Technically Speaking, August 2011

Letter from the Editor

Last month, we carried the news that Julie Dahlquist, PhD, CMT, had been named as the new editor for the Journal of Technical Analysis, which is the scholarly publication of our organization. Many of us look forward to the next issue, as we always have, to learn the details of new techniques in our field and to see examples of in-depth research topics.

Research articles can also be submitted to this newsletter. Generally, shorter articles will be found in the newsletter while detailed and thorough examinations of a topic are more suitable for the journal. The monthly publication schedule also allows for immediate feedback to the author from the thousands of members around the world who will see the article.

Hopefully you’ll find the research being offered in Technically Speaking useful. We’ve also included member profiles in this issue, which may help newer members see that there is no single career path in the field. MTA members have varied backgrounds, and success is determined by hard work more than any other factor.

We strive to provide content that is useful, readable, and varied. If you have ideas for articles you’d like to see, please let us know with an email to editor@mta.org.

Sincerely,
Mike Carr, CMT

What's Inside...

A Market Technician Considers Value at Risk

Value at Risk (VaR) is an important risk management tool used by many institutional traders. In an article called “A...

Read More

Product Review of EidoSearch: Forms Shape Ideas

Any opinions expressed in the review are those of the author and not an official position of the MTA, which...

Read More

Interview with Keene Little, CMT

How would you describe your job?

I have been a full-time trader since early 2000. In addition to trading my...

Read More

From Snow to Lo: Data Visualization and Traders

Traders use charts to visualize data, and price charts are an indispensible aspect of technical analysis. One of the many...

Read More

Member Profile: Ed Carlson, CMT

Ed Carlson, CMT, has enjoyed a long and interesting career in the financial...

Read More

Long-Term Fundamentals Offer Clues to Technicals

Technicians usually focus on price action in a stock or market. Fundamentals are often thought of as an unnecessary input...

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Trading with Volatility

Global markets have recently reminded investors that volatility is a part of the investment environment. In US markets, volatility is...

Read More

MTA Announcements

Fall 2011 CMT Exam Administration – Registration is Open!

Registration for the Fall 2011 Administration of the CMT...

Read More

A Market Technician Considers Value at Risk

Value at Risk (VaR) is an important risk management tool used by many institutional traders. In an article called “A Primer on Value at Risk” posted by the New York Society of Security Amalysts VaR is described as an important and unique measure of risk They offer Risk posted by the New York Society of Security Amalysts, VaR is described as an important and unique measure of risk. They offer praise of VaR as a practical and understandable tool: 

Most measures show risk either as a percentage (as standard deviation and tracking error do) or in units (as the Sharpe and Treynor riskadjusted measures do). VaR shows risk in terms of money—that is, the money that might be lost.

Risk has been defined in academic terms for decades. Standard deviations, a measure of volatility, have served as the core for most of the discussion. But most investors, and almost all traders, think of results in terms of dollars, and translating risk into dollars helps them to understand the possible losses in meaningful terms.

While there are several ways to calculate VaR, all of the methods work to present the expected maximum loss, in dollar terms, at a given level of confidence. For a $1 million portfolio, the monthly VaR may be calculated as $100,000 with a 95% confidence level. This means there is a 5% chance that the trader should expect to lose more than $100,000 in any month under normal market conditions.

Calculation methods include a straightforward formula that can be applied for a single asset:

VaR = ( m + z * s) * P
Where VaR = Value at Risk

m = mean returns
z = left tail risk assuming a normal distribution
s = standard deviation of returns
P = portfolio value

Complexity increases as assets or asset classes are added, since correlation, variance, and covariance must be factored into the
equation. Other models have also been developed with different assumptions. In the end, investors are looking for an answer to the question, “How much can I lose?”

Systems traders have often defined risk in various measures, including the max drawdown which is expressed in dollars. That is a
measure of how much the strategy lost in the past during its worst period of performance. A typical system trading report, generated with Trade Navigator software and data, is shown below.

Summary – All Trades Report
Position selection All trades, From date 03/29/1972, To date 07/13/2011

The system is simply the Donchain four-week rule applied to a basket of commodities. While this shows the beginning of a tradable system strategy, most of these statistics would be excluded from an academic discussion of risk.

Most software packages also include a monthly trade report, which could be used to find the VaR. A simpler approach, from the
perspective of a technical analyst, is simply to add Bollinger Bands to the equity curve of the system test results. The difference between the equity and the lower Bollinger Band at any given time is the VaR, at the 95% confidence level. Expanding the Bollinger Bands to three standard deviations would approximate VaR at the 99% confidence level.

The math is the same as seen in the formula for VaR. Mean returns would be the moving average of the system equity, the number of standard deviations used to calculate the bands replaces the factor for tail risk, and the value of the standard deviation is an explicit part of the calculation of the lower Band.

Applying this idea to the system shown above, the value risked in any given month varies with the system performance under recent market conditions. Bollinger Bands instantaneously adapt to current market conditions, and their responsiveness can be increased or decreased by changing the look back period. For this example, the default setting found in most applications of 20-periods will be used.

This simple idea is shown in the chart below. Excel is used to calculate the values.

The resultant expected worst case loss changes each month, as equity changes and as the Bands adapt to changing market conditions. VaR also changes over time, so this is a similarity shared by the two techniques. During more turbulent times, the lower Band will be further from the level of the account equity since the standard deviation of returns increases with volatility of returns. VaR calculation methods seem to be proprietary and the look back periods themselves seem to be a trade secret among institutions. 

Test results on the Donchian system shown above demonstrate that there is great potential for this simplified risk measurement
approach. The worst loss in any month, on a dollar basis, exceeded the lower Bollinger Band only twice in the 460 month testing period. That means each month it is relatively simple to obtain a number comparable to VaR at the 95% confidence level by applying Bollinger Bands to actual account performance. Gains exceeded the upper Band significantly more often, almost 6.5% of the time. Under different conditions, these gains could possibly become large losses, but the number of months where performance was beyond either Band is still in line with the estimations derived from the more complex calculations.

For a diversified portfolio, this technique offers a startling reduction in complexity since asset correlations don’t need to be considered separately. Performance numbers already include the impact of changes in correlation. Tools of technical analysis have a number of untapped applications. In this case, Bollinger Bands, a simple and widely applied indicator, can be used to evaluate risk with more simplicity than many of the standard tools used by large investors.

Contributor(s)

Michael Carr, CMT

Mike Carr, who holds a Chartered Market Technician (CMT) designation, is a full-time trader and contributing editor for Banyan Hill Publishing, a leading investment newsletter service. He is an instructor at the New York Institute of Finance and a contributor to various additional...

Product Review of EidoSearch: Forms Shape Ideas

Any opinions expressed in the review are those of the author and not an official position of the MTA, which does not endorse this orany other commercial product.

The purpose of this article is to educate readers on EidoSearch, a platform for technical and quantitative investment professionals. The article will first provide a walk-through of the primary search feature. It will also discuss other features and functions; current and future capabilities; user interface and user friendliness; research and trading applications; and how to learn more about the platform.

The EidoSearch concept is simple. Load up a chart, search for similar looking charts. Stated more technically, one selects a time series, represented by a graph, as the search query. The search results are other time series that best-fit the query, similar to R-squared. The time series can be stock prices, indicators derived from stock prices (moving averages, RSI), price charts of other asset classes, economic series, or proprietary data. The time series can either be found in EidoSearch’s database, or imported.

Let’s walk through an example using three modified screenshots from EidoSearch. A chart of Johnson & Johnson, ticker JNJ, will be the g p g , , search query. The first screen shot is of JNJ from January 2000 to June 2011. A three year period with a distinguishable pattern is highlighted. A search is run for similar patterns amongst the other stocks in the S&P 500. The results of this query appear in both chart and table format. The table includes result rankings, company name, ticker, calendar period of match, (best-fit) score, and the ability to back test. This is shown in the second screenshot.

Back test Returns

In the second screen shot, you may have noticed check-boxes with “BackTest” written next to them. In the context of EidoSearch, a back y y test calculates the returns following the selected time series for different holding periods. The holding period options are: 1 day, 10 days, 1 month, 3 months, 6 months, and 1 year. One can back test all of the search results simultaneously. In our example, for all 56 stocks that matched the search, I ran a back test for the 1 year holding period returns, yielding a histogram of returns for each result and other statistics. Primary statistics include the number of winners and losers, mean and median profit or loss, and maximum drawdown. Such statistics can be useful in risk-reward analysis. An example is shown in the following screenshot.

For a video walk-through of the search process, you can visit www.eidosearch.com.

The following is a List of EidoSearch Core Features and Functions:

Development Goals

Prioritized EidoSearch development goals include: expanding the breadth of securities for search; enabling multifactor, cross-asset class search for all variables, instead of just price and volume multifactor search; and adding frequencies other than daily to the database’s time series.

EidoSearch may benefit from adding some nonessential functions that would enhance the user experience. One is the ability to draw technical studies, like trendlines or retracements, on charts, whether they are for queries or results. Another is an undo function for certain operations. Currently, saving queries can only be done in a roundabout fashion. For securities, only line charts are available; no bar charts or candlestick charts. Also, time series are only presented on linear scales; no log or semi-log charts. Several platform functions can be more intuitive and faster.

Since patterns are fractal in nature, in theory, a search could match an intraday chart with a daily or weekly chart. EidoSearch has partially achieved such functionality. A premium feature enables one to search for predefined patterns, such as Head & Shoulders, or Double Bottoms, for any duration set by the user. For securities, these are based on close only, daily data. Adding other time frequencies, a prioritized development goal, would be a step closer towards enabling one to search for best-fit matches among any time frame for ad hoc selected patterns.

Competition

Two types of software that provide similar search functionality utilize either statistical analysis (Palantir, Matlab, and R by the R-Project) or rule-based back-testing (TradeStation). The former were designed for general data analysis, of which statistical research and financial modeling are applications. Jake Hoppe, of EidoSearch, notes that these, “contain libraries of statistical and programming operations that offer more convenience than traditional programming languages, and more flexibility than Excel.” Nevertheless, mastering or gaining proficiency in any of the above stated platforms requires a substantial amount of time. Once mastered, testing a particular trade idea, or specifying a query, may still occupy dozens or even hundreds of hours. In contrast, EidoSearch was expressly designed, to research and monitor trade ideas, and discover relationships, quickly. In seconds, anyone can perform comparable searches that yield desired data.

EidoSearch Application Examples

EidoSearch is a research tool that can aid in an investment process, whether it is used for hypothesis testing; for macroeconomic studies; for risk management; or for idea generation. Like most tools, it is inexhaustible— and like most tools, it can only get you so far. Larry Berman, CFA, CMT, CTA of ETF Capital Management, is a current user of EidoSearch. As a Commodity Trading Advisor whose firm utilizes technical and other pattern recognition methods, he states that, “EidoSearch adds a phenomenal amount of confidence as to what a potential outcome might be…and improves our ability to manage risk.” He has also used the platform to construct an index that weights the components of the S&P 500 based on technical parameters. Results from this model, back tested over a 10-year period, has produced positive alpha, aftertransaction costs. The following is an illustrativelist of other potential research applications:

Trading:

  • Test trading rules or signals established independently to validate or invalidate conclusions
  • Event Driven: search for volume only or volume and price patterns that occur prior to: acquisitions, bankruptcies, earnings reports.
    (May require the user to import data on delisted companies.)
  • Volume only or volume and price searches to identify accumulation and distribution

Technical research:

  • Both trading professionals and academic researchers will be able to back test popular technical patterns
  • Discover potentially profitable undefined or complex patterns

Macro and Fundamental

  • Using the “SearchOne” tool, search within the same economic series for recurring patterns that may have predictive value on
    economic developments
  • Combine fundamental with technical analysis by searching for results in a predefined environment, such as searching only within periods of oil shocks, economic expansion, or high interest rates.

Conclusion

To summarize, in EidoSearch, a selected time series, represented by a graph, is itself the search query. The search results are other time series that best-fit the query. The platform is built to “research and monitor trade ideas, and discover relationships” quickly. For this specific purpose, EidoSearch may currently be the best platform available to the investment community. One can expect continual additions to its feature set and improvements to its speed and user interface. 

Many of its features were not discussed in this review. Numerous research applications are possible, with a small handful illustrated in this article. The platform undoubtedly can supplement research and be integrated into an investment process, especially for technicians, quantitative analysts, and other investment professionals who work with time series. I suggest learning more about EidoSearch to see if there is a place for it in your investment process.

How to Learn More

Contact David Kedmey, dkedmey@eidosearch.com, or Jake Hoppe, jhoppe@eidosearch.com. Prospective clients are given a full tour of the platform by one of EidoSearch’s staff members. EidoSearch may also provide custom programming to meet specific client needs. Around the clock customer service is available by phone or email. The company website is www.eidosearch.com.

Contributor(s)

George Rahal

George Rahal has been writing about financial markets for several years. He began his career in Lazard Capital Markets’ equity research department. He has since been involved in technical research and trading, which he applies in his current role at Landor Capital...

Interview with Keene Little, CMT

How would you describe your job?

I have been a full-time trader since early 2000. In addition to trading my own account I also manage and trade several
small accounts for others. I analyze the financial markets and write daily market commentary (for both a paid
subscription service and my blog site (http://blog.capitalmarketvision.com/). Here’s a short bio:

Accomplishments

  • Chartered Market Technician, member of Market Technicians Association.
  • Write daily and weekly market commentary for traders and investors.
    • Analyze and write for a subscription newsletter — OptionInvestor.com — providing live market commentary for
      active traders and a weekly summary showing longer term trading signals to assist traders, investors and
      fund managers in their trading decisions.
  • Provide specialized assistance to fund managers — forecasts, market timing signals, trade setups and portfolio
    management; short term and longer term charts prepared for customers and brochures

    • Analyze financial markets (global, stock, bonds, commodities, currencies) for intermarket relationships to
      help portfolio managers make timely portfolio adjustments.
  • Trade long and short with a focus on options strategies using a market-neutral approach with directional plays
    when warranted.

Skill Set

  • Analytical and writing skills–can take complex market analytical strategies and explain to others. Can boil down to a
    roadmap approach to the market. Many technical analysis tools used but very strong with Elliott Wave analysis which
    is one of the best market predictors available, especially when using other technical tools/indicators for
    confirmation.
  • Technical analysis includes Elliott Wave Theory, Fibonacci, trend lines and channels, oscillators (momentum),
    sentiment, market breadth and many other tools to create charts that provide a trading roadmap for traders.

What led you to look at the particular markets you specialize in instead of another tradable?

Several years ago I decided I wanted to trade options and futures. For the stock market I prefer to reduce my risk by not trading individual stocks, particularly for overnight trades. The e-mini futures are an excellent trading vehicle for day trading as well as swing trading (obviously more risk holding a futures trade overnight). I prefer to sell premium and therefore like the European-style indexes, such as SPX and RUT, for selling naked or spread positions. For smaller accounts I like to use the ETFs for each (SPY and IWM, respectively). I like selling iron condors for a sideways market and naked or vertical spread positions for directional plays. When I think the market is getting ready for a bigger move and volatility is low I like to go long options, especially puts for a move down (to benefit from premium inflation as VIX climbs during a stock market decline).

Because of the intermarket relationships between the stock and bond market I also like to trade the bonds, usually the e-minis (ZN and ZB for the 10-year and 30-year, respectively). I also like the bond ETFs TLT and TBT (the inverse fund). Watching the relationship between the bond and stock market is a very useful way to help confirm a move in one versus the other (staying aware of the change in relationship over the years, such as the tight relationship between Treasury yields and the stock market since 2007).

Because of the Fed’s efforts over the years to increase liquidity in the market I also watch the U.S. dollar and commodities, specifically the metals and oil. I trade UUP for the dollar, SLV and GLD for silver and gold (as well as the e-minis — YI and YG, respectively) and USO for oil. In addition to those ETFs, especially in the secular bear market that we’re in, I also trade the inverse ETFs. The stock market and commodity markets have tended to trade counter to the U.S. dollar, especially since 2007, and they’re very good to watch for confirmation signals.

The above listed symbols make for a good variety to trade without overwhelming me when performing my daily analysis on their charts.

Do you look at any fundamental or economic inputs to develop your opinions?

I read a tremendous amount of material during the day and evenings. First of all I’m very interested in what drives the mood of the market. I also realize that while I heavily emphasize technical analysis there are many who are basing their trading/investing decisions on fundamentals and economic expectations. The market is driven by fear and greed, with fear being the more powerful emotion. I need to know what’s going to drive those emotions and when I can get a good feel for what the fundamental and economic expectations are it helps me confirm (or not) what my technical analysis is telling me. It’s my way of fighting a bias — I want to see the technical picture supporting what I believe is the mood of the market. At the end though, all trading decisions are based on the charts — I pull the trigger to get into a trade and exit the trade based on what I see on the charts. What’s known by the market is already reflected on the charts. The rest is just guesswork by prognosticators.

Can you share any longer term market opinions?

I believe in market cycles and the secular cycle that we are currently in is a bear market. The market (and economy, which the stock market predicts) was in a secular bull market from 1982 to 2000 and has been in a secular bear market since 2000. By analyzing past patterns and timing I believe we’ll be in a secular bear market into at least 2016 (it could go longer if the Fed keeps fighting it). I believe we’ve finished the cyclical bull market (2009-2011) within the secular bear and we’ll now enter another bear market leg down into 2013 (and then another cyclical bull followed by a final cyclical bear).

There are two possibilities that I see for the next bear market leg down. We are either in a large sideways consolidation (similar to the 1970s) or we’re going to keep heading lower with each leg down, similar to Japan (which is the way I’m leaning currently, based on an analogue pattern between the Nikkei 225 and the S&P 500). By several methods of projections I see a downside target for the S&P near 475 before the bear is done with us.

A swing back to a fearful social mood, currently underway, is the driver behind the return of the bear. It’s why the Fed is only an obstacle to getting through this and has no control over stopping it. We have to get through it to get to the other side. For astute traders (not buy-andhold investors), who can, yes, market time, there are significant profit opportunities in a bear market. One does not need to hole up for two years and wait for the next bull market.

What advice would you have for someone starting in the business today?

Experience is the key to success. The question is often asked about how to become a millionaire by trading the stock market. The answer is always “start with 10 million”. Education is the key but the best teacher is trading under live fire and there will be losses. The key of course is controlling the losses through proper risk management and iron-clad trading rules for stops and exit strategies. One of the first suggestions is to understand the emotional component of trading — that fear and greed thing. Getting control of that and following very strict trading rules, with no exceptions (never modify a rule while in a trade, only after), will enable you to make steady progress (base hits, not home runs). And then keep educating yourself because the market is constantly changing.

I took a lot of trading courses in the beginning of my trading career and still struggled (I’m not one of those naturally-gifted traders) for several years. I read many trading books and learned some difficult analysis techniques (such as Elliott Wave Theory). One of the most effective ways that I learned was through the MTA’s CMT program. I thought I knew a lot about technical analysis by the time I started the program (I had been a full time trader for about seven years and one who studied the market for hours on end) but by the time I was a designated CMT I realized how much had come together for me. My analysis was sharper and readers of my work noticed a big difference in the clarity of my opinions, which are not always right but at least they’re clearer (smile).

The other key to success for most traders is to find a trading buddy/mentor. By sharing your trade opinions and trades with others you’ll have someone to challenge you to be honest and unbiased. Trading groups are also very effective for this although you have to be careful with these — they can be very distracting and give you all kinds of trading ideas (hot tips) that don’t have any merit (driven by emotions rather than solid analysis). I don’t listen to the radio or TV during the day for the same reason — I stay very focused on what I’m seeing in the charts (there’s a lot of information to be gleaned other than just the change in prices).

Trading logs are highly recommended and most traders don’t do it. I found that my trading took a huge leap forward when I started writing for a newsletter. The act of writing my thoughts down, backed up with charts, solidified my thinking from which it was much easier to make a trading plan (where and when to enter a trade, how big of a trade, what my target was and of course where it made sense to place my stop). If you’re not fortunate enough to be a paid analyst/writer, do it anyway for yourself — make it your trading log. Establish a blog and do it every night even if you’re the only one who reads it. It establishes a record you can review at any time but more importantly it forces ideas out of your head and onto “paper”, an act that takes it out of the right side of the brain (the creative but undisciplined side) and places it in the left side (the analytical, disciplined side). It makes a huge difference in one’s trading results, especially if it forces you to wait for your trade setup to come to you rather than force a trade on the market just because you’re bored. Forcing trades because you “just know it’s going to work” is the fastest way of turning that 10 million into 1 million.

These questions and answers have been compiled by Amber Hestla, an independent market researcher. If you’d like to participate in a future interview, please contact her at hestlaresearch@gmail.com.

Contributor(s)

Keene Little

Keene Little has been a full-time trader since 2000. In 2003, he became an analyst/writer for an options newsletter posting daily live commentary throughout the trading day and sharing the duties with the other analysts for that site’s nightly market wrap. In...

Amber Hestla-Barnhart

Bio coming soon.

From Snow to Lo: Data Visualization and Traders

Traders use charts to visualize data, and price charts are an indispensible aspect of technical analysis. One of the many interesting aspects of technical analysis is that academia takes many of the concepts technicians study and apply a different perspective to the tool. Quantitative analysis is similar to many of the screening techniques technicians have long used, and in some cases quantitative analysis involves applying technical principles like relative strength to fundamental data. Behavioral finance is offering explanations for why chart patterns work. Data visualization is another example of this idea.

Data visualization is an effort to present information in a meaningful manner. Edward Tufte, a professor at Yale University, has been one of the leaders in this field, and has written several classic books on the subject. He defines the subject simply as “Data graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading, and color.”[1]

Excellent graphics, according to Tufte, make large data sets coherent and presents complex ideas with clarity, precision, and efficiency. Price charts accomplish these goals for technical analysts. A simple bar chart presents price and time in the simplest way possible. Candlesticks and other techniques add clarity and precision to the data without sacrificing efficiency. Those who use these techniques often find they improve analytical efficiency by allowing them to grasp additional information with a single glance. 

Tufte did not invent the field of data visualization, although he certainly is one of the greatest contributors to the discipline. He has collected countless examples and presents many in his books. One of these is the cholera map prepared by Dr. John Snow to fight an epidemic which ravaged London in the nineteenth century.

HTTP://WWW.CSISS.ORG/CLASSICS/CONTENT/8

The map plots deaths from the epidemic, with each block showing where a victim of the disease resided. Snow used it to isolate the source of the cholera, which was a water pump located near the greatest concentration of suffering. Snow’s work saved many lives and laying the foundation for the science of epidemiology.

In Snow’s map, we can also see one of the potential problems technicians face. There are outliers and anomalies in the data. Some deaths were occurring far from the deadly water pump, presenting outliers on the map. There is also an anomaly in the fact that not everyone near the source developed cholera. Snow dug into his data, visited the scene and identified that some travelled blocks to get the water, and spread the disease far beyond the source. Others lived nearby but did the opposite, going to other pumps for water which saved their lives.

Price data presents technicians with outliers, which are extremely large moves that occur in a short time. Anomalies include stocks which move counter to the prevailing stock market trend. We can argue that this is where the art of technical analysis comes in, where technicians can learn more from the deviations, when prices don’t behave as expected.

Tufte cites the work of an unrecognized pioneer of technical analysis as another expert in data visualization. After World War I, Colonel Leonard Porter Ayres produced “The war with Germany: a statistical summary” for the United States War Department. This book is filled with innovate charts and diagrams that show the magnitude of the war effort. Army units are often designated with a number to differentiate them from other units. One exam ple of Ayres’ work is shown below, where he uses Division numbers to illustrate the size and speed of the American deployment to France.

DIAGRAM 43 FROM “THE WAR WITH GERMANY: A STATISTICAL SUMMARY2”

After the publication of this study, Ayres’ successful career in the Army was recognized with an additional promotion, to the rank of Brigadier General. He then attained a level of success in his next career, which saw Ayres move into finance and work as a Senior Vice President at Cleveland Trust. In this position, he developed another visual tool that is still used by technicians who may not realize where it originated. Ayres is credited with developing the advance-decline (AD) line in 1926. The story of his innovation is well told by Tom McClellan in a short pamphlet he prepared to honor his parents, Sherman and Marian McClellan, when they were recognized with the 2004 MTA Lifetime Achievement Award.3 Tom explains how that innovation led to other advancements in the study of technical analysis.

An example of the use of the AD line is shown in that pamphlet, and reproduced below. The divergence in breadth is a visual cue to many analysts that the trend in price is about to change. The example, from the spring of 1962, highlights how useful this indicator can be.

SOURCE: HTTP://WWW.MCOSCILLATOR.COM/DOWNLOAD/SPECIAL/MCCLELLAN_MTAAWARD.PDF

In recent years, Andrew Lo, Harris & Harris Professor and Director of the Laboratory for Financial Engineering (LFE) at the Massachusetts Institute of Technology, has made great strides in the visualization of financial data.

In an interview almost ten years ago4, Lo explained why data visualization is important. He said, “If the goal is survival then what is more essential than being able to tell if the thing you see on the horizon is friend or foe, something to pursue or to flee? Evolution has made us all very visually attuned.”

As part of his work, Lo led an effort to design a visualization tool that would help traders manage risk by displaying the mean, variance, and liquidity of different investments in a three-dimensional display that, he told the interviewer “resembles the Sydney Opera House.”

Lo has also studied the head and shoulders pattern from an academic perspective.5 He quantified the rules for the chart pattern, which has been a mainstay of technical analysis since at least the 1920s. Working with fellow researchers, they concluded that this visual pattern, along with several other technical indicators they studied, “do provide incremental information and may have some practical value.”

Since Snow worked to stop the spread for cholera in London in 1854, data visualization has made major advances. Lo’s work may be an example of a future are of research in technical analysis. He finds value in presenting financial data as insightful displays. While the head and shoulders was first documented and explained nearly 100 years ago, computers now allow for quantification of visual patterns, and may lead to improved trading results. The ability of Snow to evaluate the source the data, combined with the ability to program ways to profit from the visual patterns, offers new opportunities for technicians while visual charts continue to provide options for traditional analysts.

  1. Tufte, Edward, “The Visual Display of Quantitative Information,” 1983, Graphics Press, Cheshire CT
  2. http://books.google.com/books?id=VDIpeq08BdAC&pg=PA9&source=gbs_toc_r&cad=4#v=onepage&q&f=false, page 102
  3. The entire pamphlet can be downloaded at http://www.mcoscillator.com/download/special/McClellan_MTAaward.pdf
  4. http://www.cfo.com/article.cfm/3005332/c_2984335/?f=archives
  5. Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation, Andrew Lo, Harry Mamaysky and Jiang Wang, web.mit.edu/alo/www/Papers/1705-1765.pdf

Contributor(s)

Michael Carr, CMT

Mike Carr, who holds a Chartered Market Technician (CMT) designation, is a full-time trader and contributing editor for Banyan Hill Publishing, a leading investment newsletter service. He is an instructor at the New York Institute of Finance and a contributor to various additional...

Amber Hestla-Barnhart

Bio coming soon.

Member Profile: Ed Carlson, CMT

Ed Carlson, CMT, has enjoyed a long and interesting career in the financial industry. Traditional jobs, or
at least what many think of as traditional analyst positions, are disappearing and Ed’s story may help
others find success in the field. We hope that this will be the first in a series of career paths followed by
MTA members.

Ed’s start in the business came about almost by accident. In late 1989, he had returned from a yearlong internship in China and finished his MBA that year. By early 1990 the economy was headed into a
short recession and like many recent graduates, he was having trouble finding employment. A sixmonth stint working the graveyard shift on a factory floor during the winter of 1990 gave him an appreciation for any desk job that might come along.

One day, during lunch at a small restaurant, he spotted a Dean Witter broker that he had cold called several years earlier, during his first semester in graduate school. The broker remembered Ed, and asked what he was doing. The response was similar to what many recent graduates say now, “looking for a job.” The broker suggested applying for a position with Dean Witter. Ed remembered that he had enjoyed the four months he had spent in the office. He liked the people and the idea of discussing investments and the economy with colleagues and clients appealed to him, but the idea of cold calling for customers left him even colder. The need for a job overcame any doubts, and he decided that if they would take him, he would do his best and make it a career. Time was on his side and Ed landed a financial services job during the biggest bull market in history.

This allowed Ed to rekindle his early interest in technical analysis, a subject he’d always been curious about. He read his first book on the subject while in junior high school. Although the name of that paperback book is long forgotten, Ed does remember that it was a difficult book to read and although he didn’t understand much of it at the time, he was interested enough to finish the book.

But, as he began his career as a stockbroker, there really wasn’t time or even the need for a broker to use much of any type of research. He would frequently glance at technical analysis reports, along with all the other economic and fundamental reports that a large brokerage firm typically publishes. Although they may have been fascinating, during the 1990s, research was often nothing more than a distraction from the main objective of young brokers which is opening accounts.

After the 2000-2002 crash destroyed large amounts of client wealth, he realized it was time for something other than buy-and-hold. While searching for an improved method for making decisions about investments, Ed realized that he had seen the track record of fundamental research and it had been unable to help his clients preserve wealth. He decided to give technical analysis a chance.

Ed found more success with technical analysis than he had with fundamentally driven buy-and-hold investment strategies. But eventually, he felt it was time for another change, as he recently explained:

“As difficult as it was to deal with scared customers after 2000, dealing with the regulators and the brokerage firms’ response to the plethora of new regulations was even more difficult. Each year the paperwork became deeper as the number of regulations grew. And if that wasn’t bad enough, the regulations were constantly changing or at least the firms’ methods of implementing and enforcing those regulations was constantly changing. The products we had for clients were constantly changing too in response to those regulations. Every new product meant a host of new fees and other details that had to be learned and explained to clients. I saw the future as me spending all my spare time learning about products and new rules rather than the markets.

The industry spent the late 1990s and early 2000s changing the business model of the industry. It had gone from an industry MBAs and former lawyers and accountants to an industry made up of salesmen in the worst sense; people with no real understanding of the markets, only the gift of gab. Those of us who had been around for several years used to joke that if you asked a modern broker for their top 3 ‘stock picks’, they would respond “large-cap, mid-cap and small-cap”. I was no longer proud to tell people what I did for a living. I was far enough along in my career that I could have ridden what I see as a sinking ship down into the waves. A ship that I believe will, for all intents and purposes, be sunk just about the time I would be retiring. But sinking isn’t how I want to spend the last years of my career. I’m the kind of person who always has to be working toward a goal. So 18 months ago I climbed down off that sinking ship into my little lifeboat of ideas and goals and started rowing; rowing with faith that there is land out there somewhere. I am still rowing but I believe I can at least see dry land now.”

Now, Ed considers himself to be unemployed, since he doesn’t hold a traditional job, but he stays very busy even by the standards of someone who is employed. He has a website called Seattle Technical Advisors.com, where readers can find daily market commentary as well as a full weekly report for subscribers. He admits that finding subscribers was difficult at first, but notes that it’s starting to pickup now and he is optimistic that there will be even more interest in his site after his book comes out.

He says that he’s happier now that he has left the brokerage industry, noting that, “My friends used to tell me they could hear the difference in my voice when we spoke on the phone. My success or failure depends on only one person and I like that very much. I can also grow and/or change my mind about my approach to the markets as often as I feel the need and don’t need to worry about explaining that change to anyone. Life is much simpler.”

He has just finished writing George Lindsay and the Art of Technical Analysis. The effort required five months, roughly five hours per day, to complete the rough draft. The book is due at the publisher’s warehouse on August 2.

Two years ago, Ed says that he had never heard of George Lindsay. He learned of the work in an MTA Podcast interview he did with Peter Eliades in November 2009. Peter mentioned Lindsay and Ed’s follow-up question was how he could find out more about Lindsay’s work. The only help Peter could offer was that he thought Investors’ Intelligence had some old newsletters. He was right, and Ed was able to get a copy of those newsletters, discovering that Lindsay’s methods, while not simple, intuitively made sense.

Lindsay’s work had nearly disappeared by the time Ed stumbled upon it. In addition to the small collection of writings from Investors Intelligence, he was able to obtain a few more examples of his work from John Bollinger and Janice Teisch, the widow of Lindsay’s business partner Stuart Teisch. Ed is optimistic that more of Lindsay’s work has survived, “I’m sure there are more out there and if anyone has access to them I would love to hear from you. I can be reached through my website GeorgeLindsay.com.”

Many MTA members have probably never even heard of Lindsay, and those who have seem to rarely use his methods. The one name pretty much everyone knows who had Lindsay’s methods figured out was Jerry Favors. Unfortunately, Jerry has passed away and Ed was unable to learn anything from his widow. Ed stumbled on a few technicians who were applying Lindsay’s methods, but some refused to divulge anything they knew, “as if they were guarding nuclear secrets.” Others, Ed noted were very tight lipped but smart enough to realize that, with the research he was conducting, they might be able to gain further insights into Lindsay. There was a sort of quid-pro-quo relationship that developed with these technicians.

Since Lindsay had never written a book on his market methods, anyone wanting to apply them had to find his newsletters. To make matters worse, Lindsay wrote with a very dense style. Ed commented that, “Reading those old newsletters is like drinking from a fire hose. I wanted to make his ideas more readable and save them before they disappeared forever.”

Perhaps the most famous idea shared by Lindsay is the three peaks and domed house pattern. The nominal pattern is shown below.

Starting in the fall, Ed will embark on a number of speaking engagements, mostly with CFA Societies, and will be traveling all over the country to talk about the methods in the book.

Ed intends to keep busy writing in the future. Although he hasn’t spoken to a publisher about the idea, he’s already working on his next book. In this one, he’ll apply Lindsay’s methods to the entire history of the Dow. It’s a natural follow-on to his first book and Ed believes that that anyone who becomes interested in Lindsay’s models will want more examples of how these models are applied. This is a long-term project, which he expects to take at least a year.

In the mean time, he’ll continue trading and studying the markets.

Ed Carlson, author of George Lindsay and the Art of Technical Analysis, is an independent trader, consultant, and Chartered Market Technician (CMT) based in Seattle, Washington. Carlson hosts the MTA Podcast Series: Conversations and contributes frequently to SFO Magazine. He also manages the website Seattle Technical Advisors.com, where he publishes daily and weekly commentary. He spent twenty years as a stockbroker and holds an M.B.A. from Wichita State University.

Contributor(s)

Amber Hestla-Barnhart

Bio coming soon.

Long-Term Fundamentals Offer Clues to Technicals

Technicians usually focus on price action in a stock or market. Fundamentals are often thought of as an unnecessary input to the decision making process. Robert Edwards, co-author with John Magee of the classic book on chart patterns, Technical Analysis of Stock Trends, is said to have completed his analysis of a chart without even knowing the name of the company.

This is definitely an approach that can be applied successfully. Fundamental analysts can be equally successful using only the data found in financial statements and failing to consider price charts at all. Both approaches which rely on a purist philosophy ignore a large amount of information that can be potentially useful. Recognizing this, John Bollinger, CFA, CMT, has written about Rational Analysis, which combines any potentially useful information into the analysis approach.

Fundamental data can be charted, just like price data. In the chart below, we see that earnings are plotted along with price changes for the S&P 500 Index. Prices form patterns on charts, and earnings do in some ways, as well. This chart goes back 35 years, and we can see that earnings invariably decline during recessions. They take several years to recover after a recession, and reach new highs several years after the end of the recession.

CHART AND DATA PROVIDED BY SRC STOCK CHARTS.

The most recent recession, dubbed the Great Recession by some analysts, appears to follow the same pattern as the previous examples on the chart. Recessions are indicated by the vertical grey bars on the chart. Earnings per share have reached new highs about two years after the economic downturn ends.

Stock prices show a strong correlation with earnings, over the long-term. This can be seen in the box in the upper left corner of the SRC chart, which is expanded below for clarity.

CHART AND DATA PROVIDED BY SRC STOCK CHARTS.

Over the past 25 years, earnings and price have advanced at about the same average annualized rate. Arguably, stock prices got ahead of themselves from a fundamental perspective during the internet bubble that ended early in 2000, and the S&P 500 Index is mostly unchanged over the past ten years as earnings have continued growing at a level near their historic average.

The last five years shows the depth of the recession on earnings per share and stock prices continued delivering low returns as earnings plunged and then recovered. Post-recession, we are seeing sharp moves higher in prices, earnings per share, and dividends over the past year. This is in line with the historic trends in all three data series.

Stock prices, as measured by the major indexes, are about where they were twelve years ago. Earnings and dividends have both grown closer to their historic averages than prices, which could mean that stock prices will start on a new bull market after building a base for more than a decade.

Traders won’t be able to find precise timing signals in fundamental data. But, they can find confirmation of price trends.

Contributor(s)

Michael Carr, CMT

Mike Carr, who holds a Chartered Market Technician (CMT) designation, is a full-time trader and contributing editor for Banyan Hill Publishing, a leading investment newsletter service. He is an instructor at the New York Institute of Finance and a contributor to various additional...

Trading with Volatility

Global markets have recently reminded investors that volatility is a part of the investment environment. In US markets, volatility is defined and measured by the VIX Index. This offers traders a unique insight into the implied volatility of prices. Some commentators have taken to calling the VIX a ‘fear index’ because volatility spikes as prices fall and traders seem more fearful than complacent during rapid declines, such as the one most markets experienced after multiple tragedies struck Japan in March.

While the methodology for calculating the VIX is available, it is complex and requires that liquid options markets exist for the security being  examined. Not all tradables, especially emerging markets, will necessarily have options contracts available. Global markets tend to show a high degree of price correlation in times of crisis but general tendencies such as this make poor trading rules since they only work until they stop working. This means the VIX has very limited applicability for non-US traders.

In the academic literature, financial market volatility is generally defined in terms of standard deviations. While standard deviation captures historical volatility as opposed to implied future volatility, this concept can offer us an alternative trading tool for those markets that lack a VIX index. At least visually, we can see a relationship between the two volatility measures in Figure 1.

FIGURE 1: A MONTHLY CHART OF THE S&P 500, BOLLINGER BANDS AND THE VIX SHOWS THE RELATIONSHIP BETWEEN HISTORIC AND IMPLIED VOLATILITY. (SOURCE: TRADE NAVIGATOR)

In that chart, the price of the S&P 500 is shown within Bollinger Bands. This indicator is a commonly used tool calculated to show the levels that bound two standard deviations of the average price. In theory, almost 95% of the price action should be contained within the Bands. Market prices don’t precisely follow a normal distribution and the reality is more than 5% of the price action takes place outside the Bands. However, when prices move below the lower Bollinger Band, markets are at an extreme level and risk is lower than when prices close above the upper band.

The Bollinger BandWidth is shown below prices in Figure 1, offering a visual indication of the distance between the upper and lower Bollinger Band. Higher values and a rising BandWidth are associated with increasing market volatility.

Below the BandWidth, we see the VIX and finally the chart includes the mathematical correlation between changes in the VIX and the S&P 500. Both indicators show the same general shape and the mathematical correlation conforms the generally inverse relationship between the direction of changes in volatility and changes in prices. This implies that Bollinger Bands may offer an indicator of excessive volatility in markets for which the VIX is not available.

Traders commonly use breaks of Bollinger Bands to spot trend reversals. In Figure 2, we show a slightly different twist to this idea and apply Bollinger Bands to the 26-period rate of change of prices. When the ROC exceeds the upper Band, prices are likely to have gone too far, too fast and a reversal is expected. These instances are shown with the red arrows over price. Breaks of the lower Band, indicating excessive moves to the downside are highlighted with green arrows.

FIGURE 2: APPLYING BOLLINGER BANDS TO THE RATE IF CHANGE OF PRICES IN THE SHANGHAI COMPOSITE INDEX OFFERS TIMELY TRADING SIGNALS. (SOURCE: TRADE NAVIGATOR)

Volatility extremes offer valuable trading information, however, very few markets offer an index to display volatility. Bollinger Bands, especially when applied to the ROC of prices, can overcome this limitation and offer nearly the same information for any security in any market.

This article originally appeared in Shares magazine, April 7, 2011, and is reprinted with permission.

Contributor(s)

Michael Carr, CMT

Mike Carr, who holds a Chartered Market Technician (CMT) designation, is a full-time trader and contributing editor for Banyan Hill Publishing, a leading investment newsletter service. He is an instructor at the New York Institute of Finance and a contributor to various additional...

Amber Hestla-Barnhart

Bio coming soon.

MTA Announcements

Fall 2011 CMT Exam Administration – Registration is Open!

Registration for the Fall 2011 Administration of the CMT Exam is open for all levels! Sign up today to ensure your preferred location by visiting: http://go.mta.org/registercmt. If you need help registering or have any trouble scheduling your exam with Prometric (our outside test center), contact Marie Penza at 646-652-3300.

For detailed instructions on registering online, click here.

To read an important announcement regarding the test dates for the Fall 2011 Administration, click here.

Membership Dues Renewal

Approximately 25% of our membership has dues expiring in the months from June to August! It is important that you renew in a timely fashion to ensure there is no disruption in overall MTA services. To renew…

    • Login into your account by visiting http://www.mta.org Select the MyMTA link to access your account information.
    • Once logged in, look to the right of the page. You will see a large, blue “renew” link. Click this link to begin renewing your dues.

For detailed instructions on how to renew your membership (including screenshots), click here.

After you’ve completed the renewal process online, you will receive an e-mail confirmation with a receipt for your records. If you would prefer, you can call the MTA Headquarters at 646-652-3300 and renew over the telephone with any of the MTA Staff members.

CMT Institute Preparation Courses – Registration Now Open for All Levels

The CMT Institute (CMTi) is a 4 session webinar course to help prepare you for the CMT Exam. These courses are taught with the assumption that you have completed all of your recommended reading materials.

Registration for all three levels of the CMTi is now open! For more information about the dates of the courses, the instructors, and to register for any level, visit: http://go.mta.org/cmti

Calling All Authors and Book Collectors – A Special Note from the MTAEF

The MTA Educational Foundation (MTAEF) has a unique opportunity to raise the visibility of Technical Analysis and the MTA/MTAEF Library at Baruch College!

Baruch College has always had a special relationship with the MTA. Not only being in the forefront of schools teaching Technical Analysis since 1998 and the home of the MTA/MTAEF Library, but Baruch College also gave the MTA a place to
meet after the September 11th, 2001 attacks. 

Recently, the Newman Library at Baruch College has offered to put up a display in its main reading room titled “Technical Analysis: A Global Language.” Over 100 students per semester study Technical Analysis at Baruch College and many
more use their trading room. This new display means that a bigger audience at Baruch College could be exposed to the subject in their native language.

How can you help? If you have a book on Technical Analysis written in Russian, Chinese, Japanese, Spanish, German, etc. and you would like to donate it to the MTA/MTAEF Library, please send it to the MTA Headquarters Office in New York.
If you have any additional questions about the MTAEF, the MTA/MTAEF Library, or how you can help, please contact Bruce Kamich, CMT (MTAEF President) at barchart@comcast.net.

MTA Chart Wall Informational Video – Coming Soon!

As you know from previous correspondence, the MTA recently installed a “Chart Wall” in our conference room at 61 Broadway, New York, NY. This “Chart Wall” was once the center piece in the Kidder, Peabody & Company’s Technical
Research Department’s “War Room” in lower Manhattan. 

This past week, Ralph Acampora, CMT came to the MTA Headquarters Office with a video production team and recorded an informational video on the history of the “Chart Wall” and how Technical Analysis has evolved from the 1970’s to today.

This video will be available online over the course of the next week!

Contributor(s)