutual fund manager quoted by the Times said: “What passes for research on Wall Street today is shocking to me. Instead of providing investors with the kind of analysis that would have kept them from marching over the cliff, analysts prodded them forward by inventing new valuation criteria for stocks that had no basis in reality and no standards of good practice.” Vanity Fair also ran an interesting article on the analytical community in August 2001. Clearly, at no time in the history of the markets has the phrase caveat emptor had more meaning for investors, both institutional and individual alike.
The implementation of SEC Rule FD, governing fair disclosure of material company information to both institutional and individual investors, in 2000 has restricted the ability of major brokerage research analysts to receive inside information from a company before it is released to the rest of the Street. This further reduced any advantage that can be gained by listening to most Wall Street analysts. We prefer to deal only with facts and historical models rather than opinions about supposed values. Many research analysts in 2000 and 2001 had not been in the business for 10 years or longer and therefore had never experienced the terrible bear markets of 1987, 1974–1975, and 1962.
On still another subject, many large money-management groups probably deal with entirely too many research firms. For one thing, there aren’t that many strong research inputs, and dealing with 20 or 30 firms dilutes the value and impact of the few good ones. Confusion, doubt, and fear created by conflicting advice at critical junctures may prove to be expensive. It would be interesting to know how many analysts have been highly successful in their own investments. This is the ultimate test.
A Financial World article dated November 1, 1980, also found that analysts selected by Institutional Investor magazine as the best on Wall Street were overrated and overpaid, and they materially underperformed the S&P averages. As a group, the “superstar” analysts failed on two out of three stock picks to match either the market or their own industry averages. They also seldom provided sell recommendations, limiting most of their advice to buys or holds. The Financial World study confirmed research we performed in the early 1970s. We found only a minority of Wall Street recommendations were successful. We also concluded during a period where many sell opinions were in order, just 1 in 10 reports made a sell suggestion.
On any day, most institutional money managers receive a stack of research reports. Trudging through them in search of a good stock is usually a waste of time. If lucky, they may spot 1 in 20 that’s right to buy.
In contrast, managers with access to WONDA can rapidly screen all the companies in our database. If the defense industry pops up as one of the leading industries, they can call up 84 different companies whose primary business is in that area. The typical institution might look at Boeing, Raytheon, United Technologies, and two or three other big, well-known names. Since WONDA provides more than 3,000 technical and fundamental variables on each of the 84 companies stretching back a number of years, as well as the ability to display these variables quickly on identical graphic displays, it’s possible for an institutional money manager to identify in 20 minutes the 3 or 4 companies in the entire group that show outstanding characteristics and are worthy of more detailed research. It’s a vital time-saver some of America’s very best money managers relentlessly use.
In other words, there are ways for an institution’s analysts to spend their time far more productively. Yet, not all research departments are organized to take advantage of such advanced and disciplined procedures.
How well has this approach worked? In 1977, we introduced an institutional service called New Stock Market Ideas and Past Leaders to Avoid (NSMI). Now titled New Leaders and Laggards Review, it is published every week, and its documented, 31-year long-term performance record is shown on the accompanying graph. These performance returns were audited and verified by one of the top independent accounting firms in America.
Over the last 30 years, positive selections outperformed avoids 307 to 1, and positive picks outran the S&P 500 stocks more than 41-fold. Compounding over the 30 years’ time helps make a superior long-term record like this possible. For the entire 30 years ended 2008, stocks to avoid made a teeny 19% gain. Institutions could have improved their performance just by staying out of the stocks on our avoid list. As a service to our institutional clients, we provide them with computerized quarterly performance reports for every positive and avoid suggestion made in the New Leader Ideas service. How many competing firms provide the actual percent performance of all of their ideas over an extended period?
By having massive factual data on every firm and proven historical precedent chart models over more than 100 years, we’re able to discover a stock beginning to improve or get in trouble earlier—without ever visiting or talking to the company. It may be naïve to believe companies are always going to tell you when they are beginning to have problems. By using our own factual data and historical precedent research, we discourage reliance on tips, rumors, and analysts’ personal opinions. We don’t need such information. We also do not have investment banking clients or market-making activities. Nor do we manage money for other people or hire research analysts to prepare long written research reports. So those areas of potential bias or under-performance are nonexistent.
We don’t try to call every short-term or intermediate correction. Our primary focus is on recognizing and acting upon the early stages of each new bull or bear market. This includes searching for market sectors and groups that should be bought and those that should be avoided.
In early 1982, we placed a full-page ad in the Wall Street Journal stating the back of inflation had been broken and the important stocks had already made their lows. That May, we mailed out two wall charts to our institutional clients: one of defense electronics stocks, and the other of 20 consumer growth stocks we thought might be attractive for the bull market ahead. We also made a point of going to New York and Chicago to meet with several large institutions. In these meetings, we stated our bullish posture and provided a list of names that could be purchased after these organizations did their due diligence.
The stance we took was counter to the position of most institutional research firms at that time, as well as to the negative news flooding out of the national media each day. Most investment firms were downright bearish. They anticipated another big down leg in the market. They also projected interest rates and inflation would soar back to new highs as a result of government borrowing that would crowd the private sector out of the marketplace.
The fear and confusion created by these judgments frightened many large investors. As a result, they did not fully capitalize on the fact that we had identified two leading groups for the coming bull market. It appeared professional managers had been bombarded with so much negative “expert” Wall Street input that they found positive findings hard to believe. As for us, we invested fully in the summer of 1982 and enjoyed our best performance up to that time. From 1978 to 1991, our account increased 20-fold. From the beginning of 1998 through 2000, our firm’s account, run out of our separate holding company, increased 1,500%. Results such as this remind us it may be an advantage not to be headquartered in rumor-filled and emotion-packed Wall Street. I have never worked one day on Wall Street in my entire time in the investment field.
As a savvy individual investor, you have a gigantic advantage in not having to listen to different, strongly held opinions. You can see from this example that majority opinions seldom work in the market and that stocks seem to require doubt and disbelief—the proverbial “wall of worry”—to make meaningful progress. The market contrarily moves to disappoint the majority.
Our first full-page Wall Street Journal ad was in March 1978. It predicted a new bull market in small- to mid-sized growth stocks. We had written the “Grab The Bull By The Horns” ad weeks ahead of time and waited to run it until the time was right. The right time came when the market was making new lows, which caught investors by surprise. Our only reason for placing the ad was to document in print what our position was at that point, so institutional investors could have no question about it later. We were also one of the few firms to tell its accounts they should avoid or sell tech stocks and raise cash in March, April, and September 2000.
It is at these extremely difficult market turning points an institutional firm can be of most value. At such times, many people are either petrified with fear or carried away with excessive fundamental information.
If you don’t think fear and emotion can ride high among professional investors after a prolonged decline, think again. I remember meeting with the top three or four money managers of one important bank at the bottom of the 1974 market. They were as shell-shocked, demoralized, and confused as anyone could possibly be. (The ordinary stock at that time was down 75%.) About the same time, I recall visiting another top manager. He too was thoroughly worn out and, judging from the peculiar color of his face, suffering from market sickness. Yet another top fund manager in Boston looked as if he’d been run over by a train. (Of course, all of this is preferable to 1929, when some people jumped out of office buildings in response to the devastating market collapse.)
I also recall a high-tech seminar in 1983 in San Francisco, attended by 2,000 highly educated analysts and portfolio managers. Everyone was there, and everyone was ebullient and self-confident. That marked the exact top for high-tech stocks.
I also remember a presentation we gave to a bank in another large city. All its analysts were brought in and sat around an impressive table in the board-room, but not one analyst or portfolio manager asked any questions during or after the presentation. It was the strangest situation I’ve ever been in. Needless to say, this institution consistently performed in the lower quartiles compared to its more alert and venturesome competitors. It’s important to communicate and be open to new ideas.
Years ago, one medium-sized bank for which we did consulting work insisted we give them recommendations only from among the stocks it carried on its limited approved list. After consulting with the bank’s managers each month for three months and telling them there was nothing on their approved list that met our qualifications, we had to honorably part company. A few months later, we learned key officials in that trust department had been relieved of their jobs as a result of their laggard performance.
We provided product to another Midwest institution, but it was of doubtful value because the institution had a cast-in-concrete belief that any potential investment had to be screened to see if it passed an undervalued model. The best investments rarely show up on any undervalued model, and there’s probably no way this institution will produce first-rate results until it throws out the model. This isn’t easy for large organizations to do. It’s like asking a Baptist to become a Catholic or vice versa.
Some large money-management companies with average records tend to fire the head of the investment department and then look for a replacement who invests pretty much the same way. Naturally, this doesn’t solve the problem of deficient investment methods. Security Pacific Bank in Los Angeles was an exception to this rule. In July 1981, it made a change in its top investment management. It brought in an individual with a completely different approach, a superior investment philosophy, and an outstanding performance record. The results were dramatic and were accomplished almost overnight. In 1982, Security Pacific’s Fund G was ranked number one in the country.
Some corporations put too much emphasis on saving management fees, particularly when they have giant funds to be managed. It’s usually an actuary who convinces them of the money their pension fund can save by shaving the fee by ¼ of 1%.
If corporations have billions of dollars to be managed, it makes sense for them to increase their fees and incentives so they can hire the best money managers in the business. The better managers will earn the extra 0.25% or 0.50% ten times over. The last thing you ever want is cheap advice in the stock market. If you were going to have open-heart surgery, would you look for the doctor who’ll charge the absolute least?
Here are a few tips for organizations that want to farm out their funds to several money managers.
In general, portfolio managers should be given a complete cycle before their performance is reviewed for the purpose of deciding whether to change managers. Give them from the peak of one bull market period to the peak of the next or from the trough of one cycle to the trough of another. This will usually cover a three- or four-year period and allow all managers to go through both an up market and a down market. At the end of this period, the bottom 20% of managers in performance should be replaced. Thereafter, every year or two, the bottom 5% or 10% over the most recent three- or four-year period should be dropped. This avoids hasty decisions based on disappointing performance over a few short quarters or a year. Given time, this process will lead to an outstanding group of proven money managers. Because this is a sound, longer-term, self-correcting system, it should stay that way. Then it won’t be necessary to pay as many consultants to recommend changes in personnel.
In selection of managers, consideration should be given to their latest three- to five-year performance statistics as well as to a more recent period. Diversification among the types, styles, and locations of managers should be considered. The search should be widespread and not necessarily limited to one consultant’s narrow, captive universe or stable of managers.
The corporate or pension fund client with money to be managed also has to be careful not to interfere at critical junctures—deciding, for example, when a greater proportion of the portfolios should be either in stocks or in bonds or that undervalued stocks should be emphasized.
Cities and counties that have funds to invest must be extremely careful. Few of their personnel are highly experienced in the investment field. These inexperienced people can easily be talked into investing in bonds that are promoted as being safe but that later cause enormous losses. This happened, of course, in 2008 with AAA subprime loans in real estate mortgage packages.
Clients can also interfere by directing where commissions should go or insisting that executions be given to whomever does them most cheaply. The latter, while a well-meaning attempt to save money, commonly results in forcing upon a money manager someone who provides either poorer executions or no research input of real value. This handicap costs the portfolio money, as it pays ½ point or more (or its decimal equivalents) on trades that are executed by less expert people.
In 1973, a friend suggested that we produce a weekly chart book to help retail investors find growth stocks with CAN SLIM characteristics. Our weekly Daily Graphs® books were a tremendous success because they helped investors cull through thousands of potential investments quickly and efficiently. We still print them, but in 1998 Daily Graphs moved online with applications such as Charting, Custom Screens, Industry Groups, Option Guide, and Mutual Fund Center.
In early 2010, Daily Graphs Online will again transform itself into MarketSmith. MarketSmith graphs stay true to the original Daily Graphs design. But we’ve taken the tool a few steps beyond the expected. We engaged one of the country’s premier Web site design firms to help us create a research tool that was robust enough for the sophisticated user and yet intuitive enough for the novice investor.
MarketSmith gives users access to several proprietary ratings and rankings such as Relative Strength Rank, Earning Per Share Rank, Sales-Margins-Return on Equity (SMR) Rating, and the Composite Rating using the same institutional quality data that William O’Neil + Company provides to professional money managers through the WONDA platform.
We’ve integrated a checklist feature to help remind an investor how any stock rates against important financial benchmarks.
MarketSmith has a visually intuitive stock and mutual fund database screening module. Investors can search over 7,000 stocks and 9,000 mutual funds to find those that meet specific fundamental and technical criteria.
MarketSmith users who belong to investment clubs or attend IBD Meet-ups can share database screens and stock lists and blog about their own market observations and experiences. IBD subscribers have exclusive access to IBD content such as the IBD news stories and the IBD 100.
We’ve designed MarketSmith so it can run on a Mac or PC, and there’s even a MarketSmith iPhone application for when you are away from your desk.
MarketSmith is the ultimate stock research tool that takes the information and knowledge that you gain from reading this book and brings it to life. As you gain experience and learn to effectively use MarketSmith, you can truly become an investing master.
