This article is of great interest to readers using (or planning to use)
    a computer for forecasting. MEM is the first article in a series on cyclic
    prediction. In it, Dr. Warren presents a method of adaptive filtering and
    data forecasting. The article also contains a handy glossary of cyclic terms.
    By Anthony W. Warren, PhD; pages 12–16.
By George M. Edwards, Jr.; pages 17–19.
Thompson favors us with a very practical example of how a swing chart can
    be used for price level support and resistance trading. This technique is
    easy to implement and maintain, with the added corroboration of several generations
    of use.
    By Jesse H. Thompson; pages 20–23.
In this article, Maturi takes readers through an introductory example of
    how commodity options may be used in the silver market with less worry.
    By Richard J. Maturi; pages 24–26.
By Harry Schirding; pages 28–34.
This is an intriguing tale of trading Chapter 11 stocks. Beginning with
    getting “hooked on junk,” and progressing through a discussion
    of different kinds of “junk,” Dunbar points out a number of advantages
    to trading the stocks of troubled corporations.
    By Bill Dunbar; pages 35–41.
In this article, Taylor describes how microcomputers can be used to aid
    traders in futures market trades. He discusses optimizing moving averages
    and points out a number of factors to be taken into account. In addition,
    Taylor shows examples of how to effectively display statistical results.
    By William T. Taylor; pages 48–54.
Dr. Warren continues his series of research articles on the mathematical
    forecasting process called the Maximum Entropy Method (MEM). This article
    looks at optimizing procedures in obtaining the most significant input, while
    filtering extraneous noise.
    By Anthony W. Warren, PhD; pages 55–59.
This case study is a great exercise in market observation and the decision
    process behind maintaining trading discipline. Thompson presents a study
    of price, action and resistance using soybeans as an example.
    By Jesse H. Thompson; pages 60–65.
Teaching by examples, Emmett has prepared a number of sample forecasts in
    this article based on his investigation of Fibonacci ratio patterns in market
    price and elapsed time. The subjects his studies cover: hogs, cattle, wheat,
    sugar, soybeans, Swiss franc, gold and silver futures.
    By Tucker J. Emmett; pages 66–73.
In his introductory article, Sweeney shares his experience of the transition
    from “dabbler” to full-time trader. He notes some of the pitfalls
    to avoid, as well as advantages of a life in market speculation.
    By John Sweeney; pages 74–75.
Gehm presents the reader with a run-down of key factors to consider when
    selecting a money manager. He discusses a helpful technique which can eliminate
    the fear of allowing someone else control of your money.
    By Fred S. Gehm; pages 76–79.
Using June 1984 gold as an example, Thompson presents a timely study of
    this commodity’s price action. Chart pattern and support/resistance
    area identification are highlighted.
    By Jesse H. Thompson; pages 84–86.
Dr. Lane publishes his original explanation of stochastics development and
    his observed oscillator rules. This is a “do-it-yourself” article
    on stochastic plots and their use for choosing market entry points.
    By George C. Lane, M.D.; pages 87–90.
This article documents an improvement to a BASIC computer program, TRIX,
    published in the July 1983 issue and optimized in Dr. Warren’s September
    1983 article. The program eliminates the requirement that a chart be used
    in selecting a smoothing constant. Hutson explains how to compute the required
    coefficient based on the cyclic cutoff frequency.
    By Jack K. Hutson; pages 91–93.
In this article, Schirding explains how stochastics are calculated and comments
    (with examples) on their application. His detailed description shows how
    to record stochastics and readers will learn how to “trade the line” using
    this tool.
    By Harry Schirding; pages 94–97.
This whimsical, easy-to-read piece covers the psychological conditions a
    trader must deal with for success in the stock market. Trading must be performed
    by an individual who is at constant risk of actual or emotional loss. Even
    when winning, the peril of loss is always the trader’s primary motivation.
    By Bill Dunbar; pages 98–101.
This article addresses the mathematical question of whether there is a way
    to relate a simple linear weighted moving average to an exponential moving
    average.
    By Jack K. Hutson; pages 102–103.
By John F. Kepka; pages 104–105.
By John Sweeney; pages 105–106.
By John F. Kepka; pages 106–107.
By John Sweeney; pages 107–108.
By John Sweeney; page 108.
Sweeney presents a day-trading technique he discovered as a full-time novice
    speculator. He illustrates his experience using Treasury Bonds over a three-month
    time period.
    By John Sweeney; pages 110–112.
An explanation of Fourier Spectral Analysis concentrating on the interpretation
    of the results and the intuitive, common sense aspects rather than the mathematics,
    using frequency vs. cycle length displays.
    By William T. Taylor; pages 116–122.
A look at a promising system for short-term spectrum analysis and trend
    forecasting. This article discusses the process of obtaining an optimal set
    of MEM coefficients using the author’s computer code as adapted to
    the CompuTrac system.
    By Anthony W. Warren, PhD and Jack K. Hutson; pages 123–131.
Thompson lines up some of the common pitfalls and how to avoid them.
    By Jesse H. Thompson; pages 132–135.
A reprint from August 1911 edition of
    The Ticker Magazine, with an introduction by its editor and publisher,
    Richard D. Wyckoff. This article chronicles the Joseph Leiter wheat deal
    of 1898 on the Chicago Board of Trade.
    By STOCKS & COMMODITIES Staff; pages 136–140.
By John Sweeney; page 141.
How could one exploit the fact that a consistent success/failure ratio is
    the single most important variable in trading? Here Sweeney does and bases
    it on the COMMODEX system.
    By John Sweeney; pages 142–145.
Here, the author justifies the economic basis of technical stock market
    analysis. He also identifies and explains the implications of shifting effects
    of the slope relationship between the supply and demand curves on the pattern
    of price fluctuations.
    By Kent Kachigan; pages 151–157.
Dunbar tackles the Random Walk theory/Efficient Market hypothesis: Is there
    anything to this?
    By Bill Dunbar; pages 158–163.
Kazmierczak describes how he used his Stocker1 software program to trade
    the AMEX Index.
    By Paul A. Kazmierczak; pages 164–166.
Johnson describes the stochastic oscillator program he uses on his Hewlett-Packard
    HP-41C(V) hand-held calculator.
    By Dr. Charles F. Johnson; pages 167–168.
Introducing a new method of forecasting with the Moving Window-Spectral
    method. Included is a detailed example to illustrate systematic estimation
    and forecasting and a trading rule.
    By A.D. Ridley, PhD; pages 169–173.
Starting with a bit of advice from Ben Franklin, Gehm offers a few ways
    to routinize your decision-making through the use of a BASIC computer routine
    outlined in the article.
    By Fred S. Gehm; pages 174–180.
How to choose smoothing factors for your exponentially smoothed moving averages.
    By Donald R. Lambert; pages 182–183.
By John Sweeney; page 184.
A detailed description of forecasting with maximum entropy which includes
    a BASIC computer routine. (See the February 1985 issue for additional program
    information)
    By Anthony W. Warren, PhD and Jack K. Hutson; pages 189–196.
A rundown of the Dow Theory and how it works.
    By Timothy A. Maguire; pages 197–201.
Dunbar wondered how to pick market bottoms and tells you what he found out
    in his investigation.
    By Bill Dunbar; pages 202–206.
Thompson examines some old axioms well worth reconsidering.
    By Jesse H. Thompson; pages 207–208.
The use of “differencing” (otherwise known as oscillators or momentum)
    and how it relates to price movement is examined.
    By John Nicholas; pages 209–211.
Frankel looks at a number of popular software packages designed expressly
    for the technical trader.
    By Gerald Frankel; pages 212–216.
This short article argues the point that although trend-following may be
    dated, experts have time and again proven its worth for trading.
    By Jesse H. Thompson; page 216.
By Harry Schirding; pages 217–218.
By John F. Kepka; pages 218–220.
Sweeney illustrates the saying “When you’re on top, don’t
    believe it” with T-bonds and Deutschemarks.
    By John Sweeney; pages 221–223.