V.3:3 (106-109): Part 1. Concepts and Examples A Trend Following Method for All Seasons by Anthony W. Warren
Product Description
Part 1. Concepts and Examples
A Trend Following Method for All Seasons
by Anthony W. Warren, Ph.D.
Introduction
Trend following methods based on plots of raw and moving average data are one of the oldest and most universally used techniques of technical analysis. However, these techniques are appropriate for only certain types of markets, characterized by great cyclical movements or trends, and are not useful in long accumulation and distribution periods when the underlying market is flat. Moreover, even in trending markets the traditional moving average trading techniques tend to be susceptible to false alarms caused by short term market reversals. In this article we discuss a trend following method which remedies most of these difficulties by
(1) Establishing upper and lower trend channel lines which characterize the statistical fluctuations in the data, and
(2) Utilizing a moving average or recursive filter to define trading points and trading regions OUTSIDE the uncertainty band between the trend channel lines.
This concept is not really new. However, it has only recently become implementable in a reasonably economic and automated fashion, with the growth in power and usefulness of the personal computer. We will discuss the implementation aspects of this method in a follow-up article. In this article wt show the superiority of this method over the usual trend following technique based on moving averages.
At its basis, our trend following concept identifies three trading regions when one should be LONG, when one should be SHORT, and when one should be OUT, i.e. noncommitted. These regions are defined by the following rules:
Introduction
Trend following methods based on plots of raw and moving average data are one of the oldest and most universally used techniques of technical analysis. However, these techniques are appropriate for only certain types of markets, characterized by great cyclical movements or trends, and are not useful in long accumulation and distribution periods when the underlying market is flat. Moreover, even in trending markets the traditional moving average trading techniques tend to be susceptible to false alarms caused by short term market reversals. In this article we discuss a trend following method which remedies most of these difficulties by
(1) Establishing upper and lower trend channel lines which characterize the statistical fluctuations in the data, and
(2) Utilizing a moving average or recursive filter to define trading points and trading regions OUTSIDE the uncertainty band between the trend channel lines.
This concept is not really new. However, it has only recently become implementable in a reasonably economic and automated fashion, with the growth in power and usefulness of the personal computer. We will discuss the implementation aspects of this method in a follow-up article. In this article wt show the superiority of this method over the usual trend following technique based on moving averages.
At its basis, our trend following concept identifies three trading regions when one should be LONG, when one should be SHORT, and when one should be OUT, i.e. noncommitted. These regions are defined by the following rules:
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