Q & A

Q & A

Questions? Here Are Some Answers

Why did you stop managing accounts?

For many years we managed accounts for others, targeting annual returns of about 20% and holding most positions more than 6 months.  However, we had also developed a very high return discipline that we had been testing.  A little market history might be helpful here.  The market goes through shifts in “style.”  These shifts influence the kinds of investment strategy that will be most successful.  We will spend some time on this answer because new traders and investors might learn something from reading about our attempt to use a high-performance discipline with client accounts, the different performance targets, why a high-performance discipline was not practical, the need for a strict adherence to the rules of a discipline, the trade-offs required, and why we finally decided to leave the advisory business. 

In short, we decided that leaving the advisory business was necessary to release the full power and profitability of the Disciplined Growth Strategy for the personal accounts of company members.  [Disciplined Growth Strategy is the name we created to refer to our high-return trading discipline.  Even if somebody else uses the same name for a trading discipline, the discipline they are referring to will not be the same because the discipline we use is proprietary and not in the public domain] Managing the accounts of others for a fee (but not using the discipline for our personal accounts) was less attractive to us than giving up the fees and fully implementing the discipline for our personal accounts.  However, there was much more that went into the decision than this.  Let’s look at some of the factors that were involved.

Because the high-performance discipline required a different mindset and way of thinking than conventional approaches to investing, we found it difficult to effectively use the discipline in our own accounts while using other strategies for clients.  For us, the mindsets behind the different approaches to managing investments “collided” and “interfered” with each other.  The account management process, the regulatory paperwork, the wide range of investment needs of our clients, and their widely divergent attitudes about “appropriate holding periods” imposed too many constraints and added too much clutter to the trade-decision process.  To do it right, all accounts would have to make the same trades at the same time. 

However, we could not get all our clients to consent to a strict adherence to the discipline.  Although a few clients were ready to implement the discipline, others complained or were prone to confusion whenever trade activity levels increased.  Some even seemed to want to “buy and hold” without implementing any selling discipline at all.  For example, if our algorithms issued a sell signal and we sold a declining stock quickly with only a small loss, some clients became upset and called to advise us (in no uncertain terms) that we should have given the stock more “breathing room.”  We concluded from these and other comments that some of our clients would prefer that we “rode” a stock up and down like a roller coaster through several cycles before even thinking about selling.  They would also prefer that we ignore our algorithms when they indicate that a small decline had a very high probability of growing into a larger loss.  While riding a stock up and down through several cycles may be acceptable when you are trying to generate a return of 15% (assuming that none of those down moves become nightmarish), experienced traders know that this tolerance for loss has no place in the execution of any truly high-performance investment discipline.  We could not trade as freely for our clients as the discipline required.  Furthermore, because we needed to manage the personal accounts of members in the same way as we managed client accounts, our members could not come close to achieving for their own accounts the growth potential of a strict adherence to the discipline.   

We even considered the possibility of continuing with only those clients who were fully committed to achieving high performance and who did not care what level of trading activity it required to get there.  The problem with that idea was that the number of candidates was small (most of our clients were retired or nearing retirement) and the risk of regulatory censure we would assume was too great relative to the fees we could charge.  If one person became confused because of the trading activity, or if we had a temporary slump that frightened somebody to the point that they contacted the SEC or other regulatory authorities with a complaint, then we would have to take time and energy from our enterprise to explain or defend our methodologies to regulators who are committed to the conventional wisdom that one should buy and hold stocks through their ups and downs and eventually sell them when they are higher.  [While this approach might work sometimes for people who do not have the disciplines and tools to be effective traders, it will not enable a person to achieve the high returns we were targeting.]   

We have a discipline that has generated about 20% a year for 15 years.  This strategy is designed for intermediate-term investors in utility stocks.  We have another slightly stronger discipline that has averaged about 26% a year and that buys any kind of stock.  Let’s refer to these disciplines as “20% systems” (reflecting their targeted level of performance).  However, the discipline we wanted to use for client accounts (the Disciplined Growth Strategy) was far stronger than either of these “20% systems,” but it required a more active and disciplined approach to trading.  If a person makes a half-hearted attempt to use the Disciplined Growth Strategy (if a person does not sell immediately when the model says it’s time to sell, and so on), performance will suffer.  Under those conditions, the performance of the Disciplined Growth Strategy will not be as good as that of our “20% systems.” 

An analogy might help you to wrap your mind around the problem.  Assume that the cylinders in the engine of a racing car are similar to the rules of an investment discipline.  Optimum performance of a racing car can not be achieved unless all cylinders are firing correctly.  In the same way, optimum performance cannot be achieved with a high-performance trading discipline unless there is strict adherence to the rules of the discipline.  A high-performance racing car will not perform as well as the average family car if you disconnect the spark plug wires to four of the eight cylinders in its engine.  In the same way, following only a few rules of a high-performance investment discipline will result in relatively poor performance.  Performance will tend to be inferior to that of the 20% systems.  The interdependent rules that comprise a high-performance discipline also function as a kind of glue that gives the discipline its integrity.  Ignoring some of the discipline’s rules will weaken or even destroy the discipline’s integrity.  In other words, “things will fall apart.”  The unwillingness of a significant number of clients to follow the rules of the Disciplined Growth Strategy left us in a quandary.  We were convinced that consistent returns well above 20% were realistic goals when using a good stock-trading discipline (without the use of short-selling, options, currencies, or commodities).  We either had to give up any hope of using the  Disciplined Growth Strategy for client accounts and return to the use of more conventional investment disciplines, or we had to quit managing accounts and use the much more powerful discipline for our own accounts.  There was another factor at work. 

Wendy Felt, the daughter of Winton Felt and co-editor of The Valuator, had been preparing to take over parts of our portfolio management business and planned to use the discipline that she had been using for her own account to manage the accounts of her clients.  However, when she saw the reluctance of clients to implement discipline, and concluded that their attitudes could also result in problems with securities regulators, she realized she would have to use a much less powerful approach to investing in managing client accounts.  That would also interfere with her use of more powerful disciplines for her own account.  She weighed the burdens and problems of managing money for others to target returns of maybe 20% to 30% against the freedom she would have from client and regulatory difficulties while trading her own account without restraints and targeting much higher returns.  She decided to choose the latter.  Winton Felt reached similar conclusions from a different perspective.  He decided that working together with Wendy and being able to use a more disciplined approach to investing without opposition from clients or any other constraints would be much more enjoyable.  He decided that working closely with his daughter in a profitable enterprise of mutual interest in which they could stimulate and encourage each other in creative ways was a very attractive alternative to the constraints, burdens, regulatory overhead, and limitations on performance that are part of the investment advisory business.  Simply put, he wanted to have fun playing with his daughter. 

Now let’s look at it from a strictly business perspective.  Managing client accounts in the hope of achieving a return of 20% to 30% while collecting a management fee was not as attractive to us as taking the firm out of the portfolio management business, fully implementing our disciplines for member accounts, and targeting returns twice as great.  While there was no guarantee that we would always hit our performance targets, we had concluded that our disciplines made it worth the effort.  It seemed a shame not to even try to implement disciplines that took so many years of research and testing to create.  How many investment advisors even hope to achieve that level of performance?  If they thought they could, wouldn’t they simply trade their own accounts?  Why would they work for a fee and put up with all the regulatory hassles?  On the other hand, we know of some traders who consistently achieve these higher performance levels when managing their own money.  We have studied, conducted research, and tested trading systems for many years.  At one point we dedicated 8 or more hours a day (for 3 of those years) to designing and/or testing the profitability of many thousands of disciplines.  We satisfied ourselves that our disciplines could do what they were created to do if they were implemented correctly.  We wanted to share what we learned with clients by employing those disciplines in the management of their accounts to achieve performance rarely seen by investors.  We just could not get the level of client consent we needed to implement the discipline effectively.

Once we came to the conclusion that the goal of implementing our disciplines for a large number of clients with widely divergent attitudes about investing was not practical, we decided that the best way we could put all that work and knowledge to good use would be to enable our members to implement what we had learned.  We understood the disciplines well enough to fully trust them.  The trading activities of members could then be used as resource material for the teaching and training activities of the company.  Our products flow naturally out of our own trading needs and/or experiences.  For example, even if nobody subscribed to them, we would still produce The Valuator, StockAlerts, and Strongest Stocks for our own purposes.  The power of these tools may not be immediately obvious to the casual user (who only wants to be told what to do), but they were designed for us and for traders like us who prefer to make their own decisions.  We decided that since we produce them anyway, we might as well make them available to subscribers.  Thus our own desire for these resources has resulted in the availability of tools that can, if used correctly, benefit others.  Our visitors, subscribers, and licensees can therefore benefit from our experiences and information while trading as conservatively or as aggressively as they desire.  The members of our company, on the other hand, can benefit from being able to fully implement our disciplines for our own accounts.    

Thus, we finally came to the conclusion that life would be simpler and there would be fewer headaches and less stress for our members if the company focused on providing resources for investor enablement and stopped managing accounts.  Accordingly, with the unanimous agreement of our members, “enablement” became the focus of StockDisciplines.com, a.k.a. Stock Disciplines, LLC.  The firm now gives no investment advice.  We never make stock recommendations or any other personal recommendation related to investing.  Dr. Felt had a lengthy conversation with a spokesperson for a securities regulatory authority before leaving the advisory business.  The regulatory spokesperson was asked the following question.  If a person is no longer a registered advisor and does not get fees for managing accounts, if he received a small fee for a market-related subscription (like a market letter), would he be in violation of any regulations if he gave free advice?  The answer was that even if the advice were given free of charge, he would be in violation of securities regulations if he were not a registered investment advisor.  The representative of the regulatory authority said that in this situation, the subscription fee would be interpreted by regulators to be a fee for advice rather than for the subscription.   [Client ability to influence and interfere with our trading procedures by imposing their own individualized suitability constraints is part of the client-advisor relationship and is part of what it means to be a licensed advisor.  It was also a primary incentive for giving up the license.  If we were to get a fee for any service or subscription that makes recommendations, giving even free advice would require that we subject our operations and our trading to the fiduciary responsibilities, interference from clients, regulatory constraints, and compliance requirements from which we sought to be free].

 Instead of giving personal recommendations, we simply try to enable others to do a better job for themselves.  That way, we no longer have to indulge securities regulators who are constantly demanding more paperwork (at the time of our withdrawal from the advisory business securities regulators required that each advisory firm have at least one employee whose full-time responsibility is to keep the firm compliant with all the regulations).  

On the personal level, the trading of our members is now their own business, and they can do it without client needs and biases interfering with how our members manage their own portfolios.  It was difficult for clients to grasp and then act on the fact that it is not finding big winners but avoiding big losers that produces great returns.  This is an oversimplification, but it drives home an important point.  The point is that most people approach investing with unproductive goals and incorrect thinking.  Their perception is that to be a big winner in the market you must learn to pick big movers.  However, the real way to become a winner is to learn about finding setups, the correct timing of entry and exit points, and strictly limiting losses.  Changing our company’s focus gave us a win-win business model.  On the one hand, if they learn to use them correctly, our customers and visitors can benefit from the use of our tools and information.  On the other hand, our members get to trade our disciplines correctly and without interference from clients.  Everybody benefits from this arrangement.

You say it is possible to generate far more than 20% net return per year most years.  Top traders at major brokerage houses have tried for years and we keep hearing about them taking huge losses.  I am skeptical. 

On the one hand you have “hot shots” with new MBAs and bright ideas about how to trade.  They risk their firm’s money, not their own.  They are young and in a hurry to make a name for themselves.  In order to make it “big,” they leverage their firm’s money.  Their thinking is that if they are right, they want the most “bang for the buck” they can get.  They are sure they are right.  However, leverage is a two-edged sword.  It is a little known fact that 80% of those who play the futures markets eventually lose all their money.  That’s because most of those traders use huge amounts of leverage.  The overuse of leverage can be like playing the slot machines in Las Vegas.  It is possible to do well for a time, but if you play long enough, you will lose it all.  Most newcomers with inflated perceptions of the effectiveness of their approach do not focus enough on risks and loss.  They are focused on opportunities and gain.  That is a big mistake.  

On the other hand, you have somebody who is not in a hurry.  He spends several years doing little else but test thousands of strategies with real data on thousands of stocks over a wide variety of market conditions covering many years.  The point of his research is not to find the strategy that got the best return.  That would be “curve fitting.”  That means he would end up finding the strategy that happened to generate the best return under specific conditions for a specific stock.  Such a strategy might be a poor performer under other conditions and with a different stock.  Instead, the goal was to find the strategy out of many thousands of strategies that works best with most stocks under most market conditions most of the time.  Such a strategy may not be the best to use for a particular stock at a particular time.  At various times the market favors blue chips, small caps, dividend payers, growth stocks, value stocks, utilities, or whatever.  The key is to find the characteristics of a strategy that works very well most of the time regardless of the market’s prevailing bias.  We will not go into the design details of the research, but we will give an example of one of its elements.  To find the best strategy out of, say, 1000 strategies, you might start by applying each strategy to each of 5000 stocks over a period of 20 years.  Take one strategy as an example.  You might compute the total return of the strategy for each one of the 5000 stocks over a 20 year period.  Then you might add the returns of the strategy for all 5000 stocks to get the net total return in dollars of the strategy for a “portfolio” consisting of 5000 stocks (with the same amount of money initially invested in each stock).  You would repeat the procedure for each of the 1000 strategies and then rank the strategies according to their performance (revealed by the dollar value of the 5000-stock portfolio after using each of the strategies for 20 years).  The strategy that achieved the greatest gain in dollars would be the strategy that generally performed best most of the time for most stocks (it is not quite as simple as stated, but it will do to illustrate the point).  That does not mean the strategy will perform best for any particular stock in the future.  Once you have tested 50,000 strategies or more using this approach, it is then necessary to find the common elements of the best performing strategies. 

Statistical procedures were used to assure “robustness” of the findings.  For example, would a slight change in any parameter or variable cause a significant change in performance?  A robust strategy does not fall apart with small changes.  The work required by the design of the study ranged from 8 to 16 hours a day for three years.  This is definitely not the approach of a person in a hurry to make a name for himself by gambling with his firm’s money.  It satisfies the ego to find the big winners.  However, all our research told us that finding big winners is not the right goal for those who want to be winners.  The real trick is to avoid big losses.  For example, in one study a major stock (IBM) declined over 70% in just a few years.  One of our better strategies managed to make a large annual profit on the same stock during those declining years without selling short or using margin.  All the strategy did was buy and sell without the use of leverage.  The stock could hardly be called a big winner, but the strategy definitely was.  Avoiding loss is not as ego-satisfying as finding a stock that doubles quickly.  However, finding big winners is something of a gamble.  You do not have much control over how far or how quickly a stock will rise.  However, you can control how much you lose.  That is something that is defined by your discipline.  If you want to be a gun-slinger, be sure you are using the money of someone who needs a tax write-off.  If you want to be a real winner, you must exercise a discipline of controlled losses.

The traders that are always in the news are generally not the most successful traders.  In fact, they are usually in the news because they have caused some major problems for their companies.  There are traders who regularly gain 40% or more in the market.  However, most of them prefer to remain out of the spotlight.

If you are skeptical, fine.  Continue to invest the way you always have.  It is our opinion that to be highly successful in the market long-term, it is necessary to have a discipline and to believe in that discipline.  If you do not believe in your discipline, you will second-guess it.  If you do not trust your discipline enough not to second-guess it, you do not really have a discipline.  A person who is skeptical about the efficacy of his discipline will not be among the consistent winners in the stock market, though he might occasionally be a winner by accident.

We have no need or even the slightest desire to prove that such returns are possible.  Even audited performance reports would not “prove” anything to the doubters, and those who believe it can be done do not need proof.  The doubters would only say “That was then, bet they couldn’t do it now.”  We view our performance as our own business and it is a private matter.  We intend to keep it that way.  Besides, it is to our advantage to have a lot of people in the market thinking, investing, and trading in conventional ways.  Believers are the ones who are most likely one day to become our competitors in the market.  Even so, we are convinced that there will always be enough sheep in the market to provide all the shearers with an adequate supply of wool.

Do you have performance reports?

Specific buy and sell data for specific stocks is necessary for a performance report. An advisor who uses conventional methods of finding stocks based on a valuation model can say, “this stock is undervalued and therefore a buy if it is available at $25 a share.” Some may use a little technical analysis and say that if it breaks out above resistance at $30, it is a buy. Such investors are happy with a return of 7% to 20% a year. When the stated event occurs, the name of the stock, date and purchase price can be used in creating a performance report. When we were in the money management business, we made buy and sell decisions for client accounts. We generated performance reports so clients could see how we had done. When there is a single entity or individual who makes all investment decisions, those decisions are specific and a part of recorded history. The results of those decisions define the performance of that individual, and it makes a lot of sense to generate a report of that performance for those who pay for his decision-making services.

However, we no longer manage money, and we do not make investment recommendations. We are now trader/investors. In order for us to have a chance at getting the returns we are after (far greater than 7% to 20%), we must use a very different approach than the “conventional” approach mentioned above. Instead, we created algorithms that enable us to scan thousands of stocks and identify those that have what we call a “setup pattern.” These patterns are usually seen just before a price surge. A price surge does not occur every time we find such a pattern, but the probabilities of a price surge within two weeks are greatly increased when a stock’s chart does show a “setup pattern.”

The bottom line is that our lists are NOT buy or sell recommendations. Also, not all setups are attractive (because of overhead resistance, and other factors our algorithms cannot “see” but have to be spotted by visual inspection of the stock’s chart).

There is another problem with creating a performance report. Whose performance do we report? Richard Dennis, a well known trader, once conducted an experiment in which a group of traders were taught how to use a specific trading system. They were given the same stock information and the same rules. Some made great returns and some lost a great deal. There was a wide range in performance because people, even in a controlled environment, implemented the same discipline differently.

When we post a list, some will act immediately and some will delay a few days. People will buy or sell at different prices and at different times. The prices on the list are history. It is nearly impossible that anybody could buy all the stocks on the list at the prices listed. Some might argue that we could base our performance reports on the prices given on the reports we publish. We could do that, but it would not mean anything. Even our own traders do not think all the stocks on our lists are worth buying. Which stocks would we list in our performance report? Out of 50 stocks listed on a given day, we may decide that NONE are worthy of purchase because of nearby overhead resistance or because of something else that makes the stock undesirable. Including those stocks in a performance report would be ridiculous. The decision of what to buy and when to buy it is a very personal decision. Our own traders do not buy the same stocks, and even if they do, they will usually buy them at different prices.

Using the lists generated by our algorithms, we can spend our time more efficiently by reviewing only those stocks that have satisfied certain minimal requirements that make it more likely that there will be a price surge soon. THAT IS ALL THE LISTS ARE FOR. They are NOT lists of recommendations. We make the lists available to our subscribers so they can use them the same way we use them.

You say you focus on “setups.” Explain.

“Setup patterns” cannot be identified by using fundamental analysis or the other analytic techniques of the more common approaches to investing.  First, it was necessary to identify what setup patterns look like.  We have a page that identifies and illustrates some setup patterns (see the “Stock Alerts” page).  These patterns are usually seen just before a price surge. However, they can also be found in stocks in stocks that already have a strong pattern.  A price surge does not occur every time we find such a pattern, but the probabilities of a price surge within two weeks are greatly increased when a stock’s chart does show a “setup pattern.”

Let’s look at one example to see how this works.  Our years of experience and research tell us that large institutional investors pay close attention to the 50-day moving average. We have noticed that when the 50-day moving average is climbing at a good rate, and the stock is well above that average, the stock will eventually return to the average and then accelerate away from it again. That is, the average will rise, and the stock will decline until the two meet, and then the stock will “bounce” off the moving average and begin to climb again. It does not always happen that way, but it is a high-probability scenario. When a stock has been above a strongly rising 50-day moving average and has declined almost to the point of reaching its 50-day moving average, our algorithm will identify the stock as a “setup” and include it on its list of stocks that have various “setup” configurations.  As the stock draws very close to its moving average, institutional investors tend to consider the stock to be a bargain and begin to buy. Why? Buying when a stock is at its rapidly rising 50-day moving average is a relatively low-risk purchase. It is unlikely that a stock will fall significantly below its 50-day moving average when that average is rising at a good pace. Because our algorithm has alerted us to the configuration of the chart’s pattern, we can monitor the stock and see if there is a “trigger event” (a reason to act). The stock will either “bounce” off its 50-day moving average, or it will decline below it. Our experience tells us the odds favor a “bounce.” When we see that the stock has reached its 50-day moving average, and its price activity reflects new buyers entering the market (the stock’s high is higher than the previous day’s high and the volume increases), we have our “trigger event.” We can then buy, place a tight stop loss order, and wait. If the stock does not follow through within two weeks, we sell. We sell because we bought on the premise that it was about to surge. If that does not happen, there is no reason to keep the stock. We do not want to tie money up in non-performing stocks, because that reduces our own performance. [If you do not pull the weeds in a garden, you will end up with a garden of weeds] By selling, we free up money so it can be re-deployed to another more promising situation. If it does surge, we hold it until the stock runs out of “steam.” That could take a few days, weeks, or even many months. This approach could be used as an entry strategy whether a person is a short-term trader or long-term investor. However, despite the “trigger event,” there may be a good reason to avoid buying the stock.  If a stock has this pattern, it will rank highly in the “Strength Rank %” column of The Valuator because a rapidly rising 50-day moving average will naturally rank high for strength.

Here is an example of of a setup from our recent “Strongest Stocks” list.
People often look at such a chart and say “looks like it is about to fall, it has gone too high,” or “I am afraid of this one, it is too late to buy it.”  Those who try to buy a stock before it begins to surge do not have momentum on their side.  They buy stocks that are “dead in the water” because of a “story” that excites them (a promising treatment for cancer, a cure for dementia, or whatever).  They have a “hold and hope” strategy. This chart was made shortly after the market opened, and it is already making a new high.  If we had waited until the close of market, the high indicated would have been higher and the comment would have been the same.  A week later, with a higher high, we would hear the same comment.  The truth of the situation is that this stock has considerable momentum.  That is, if you buy now, the odds are that it will rise before it falls.  That is, the odds are on the side of the buyer, not the seller.  Therefore, this can be seen as a setup, not because it is about to surge, but because it is already in the process of surging.  A person can either wait for some sign of consolidation (a little sideways action followed by a move higher, or a modest pullback followed by a higher high than that of the previous day, especially if there is an increase in volume).  Such stocks can be bought and followed with a tight stop loss as they rise.  Of course you will be stopped out occasionally.  There is no strategy that can guarantee a profit.  The best we can do is to invest in situations where the odds are in our favor.  In this illustration, the odds favor a profit because momentum is working for you.

When we see a pattern develop like the one above, we look for overhead resistance a little above the purchase price or some “defect” in the pattern that increases risk or that makes the outcome of a purchase “iffy.” For example, besides overhead resistance, we look at downward spikes. If the stock has a pattern of spiking below its trendline or significant moving average, we suspect that somebody is purposely taking out the trailing stop losses. That is, they run the price of the stock down enough to trigger stop losses (further depressing the price) so they can buy it back at the lower price. Another example would be a stock that is declining toward support and then it gaps down with a volume surge before it reaches its support. That action increases the odds that the support will not hold up under the selling pressure. We avoid stocks that give such warning signals.

Focusing on stocks in a setup configuration and avoiding those with obvious danger signals greatly increases our odds of making a successful investment. Waiting for a “trigger event” increases those odds even more. However, by screening out stocks evidencing any of a variety of danger signals, we might eliminate most or even all of a 50-stock list. When that happens, we will simply wait for another list and try again. Since stocks in a setup configuration are far more likely to surge within a few days, we make far more efficient use of our time by reviewing the short lists generated by our algorithms than by searching through thousands of stocks that are not in a setup configuration and do not have the high probability of an almost immediate surge. Though stocks that have a setup configuration do not always surge, they are far more likely to surge (and without much delay) than stocks that do not have a good setup pattern.

The bottom line is that our lists are NOT buy or sell recommendations. We often reject most of the stocks on our lists. We do not project ahead and say “if this stock reaches $25 it is a buy.” If we did that, we would be tracking hundreds of stocks that are not ready for purchase, and the fact is that just because a stock reaches a particular price, that does not make it a good purchase candidate. How it reaches that price is extremely important in a high-performance system. There is no way that we can say of a stock that is NOT in a setup configuration, “if it reaches a certain price, buy it.” Why? If it is not in a setup, we automatically reject it rather than spend time monitoring it. Even if it is in a “setup,” setups are short-term configurations (lasting a day to a few weeks, depending on the type of setup), meaning that there is a time window in which to act, but only if certain conditions are met within that time window. Buying is not simply a matter of price. How and when a stock reaches a price are critical considerations. Some “setups” can evaporate in a few days. If the price is right but the setup is gone, we are far less likely to buy the stock. For a high-performance trader/investor, making a good trade is a matter of timing. First, we do not buy stocks that are not in a setup configuration. Second, setups may not last more than a few days. Third, not all setups are attractive (because of overhead resistance, and other factors our algorithms cannot “see” but have to be spotted by visual inspection of the stock’s chart). Fourth, activity just before the trigger event can cause us to reject a stock. We evaluate stocks in the present, not in the future.
To see some examples of “setups,” use this link, which takes you to the bottom half of the page at  StockAlerts

On the Home page you seem to pay more attention to the Dow Jones Industrial Average than to the S&P 500. Why?

New visitors may wonder why we give a more detailed discussion of the Dow than of the S&P500. We acknowledge that the S&P500 is a better representation of the broader market because of its makeup and construction. However, at one time we provided market timing services as investment advisors, and we analyzed signals generated by the Dow and the S&P500. We found that we got much better bottom line results when timing entries and exits using signals generated by the Dow. Ironically, even when we timed Mutual funds and ETFs that invested only in the S&P500, using the Dow as a signal generator instead of the S&P500 gave better results! The greater breadth of the S&P500 (and Nasdaq) and the proportionally greater impact of the undisciplined activities of small investors add “noise” to the patterns of the S&P500 and Nasdaq. Relative to the total amount invested, the Dow has the greatest concentration of big money that is managed by disciplined professionals (less “noise”). In general, signals generated by the Dow have greater clarity (are more reliable) than signals generated by the S&P500. Since Apple, Cisco, Intel, and Microsoft are in the Dow, and since they are among the heaviest weighted (most influential) stocks in the Nasdaq, the Dow also gives pretty good signals for the Nasdaq (minus the greater “noise” of the Nasdaq). Indexes like the S&P 500 and Nasdaq Composite Index do not include volume data. Certain indicators (like Chaiken Money Flow, for example) cannot be used with those indexes because of the volume data required, but such indicators can be used with the Dow. In that regard, the Dow can be used as a surrogate for those Indexes. In the past, we provided information for the S&P500 and the Nasdaq Composite Index that was very similar to that given in the paragraphs immediately below the Daily Chart of The Dow. We decided that the practice was unnecessarily repetitive and tiresome for the reader, because both Indexes tended to rise or fall with the Dow. Note: Contrary to what brokerage houses and mutual funds want you to believe (because they want you to leave your money in their funds rather than move it around), it is possible to profitably “time the market.” The average investor is just too emotion-bound and undisciplined to do it correctly. (We do not offer timing services.)

You seem to make little or no distinction between “Trader” and “Investor.”  Why?

On this site, the words “trader” and “investor” are used interchangeably because the subject being discussed will almost always involve the same considerations whether you are a trader or investor.  For example, we look much more closely at the tactical considerations of buying and selling than at the length of time between the two.  If it makes a difference, we will make the distinction in our comments.

How do you teach?

Visitors learn by poking around this site. Each section has information. Even this page is a teaching tool. Some ideas conveyed in “Market Review” transfer to individual stocks. For example, most of the indicators can be applied to stocks. Learning how to read them for the market is transferable knowledge. We also use tutorials to teach. Please bear in mind that this site is new. We think of the 25 or so tutorials listed at the time of this writing as only the beginning. We expect to have many more tutorials posted over time. Studying and thinking about what is said in the tutorials can be extremely useful. For example, our discussion of the CCI is, in our opinion, one of the best available. Other sites may display the CCI, but most don’t say much about how to use it. Some of our tutorials emphasize the thinking process. The particular stock used to illustrate a concept is not really important. It’s the process of analysis used in approaching a situation that is important.

I am surprised at the prices of your services

To the best of our knowledge, there are no other sites that offer services similar to ours, so it is difficult to determine what is a “normal” fee structure. However, we have extensive experience in the financial industry, and we estimate that “normal” prices for financial services like ours might cost four to five times as much as we charge (and some would charge much more). We are conducting an experiment. We wanted to see if offering our services at very low rates would bring in enough subscribers to compensate for the low fees. We recently surveyed market-related Websites to see what they charged for subscriptions.     Click here to see survey data.  

Windows users may also click with the right mouse button while on the desktop and select “New” then “Shortcut.” In the window that appears type “https://www.stockdisciplines.com” without the quotes and click “Next.” Type a name for the shortcut in the window. For example, you could simply type the word “Stocks” (without the quotes) and then click on “Finish.”

What is a simple way to place a shortcut to your website on my desktop?

Look at our URL in your browser. Notice that just to the left of our URL is a small picture. In Internet Explorer it is usually an ‘e’ but it may be some other picture. Click on this small image and drag it to your desktop. This creates a shortcut to our website on your desktop. If you cannot see your desktop, your screen image is probably maximized. In the top right-hand corner, you will probably see _ □ x. If the middle symbol is overlapping squares instead of a single square, click on the overlapping squares. A single square will now appear. Move your cursor to the right edge of your screen. It will change to an arrow. Press your mouse button and drag the edge of your screen image to the left. Your desktop should become visible. If not, repeat the process on the screen image that has become visible. Eventually, you’ll get to your desktop. Once you can see your desktop, click on the image at the bottom of your screen that represents our website. Now you can perform the procedure described in the first paragraph. The top right-hand corner of your screen image has been changed to _ □ x. If you want to maximize it again, click on the square. Alternatively drag or copy the following icon to your desktop.