Technically Speaking, March, 2005

From the Editor’s Desk

This month’s newsletter is the largest that we have published in recent memory. There are two reasons for that – the Seminar announcement and the incredible contributions from the membership. The second half of the newsletter is devoted to providing complete details on the upcoming Seminar. The intent is to answer any question you may have and allow you to decide whether or not this event is for you. I’m sure you’ll agree with me that this event is for anyone with an interest in the markets.

Even without the seminar announcement, we would have a very large newsletter thanks to groundbreaking articles submitted by our own members and affiliates. This newsletter is a great opportunity to publish short pieces of research. Although it is not necessary to write in accordance with the scholarly standards of the Journal of Technical Analysis, we will gladly accept thoroughly tested ideas that can help fellow traders profit.

Frank Testa provided an article on a new point-and-figure technique and Eric Davidson wrote about a practical means of attaining a disciplined approach to trading. We also have reproduced two pieces of research by Arthur Merrill, CMT, who passed away in January, with the assistance of John McGinley, CMT.

We hope you enjoy this issue, and look forward to seeing many of you in New York. If you will be attending the seminar and would like to talk about a newsletter article, please let me know. I would be happy to sit with you and complete an interview or summarize your ideas on technical analysis.

Cordially,
Mike Carr, CMT
Technically Speaking Editor

What's Inside...

What an Honour

Jordan Kotick, CMT

I mentioned two key people last month who were instrumental in our recent success with the NYSE and NASD. This...

The MTA Says Thank You

John R. Kirby

Last month I gave you the news that the NYSE had accepted the CMT 1 and CMT2 as an alternative...

Incorporating Volume into Point & Figure Charting

Frank E. Testa, CMT

Editor’s Note: This article is best read in the full-color PDF edition of Technically Speaking, available on the MTA web...

Chi Squared

Arthur Merrill, CMT, was a leading advocate of the need to apply statistical rigor to technical analysis methods. He frequently...

Advance Decline Divergence Oscillator (ADDO)

This indicator was developed by Arthur Merrill, CMT, who passed away...

Decision Making

Robert Colby, CMT

Robert Colby, CMT, spoke at the educational meeting of the New York MTA Chapter on November 15, 2004. This presentation...

Conversations with the Board of Directors

Michael Kahn, CMT

The MTA is changing, and those changes are intended to lead to broader respect of technical analysis within the investment...

The Competency Model

Eric Davidson, CMT

In the Summer/Fall 2004 issue of The Pristine View, Andrew Kezeli described the stages of growth a trader must experience...

Regions Committee Update: Where the Rubber Meets the Road!

Tim Snavely, CFA, CMT

The regions committee continues to work hard to develop its structure and programs to better facilitate the MTA’s mission –...

What an Honour

I mentioned two key people last month who were instrumental in our recent success with the NYSE and NASD. This month, I want to shine the spotlight on a third, a gentlemen without whom, like John Kirby , like Ralph Acampora, we simply would not have been successful. This gentleman is David Krell.

As some of you may be aware, David is a Past President of the MTA and also an MTA member. He is the President of an SRO himself and even though these recent CMT-friendly and MTA-boosting decisions did not affect his business directly, he nonetheless dedicated a lot of time, effort and patience with our efforts. He was, in effect, the Master of Ceremonies of the entire process and production. He advised and councelled, he guided the MTA through and around the rocks and potential potholes of the process. Like I mentioned last month, if you think that the recent decisions are good for technical analysts, good for the MTA, good for the CMT, like John and Ralph, please thank David if you see him.

On another note, though you will be hearing much more about this going forward, I want to mention our upcoming seminar in NY. I am not one to trumpet something unless I believe in it but consider: the best and the brightest, excellent outside speakers, the momentum (internally and externally) recent decisions from the SROs are bringing us, all in the center of the financial world. I cannot think of a better time, better location, and stronger potential for a successful seminar.

Sincerely,
Jordan E. Kotick, CMT
MTA President

Contributor(s)

Jordan Kotick, CMT

Bio Coming Soon.

The MTA Says Thank You

Last month I gave you the news that the NYSE had accepted the CMT 1 and CMT2 as an alternative to the series 86 for technical analysts. Shortly on the heels of that announcement, but too late for press time, the NASD made a similar announcement.

This was a long and hard process for the MTA, but we also need to be thankful. The regulators were tough, but they also listened, and they took us seriously. After the announcement, Stuart Kaswell drafted, and with the approval of your board sent a thank you letter (reprinted below) to the regulators.

These people served the MTA well. They do not get many thank you letters. If you would like to add yours thanks to them, please go ahead.

Sincerely,
John Kirby

Contributor(s)

John R. Kirby

Bio Coming

Incorporating Volume into Point & Figure Charting

Editor’s Note: This article is best read in the full-color PDF edition of Technically Speaking, available on the MTA web site. The P&F charts included in this article are in color. They are reproduced here in blackand-white, but readers familiar with basic P&F techniques will have no trouble understanding the shading.

Point & Figure Charting provides an excellent mechanism for pinpointing precise buy/sell levels, as this charting method is solely concerned with plotting price movements in columns occupied by “X’s” and “O’s” to denote buying and selling demand, respectively. However, the shortcoming of this charting method is its total disregard for the importance that time and volume play in the formation of a stock’s pattern. As most market technicians acknowledge, volume often precedes price. To this end, I have devised a way of incorporating volume and time into the Point & Figure method of charting as describe in more depth below.

To assess the underlying strength/weakness of a given price move, technicians will often rely upon the total volume of shares traded to assist in this endeavor. By comparing the stock’s volume to its 30-day average daily volume, we are able to determine if the stock attracted unusual buying demand or was the rally accompanied on light trade, which often is a precursor that the buying demand is withering and that a downturn in the stock is imminent. Consequently, the technician that relies solely on charting price movement is vulnerable to missing key red flags. By varying the color of the boxes, we are able to depict the demand or lack thereof of a security. In addition, by making the “X’s” and “O’s” case sensitive, we can gauge the time of the move as described later in this report.

Box Colors

The method that I have developed compares the stock’s movement to its 30-day average daily volume. If the advance transpired in above average trade, the color of the box will be dark green indicating strong buying demand. However, if the advance took place in below average trade, the color of the box will be light green, indicating tepid buying demand. On the other side of the ledger, the color of the box of a stock that has fallen in above average trade will be dark red, indicating strong selling pressure, while a stock that has fallen on below average trade will have a pink box.

The mechanics of charting the enhanced version of the Point & Figure chart is identical to the widely known method of Point & Figure charting. Namely, if you are in the “X” column, the technician would first look at the session’s high to determine if an “X” could be placed. If the stock did not advance, then a comparison of the session’s low to the assigned box value and reversal value would determine if a crossover into the “O” column is necessary. At this point the chart pattern under the enhanced version will be identical to the customary way of utilizing the Point & Figure chart. The difference takes place when comparing the stock’s volume to its average daily volume. The two ways to accomplish this task is to compare the session’s volume to the average daily volume on that day, this is called the “Snapshot” version, since you are looking only at that particular point in time. The second way entails accounting for all of the trading that took place since the last assignment of an “X” or “O”. I refer to this method as the “Rolling,” since it encompasses all trading. Further discussions of these two methods, along with specific graphs, of each are depicted later in this report.

The Essence of Time

As noted earlier, by making the “X’s” and “O’s” case sensitive, we can visually illustrate the robustness of the move. The capitals will denote the end of the move, while the lower case letters will be used to show the changes between the last movement. For instance, if a stock is in the “X” column with a box size of 1 point and moves up five points in the session, the “X’s” will consist of four lower case “X’s” followed by a capital “X,” thereby indicating a strong move of five points. Moreover, if the movement was accompanied by above average trading, the boxes would be filled in dark green. This is a particularly bullish move that presents much more information to the technician in one simple graph that the current user of the Point & Figure methodology would not detect. Conversely, if a stock grinds its way higher by adding a point every session, the boxes would consist of all capital “X’s”. If volume was light, the boxes would be colored light green to forewarn the technician of a slowdown in demand.

The Snapshot Method

The Snapshot method involves comparing the stock’s volume ONLY on the day when the price movement dictates the placement of a new “X” or “O” in the box to its 30-day average daily volume. In effect, trading sessions that transpired whereby no change in the Point & Figure chart took place are not factored into the equation. For example, if shares of ABC rose 4 points, but the volume during the session was below the 30-day average, the chart would consist of three lower case “X’s” followed by a capital “X” and the color of all four boxes would be light green.

The Rolling Method

The Rolling method involves comparing the stock’s average volume during the price movement to its 30-day average daily volume on the day that necessitated the movement. As a result, this method takes into account all of the trading that transpired between the time of the last movement and the current change. For example, if shares of ABC rose 4 points, but the average daily volume during the move was lower than the stock’s 30-day moving average, then the chart would consist of three lower case “X’s” followed by a capital “X” and the color of all four boxes would be light green.

The example below illustrates the difference between the Snapshot and Rolling Methods.

In this example, since July 7 is the starting point, the color of the box under either method is determined by comparing the session’s volume to the 30-day average volume. The “X” would be placed in the box corresponding to the $37 stock price and the box color would be dark green to indicate above average volume. Subsequently, the stock’s rise to the $38 level on July 15 was accompanied by above average trading during the session (Volume of 486,200 shares versus the 30-day average of 459,920 shares), thus under the Snapshot method a box at the $38 mark would be dark green and consist of a capital “X.” For all intense and purposes the trading that transpired between July 7 and July 15 would be considered “noise” and thus not factored into the Snapshot method. However, utilizing the Rolling method, which takes into account each session’s volume between July 7 and July 15, the average volume during this timeframe was 357,533 shares, which came in below the prevailing 30-day average daily volume and thus the color of the box would be light green.

Rolling Method Versus Snapshot Method

As far as which method provides more reliable signals, further tests need to be conducted. As you will see in the following examples, there are times when the Snapshot method generates ideal buy/sell signs, while other times the Rolling method is more accurate. The importance of this exercise is to incorporate an additional dimension (time and volume) into the strengths of Point and Figure analysis to make this charting method even more powerful.

Point & Figure Charts with Total Volume

You may have come across a technique involving the placement of volume below the Point & Figure Chart. While this method is useful in gauging the total number of shares that traded while the stock journeyed between the “X” column and the “O” column, it does not display the intricacies of the price/volume action as precisely as either the Snapshot or Rolling methods. Refer to examples E in the following section for a sample of this technique.

Example A:

While the Snapshot and Rolling methods of constructing these Point & Figure charts look virtually identical, there are subtle differences that are apparent. Namely, the rallies to the triple top using the Rolling method have occurred on below average volume (indicated by the lighter shade of green boxes), thereby alerting the technician that the buying demand at the $26 price level was slowing and thereby lessening the chances for a sustainable breakout. Also notice that in the first column of “O’s” the stock moved from the $26 mark to the $22 level in one swoop as evident by three consecutive lower case “o’s” followed by a capital “O.”

Example B:

would have accurately characterized the true movement of the stock as the breakouts at the $39 and $43 marks remained intact and were accompanied by above average volume on the day of the movement. Conversely, relying on the Rolling method would have likely caused some hesitancy on the part of going long the breakouts since the average daily volume between the price movements were less than the prevailing 30-day average daily volume.

Example C:

In example C of Zimmer Holdings (ZMH), notice how the rally from the $70 level to the $80 mark transpired predominately on below average trade, thereby calling into question the buying power behind the advance and breakout above $77. However, after trading down to $67, the stock strung together a sharp rally on above average trade, as evident by a move from $68 to $76 (Eight lower case “x’s” and one upper case “X”). Subsequently, the stock pushed itself to $81 before encountering a pullback on light trade (ideal stock behavior), though the ensuing rally also took place on lighter trade which would certainly raise suspicions as to the sustainability of the rally.

Example D:

The Rolling method of Zimmer Holdings (ZMH) is virtually identical to the Snapshot view of Zimmer in the prior example, except for the leg up from $68 to $81 was not a solid dark green column, but was interrupted by an advance on lighter volume.

Example E:

In the final example, volume is displayed below the Point & Figure chart. The totals are calculated by adding up the volume of each session that the stock occupies time in the “X” and “O” column. Notice that the stock’s rally attempt from the $22 mark up to the $26 level was accompanied by a slowdown in volume (2nd green column) compared to the initial trip down from the $26 mark (1st red column). Subsequently, the rally encountered heavy selling pressure as volume while the stock resided in the “O” column totaled nearly 80 million shares. The ensuing rally has propelled the stock back to the $26 mark with volume approaching 60 million shares.

Contributor(s)

Frank E. Testa, CMT

Frank E. Testa, CMT is the Chief Technical Analyst and Vice President at CapitalBridge and has more than 20 years of investment experience. He has developed the Power Point and Figure Charting Method that appeared in the 2005 edition of The Journal...

Chi Squared

Arthur Merrill, CMT, was a leading advocate of the need to apply statistical rigor to technical analysis methods. He frequently employed the Chi squared test to assess the validity of his backtested results. This difficult concept is usually explained over the course of several dozen pages in collegelevel statistics textbooks. Demonstrating his extraordinary ability to make the complex simple, Art published this concise and understandable explanation in his newsletter in August 1986:

If, in the past, the records show that the market behavior exhibited more rises than declines at a certain time, could it have been by chance? Yes. If a medication produced cures more often than average, could it have been luck? Yes.

If so, how meaningful is the record?

To be helpful, statisticians set up “confidence levels.” If the result could have occurred by chance once in twenty repetitions of the record, you can have 95% confidence that the result isn’t just luck. This level has been called “probably significant.”

If the result could be expected by chance once in a hundred repetitions, you can have 99% confidence; this level has been called “significant.”

If the expectation is once in a thousand repetitions, you can have 99.9% confidence that the result wasn’t a lucky record. This level has been called “highly significant.”

If your statistics are a simple two way (yes-no; rises vs. declines; heads-tails; right-wrong), you can easily determine the confidence level with a simple statistical test. It may be simple but it has a formidable name: Chi Squared with Yates Correction, one degree of freedom!

Here is the formula:

χ² = (D – 0.5)2 / E1 + (D – 0.5)2 / E2

Where D = O1 – E1 (If this is negative, reverse the sign; D must always be positive)
O1 = number of one outcome in the test
E1 = expectation of this outcome
O2 = number of the other outcome
E2 = expectation of this outcome
χ² = Chi squared

If above 10.83, confidence level is 99.9%
If above 6.64, confidence level is 99%
If above 3.84, confidence level is 95%

An example may clear up any questions:

R = number of times the day was a rising day in the period 1952 – 1983
D = number of times it was a declining day
T = total days
% = percent
ER = Expected rising days
ED = Expected declining days

Overall, there were more rising days than declining days, so that the expectation isn’t even money. Rising days were 52.1% of the total, so the expectation for rising days in each day of the week is 52.1% of the total for each day. Similarly, ED = 47.9% of T.

For an example of the calculation of χ², using the data for Monday:

O1 = 669
E1 = 799
O2 = 865
E2 = 735
D = 669 – 799 = -130 (reverse the sign to make D positive)
χ² = (130 – 0.5)2 / 799 + (130 – 0.5)2 / 735
= 43.8, a highly significant figure; confidence level is above 99.9%

If expectation seems to be even money in your test, such as right/wrong), the formula is simplified:

χ² = (C – 1)2 / (O1 + O2)

Where:

χ² = Chi squared
C = O1 – O2 (If this is negative, reverse the sign, since C must always be positive)
O1 = number of one outcome in the test
O2 = number of the other outcome.

[Chi squared is not always the correct statistical tool. When the number of observations is less than 30, Art used a test based upon the T-table statistic:]

The problem: In a situation with two solutions, with an expected 50/50 outcome (heads and tails, red and black in roulette, stock market rises and declines, etc.) are the results of a test significantly different from 50/50?

Call the frequency of one of the outcomes (a), the frequency of the other (b). Use (a) for the smaller of the two and (b) for the larger. Look for (a) in the left hand column of the table below. If (b) exceeds the corresponding number in the 5% column, the difference from 50/50 is “probably significant”; the odds of it happening by chance are one in twenty. If (b) exceeds the number in the 1% column, the difference can be considered “significant”; the odds are one in a hundred. If (b) exceeds the numbers in the 0.2% (one in five hundred) or 0.1% (one in a thousand), the difference is “highly significant.” Note that the actual number must be used for (a) and (b), not the percentages.

Example: In the last 88 years, on the trading day before the July Fourth holiday, the stock market went up 67 times and declined 21 times. Is this significant? On the day following the holiday, the market went up 52 times and declined 36 times. Significant?

For the day before the holiday, (a) = 21 and (b) = 67. Find 21 in the left hand column of the table; note that 67 far exceeds the benchmark numbers 37, 43, 48, and 50. This means that there is a significantly bullish bias in the market on the day before the July Fourth holiday.

For the day following the holiday, (a) = 36 and (b) = 52. Find 36 in the table. The minimum requirement for (b) is 56; 52 falls short, so that no significant bias is indicated.

Table for Significance of Deviation from a 50/50 Proportion: (a) + (b) = (n)

This is essentially the T-table statistic. It should be used instead of Chi Squared when the number of observations is less than 30.

Source: Some of the figures were developed from a 50% probability table by Russell Langley (in Practical Statistics Simply Explained, Dover 1971), for which he used binomial tables. Some of the figures were calculated using a formula for Chi Squared with the Yates correction.

Contributor(s)

Advance Decline Divergence Oscillator (ADDO)

This indicator was developed by Arthur Merrill, CMT, who passed away in January at the age of 98. Arthur tracked this indicator publicly in his newsletter, Technical Trends, for many years. Below is the description of the ADDO, as written in May 1985 and originally published in that newsletter:

The most popular method of noting disparity of the A/D line with the Dow is to visually compare a cumulative curve of (A– D) with a curve of the Dow Industrials. This is difficult, since one is a price curve and one is a cumulation, which could start anywhere.

We have developed a formula to solve this problem using regression. The resulting index can be interpreted easily: When it is positive, the Dow is tending to pull ahead of A/D; when it is negative, the Dow is falling behind.

Details

Data Base

Advances, Declines, unchanged, daily for the year preceding the current date.
Dow Jones Industrials, weekly close, for the 52 weeks preceding the current week.

Calculation

The daily advances, declines and unchanged are totaled in each week to yield a weekly series.
A weekly ratio is calculated

Ratio = (A – D) / (unchanged)

This ratio is Edmund Tabell’s idea, passed on to us by his son, Tony Tabell, CMT. “Unchanged” is used in the denominator, rather than “total issues.” The reason for this is to magnify the ratio when the market has real conviction. If it does have conviction, there will be a small number of “unchanged” and the ratio will be relatively high; when the market lacks conviction, there will be a large number of “unchanged” and the ratio will be relatively low.

The weekly ratio is then cumulated.
A regression line is then calculated (see any statistics textbook). See chart. DJI is used in the Y axis, and the cumulative ratio in the X axis. For any value of the cumulative ratio in the X axis, go vertically to the line and you obtain the expected value of the Dow for that value of the cumulative ratio.
ADDO is then a simple calculation of the percent deviation of the DJI from the regression line. A positive ADDO will mean that the Dow is pulling ahead of A/D, and a negative ADDO will mean that it is falling behind.

Contributor(s)

Decision Making

Robert Colby, CMT, spoke at the educational meeting of the New York MTA Chapter on November 15, 2004. This presentation can be downloaded in its entirety from http://www.mta.org/membership/video/20041115Colby/index.htm. In his talk, Robert provided answers to several challenging questions:

Can we take the guesswork out of investing and trading?
Is there any method for finding decision-making systems that can help us maximize reward/risk performance in the future?
Does historical precedent really mean anything?
Is back testing relevant and necessary?
Should we even bother to optimize?
How can we feel confident about our methods?
Can we free ourselves from opinion, bias, hope, greed, and fear?

Bob began his presentation with an in-depth discussion of the exponential moving average (EMA). He observed that it is not really a moving average, but is technically a smoothing of data based on its calculation method. It is his opinion that the EMA is the best moving average and is increasingly preferred by technicians. The calculation method for the EMA represents an excellent compromise between the simple moving average which is too slow, in his opinion, and the weighted moving average which he finds to be too jumpy.

One advantage of the EMA that Bob identified is that it follows the trend of current data smoothly. He attributes this to the fact that the average is never distorted by old data since old data does not suddenly drop from the calculation as it does in other moving average calculations. Bob paraphrased Alexander Elder who warns against using data which has experienced distortions caused by the dog that barks twice. In a simple moving average, data representing an unusually wide-ranging day may erratically impact the average on the day it occurs and again when it is dropped from the calculation. In an EMA, the effect of past data gradually fades away, and correctly avoids the problems associated with erratic price movements. Bob reviewed the formula to calculate an EMA:

EMA = ((CloseToday – EMAYest) * K) + EMAYest

where K = exponential smoothing constant = 2/(Time periods+1). As an example, a 1% smoothing is roughly equivalent to a 200-day moving average.

When testing, he compares today’s closing price to yesterday’s EMA, thus allowing test results to reflect execution at today’s closing price. After testing more than 100 indicators, Bob found that profit is maximized using short-term moving averages. Compared to a simple moving average, EMAs delivers better results at all values from 1 to 200 days, with the exception of 14 results. On average, the EMA outperforms the simple moving average of the same time frame by a factor of 3.2:1. Expanding his testing to include timeframes of 200 days to 2,000 days, Bob found that EMAs outperform simple moving averages in 64% of the period lengths.

Testing also revealed that as the length of the EMA increases from 50 to 200 days, profit declines fairly steadily. A similar effect occurs for simple moving averages, but the decrease in profitability is more erratic. Bob attributes this to those unusually large outliers dropping off the data, creating erratic trading results.

While providing very specific and detailed test results, Bob reminded the audience that his results are simply the results of the tests he conducted. Before trading, the individual trader should conduct exhaustive backtesting on the instruments selected for trading. Bob stressed that personally testing his ideas prior to trading is critical.

In his book, Bob comparably measured the performance of 127 technical market indicators. He consistently started each indicator system test with an amount of $100, and that amount grew according to the Profit and Loss effectiveness of each indicator. Time periods used to test each indicator were usually daily data from 1900 to 2001, if available, otherwise the maximum data available. In some cases, weekly or monthly data had to be used. “Annual Relative Advantage” is the result of “Versus Buy & Hold” divided by the number of years in the test. He found this ratio makes indicators measured over different time intervals more comparable and the test results allowed him to objectively compare one indicator to another. During his presentation, he shared the top 10 indicators:

Bob also discussed a variety of indicators which both outperformed and underperfomed buy and hold. All tests were conducted on a strictly mechanical basis, and he concedes that this is a limitation of his efforts. Many indicators, such as Bollinger Bands, work best with some interpretive rules. The complete test results are available at his web site.

Never published before, but presented to the audience in New York, were the results of tests Bob conducted on fundamental data. This work was not included in his book because of limitations on book size. The results show that fundamental and economic data do not generally provide profitable stock market timing signals.

A limitation of this data is the lag – often measured in months between the measurement period and the reporting date. Bob noted that although profitability is not good, the winning percentage is often high, and these indicators may have a use in analysis.

As anyone who has read his book is aware, Bob is a staunch proponent of testing, if the testing is properly conducted. To assist the audience with test design, he discussed logical pitfalls and identified six common errors to avoid:

Avoid indicators that signal twice based on the same data, such as stochastics, rate-of-change, momentum and simple moving averages.
Be aware of structural changes in a market over time. Examples: odd-lot trading data, Specialist and Member Short Sales ratios, number of issues traded, and volume. This data needs to be statistically normalized by, for example, use of ratios or deviation from trend ratios. The current relevancy of the data, based upon structural institutional changes, also needs to be assessed.
Avoid working with dollars or points after a big price move. Use percentage changes instead.
Avoid too much complexity and curve fitting – it may make the underlying logic of the rules too difficult to comprehend.
Experience is NOT the best teacher. Instead, simulate or back test. Computer testing can be much less expensive than experience.
Avoid “Trader’s Hell.” We must make certain our trading rules cover all bases, leaving no gaps that can turn into yawning chasms of uncertainty, indecision, hesitation and dysfunctional emotional excesses.

Bob concluded his talk by detailing the steps he used to conduct the testing for his book. Before presenting the nine steps to walk-forward simulation of technical market indicators, he noted that although the process is intuitively obvious, it took him some time to figure out.

Form a hypothesis, one that is well-founded in logic and observation. For example, trendfollowing may be basis of a hypothesis.
Get data, the largest quantity of accurate historical data. The more data, the greater the significance of our test results.
Check data to ensure its accuracy. No data source is perfect, so it is best to chart to chart the data and verify apparent outliers.
Segment data. Divide the database into reasonable fixed length intervals. For example, using a 100-year database of DJIA daily prices, you could begin testing on a 20-year segment, reserving the rest of the database for walk-forward testing.
Optimize using the earliest data segment, maximize reward/risk performance.
Walk forward using the parameter from Step 5 on out-of-sample, unseen data.
Add the data segment used in step 6 for walk forward simulation.
Repeat the cyclical pattern established in Steps 5, 6, and 7 until we use all unseen data.
Evaluate results for a realistic perspective on performance through time. We now have an objective basis to accept or reject our indicator hypothesis.

Contributor(s)

Robert Colby, CMT

Robert W. Colby, who holds a Chartered Market Technician (CMT) designation, is the Chairman and Founder of the Robert W. Colby Asset Management, Inc, a technical market analysis company. He also writes a daily newsletter, performs custom technical research for institutional investors,...

Conversations with the Board of Directors

The MTA is changing, and those changes are intended to lead to broader respect of technical analysis within the investment community. After less than six months of assessing the current state of the organization, the Board of Directors seated in July of last year held an intensive retreat at the MTA headquarters in Woodbridge to chart the way ahead. During a weekend of often intense debate, they found much right with the MTA. However, there is always room for improvement, and that meeting with a strong resolve to capture the talents and energy of the MTA membership to build on more than 30 years of tradition and strengths.

Director Michael Kahn took a few moments to respond to some questions about what members and affiliates should expect to see in the near future.

Q: The Board of Directors has added member communications to your responsibilities – can you describe what this includes?

A: This question is a bit broader than that. Each member of the Board is going to own a list of projects. For example, there will be one Board member who is the point man on the CMT program, one for dealings with IFTA, one for administrative issues and many, many more. Since we have resolved to open up the running of the organization and make things a lot more transparent to the membership we have decided that we need someone to keep a finger on the pulse of the group, to keep both ears open to needs and problems and to be able to communicate information back to the membership. I “own” this one.

Part of the communications plan is to have committees report back to the board each month and publish some form of progress report in the newsletter. In addition, the Board itself is going to publish monthly and again quarterly so everyone knows what is going on.

Q: What has the Board accomplished in the short time you’ve been a member?

A: I joined the Board last July and unless you were too busy making profits in the market to notice the MTA was having a rough go. From that time to November, I will admit to being slow on the uptake and slow to realize what had to be done to get the MTA back on track. Our meeting in December accomplished many things and the organization was given what I think was a pretty substantial makeover.

The number one accomplishment has been to stop the bleeding and start to mend fences. We lost members last year but at the same time made some excellent progress. With our new management team in place we are already starting to implement new ideas that I am confident will result in several things for members and affiliates – Legitimacy, Professionalism, Education and Jobs.

Q: While the loss of membership is a serious concern, there has also been a great deal of growth within the MTA. Isn’t the CMT program growing and bringing in new members in almost equal number to the losses?

A: Yes, the MTA is still growing with new members and CMT candidates but we are not after growth for growth’s sake. We want to maintain the value of membership and even more importantly the value and prestige of having the letters C.M.T. after your name.

Q: Can you discuss your priorities for the next six months as a Board member? What about your vision of the MTA twelve months from now?

A: This is a great question as there are a ton of huge initiatives now underway. Top priority is getting our house in order. We are working on getting a “top 10” list of goals together and addressing the most important challenges now facing us, like making the CMT program the best certification program anywhere.

Another major goal is establishing an exam at the SEC level to bring technical analysis up the officially recognized level of fundamental analysis. We are also looking at reestablishing our relationship with NYSSA, find an appropriate presence in New York City to replace what was lost in September 2001 and make the long awaited changes to the Constitution using proper procedure and a membership vote.

The list goes on and we’ll be able to discuss that more soon. As for where we want to be 12 months from now, I think we all agree that establishing the MTA as the place to be for technical analysis education, certification and support, with support including such things as job creation and establishment of regulatory voice.

Q: Besides serving the MTA, you have a job, which obviously takes a great deal of your time. Can you describe what you do professionally?

A: The job that actually pays me is that of a freelance technical analyst. Many members know me from Barron’s Online where I write a twice weekly column called “Getting Technical.” I also publish a daily technical analysis newsletter on all markets and contribute articles to Barron’s magazine, SFO magazine and others as the opportunities arise. It beats commuting to an office everyday, that is for sure, although I do miss the camaraderie of a trading floor.

Q: How much time do you devote to MTA responsibilities?

A: I would say that I spend some time every day with MTA business, from monitoring the message boards to bouncing ideas off other Board members. Aside from regularly scheduled board meetings, many of us talk informally about what we should be doing next with all recommendations getting back to the Board for information at a minimum and approval, if needed.

There are many “grunt work” activities, too, like actually compiling member ideas and comments into a list of action items, prioritizing them and then getting them assigned. One good example is looking at overhauling the committee structure so that we align them, and our volunteer resources, with the goals we want to achieve.

Q: What can members and affiliates do to help the Board meet their ambitious goals?

A: Volunteer. The most precious resource we have is our membership. For those new to the group, volunteering to serve on a committee is a great way to serve the MTA by contributing your time and an even greater way to serve yourself by networking with other members and affiliates. For the more seasoned among us, it is a great was to stay in touch with others and even pay it forward by helping forge the future of technical analysis.

Thank you, Mike

We’ll be talking to other Board members as a regular feature of Technically Speaking. Questions from members or affiliates may be sent directly to Board members at any time, or submitted to editor@mta.org

Contributor(s)

Michael Kahn, CMT

Michael Kahn, who holds a Chartered Market Technician (CMT) designation, is a seasoned financial services strategist, analyst, columnist, educator and speaker. Michael has been working with charts and technical analysis since 1986. He is the author of three books on technical analysis...

The Competency Model

In the Summer/Fall 2004 issue of The Pristine View, Andrew Kezeli described the stages of growth a trader must experience on the way to mastery via the use of the Competency Model (“Trading Survival 101”). In this article, I will break down the competency model (Figure 1) even further, so that each student can gain a clearer understanding of each step required towards mastery in the field of technical speculation. It is my belief that when purpose and clarity are coupled with discipline and drive-over long stretches of practice, hard work, and time-the road towards success becomes not only possible, but inevitable.

The Competency Model

FIGURE 1

Stage 1 – Unconscious Incompetence
Stage 2 – Conscious Incompetence
Stage 3 – Conscious Competence
Stage 4 – Unconscious Competence

Moving into Stage 2

Once we recognize that we are ill-equipped as new traders and self-directed investors to compete in the trading arena, what skills then do we need to move from Stage 1 to Stage 2 and on to Stage 3? To achieve mastery of a given set of trading skills, one must have a definite set of understandable rules to follow. Following these rules correctly should result in a positive result at least some of the time. How many times a positive result needs to occur in order to ensure profitability is a function of both the risk-to-reward equation and batting average, or the total number of winning plays out of the total number of chances, or plays taken. Both of these measures of risk should be incorporated into a trader’s money management plan. In other words, you need to be able to identify certain patterns from the quantum soup of random ticks that occur throughout the day as the markets are open.

We are looking for events that occur very infrequently in relationship to the total number of equities, currencies, commodities, or index futures trading on any given day. The large majority of technical data we look at is simply random. We may look through 1,000 price variations and find only three or four that we determine have a favorable odds scenario. However, couple this fact with the knowledge that equities trade on numerous timeframes and that each timeframe may offer its own set of odds, and you will see that it is possible to extrapolate enough high odds scenarios out of several given time periods to make the endeavor worthwhile. This is what we do as traders with a technical approach. We are looking for very specific price and volume patterns. Not only that, we are looking for very specific patterns indicating supply and demand imbalances in very specific places within the larger context of various securities and financial instruments.

So, how do you obtain the patterns? The answer is simple: education, exposure, and observation. You can get an education from various outlets, including educating yourself from books, industry newspapers, industry periodicals and trading schools. Perhaps you even work for an investment bank or hedge fund that engages in proprietary trading and teaches newer traders. Either way, as the old saying goes, you are going to pay tuition somehow, whether to the markets or for education. The decision is up to you.

In truth, even with a proper education, the market itself will require some form of tuition, usually through months to years of immersion and exposure. It might even be said that the only Holy Grail is rolling up your sleeves and set about gaining the necessary experience that only comes through hard work. Yet, even with the knowledge that an extended learning curve is required, you can feel assured that you are setting yourself up with the best odds of success in the long run if you start yourself off on the right foot. You can do this by starting with some form of quality education, one that may serve to shorten the required learning curve and perhaps even avert disaster and ruin along the way. Without some type of education, how will you know which rules to follow? And if you have made up your own rules, how do you know they are good ones? Without such knowledge, you may forever be lost in the mental haze and fog that embody the unconscious incompetence of stage 1; the stage that the majority of novice market participants never emerge from.

A Model Within a Model

Let’s examine a model that will allow us to develop the necessary confidence required to follow through with our trading plans and money management guidelines that we have set up for ourselves. If you have been trading a single setup and have found that, on balance, the setup is a loser, are you then going to have the confidence to trade it with discipline? Certainly not, and with good reason: It makes no common sense.

Okay, so how many of you know which of your setups are working well and which of your setups are not at any given time? It’s likely that very few of you can answer yes to that question. Or, how many of you can clearly define your market activities well enough to establish the differences between various setups? Many cannot and this is one reason they often remain locked in the mental and emotional wasteland that tends to characterize the novice group as a whole. Most price patterns work well in only certain types of markets; other price patterns may work sufficiently well in most markets, and some price patterns out there may not work at all. How do you know what’s working well in the current market and how do you know what’s not? Most novice traders want the excitement of trading during market hours but shun the far more important work that occurs when the market is closed. Novice traders have no way of separating what they are doing right from what they are doing wrong. They often grab at all sorts of random price actions and movements they really don’t understand and thereby have no way of classifying the differences. Therefore, to most easily and effectively analyze your correct and incorrect actions, you will have to be able to separate, classify, and define your actions. And this is easier to do while actively trading two different setups versus twelve. And it’s much easier to do while conscientiously studying trade setups in the quiet of the market after hours.

Which Setups Should I Pick?

One opportunity that may become invaluable to you is to research and analyze various tactics and strategies to identify the last 100 setups. Some strategies are very rare events and only occur once every few days, whereas others on smaller time frames may occur dozens of times in a single day. Your personality as a trader, your risk profile, and your trading plan will dictate which of these tactics you focus on as well as on which time frames to focus. Knowing how often these setups occur can serve as a benchmark for how often you should be identifying quality trades. Additionally, looking back over previous triggers can help you determine if you are identifying patterns correctly and also go far in helping to develop your eye as a technical analyst.

Bear in mind that any technology may not identify perfect setups every time. There is no perfect system. It takes a trained and experienced trader to extract the best opportunities from the ones that barely meet the basic equation and algorithm required to trigger an alert. Furthermore, it requires knowledge of what market phase the general averages are in to point the user to the correct tools and tactics to utilize at any given time. Certain strategies are only applicable in certain markets. As in many other fields, context is everything.

Looking back at charts using this rudimentary form of back testing to test if your entry, target, and stop criteria are valid is one way of determining if a given strategy is effective in the current market. It is also helpful in determining if you are trading this strategy correctly. Another way to track individual strategy effectiveness is by keeping thorough data on your own results. To keep accurate tabs on various strategies, you would have to track not only those trades that you took but also those that you did not take that met the required criteria for a setup. In the absence of this additional data, you would only know if the trades you are taking are working well. This leaves a lot of room for error on the trader’s part and can lead to erroneous results for various strategies’ effectiveness.

Feedback Loops

It may be prudent to simply pick a few entries and paper trade them for a while, collecting a large enough pool of statistics to extrapolate meaningful information, such as: What type of market does this strategy work best in? What time of day does this strategy work best in? Which time frames does this strategy work most often in? Building your own spreadsheet is a relatively simple task, as illustrated in figure 2.

FIGURE 2

Once you have a large enough pool of data, you can then determine which play types are working best. These play types are the logical choices with which to move forward through the learning curve. Your task at this stage is to focus solely on them. You only need two to three highly reliable tactics to profit from the markets. So your task now is to master these few strategies. Learn them backwards forwards, and upside down. More importantly, learn the mistakes you make with them and work on correcting them. Mental mistakes fall under the category of “Trading Psychology”, an often overlooked subject that can account for the overwhelming majority of a trader’s success or failure. In fact, it is often said that the psychological element accounts for 85% of success or failure. While trading psychology is beyond the scope of this article it is important to realize that, in order to make mistakes, one must first have rules to break, and that is our concern here.

From Stage 2 to Stage 3 and Beyond

Collecting and maintaining this type of objective data can be burdensome, time-consuming and tedious. It is well for the individual trader and investor to realize that his or her competition, such as the roughly 7000 hedge funds in operation today, have plenty of resources and manpower to allocate towards staying abreast of this information. Most novice traders do not have the passion or drive to maintain this data and push through these barriers in order to break down the walls of confusion that separate the losing majority from the winning minority. However, you can’t get to Stage 3 of the Competency Model unless you’ve been through Stage 2, and you certainly can’t get to Stage 4 until you’ve walked the gauntlet of the prior three stages. It takes a relentless and tenacious mind to persevere when month after month pass and the only reward is often more pain and frustration. Yet, for the persistent and determined, conducting these types of studies outside of market hours is exactly what can help catapult you forward in your market understanding and can eventually lead to more favorable results. You will have the ability to extrapolate a lot of information about your personal trading style and constructive and destructive habits. This knowledge then becomes the catalyst for enacting the change and finding the discipline that is necessary to achieving consistency in your results.

Getting through the steps of the Competency Model need only be as difficult as you decide to make it. With a bit of perseverance and the tools and strategies I have outlined in this article, you will be on your way towards trading.

Contributor(s)

Eric Davidson, CMT

Eric Davidson is EVP, Strategic Partnerships & Accounts at Neuravest Research. Eric ensures the success of strategic accounts and develops new business with alternative data providers and forward-thinking investment management firms. He has more than fifteen years of experience in operational, business...

Regions Committee Update: Where the Rubber Meets the Road!

The regions committee continues to work hard to develop its structure and programs to better facilitate the MTA’s mission – increasing the exchange of technical market analysis among dedicated professionals and educating the public as to the benefits of technical analysis. To this end, we have several initiatives under way. If you would like to help, please contact Tim Snavely at tim_snavely@rhco.com

Probably the most exciting thing that we are doing at the Regions level is CHAMPIONING BETTER TECHNOLOGY for the organization as a whole! We continue to advocate a much better website, and the Regions Committee shared a proposal for improving our website with the MTA Board last December. Virtually all of our constituents use technology for capturing data, reviewing charts, and analyzing financial markets. The MTA has a strong technology backbone, but it needs a facelift on the front-end. A more web-centric MTA could enable us to better share outstanding analysis, resources, and content – fulfilling our MISSION and improving the benefits of membership and affiliate status. Regions has been working with MTA staff Len MacDonell and Jeanne Farrelly, especially, to put in place technology equipment and processes that allow us to capture the expert analysis presented at regional chapter meetings and share it with MTA-ers around the country through the MTA website. Leveraging our content and resources for the benefit of everyone is key, and a website facelift would go a long way toward achieving the MTA’s shared goals.
Over the next two months, we will share with all MTA-ers digital recordings of analysis by John Murphy and Martin Pring due to the efforts of our volunteer Chapter Chairs and the hard-working MTA staff. In addition, this work should also enable us to capture some content at the MTA Conference on May 19-22 to be compiled into content that can benefit all duespaying constituents. As an aside, congratulations are due also to Dave Clemens and Barry Sine for their hard work and new ideas in the area of MTA seminars and conferences.
Also, Ron Brandt, Cincinnati MTA Chapter Chair, is heading up an effort to review proposed regional Chapter By-Laws that would formalize the relationship between the chapters and the national MTA organization. Ron is reviewing structures that will continue to allow our chapters to customize the way in which each chapter addresses its own constituents, but will also allow us to formalize financing and operational policies and procedures across the nation, as well as any other potential issues.
Speaking of procedures, we recently developed some literature to streamline our processes, including an application for chapter officer applicants and a brief “How To” for getting chapters started. Meanwhile, we are attempting some pilot initiatives in Atlanta, thanks to a great Steering Committee there, and Armond Davis is working in Atlanta on a census, or survey, of our chapter participants to better understand our constituents and their needs. If you are in the neighborhood, join us to hear Martin Pring talk to the Atlanta MTA Chapter on the evening of April 28th.
Our mantra at the Regions committee for the past two years has been “Continuity and Support.” We continue to emphasize for our chapter chairs the importance of putting in place support personnel to help with the programming, scheduling, and coordinating of chapter events for our varied constituents. If you would like to VOLUNTEER, please contact your chapter chair – they could likely use some help! Our next task is to review potential incentive programs at the National level to see if we can put in place some small incentives or mechanisms to better support our volunteer chairpeople with additional volunteers and backups. Each of our chapter chairs is a professional who spends considerable time and effort to provide education and programming to a community. We need to do everything we can to put in place a framework to support these efforts and maintain the continuity of each chapter through transitions of leadership.
NEW Chapters: We are pleased to see continued strong demand for new chapters across the nation. In the past year, we have added MTA Chapters in Minneapolis, Portland, San Diego, Orlando, Tampa Bay/St. Pete, and Dallas. Some of these chapters are still getting off the ground, or are in varied stages of development – many could use a helping hand, so don’t hesitate to contact the chapter chairs shown below.

If I had just one thought to share with everyone, it would be this: The MTA is the best positioned organization in the world to bring expert market analysts and amateur technicians and investors together. It is time to realize this reality. The regions committee is where the Rubber meets the Road at the MTA and we aim to establish this organization at the corner of MACD Avenue and Trend Followers Boulevard.

The following are recent additions to the Regions/additions list on the back page of this newsletter.

Dallas: Mike Allocco; mallocco@mcstay.com
Florida, Tampa/St.Pete: Will Shahriari;wshahriari@yahoo.com
San Antonio: Transitioning – Needs a new Chair – Duke Jones; duke.jones@sectorrotation fund.com

Contributor(s)

Tim Snavely, CFA, CMT

Tim Snavely, CFA, CMT, is the current Vice President of the MTA. He graduated as the outstanding undergraduate student in finance from Emory University in 1997, and then joined the Investment Strategy team at Robinson Humphrey in Atlanta, GA.