Technically Speaking, March 2013

LETTER FROM THE EDITOR

The MTA has long recognized the value of diverse techniques in the field of technical analysis. In this month’s newsletter we try to live up to that tradition and present both visual and quantifiable approaches to analysis.

We start with an overview of the career of John Bollinger, CFA, CMT. We then summarize the career of Susan Berger who has spent 45 years working in technical analysis (so far) using the techniques she learned from John Magee. It is fascinating to read how Susan did things when working with Magee. It is equally fascinating to think back at the advance that Bollinger Bands represented when they were introduced about 15 years into Susan’s career. Chart paper and grids for calculating indicators were being replaced by personal computers in the 1980’s and John Bollinger was among the first to recognize that new environment. He introduced an indicator that would have been unthinkably complex to implement in the 1970’s.

Several newer techniques are also featured in articles by Scott Hathaway and Alan Hall who works with Dr. Robert Pechter, Jr., CMT, at the Socionomics Institute. Dr. Prechter will be sharing his latest work at the MTA Symposium in a few weeks along with a number of other speakers. The Symposium will truly be a showcase for the diverse techniques of technical analysis as an amazing group of experts share their research and experience.

As always, we would appreciate receiving any comments you have on the newsletter, which can be emailed to editor@mta.org.

Sincerely,
Michael Carr

What's Inside...

JOHN BOLLINGER: A BRIDGE TO THE FUTURE OF TECHNICAL ANALYSIS

There are always a number of ways to characterize a career. John Bollinger made a significant contribution to the Body...

Read More

22 BOLLINGER BAND RULES

Editor’s note: In Bollinger on Bollinger Bands, there were “15 Basic Rules” included, a list that has grown to 22...

Read More

MORE MAJOR ACCOMPLISHMENTS OF GAIL DUDACK, CMT

Last month we highlighted the career of Gail Dudack, CMT, now the Managing Director of Dudack Research Group a division...

Read More

IN MEMORIAM: DR. MARTIN ZWEIG

The investment community lost one of its leaders in February when Dr. Martin...

Read More

DEFINING SUCCESS IN TECHNICAL ANALYSIS: SUSAN BERGER’S 45 YEARS IN TA

Technical analysis is still a relatively young field of study. Edwards and Magee...

Read More

CURRENT VIEWS OF CLASSIC TECHNICAL ANALYSIS TECHNIQUES

Editor’s note: this is an example of Susan’s work. It is interesting to see how it applies the fundamentals defined...

Read More

INTERVIEW WITH MUKUL PAL, CMT

THIS ARTICLE WAS EDITED.  REVISED ARTICLE IN NEXT MONTH’S ISSUE

Read More

THE PERFORMANCE OF INSTITUTIONAL PORTFOLIO MANAGERS WHO USE TECHNICAL ANALYSIS

Editor’s note: This paper was recently published at the Social Science Research Network, http://go.mta.org/3437. It presents an academic view of...

Read More

MTA EDUCATIONAL FOUNDATION UPDATES

Mike Epstein Award. The MTAEF announced the presentation of the 2012 Mike Epstein Award to Julie R. Dahlquist, Ph.D, CMT...

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THE THIRD, PART TWO: TWO DISTINCT PARABOLIC POSSIBILITIES FOR THE S&P 500

I offer this parabolic article exactly 1 year after my previous parabolic article in Technically Speaking, Mar 2012, which can...

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SOCIONOMICS AND THE ELLIOTT WAVE MODEL PROVIDE A FRAMEWORK FOR PROJECTING THE LAG TIME FOR NEWS

One of the most important things to understand about the stock market is its relationship to news. Aside from emotional...

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JOHN BOLLINGER: A BRIDGE TO THE FUTURE OF TECHNICAL ANALYSIS

There are always a number of ways to characterize a career. John Bollinger made a significant contribution to the Body of Knowledge and the practice of technical analysis with Bollinger Bands. This indicator adapts to the recent market action and helps answer the question of “when should we consider prices to be high or low?” With Bollinger Bands, the advice to “buy low, sell high” can be quantified and acted upon.

While this contribution is significant and could characterize John’s career, we could also view his career as a bridge to the future. In the early 1980’s, Bollinger Bands used the new technology of personal computers to link the past with the future.

Technical analysis began as a visual tool, and Bollinger Bands help place what we see on a chart into context by defining high and low. Bollinger Bands are in a way a bridge from the visual age of technical analysis to the modern age of technical analysis where computers display indicators and analysts can test any idea. It is possible to calculate Bollinger Bands by hand but few would do so. Without their visual appeal, they may not have been as well received among individual traders. Without the ability of charting software, Bollinger Bands would be too difficult to use for all but a few professionals.

Since the early days of technical analysis, the focus has been on charts. Price charts show data that reflects the three tenets of the field:

  • Markets discount the future.
  • Prices move in trends.
  • History is repeated in the price patterns that can be observed.

In addition to charts, technicians also used mathematical tools but many were designed with simplicity in mind. A 10-day moving average, for example, involved adding the numbers and moving the decimal point one place to the left. While the tools identified by early technicians were effective, some analysts realized that more complex mathematical tools would adapt to prices. This insight may have been the basis for trading bands.

The history of trading bands is well-documented in Bollinger on Bollinger Bands, John’s book that was published in 2001. History is important to any field and this book documents the development of bands as indicators starting in 1960. At least eight different types of indicators using bands were found in the archives of technical analysis. Experimenting with what was known in the 1980’s, using a computer with 32 kilobytes of memory, John settled on the formula for Bollinger Bands.

Bollinger Bands were a great leap forward for analysts. John harnessed the power of computers, a new tool at the time. Prior to that, indicators were calculated by hand or with calculators. J. Welles Wilder had published New Concepts in Technical Trading Systems in 1978. That book included worksheets consisting of grids to help analysts set up the calculations.  Originally, John calculated long-term standard deviations and used those values to set adaptive percentage bands. He soon noticed that the market action would drift away from the settings he had calculated and hit upon the idea of using a “moving” standard deviation. The insight was profound but without computers Bollinger Bands would have been restricted to professional traders and Wall Street research firms.

Computers and charting software made Bollinger Bands available and useful to all traders. That availability led to additional research into the indicators and the development of new ways to use them.

It was a result of the availability of the Bands and several indicators like BB BandWidth and %b that led to the inspiration for new indicators.

As John explained in an interview with Technical Analysis of Stocks and Commodities magazine, “I had the pleasure of spending time with Ian Woodward, who has been doing some interesting things with Bollinger Bands. It was an inspiring time for me. Over the next few weeks, I realized that I could develop an entire framework of indicators around Bollinger Bands that covered virtually all of the traditional technical analysis tasks.”

In the coming months, John will be offering additional details on the work he has been doing and in time these new indicators will most likely lead to additional indicators. It will be interesting to see how this unfolds and how Bollinger Bands and the suite of indicators derived from this tool will impact the future of trading.

This work is another bridge towards the future of technical analysis. John is now taking an indicator and creating an analytical framework. This opens new avenues of research and will help shape the field of technical analysis in the decades to come.

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...

John Bollinger, CMT, CFA

John Bollinger is President and Founder of Bollinger Capital Management, Inc., an investment management company that provides technically-driven money management services and develops proprietary research for institutions and individuals. He is probably best known for his Bollinger Bands, which he developed in...

22 BOLLINGER BAND RULES

Editor’s note: In Bollinger on Bollinger Bands, there were “15 Basic Rules” included, a list that has grown to 22 as John incorporated new experience and insights into his work.

Bollinger Bands® were created by John Bollinger, CFA, CMT and published in 1983. They were developed in an effort to create fully-adaptive trading bands. The following rules covering the use of Bollinger Bands were gleaned from the questions users have asked most often and our experience over 30 years with Bollinger Bands.

  1. Bollinger Bands provide a relative definition of high and low. By definition price is high at the upper band and low at the lower band.
  2. That relative definition can be used to compare price action and indicator action to arrive at rigorous buy and sell decisions.
  3. Appropriate indicators can be derived from momentum, volume, sentiment, open interest, inter-market data, etc.
  4. If more than one indicator is used the indicators should not be directly related to one another. For example, a momentum indicator might complement a volume indicator successfully, but two momentum indicators aren’t better than one.
  5. Bollinger Bands can be used in pattern recognition to define/clarify pure price patterns such as “M” tops and “W” bottoms, momentum shifts, etc.
  6. Tags of the bands are just that, tags not signals. A tag of the upper Bollinger Band is NOT in-and-of-itself a sell signal. A tag of the lower Bollinger Band is NOT in-and-of-itself a buy signal.
  7. In trending markets price can, and does, walk up the upper Bollinger Band and down the lower Bollinger Band.
  8. Closes outside the Bollinger Bands are initially continuation signals, not reversal signals. (This has been the basis for many successful volatility breakout systems.)
  9. The default parameters of 20 periods for the moving average and standard deviation calculations, and two standard deviations for the width of the bands are just that, defaults. The actual parameters needed for any given market/task may be different.
  10. The average deployed as the middle Bollinger Band should not be the best one for crossovers. Rather, it should be descriptive of the intermediate-term trend.
  11. For consistent price containment: If the average is lengthened the number of standard deviations needs to be increased; from 2 at 20 periods, to 2.1 at 50 periods. Likewise, if the average is shortened the number of standard deviations should be reduced; from 2 at 20 periods, to 1.9 at 10 periods.
  12. Traditional Bollinger Bands are based upon a simple moving average. This is because a simple average is used in the standard deviation calculation and we wish to be logically consistent.
  13. Exponential Bollinger Bands eliminate sudden changes in the width of the bands caused by large price changes exiting the back of the calculation window. Exponential averages must be used for BOTH the middle band and in the calculation of standard deviation.
  14. Make no statistical assumptions based on the use of the standard deviation calculation in the construction of the bands.  The distribution of security prices is non-normal and the typical sample size in most deployments of Bollinger Bands is too small for statistical significance. (In practice we typically find 90%, not 95%, of the data inside Bollinger Bands with the default parameters)
  15. %b tells us where we are in relation to the Bollinger Bands. The position within the bands is calculated using an adaptation of the formula for Stochastics 
  16. %b has many uses; among the more important are identification of divergences, pattern recognition and the coding of trading systems using Bollinger Bands.
  17. Indicators can be normalized with %b, eliminating fixed thresholds in the process. To do this plot 50-period or longer Bollinger Bands on an indicator and then calculate %b of the indicator.
  18. BandWidth tells us how wide the Bollinger Bands are. The raw width is normalized using the middle band. Using the default parameters BandWidth is four times the coefficient of variation.
  19. BandWidth has many uses. Its most popular use is to indentify “The Squeeze”, but is also useful in identifying trend changes…
  20. Bollinger Bands can be used on most financial time series, including equities, indices, foreign exchange, commodities, futures, options and bonds.
  21. Bollinger Bands can be used on bars of any length, 5 minutes, one hour, daily, weekly, etc. The key is that the bars must contain enough activity to give a robust picture of the price-formation mechanism at work.
  22. Bollinger Bands do not provide continuous advice; rather they help indentify setups where the odds may be in your favor.

A note from John Bollinger:

One of the great joys of having invented an analytical technique such as Bollinger Bands is seeing what other people do with it. These rules covering the use of Bollinger Bands were assembled in response to questions often asked by users and our experience over 30 years of using the bands. While there are many ways to use Bollinger Bands, these rules should serve as a good beginning point.

Copyright Bollinger Capital Management. Reprinted with permission.

Contributor(s)

John Bollinger, CMT, CFA

John Bollinger is President and Founder of Bollinger Capital Management, Inc., an investment management company that provides technically-driven money management services and develops proprietary research for institutions and individuals. He is probably best known for his Bollinger Bands, which he developed in...

MORE MAJOR ACCOMPLISHMENTS OF GAIL DUDACK, CMT

Last month we highlighted the career of Gail Dudack, CMT, now the Managing Director of Dudack Research Group a division of Wellington Shields & Co. LLC.

After the newsletter was released, George Schade, Jr., CMT, pointed out that Gail was a recipient of the MTA Annual Award in 2007. Quoting from George’s presentation provides a more complete picture of Gail’s career:

“The Annual Award is the MTA’s highest honor intended to recognize those technical analysts who have significantly contributed to the advancement of our craft. Discovery and innovation are honored as well as having gained the pinnacle of professional reputation. Today, we honor Gail M. Dudack, CMT who exceeds those standards.

With us today, are Gail’s husband Pat and her son Ross. (Editor’s note: in the picture below are Pat, Ross, MTA President Phil Roth, Gail, and George Schade).

Gail’s distinguished career as a market strategist, analyst, and technician, which began in 1971, has been exemplified by proficiency, honesty, and service. In April 1998, she believed that stocks were 20% overvalued and saw a lot of volatility in the year ahead. In December 2002, Fortune reported that Gail had been “absolutely right about the bubble.” By then, she was talking about total return investing – the power of dividends.  She called it “turtle investing.” That was the announcement of a strategy whose profitable value became quite evident shortly thereafter. Maggie Mahar prominently featured Gail’s impressive track record in Maggie’s historical classic book Bull: A History of the Boom, 1982-1999.

Gail’s professional honesty is exemplary. For example, she stuck to her views and opinions of the markets during the late 1990s, a courageous stand in the face of great criticism. Had Gail been a baseball umpire, we would say she calls ‘em as she sees ‘em.

Gail has served this organization well. She has served as Treasurer, twice as Secretary, twice as Vice President, and was the first member twice elected President. During her Presidency, she was a leader in two watershed events: the creation of the CMT Program and the creation of IFTA. She has also served the Securities Industry Association as well as the New York Society of Security Analysts.

In 1997, Gail was interviewed for a book. She was asked what her goal had been. Gail answered, “Being good at what I did was my goal.” You indeed have met your goal and continue to do so, and today, we honor you.

With great pride, on behalf of all your colleagues in the MTA, I present you, Gail, with our Annual Award.”

BUILDING THE FUTURE OF THE CMT PROGRAM

The CMT Program was created when Gail Dudack, CMT, was the MTA President from 1985 to 1987. The program has been continuously updated since then and the Board of Governors (BoG) of the CMT Program is requesting help in that process.

If you are interested in preparing questions for future exams, please contact the CMT Program Director, Jeanette Young, CFP®, CMT, at 646-652-3300 x13 or jeanette@mta.org.

Contributor(s)

IN MEMORIAM: DR. MARTIN ZWEIG

The investment community lost one of its leaders in February when Dr. Martin Zweig passed away. Dr. Zweig contributed to the acceptance of market timing in the 1980’s. He achieved success with an advisory service and managing money in private accounts and closed end mutual funds. His award recognizes that, “He was one of the first practitioners of technical analysis to validate his research with solid statistical evaluation and subject his work to the rigors of academic challenge and debate. His testing work set the rigorous standard that we now employ in evaluating papers for the Journal and the Charles Dow Award.”

Dr. Zweig completed his bachelor’s degree at University of Pennsylvania’s Wharton School of Finance and then earned an MBA at the University of Miami before completing a Ph.D. in finance at Michigan State University. His doctoral thesis, written in the late 1960’s, was on relative strength.

In the early 1970’s, Dr. Zweig wrote several articles for Barron’s and made a number of successful market predictions. He also began publishing The Zweig Forecast, an investment newsletter which was highly ranked by The Hulbert Digest as one of the best performing newsletters of the 198’0s and early 1990’s. The newsletter delivered an average annual gain of 16% from 1980 to 1995, outperforming all other market advisory services during that time. He was also a regular guest on PBS’s popular Wall Street Week and he predicted the stock market crash of October 1987 in an appearance on that show the weekend before the crash.

Dr. Zweig also wrote a book, Winning on Wall Street (1986), which provided detailed insight into his methods. In the book, Zweig presents a number of monetary indicators that he monitors, along with technical and fundamental indicators. He combines the various indicators into a model that assesses market risk and invests in equities when risk is relatively low.

In looking at monetary indicators, Dr. Zweig reviews the prime rate to assess the impact of interest rates on businesses.  Installment debt is monitored to determine the impact of debt on consumer spending. His Fed indicator follows the Federal Reserve’s discount rate and the central bank’s reserve requirements.

Market momentum is also important to consider. Zweig Breadth Thrusts are often found at market bottoms. The Advance/Decline Line can be expressed as a ratio. When this ratio moves from below 40% to above 61.5% within ten days, it gives a buy signal. This indicator was written about in the 1980’s and correctly forecast the market bottom in March 2009.

Dr. Zweig also studied up volume as a ratio of total trading volume and found that when 90 percent of the volume is upward, a significant, bullish market move should be expected.

The Four Percent Model is a simple trend following tool that Dr. Zweig presented. He applied the model to the Value Line Composite Index although it can be used with any index. Variants of the indicator are also popular. Using the weekly close of the Value Line Index, a buy signal is given when the index rises 4% or more from its previous low. A trend reversal of 4% from a previous peak is a sell signal. In an update to his original book, Dr. Zweig provided results that showed from 1966 through 1993, the Four Percent long/short trading strategy delivered a 12.6% annualized return, compared to a 2.7% gain for the Value Line Index.

On a fundamental basis, Dr. Zweig wrote that he liked to buy stocks of companies that have reported earnings growth in at least four of the last five years and show earnings growth year-over-year in the most recent quarter. He also looks for sales growth over those time frames.

He then filters stocks based on the price-to-earnings (P/E) ratio. Dr. Zweig follows a philosophy that has become known as growth at a reasonable price (GARP). He is looking for stocks where the P/E ratio is less than the earnings growth rate. The P/E ratio of a company he is looking at buying should also be in line with the P/E ratio for the stock’s sector. For buys, he sets a minimum P/E ratio of 5 since stocks with ratios less than that are prone to having operational or financial problems.

Technical analysis is also applied to the trading decisions. Dr. Zweig likes stocks that are outperforming the market and he prefers buying breakouts from basing patterns.

Dr. Zweig has been credited with developing a number of technical tools, including the puts/call ratio, a well-known sentiment indicator.  His numerous accomplishments were recognized by the MTA in 2012 when Dr. Zweig was selected to receive the MTA Annual Award.

Contributor(s)

DEFINING SUCCESS IN TECHNICAL ANALYSIS: SUSAN BERGER’S 45 YEARS IN TA

Technical analysis is still a relatively young field of study. Edwards and Magee first published Technical Analysis of Stock Trends in 1948. John Magee would continue his work for almost forty years after that. Recently, an analyst who learned technical analysis by working directly with him began an independent advisory service using the same techniques she learned from Magee.

Susan Berger is an example of what a successful career means in technical analysis. Although she entered the field in 1968, her story is far from dated and presents a guide to what is possible today.

Success came from:

  • Finding a mentor and working hard to learn from them.
  • Studying.
  • Paying attention to the details and mastering the fundamentals.
  • Being flexible and taking advantage of opportunities that presented themselves.

In 1968, Susan was hired at John Magee to chart stocks. This means she posted prices by hand on 11×17 inch sheets of mylar. Stocks were kept in file folders and Susan or one of her three coworkers would grab a file, look up the prices in the tables of The Wall Street Journal and mark the open, high, low and close along with volume on the page. Dividends were annotated to distinguish their impact from price gaps on the charts. This process was repeated throughout the day.

Hundreds of NYSE and AMEX-listed charts would be updated in the morning. Afternoons would be spent preparing charts ordered by clients.  This was a different era and Magee was one of the few sources for individual charts. The company was known for high quality charts. To ensure accuracy and neatness, one of the women in the chart room would read the prices while one drew them with a ruler and pen. Titles and symbols were added with press on letters and numbers, which had to be secured with scotch tape.
A ruler and pen were the equivalent of a graphics program at that time.  Many charts were updated free hand but when it came time to prepare them to send out, someone needed to ink the price and volume data on the chart using a ruler, so the charts would look neat. Inkers strived for accuracy and the charts were on large paper so that people could maintain the charts themselves. Magee also had a good business selling chart paper.  There were a lot of individuals and portfolio managers that charted their own stocks at that time.

If a client needed a chart for a company that was not one of the charts maintained daily, it had to be constructed from scratch. Prices would be read from books with tables showing the stock history. But those books took months to print and distribute so custom charts often meant going through piles of torn out quote sections of the WSJ.

The mylar charts were only the first step. Magee also had a diazo machine, an early architect drawing machine that used barrels of ammonia. This work required masks to protect against the smell and a response from the fire department to clean up spills. The mylar chart went over a special paper that was run through the room-sized diazo machine and out would come a finished chart. Clients might order 50 charts a day because this was the only way they could get them. A chart cost $11.00 (about $64 in today’s dollars) and was sent out in a cardboard tube. Magee was also the only source for the charts in Barron’s for a time.

Magee also published a weekly stock advisory service which required additional industrial sized machinery. There was an addressograph machine, which loudly punched out metal plates with client names and addresses.  There was also a giant printing press.

John Magee was an iconic figure and money managers would often make a pilgrimage to see him. A tour would include a view of a room full of old Wall Street Journals. Magee is famous for being a pure technician who used only charts. He didn’t read the news and would explain to visitors that he would not read the newspapers until they reached a certain stage of yellow, ensuring that he would not be influenced by the fundamentals.

For the weekly stock advisory service, Magee would write the first page during the week. Susan recalled:

Back then, technical analysts did far more than look at charts. There was a lot of written material that provided kind of an education on human nature. Those weekly commentaries were always illustrated with clever examples.

On Friday night, John Magee and another analyst would look through all of the folders and charts. They wore green visors and worked until late in the night to find four stocks to buy or sell short.

Work filled six days a week for about the first ten years of Susan’s career because Saturday was when the service went out. A staff of six was needed to put it together: a typist, proofreader, chart inker, printer, shipper, and John Magee overseeing it all. Everyone on the team was involved in collating, stapling and envelope stuffing.

Magee’s service employed at least ten people, full-time, to produce charts and commentary. By comparison, Susan now prepares an advisory service on her own with just a Mac.

As John Magee got older, he was unable to go through hundreds of charts every week to find the strongest stocks. Susan stepped in to help. When Magee was recovering from surgery one week, she surprised him by finding the charts he needed for the newsletter. She had learned how to spot  strong stocks from charting by hand and helping him prepare figures for revisions to Technical Analysis of Stock Trends.

The career lessons for analysts seeking success are:

  • No job is too small to do.
  • Learn from every task you complete.
  • Use what you learn on the job and show initiative.

Eventually, Magee sold his company to a brokerage firm in Boston and Susan moved there with the company.

In her new position, she managed the chart department, helped with the stock advisory service, and started her own institutional service. In a few years, the principals of the small brokerage firm wanted to retire and they sold the firm and John Magee Inc. to a penny stock firm. Susan was uncomfortable with this turn of events and moved to Fidelity. She explained:

I really zeroed in on that company because they understood the value of technical analysis and it was such a successful company. I couldn’t get hired as an analyst, so I got in with my experience in charting and was hired with the task of automating the famous chartroom. I learned programming and with an in-house, highly skilled programmer, we did automate the entire room.

Of course, what I wanted was to be an analyst, so I applied for the job, and when they realized my back ground I was promoted to technical analyst. I started out with the technology sector, and after a few initial missteps (mandatory I’m afraid), I was on my way. I went on to create a weekly commentary on the market, which I used to go around with and chat about to the portfolio managers. It was helpful for them to see the structure of the market. Not complicated at all.

Recently, Susan offered some insights into her career that could help anyone, in any career:

I don’t think I felt anything but relief that I didn’t have to chart stocks by hand anymore. However, after all those years, I did have something ingrained in me as to what works. There is an ability that has to be there, but most of all it is experience. I don’t think you have to actually post the charts to get it, it is one way, but going over and over the charts, and learning from your mistakes and seeing what works the best. There is no easy way to get experience, frankly there will be times that are beyond awful, there is no escaping that, the ones that succeed are able to adjust quickly, and move on.

After 45 years in technical analysis, even though Susan loved her work at Fidelity, she felt it was time to slow down and decided that starting her own service was the perfect solution. When I asked when she would retire, she said, “I have noticed that technical analysts never completely retire. It is impossible to quit the stock market, and that feeling of getting it right.”

This slower pace will involve reviewing 1000 to 1500 charts a week, and make list of strong charts. That accounts for about 90% of her work. The rest of her time is spent writing, researching and learning.

Mark Dibble worked with Susan at Fidelity for eighteen years. His admiration and respect shows:

“Susan is a pure technician in the Edwards and Magee tradition and always has an objective view of the investment landscape and was never burdened by institutional bias, fundamentals, or the lofty macro opinions of others. She was a joy to work with and set a high personal example with her hard work, determination, and love of our craft, especially in the face of adversity. Susan broadened the reach and credibility of technical analysis at Fidelity. But passionate technicians never stop looking at charts and Susan continues to opine at SusanBergerStocks.com.”

When I asked how someone starting today could find success in technical analysis, Susan again offered an insight that could help a great deal in any career, “My best advice is to live below your means. That is something I always stressed to the new analysts. It is important to manage any stress you can.”

To follow Susan’s work in the next phase of her career, readers can visit http://susanbergerstocks.com/

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...

CURRENT VIEWS OF CLASSIC TECHNICAL ANALYSIS TECHNIQUES

Editor’s note: this is an example of Susan’s work. It is interesting to see how it applies the fundamentals defined by Edwards and Magee.

Dow Theory (prepared January 7, 2013)
The Dow Theory is supposed to be intermediate in nature. However, the possibility of a Major Base

Breakout in the Transportation Average seems to make it more significant.  A break above 13650 on the Dow Jones Industrial Average and a break above 5600 in the Transportation Average would qualify as a Dow Theory bullish signal.

Russell 2000 Small Cap Index
There is no other way to classify the chart than Strong. This is backed up by the growing list of individual stocks that are also very attractive.

S&P Mid Cap Index
This index also has had a bullish resolution to a two year Ascending Triangle.

I screened the Mid Cap Indexes for buys and I added a lot. I want to highlight the majority of these emerging strong small and mid cap stocks because they will likely lead. Going forward, I’m thinking of changing my approach to the smaller cap area. There would be more impact, with so many strong stocks, if I looked more towards highlighting the strongest industries and stocks, rather than monitoring a growing list of recommendations.

Contributor(s)

Susan Berger

Susan Berger worked with John Magee from 1968 until his retirement and then worked as a technical analyst at Fidelity Investments. She now provides independent research and additional information can be found at http://susanbergerstocks.com/.

INTERVIEW WITH MUKUL PAL, CMT

THIS ARTICLE WAS EDITED.  REVISED ARTICLE IN NEXT MONTH’S ISSUE

Contributor(s)

THE PERFORMANCE OF INSTITUTIONAL PORTFOLIO MANAGERS WHO USE TECHNICAL ANALYSIS

Editor’s note: This paper was recently published at the Social Science Research Network, http://go.mta.org/3437. It presents an academic view of how technical analysis contributes to the performance of professional money managers. An experienced money manager who uses technical analysis reviewed the paper and commented that, “The really striking thing about the results is how much higher skew and kurtosis are with managers using technical analysis. So, while the returns are slightly better, the shape of the returns is very different.

Positive skew basically means that the losers are small, while there are occasional big winners. More of the distribution is positive. It suggests to me that technically oriented managers are cutting their losses and letting their profits run.

High kurtosis (leptokurtic) indicates a high, narrow distribution of returns. It means that a lot of trades are clustered around the mean return. It suggests to me that technical traders have a lot of scratch trades and make most of their money on the big winners.” 

Abstract: This study takes a novel approach to testing the efficacy of technical analysis. Rather than testing specific trading rules as is typically done in the literature, we rely on institutional portfolio managers’ statements about whether and how intensely they use technical analysis, irrespective of the form in which they implement it. In our sample of more than 10,000 portfolios, about one-third of actively managed equity and balanced funds use technical analysis. We compare the investment performance of funds that use technical analysis versus those that do not using five metrics. Mean and median (3 and 4-factor) alpha values are 
generally slightly higher for a cross section of funds using technical analysis, but performance volatility is also higher. Benchmark-adjusted returns are also higher, particularly when market prices are declining. The most remarkable finding is that portfolios with greater reliance on technical analysis have elevated skewness and kurtosis levels relative to portfolios that do not use technical analysis. Funds using technical analysis appear to have provided a meaningful advantage to their investors, albeit in an unexpected way.

Among the results presented in the paper:

  • Technical analysis is very important, important or used by 13% of managers responsible for balanced funds and 32% of equity fund managers.
  • Compared to fund managers that that say they do not use technical analysis, managers using technical analysis:
  • Have slightly higher equally weighted mean and median three-factor (market, size, book-to-market) and four- factor (plus momentum) alphas.
  • Higher benchmark-adjusted returns, especially during bear markets.
  • Higher performance volatility.
  • Elevated return skewness and kurtosis which is likely advantageous, in combination.

Many of the results in the paper are summarized in charts, including the one below which shows that managers reporting the use of technical analysis delivered better returns over the period studied:

Contributor(s)

David Smith

BIO COMING

Christophe Faugere

BIO COMING

Ying Wang

BIO COMING

MTA EDUCATIONAL FOUNDATION UPDATES

Mike Epstein Award. The MTAEF announced the presentation of the 2012 Mike Epstein Award to Julie R. Dahlquist, Ph.D, CMT and Charles D. Kirkpatrick II, CMT. The Mike Epstein Award, established in honor of the work Mike Epstein did on behalf of the Foundation, is given to people who best exemplify Mike’s goals of supporting technical analysis in academia and in practice. Ms. Dahlquist and Mr. Kirkpatrick are perhaps best known for their outstanding book, Technical Analysis: The Complete Resource for Financial Market Technicians. Their book, revised in 2010, has been an integral part of the CMT program since shortly after its original publication.  Both Julie and Charles spent many years teaching and promoting technical analysis on the college campus prior to writing the book. Julie, who received her Ph.D from the Texas A&M, is currently senior lecturer, Department of Finance, at the University of Texas at San Antonio College of Business. Charles, who received his MBA from Wharton, is President of Kirkpatrick & Company, a firm that specializes in technical research.

MTAEF Store. The MTAEF’s online store is up and running. Proceeds from sales will help further the Foundation’s efforts to incorporate technical analysis into courses at the college level. In addition to updating our courses in technical analysis and providing lecturers at colleges around the U.S., the MTAEF is offering scholarships for the MTA’s CMT program to qualified undergraduates. Among the items available at the store now are framed antique stock certificates, including certificates from Western Oil & Refining, Merchants & Planters Bank, Ashland Coal & Iron Railway, and the Stutz Motor Car company.

Election. The MTAEF Directors will vote on nominations for new officers at its March meeting. The MTAEF is not a membership organization; it consists of Directors and advisors. The Directors will vote on the following slate:

President: J. Cody Tafel, CMT           Vice President: Philip J. Roth, CMT
Treasurer: Craig Cohen, CMT          Secretary: Keith Applegate, CMT

Help the MTAEF. To broaden its educational efforts around the country, the MTAEF need your help. If you have university contacts or if you want to make an effort in establishing contacts at a particular school, the MTAEF is interested. The Foundation wants to establish new college relationships.  There are many ways of helping us get in the door. If you are a graduate and know key professors or deans, give them a call or stop in for a visit. While a school may not have an interest in teaching a full course in technical analysis (most do not, at first), the school may consider an introductory lecture. A presentation can be made to a group of students in a finance club or to participants in an active trading room. Check out your alma mater or a local school for trading rooms and finance clubs. If there is interest, the MTAEF can help you make a presentation or make a presentation for you. We have found that initial disinterest or hostility is followed by “Wow, I had no idea that’s what technical analysis is and how useful it can be in helping our students get jobs and in improving their career opportunities.” 

Contributor(s)

THE THIRD, PART TWO: TWO DISTINCT PARABOLIC POSSIBILITIES FOR THE S&P 500

I offer this parabolic article exactly 1 year after my previous parabolic article in Technically Speaking, Mar 2012, which can be used as a reference for this article.

INTRODUCTION
As of this writing (February 25, 2013), the S&P 500 is precariously dancing just underneath massive resistance from the preceding towering highs of 2000 and 2007. It is only natural to conjure several, or perhaps many, realistic possibilities for the market at this juncture, such as a triple top with a crushing downtrend back to major support (with a parallel double-top for the Dow), or perhaps a lesser correction followed by a successful break of resistance and a new extended bull run.

In this article, I’ll offer a parabolic perspective utilizing ‘the third’ which graphically outlines both of these possibilities by:

  1. Clearly identifying current price and all major reversals (and some minor) as harmonically tied to the low of 102.00 of Aug 1982 via
    fractional relationships.
  2. Extrapolating two distinct patterns of tops and bottoms from the fractional relationships observed.
  3. Most importantly, identifying target support and resistance curves and price ranges for both possibilities, as indicated by these patterns.

PARABOLIC CURVE SET-UP

Using a monthly chart with a focus on the low of 102.00 in Aug 1982, an ‘ascending decreasing’[1] curve is drawn, which squares time to get price (x^2,y):

TIME: Since the low’s price of 102.00 would produce immensely large cycle points, the square root of 10.0995 (10.10 rounded) is used and converted to 10.10 months. This basic unit of 10.10M is then multiplied by the square number series (1,4,9,16,25,36,49…) to arrive at the ever-expanding ‘cycle’ shown.

PRICE: The low’s price of 102.00 is used to generate the price levels above (a standard procedure for identifying support and resistance levels).

Notice that level 14 is 1530.00 (derived by adding 14 x 102 above the low) which provides accurate resistance for both the important rally top of August/September 2000 at 1530.09 (point D, the ‘real top’) and the current high of 1530.94 at point E, just after the time point 36 (6^2), which is 10.10M x 36 = 363.6M from the low, which points to November/December 2012.

The basic parabolic curve (black) is drawn by simply connecting a 1×1 relationship on the grid.[2] Therefore any grid point on this curve would be a perfect squared relationship between time and price, from the perspective of the low of 102.00 in August 1982.

It is informative to note the general market behavior below and above this curve, regarding its overall strength and volatility. They are literally two completely different markets!

This basic curve provided resistance for the top of the crash of 1987 (point A) and for the topping market throughout 1993-1994 (point B). The subsequent breakout above that curve announced the almost vertical climb to the 2000 top. Eventually the market returned to this key relationship, and provided a perfect and much needed bounce for the market in 2009 at point C.

Now let’s review those other points and find some patterns for speculation.

BREAK OUT ‘THE THIRD’…

All pertinent points come into perspective by multiplying (and dividing) the price amount by thirds’:

Most interesting to note is that initial support in May-July 1984 came from the 1/3 curve, which when inverted (literally: 1/3 flipped is 3/1 or just 3) as curve 3 provides the top of the market in 2000, as the blue and red arrows indicate!

The all-time high of 1576.09 in October 2007 is seen here as divergent (weak) compared to its predecessor. The massive slide back to ‘center’ (curve 1) would certainly concur.

Notice the bottom of the crash of 1987 is on the ½ curve. Inverting this will come in handy later.

All other major points are marked by thirds, in addition to the minor low of 2011 at 1 2/3. This is quite a statement, offering a parabolic glimpse of whatever underlying mechanism is at hand. The ‘Invisible Hand’ of the marketplace leaves traces.

With the current price just underneath the 2 1/3 curve, does this mean another major turn? Let’s analyze the specific fractional relationships of the major points to find out.

FINDING FORMING PATTERNS

Here is a potential pattern forming that is lowering by 1/3, for both the tops and bottoms:

The market is at a crucial decision point, based on ‘the third’. I predicted in a blog last April that the S&P would need to rise to the 2 1/3 in order to match the previous two highs at 3 & 2 2/3, from a constant diminishing movement of 1/3. I have been patiently waiting for this tap of resistance, and now the time has come![3]

Indeed, the two major bottoms are also in the same relationship of the lowering third. The next fractional curve in this relationship is the 2/3 curve as shown, with the next potential bottom around the dismal range of 530-550.

Here’s a ‘measured move’ effect using fractional curves, naturally arriving at the same unfortunate conclusion:

Both preceding major downtrends are perfect drops of 1 2/3. This is redundant, as the previous chart indicates the same 1/3 downward relationship from both the high and low of the first downtrend, however it is still visually impacting.

Is this the shape of things to come? Before you put down your bull cape and don your bear hunting attire, let’s counter with ‘the half.’

REGRESSION FROM ‘THE HALF’

Remember the bottom of the crash of 1987 at the 1/2 curve as shown on the second chart? By ‘flipping’ it (inverting) we get literally curve ‘2’ (doubling price from the original curve). This curve was an immediate disappointment to my tops and bottoms radar last spring, which was so elated from the thirds curves. Only recently did I discover what the real gem of this 2 curve is regression to the mean.

According to this structure, every major turning point since 2000 is counterbalanced about this curve 2:

  1. The 2000 top is counter-balanced by the 2009 bottom, as perfect integer movements of 1 above and below, indicating that the 2009
    low is a closure of sorts to the massive correction.
  2. The uptrend from 2002 to 2007 is a perfect expression of 2/3 below and above (1/3 less than the previously mentioned two points),
    providing a balanced retracement during the larger downward movement to curve 1 (a ‘home base’ of sorts)
  3. After cleaning the slate by coming back to regression in early 2011, the market made another move away from regression down by 1/3
    (1/3 less than the previously mentioned two points) to the 1 2/3 curve, then breaking above and now topping at the perfectly counter-balanced 2 1/3 curve, exactly 1/3 above.

This chart not only shows that the entire market from 2000 is counterbalanced perfectly about curve 2 by using thirds, but that the current market is also reversing in a like-wise manner, in a perfectly diminishing pattern of 1/3.

The implication here is that the market should return to the regression curve 2 at roughly 1340-1355, upon completing this 1/3 counter-balancing rally away from regression.

The big question is, ‘What then?’

S&P 500 AT 2000?

If the market bounces from regression, then it is indeed a new day under the sun, since the pattern of counter-balancing moves is now at zero! Three perfect sets of moves away from regression have passed at that point (1, 2/3 & 1/3 in order), which implies a closed set that makes room for a new dynamic, such as a bull run back up to curve 3 (and beyond), as seen here from a simple channel perspective.

Unfortunately, there is no indication of exactly when the market would reach this upper channel, but a proportionate move up would reach curve 3 around 2000-2200. There is certainly a lot that could happen on the way there.

BRINGING IT BACK HOME

Reverting back to our original two scenarios for the market: If the market breaks down below 1340-1355 at regression (curve 2), then evidence is given for a harmonic large downtrend to curve 2/3 at around 530-550, providing the massive triple-top pattern with a subsequent major downtrend.

However, if the market can stay above 1340-1355 at regression (curve 2), then the counter-balancing is holding, and that would indicate a successful break of resistance from previous major highs along with an extended Bull Run to curve 3 at 2000-2200.

Of course, an additional scenario is that current resistance at curve 2 1/3 does not hold at all, and price runs away and refutes the entire 13 year sideways market!

CONCLUSION

The power of the third knows no bounds, especially utilized in this parabolic structure from a major low.

In its literal form of 1/3, it provided the actual lowering pattern of 1/3 curves as well as the shrinking of the patterned movements away from regression, terminating in the next possible move back to regression, which the market would have to perform in the coming month(s).

In its expanded form of third fractions, it dictated all major points short of the bottom of the crash of 1987 (whose fractional harmonic of 1/2 offers the missing key of regression). The first pullback area of 1984 at the 1/3 curve is perfectly closed by the market top of 2000 at its inversion curve of 3.

ENDNOTES
[1.] This is the opposite of squaring price to get time (x,y^2) which gives an ‘ascending increasing’ curve normally thought of as ‘parabolic’.

[2]. Again, for a more detailed look at building parabolic curves in this fashion, please refer to my article ‘Back to the Drawing Board: Parabolic Curves and the Dow’ in the March 2012 edition of Technically Speaking.

[3.] Although I erased that blog I still have the chart, and luckily another chart and analysis was put up on my website in March 2012 which remains to this day.

Contributor(s)

Scott Hathaway, CFTe

Scott Hathaway, CFTe is the Co-Founder and Manager of Pattern to Profit, LLC, a new independent technical investment research firm utilizing unique geometric analysis of global markets. A musician by trade, Scott committed to the constant study, exploration and innovation of the charting...

SOCIONOMICS AND THE ELLIOTT WAVE MODEL PROVIDE A FRAMEWORK FOR PROJECTING THE LAG TIME FOR NEWS

One of the most important things to understand about the stock market is its relationship to news. Aside from emotional reactions
lasting just minutes, news does not cause the market to move in any meaningful sense. News is the result of trends in social mood.
Many people who say they understand this idea nevertheless continue to monitor news as if it is meaningful to their investment
decisions. This belief is deadly. Alan Hall, a researcher at the Socionomics Institute, has visually depicted the hypothesis of mood causality so that you will get it. For pure practical value, this is one of the most useful reports about markets you will ever read.

—Robert Prechter

The Wave Principle regulates expressions of social mood, which manifest in social actions with various lag times. This study
proposes that we can use knowledge of these lag times to anticipate fundamental news. To understand socionomic forecasting, it is crucial to understand why some expressions of social mood lag others. Simply stated, people can take some actions immediately in response to social mood, while others take time to coordinate and mobilize.

For example, people can express changes in social mood nearly instantaneously by buying and selling stock. Therefore, the stock
market is a nearly immediate expression of changes in social mood.

But people cannot take immediate action on economic and political decisions, even those made simultaneously with changes in social mood. Robert Prechter explained this point in the August 1985 Elliott Wave Theorist Special Report, “Popular Culture and the Stock Market”:

Major fundamental historic events which are often considered important to the future (i.e., economic activity, lawmaking, war) are not causes of change; they are the result of mass mood changes which have already occurred. The reason that such events are lagging indicators of mood change is that it takes a good deal of time and an extensive swing in mood throughout the populace for the shared mood change to result in such events.

He expanded on this idea in a November 25, 2010 address to students and faculty of the Saïd Business School, University of Oxford:

Let’s suppose a business person is getting more optimistic, and he decides to expand his business. He can’t carry out his plan in minutes or hours. He has to draw up a plan. He has to meet with bankers or venture capitalists.  He has to create new advertising. He has to go through a hiring process. He has to scope out new space to buy or rent. It could take him weeks if not months to bring about tangible results. Conversely, if social mood turns toward the negative, a more pessimistic business person who decides to contract his business might have to sell off inventory, cut back on staff, close a division, and so on. These things take time.

The September 2004 issue of Elliott Wave Theorist included a chart diagramming “the relative temporal relationship between immediate social actions, which can constitute sociometers, and lagging social actions, which often constitute news.” The April 2012 issue updated that chart, shown here as Figure 1:

Toward the left, the jagged black line depicts immediate responses to social mood, giving us, for one thing, the fractal construction of the stock market.  The green dashed line to its right represents a moderately lagging response, such as the economy. …Then there are the really lagging results, depicted by the red line. They include such things as major political actions, because to effect them people first have to form a consensus, and then they have to go through a legislative procedure. All of this takes time. Observe that the longer time it takes to act, the less precisely a set of actions reflects the fluctuations in social mood. The reason is that the lag time for each action is different, so the aggregate expression is less defined.

The latest turns in the economy reflect this lag time. An “official” NBER recession began in December 2007, two months after the stock market peaked; and the recession ended in June 2009, three months after the stock market bottomed.

Political entities cannot act instantaneously upon changes in social mood, either. It takes time for social mood to become extreme enough to motivate enough people to desire and/or demand action from political officials, and it takes time for political entities to turn motivations into plans and plans into actions. As a memorable recent example, social mood, as evidenced by the trend of the stock market, turned down in 2000. But Congress did not vote to take the collective action of declaring war on Iraq until October 10-11, 2002, two days following the low of a 34-month, 38% decline in the DJIA. Then it took the U.S. government another five months to actually start the fighting.

Figure 2 (reprinted from “There’s Always a Mix,” from the May 2011 issue of The Socionomist) illustrates the idea that there are always positive and negative expressions of social mood, but they vary in quantity and intensity. The horizontal bar is posted at the midway point.

Figures 3A and 3B each show an idealized “impulse,” or five-wave, structure from the Elliott wave model, marked with the point of change in the dominance of positive or negative social mood. Each of these “Prechter Points” occurs at the structural center of the largest third wave operative, in either direction. Within the largest-degree positive trend in effect, it marks the point at which people on balance shift from fearing the worst to hoping for the best.  Within the largest degree negative trend
in effect, it marks the point when people on balance shift from hoping for the best to
fearing the worst.

After the Prechter Point occurs, lagging expressions of social mood tend to begin flooding more one sidedly in the direction of the social mood trend.  They don’t become starkly one-sided until months later. (For examples of social expressions surrounding a large-degree Prechter Point in a bull market, see “Social Mood and the Future of Wealth,” in the August 2009 issue of The Socionomist. For a broader discussion, see the February 2011 Elliott Wave Theorist.)

Figure 4 imposes Figure 2 over a graph of the Dow Jones Industrial Average for the bear market of April 1930 to July 1932. It includes the traditional Elliott-wave labeling as published in past issues of The Elliott Wave Theorist, including most recently the April 2009 issue.

The smooth descending line in Figure 4 is a six-month moving average of the DJIA shifted six months into the future. At major turns, it lags prices by roughly nine months. It is designed to approximate lagging expressions of social mood, such as extremes in economic and political news. It is best to think of this lag line as the approximate centerline of a broader swath of probability, much as volatility bands are designed to contain most of the price action in a graph of stock prices.

Pessimism became the dominant stock market sentiment at the Prechter Point of mid-September 1931. But notice that the “lag line” did not reach the price level of the Prechter Point until near the time of the end of wave C, which marked the beginning of reports of the worst economic, political and social news of the decade. In other words, the stock market indicated what was happening with respect to social mood months before the media reported news of the economic and political consequences of the negative mood trend.

Socionomic theory explains why social expressions continually follow this form. Observe that socionomic causality is the opposite of the news-based causality conventionally assumed:

…the stock market does not see into the future…. it reflects instantaneously the causes of the future. Optimistic people expand their businesses; depressed people contract their businesses. … The actions of human beings spurred on by an increasingly ebullient or pessimistic social mood cause earnings to rise or fall. … The same thing is true of political action. Politicians do not turn the tide of a bull or bear market by enacting or abandoning policies. The mass emotional environment, as reflected by the market, forces them at some critical point to act.

—The Wave Principle of Human Social Behavior, Chapter 18, adapted from The Elliott Wave Theorist, August 3, 1979, reprinted in Pioneering Studies in Socionomics, 2003

Lagging Expressions of Social Mood: Social, Economic and Political

The above discussion is a preamble to relating a memorable experience I had while searching the Google News archives. Google News handily returns images of old newspaper pages with one’s search term highlighted. For one article, I wanted a screen-capture of a clean, non-highlighted image. So, I searched for a headline that appeared on an adjoining page, “500,000 Chicagoans,” thinking it was unusual enough that it would lead me back to the same two-page spread. It did, but I serendipitously got another hit on this unusual phrase. One of the stories was from 1931 and the other from 1932, at times that happen to have been four months before and nine months after the Prechter Point in wave C.


At right is the first of the two articles, issued on May 14, 1931 by the Associated Press.  Remember, this event occurred almost halfway down in the biggest collapse in stock prices in American history.

This story describes a public gathering packed so tightly that “several score of persons were overcome, so great was the press of the crowd.” [1] One man died and many needed first aid, but not because of violence; in fact, the crowd was festive and well behaved, according to the cheery reporter.

Note the upbeat unity of the crowd reported near the end of the article.  Social mood had been trending negatively for 21 months—since September 1929—and the country was suffering financially. But the critical psychological threshold—the September 1931 center of wave C—still lay ahead. Note, too, that the hero of the crowd was not a military officer or a politician but a Chamber of Commerce president. Society was still clinging to hopes of business resurgence even as it became increasingly less optimistic.  The crowd in Chicago knew nothing of what lay ahead. But social mood and fundamental economic conditions were about to worsen drastically.


Pessimism became socially dominant when stock prices plummeted through the Prechter
Point. At left is the second article, published a year later by The Toledo News-Bee on June 3, 1932, nine months after the September 1931 Prechter Point and a month before the bottom in stocks.

As you can see, this second story is starkly different, and so are the next two articles, which were adjacent on the same page of the newspaper.

The next two two suicide stories bring to life the grim statistics on U.S. suicide rates, which reached their all-time high—still never exceeded—as darkening social mood carried the stock market to its 1932 bottom.

Figure 5 (below) adds a few key news reports to the bear market picture shown in Figure 4. The numbers along the lag line refer to notable anecdotal expressions of prevailing sentiment, listed in chronological order on the ensuing pages. In 1930, our lag line peaked nine months after the Dow, illustrating the persistent post-peak optimism that helps explain investors’ tendency to hold on to losing stocks during the initial stages of major declines. Observe how the tone of social expression changes after the Prechter Point (indicated on the chart with a red asterisk). In 1933, our lag line bottomed eight months after the Dow, coinciding with the worst economic and political news and illustrating the persistent post-bottom despair that helps explain investors’ tendency to sell or avoid stocks during the initial stages of major advances. Economic fundamentals began weakening before the Dow’s peak in 1929 but after the highs in most stocks, as indicated by the 1928 peak in the advance-decline line.

Positive economic fundamentals lag some market peaks, creating the same profile we see at bottoms. Social psychology remained predominantly optimistic until the Prechter Point in 1931. Although the consequences of trends in unconscious social mood never manifest in exactly the same way, we observe at least one reliable dynamic: positive psychology fools people after tops, and negative fundamentals fool people after bottoms.

News Stories Numbered in Figure 5

The first of these stories is an excerpt from John Kenneth Galbraith’s book, The Great Crash 1929. Galbraith describes a prescient exception to the prevailing optimism of the time. The remainder of these stories represent typical Google News Archive search returns for “economic outlook.”

1. In November 1929, a few weeks after the crash, the Harvard Economic Society gave as a principal reason why a depression need not be feared its reasoned judgment that business in most lines has been conducted with prudence and conservatism. The fact was that American enterprise in the twenties had opened its hospitable arms to an exceptional number of promoters, grafters, swindlers, imposters, and frauds. … a kind of flood tide of corporate larceny. In November, it said firmly that a severe depression like that of 1920-21 is outside the range of probability. We are not facing protracted liquidation. This view the Society reiterated until it was liquidated.

However there were exceptions. One was Paul M. Warburg of the International Acceptance Bank, whose predictions must be
accorded the same prominence as the forecasts of Irving Fisher.  They were remarkably prescient. In March of 1929 (#1 in Figure 5), he called for a stronger Federal Reserve policy and argued that if the present orgy of “unrestrained speculation” were not brought promptly to a halt there would ultimately be a disastrous collapse.  This he suggested, would be unfortunate not alone for the speculators. It would “bring about a general depression involving the entire country.…” As the market went up and up, his warnings were recalled only with contempt.

—John Kenneth Galbraith, The Great Crash 1929

Figure 5

2. Stock prices have reached what looks like a permanently high plateau…. I believe the principle of the investment trusts is sound
and the public is justified in participating in them…. [I expect] to see the stock market a good deal higher than it is today, within a few months.

—Irving Fisher, Yale economist, Milwaukee Journal, October 16, 1929

3. [Nearly] all of the standard railroad stocks are cheap and the industrial list is filled with stocks selling at real bargain prices. …
Prudent investors are now buying stocks in huge quantities and will profit handsomely when this hysteria is over… . my friends and I are all buying stocks.

—John J. Raskob, “one of the country’s leading industrial and political leaders”
—The New York Times, October 30, 1929

4. I am convinced that through these measures we have reestablished confidence.

—Herbert Hoover, President of the United States, December 1929

5. EDITORS REPORT TO HOOVER; Heads of Trade Organs Says Business Outlook is Good.

—The New York Times, December 17, 1929

6. OPINION IS DOUBTFUL ON OUR 1930 OUTLOOK; London Not Reassured by Trade Returns

—The New York Times, January 27, 1930

7. HARDWARE OUTLOOK GOOD.; Orders Booked in Week Indicate Feeling of Optimism.

—The New York Times, February 05, 1930

8. [The] intensity of the speculative boom which reached its climax in the crash of last fall was as great or greater than that of “any of our major manias before,” but … the intensity of the slump which followed it was greatly diminished by the efforts put forth to prevent it. … There has been no significant bank or industrial failure.  That danger, too, is safely behind us.

—Herbert Hoover, The Evening Independent, May 1, 1930

9. ADVERTISERS OPTIMISTIC

—The New York Times, May 07, 1930

10. GUARANTY SURVEY SEES SLOW UPTURN

—The New York Times, July 28, 1930

11. EUROPEAN OUTLOOK IN TRADE IMPROVES

—The New York Times, October 22, 1930

12. HOOVER URGES CONGRESS TO ECONOMIZE AS HE PRESENTS RECORD PEACE BUDGET; 4,860,000 NOW IDLE IN NATION … .
Warning Congress to avoid embarking on any new or enlarged ventures… .

—The New York Times, December 04, 1930

13. BRIGHT REALTY OUTLOOK

—The New York Times, March 08, 1931

14. TAX COLLECTIONS CONTINUE TO FALL

—The New York Times, March 25, 1931

15. ECONOMIC RECOVERY IN SIGHT

—The New York Times, June 07, 1931

16. Depression Losing Grip … Forget Gloom, Banish Fears…

—Herbert Hoover, The Milwaukee Journal, June 16, 1931

• Prechter Point: Mid-September, 1931.

17. J.E. ALLEN HOPEFUL ON REALTY OUTLOOK

—The New York Times, December 24, 1931

18. Unemployed autoworkers demonstrated in The Ford Hunger March from Detroit to Dearborn. Authorities shot and killed five workers and injured 60, many by gunshot.[3]

—Sugar, Maurice (1980). The Ford Hunger March, March 7, 1932

19. We are likely to have a complete economic collapse in Europe within the next few months. L.S. Amery, British House of Commons.

—New York Times, May 27, 1932

20. July brought violent deaths among the Bonus Army, 43,000 World War I veterans and their families who occupied areas of Washington for over a month to demand immediate payment of government-promised compensation for wartime service. After police shot and killed two of the veterans, troops commanded by General Douglas MacArthur and Major George Patton used bayonets and poison gas to drive the rest of the protesting vets out of the city.

—“Bonus Army Spectacle, U.S. Capital, 1932: What Really Happened” July 28, 1932

• Stock market bottom: July 1932.

21. “Striking farmers now fight hunger. Several clashes with deputies occur—tear gas disperses big mob.”[4]

— The Montreal Gazette, August 25, 1932

22. “Famine Widespread In Quebec Region–10,000 people on the verge of starvation and another 60,000 faced with an acute
shortage of provisions … .”[5]

—The Rochester Evening Journal, December 8, 1932

23. “Unemployment Soars to New Record Mark

Unemployment has reached an ‘all time peak’ with more than 11,600,000 persons now out of work in this country, according to
President William Green of the American Federation of Labor. … ‘We are experiencing the worst unemployment crisis in our history,’ the labor leader said. ‘Those out of work are in greater need than ever before, for after three years of depression their resources are exhausted. Mental and physical wreckage caused by depression is driving families to seek relief in constantly growing numbers.’”

—United Press, January 7, 1933

24. “HOARDERS IN FRIGHT TURN IN $30,000,000; Gold Pours Into Banks and the Federal Reserve as Owners Act to Avoid Penalty.
NAMES TAKEN OFF LIST Even Christmas Coins Help to Swell Week’s Recovery of Metal to $65,000,000. Spurred by fear of public
exposure and the threat of fines and imprisonment, gold hoarders scurried back to the Federal Reserve Bank and its member
institutions yesterday to redeposit the yellow coins that they had lately stampeded to withdraw. … little piles of gold pieces brought in by frightened individuals… . The repentant hoarders displayed a good deal of agitation, but they were received courteously by the guards of the Reserve Bank and came out with an evident air of relief when they had disposed of their dangerous treasure. The drastic character of the proposed law against gold hoarding frightened even those who had not thought of themselves as hoarders, but who suddenly recalled a few odd coins left over from Christmas presents which had not been spent because they were too ‘pretty’.…The importance of the return-flow of gold to the Federal Reserve bank was emphasized by bankers, who pointed out that the $65,000,000 recovered so far this week could be used as the basis for the issuance of $162,500,000 of Federal Reserve notes or a very much larger amount of the new currency.”

—New York Times, March 10, 1933

25. “PROLONGED ILLNESS FOUND AMONG IDLE; Survey Shows 40% of Sick on Relief Rolls in State Have Been Ailing for Year. OTHERS AVERAGE 25 DAYS”

—New York Times, April 16, 1933

26. “There is a deeper feeling of pessimism among many of the delegations tonight regarding the… World Economic Conference
than there has been since it assembled.” 

—The New York Times, June 21, 1933

27. Screenshot from The New York Times, “A Chronological Survey of the Outstanding Financial Events of the Past Year” [1933]:

A few public protests and brief riots occurred in the first portion of the decline in 1930 and 1931, but expressions of the increasingly negative mood became angrier and broader following the Prechter Point and especially after the low in stock prices.

Peter Dreier, a professor of politics at Occidental College in Los Angeles, recently wrote, “Riots occur when people are hopeless. Civil disobedience takes place when people are hopeful.”[6] (Emphasis added.) Knowing when such a change occurs is important, and the Elliott wave model can help: People tend to begin abandoning hope after the wave structure passes the Prechter Point.

As indicated in Figure 5, lagging expressions of social mood hit their low in 1933 and produced the worst economic conditions of the decade. As a thought experiment, imagine that you had been among investors who still held stocks at the wave C low. Then consider how challenging it would have been to hold on to them while reading the news items listed in Figure 5 for the year 1933, when negative social events, produced by the preceding negative social mood, reached a climax. Most people would not have been able to resist the urge to abandon their holdings. But had you incorporated the socionomics model of coincident and lagging social change, you would have understood that the bad news was irrelevant to your investment decision-making. If you employed the Elliott wave model, you might have been motivated to buy stocks, while others, stuck in the natural human default of assigning social-mood change to external causes such as economic and political news, would have despaired—as always—and sold out near the low.

The News Progression in 1972-1974

Here is another example of leading and lagging expressions of social mood.  Figure 6 shows the 1973-1974 decline in the DJIA, the largest and steepest decline in the grueling 16-year bear market of 1966-1982. As happened in April 1930, the 1973 lag line peak coincided with a B-wave peak. But this peak was qualitatively different because it occurred seven years into a bear market. Social optimism remained evident in news stories, but it was not as pervasive as in 1930. In this case, positive economic consequences clearly lagged the market peak, providing a handy rationale for post-peak optimism.

Once again, much as in 1933, the low in our 6-month lag line roughly coincides with the worst economic and political news of 1974-1975. In 1975, some six to nine months after the low of wave C, U.S. unemployment hit a 33-year high, the federal deficit reached a 32-year high, U.S. investment and disposable income hit lows, and Saigon fell to the Communists, giving them victory in the Vietnam War. Here are some representative news reports from that period:

Figure 6

Headlines from The New York Times Article Archive, July 1972-December 1974

These are typical examples of headlines that express then-current perceptions and/or expectations about the future as returned in searches for “economic outlook.”

Reserve Chief Optimistic on the Economy

—July 27, 1972

Economic Seers Preview ‘73 as Another Bumper Year for Business

—August 07, 1972

“Continued Economic Growth Is Predicted for 1973”

—September 28, 1972

* Stock market top: January 1973.

Heartening Signals Sighted

—May 06, 1973

The Astonishing Boom…

—August 29, 1973

WESTERN industrial nations are experiencing their greatest economic boom in more than two decades. ECONOMISTS SEE A ‘SOFT LANDING’ WHEN BOOM ENDS

—September 02, 1973

Forecasts’ Tone Improves

—October 21, 1973

Some Signs Point to the Right Path; The Economy The Nation

—November 04, 1973

World’s Business Slowing … Evidence is mounting that the worldwide economic boom of 1972-73 has cooled off and that a less frantic period of economic growth has set in.

—November 18, 1973

Business Is Optimistic on Economy

—December 10, 1973

Economic Outlook Gets Gloomier

—February 13, 1974

It’s Still Early, but Economy May Have Seen the Worst

—March 24, 1974

Economic Storm

—May 31, 1974

The Sky Is Falling

—June 30, 1974

* Prechter Point: August 23, 1974.

A Bundle of Economic Dilemmas

—September 05, 1974

It’s a Recession, All Right

—October 27, 1974

A Nation in Deep Gloom

—November 24, 1974

The Economic Threat… The year is ending with much of the nation in a state of deep anxiety over the course of the economy. There has been nothing like the present degree of apprehensiveness— or confusion— about the business outlook since 1930….

—December 29, 1974

The News Progression in 2007-2012

Figure 7 shows the bear market of 2007-2009, which was the largest and steepest decline in stocks since 1929-1932. To better understand the most recent changes in expressions of social mood, we include the subsequent recovery rally.

As you can see from the notes on the chart, a number of positive economic consequences lagged the October 2007 peak in the stock market.  Expressions of mood and economic consequences also lagged the March 2009 bottom in the stock market, as bad economic news subsequently flooded the media. The lag is evident with respect to the rally from 2009 to 2012 as well. For example, in April 2011, the Dow made a small-degree peak just after our lag line bottomed, producing the mixed social expression
typical of a bear-market rally. On April 12, the IMF announced that the global economy was strengthening, yet the next day, the Obama administration warned of a looming “economic Armageddon.” From that peak, stocks fell into September, yet our theoretical lag line continued higher, and lagging expressions of social mood continued to wax positive right along with it. The November 2011 issue of The Elliott Wave Financial Forecast listed a number of them:

  • Industrial production rose in October at the fastest pace in three months at the nation’s factories, utilities and mines.
  • Factory output, the largest component of industrial production, increased a solid 0.5 percent. It was the fourth straight monthly gain.
  • The auto industry has rebounded to drive most of the growth factory output. Production of motor vehicles and parts rose 3.1
    percent in October, the fourth straight monthly gain. Light trucks were the biggest contributor.
  • Retail sales last month were higher than analysts had expected, rising 0.5 percent, according to the Commerce Department.
  • Wal-Mart, the country’s biggest retailer, said it had posted a quarterly increase in sales after nine consecutive quarters of
    declines.

Even better economic news came in December. Reuters reported on December 22 that Toyota forecast a 20% jump in global sales. That same day, The New York Times described these “unexpected” results and treated them as new causes:

As the fourth quarter draws to a close, a spate of unexpectedly good economic data suggests that it will have some of the
fastest and strongest economic growth since the recovery started in 2009, causing a surge in the stock market and cheering economists, investors and policy makers.

In recent weeks, a broad range of data—like reports on new residential construction and small business confidence—have beaten analysts’ expectations. Initial claims for jobless benefits, often an early indicator of where the labor market is headed, have dropped to their lowest level since May 2008. And prominent economics groups say the economy is growing three to four times as quickly as it was early in the year, at an annual pace of about 3.7 percent.

President Obama got a lift in the polls in November 2011, and he was reelected a year later amid even more optimism, confidence and bonhomie.  These are lagging expressions of the previously positive trend in social mood. Going forward, this lag implies that optimism and positive economic consequences will likely linger for months after the peak of the Dow rally from 2009. Since the Dow made a new four-year high in October, we would expect that most people will maintain hope well into 2013, much as they did in 1930, 1973 and 2008. If the stock market makes another new high, that period will extend accordingly.

This relationship between immediate and lagging social expression explains why people remember news causing market moves. In the months of maximum emotion, such as the final months of the 1990s advance or the 2007-2009 decline, news finally aligns with the trend. People connect the two and believe the news is causal. In most of the trend, emotions are more subdued and the market/news alignment is weaker.

Socionomic theory, as elucidated in these charts, explains why it is futile for investors, economists, politicians and others to base their decisions—as they ceaselessly do—on present news and social events that are in fact results of the preceding trend in social mood. Most people miss the turns in social mood and the stock market because they tend to assign social-mood and stock-market causality to “good news” or “bad news” reported long after the change in the trend of social mood has already occurred. The best economic news tends to come when the stock market is already past its high, and the worst economic news tends to come when the stock market is already past its low. The more aware you become of this dynamic, the more you can think independently of the crowd. That insight—provided only by socionomics and the Elliott wave model—can be immensely useful.

Notes

[1] 500,000 Chicagoans revel: Merrymakers turn downtown district into circus at all-Chicago trade jubilee (1931, May 14). Youngstown Vindicator, Retrieved from http://news.google.com/newspapers?id=549cAAAAIBAJ&sjid=3VcNAAAAIBAJ&pg=1735,5732529&dq=defense+budget&hl=en.

[2] US suicide rate rises, falls with economy (2011, April 15). EconomicCrisis.US, Retrieved from http://economiccrisis.us/2011/04/suicide-rate-rises-falls-economy/.

[3] Ford Hunger March. Wikipedia, Retrieved from http://en.wikipedia.org/wiki/Ford_Hunger_March.

[4] Striking farmers now fight hunger. Several clashes with deputies occur—tear gas disperses big mob (1932, August 25). The Montreal Gazette, retrieved from http://news.google.com/newspapers?id=KoFhAAAAIBAJ&sjid=PpkFAAAAIBAJ&pg=6881,3153898&dq=hunger&hl=en.

[5] Famine widespread in Quebec region (1932, December 8). Rochester Evening Journal, Retrieved from http://news.google.com/newspapers?id=inpZAAAAIBAJ&sjid=-UgNAAAAIBAJ&pg=5063,3481712&dq=st arvation&hl=en.

[6] Dreier, P. (2011, September 20). Protests? yes. riots? no. Huffington Post, Retrieved from http://www.huffingtonpost.com/peterdreier/protests-yes-riots-no_b_971136.html

Contributor(s)

Alan Hall