Hill examines common congestion areas (price levels at which neither the bulls
nor bears are in complete control) such as the line congestion area and the
small congestion area. Through recognizing these patterns, traders can anticipate
reversals and the end of a move.
By Holliston Hill; pages 13–18.
What can and should you expect from a firm’s investor relations services?
By Carolyn Kott Washburne; pages 19–21.
Kalt offers a method for determining how long you can last in a managed account
before your specified percentage loss closes you out. The method presented
can be used to quantify the characteristics of the trading systems being analyzed.
By Sherwin Kalt; pages 22–25.
An insider’s insights into shady practices that have become commonplace
at the exchanges.
By Allen D. Hanson; pages 26–27.
Kepka offers his modification of the “K” and “%D” stochastics
oscillators to day-trade S&P futures.
By John F. Kepka; pages 32–36.
Even in a bull market, some industry groups will eventually falter. Dunbar’s
Non-Carryover Hypothesis attempts to analyze the trends.
By Bill Dunbar; pages 37–41.
By John F. Kepka; pages 37–39.
By John Sweeney; page 39.
By John Sweeney; pages 40–41.
By John Sweeney; pages 41–42.
Beginning with a discussion of the basic nature of cycles, Taylor explains
how to interpret the results of spectral analysis. He explains in detail the
detection and measurement of phase relationships of cyclical components from
two or more time series.
By William T. Taylor; pages 52–56.
A look at the “strangle,” a neutral option strategy.
By STOCKS & COMMODITIES Staff;
pages 57–58.
A look at the basic premises of the Dow Theory. Also included are some hypotheses
Dunbar thinks are essential in using Dow Theory effectively.
By Bill Dunbar; pages 59–63.
A rundown on the Median Line method of geometric technical analysis, also known
as the Andrews line method. Beginning with the basic concept, French explains
how to draw and use median lines.
By Thomas E. French; pages 64–65.
Sweeney describes the step-by-step routine he followed as a new trader.
By John Sweeney; pages 66–68.
An explanation of the concept of beta (a comparison between the movements of
an individual stock or portfolio and the movements of the market as a whole)
and how it relates to the valuation of portfolio risk.
By Scott S. Silver and Gary M. Wingens; pages 72–73.
The Fibonacci mathematical number series can be used to forecast trends in
futures. Emmett applies the Fibonacci series to Treasury bonds as an example.
By Tucker J. Emmett; pages 77–78.
What can you do when your new computer is a lemon? Sherry describes the laws
covering this area.
By Clifford J. Sherry, PhD; pages 81–82.
By Herbert R. Sorock; page 87.
It’s worth your while risk-wise to get acquainted with options trading.
Here’s an introduction.
By STOCKS & COMMODITIES Staff; pages 95–99.
A continued look at the Dow Theory, its history and how it works.
By Bill Dunbar.
An updated trend-following method designed to correct some traditional weaknesses
by establishing trend channel lines and using a moving average or filter to
locate points outside the trend channels.
By Anthony W. Warren, PhD; pages 106–109.
By William T. Taylor; pages 110–111.
It’s worth your time to shop around for a discount broker. Here’s
what to look for.
By Richard J. Maturi; pages 114–116.
By John F. Kepka; pages 117–120.
This article explains trading liquidity and how it relates to the Gregg Corporation’s data and calculations on trading activity featured in STOCKS & COMMODITIES
magazine.
By Scott J. Silver and Scott S. Levokove; page 121.
A look at the Composite Index of Leading Economic Indicators and how it can
be used to anticipate recessions.
By Clifford J. Sherry, PhD; pages 122–124.
A primer in recognizing market reversals with head-and-shoulders formations.
By Timothy A. Maguire; pages 131–134.
The “rules” of recognizing and handling risk.
By Allen D. Hanson; page 135–136.
Several good reasons why you should look into options trading.
By David L. Caplan; pages 18–21.
Williams’ modifications on the oscillator principle.
By Larry Williams; pages 140–141.
Kepka presents some insight into using AutoRegressive Integrated Moving Averages
on the S&P 500 index futures.
By John F. Kepka; pages 142–144.
By Harry Schirding.
Trading involves risk. But this instructive article tells you how to place
protective trading stops to limit possible losses.
By John Sweeney; pages 157–158.
Morris re-examines Wilder’s Relative Strength Index and offers adjustments
to make the popular indicator more useful. He uses an exponential moving average
to give recent data more weight in the calculation.
By Gregory L. Morris;
pages 159–161.
An introduction to the use of the Kalman filtering process to smooth data and
reduce data “noise.” Includes equations and a computer routine to
use for filtering data.
By Vince Banes; pages 162–165.
By John Sweeney; page 166.
Are prices random or predictable? Statistical computations (primarily the chi-square
statistic) can be used to determine whether or not the action of prices is
random and/or independent.
By Clifford J. Sherry, PhD; pages 168–170.
Maturi uses the example of Irwin Jacobs to show opportunities for trading based
on acquisitions and mergers. Includes information on convertible bonds, timing
of trades, and the conversion equivalent.
By Richard J. Maturi; pages 172–175.
An introduction to the concepts of Gann including Gann lines, angles, pivot
points, support and resistance. Also includes graphic illustrations of these
concepts and examples using actual data (pork bellies, British pounds, KC ValueLine).
By Robert Pardo; pages 177–182.
With the increasing number of large funds and institutional investors in the
market, is everyone following the same indicators with the same systems? If
you think so, take a look at Patricoff’s “Game Theory.”
By Henry S. Patricoff.
By John Sweeney; page 188.
An insider’s view of ways in which exchanges can exert control to maintain
a stable market. Hanson also explores the possibility of the trading ’window’ (the exchange) closing and the effects of such an action on traders.
By Allen D. Hanson; pages 194–195.
Kepka combines AutoRegressive Integrated Moving Averages from daily data, stochastics
and S&P 500 futures data to demonstrate the use of these techniques. This
follow-up article enlarges on previous articles presenting ARIMA and stochastic
techniques and offers examples of their use on real data.
By John F. Kepka; pages 196–199.
These lessons learned by a novice trader can help other new traders avoid the
pitfalls of using a discount broker without the proper knowledge of the rules
of the market.
By Dan Weinberg; pages 201–203.
An introduction to oscillators that includes how to create them, use them and
choose appropriate moving average time periods to anticipate price reversals.
By John Navarte; pages 204–206.
A basic guide to writing and using call options.
By Richard J. Maturi; page 207.
By John Sweeney; page 208.
Auto- and cross-correlation statistical techniques can be used to determine
the interdependency of time series data. Includes methods of determining correlation
using chi-square statistics.
By Clifford J. Sherry, PhD; pages 213–215.
By John F. Kepka; pages 216–217.
Welles Wilder’s Directional Movement Indicator is modified to allow a
variation of the time period used for the calculations. Also included are the
results of research conducted using the modified Directional Movement System
on real data.
By Thomas P. Drinka and Steven L. Kille; pages 218–221.
A re-evaluation of gold stock trading strategy.
By Richard J. Maturi; pages 222–225.
A listing of leaders in the U.S. Trading Championship competition.
By Norm Zadeh; page 226.
An example of the thinking behind taking an actual position, in this case in
energy instruments. A CTA and CPO looks at oil prices and makes a prediction
based on both technical and fundamental factors.
By Joseph Holleman; pages
233–234.
An examination of several technical indicators including Relative Strength,
moving averages, oscillators and Williams’ %R. Includes comparative research
results based upon the indicators listed above to determine their profitability.
By Thomas P. Drinka, Steven L. Kille and Eugene R. Mueller; pages 235–239.
A continuation of Weinberg’s experiences as a novice stock trader.
By Dan Weinberg; pages 240–241.
An introduction to the use of cycle analysis to determine profitable investment
strategies. Also includes a computer program designed to develop a trading
system based on cycle analysis.
By John F. Ehlers; pages 242–246.
How to construct advance-decline lines to track the movement of markets with
the New York Stock Index and the Dow Jones Industrials. The author details
how to plot the data and use it to determine positioning for trades.
By Howard Waxenberg; pages 247–250.
A follow-up article which provides a BASIC computer program implementing the
alpha-beta trend-following method as outlined in an earlier article. Mathematical
foundations for the method are provided as well as graphic examples showing
the method’s output using actual data.
By Anthony W. Warren, PhD;
pages 252-255.
By John Sweeney.
A review of several books dealing with trading psychology.
By Fred S. Gehm; pages 257–258.
By John Sweeney; pages 42–43.