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Mechanical trading systems - Weissman R.L.

Weissman R.L. Mechanical trading systems - Wiley publishing , 2005 . - 240 p.
ISBN 0-471-65435-3
Download (direct link): mechanicaltradingsystems2005.pdf
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RSI = 100 - 100/1 + RS
Average of X days when the market closed up
where RS = ----------------------------------------------------
Average of X days when the market closed down
Fourteen periods—such as days or weeks—are most commonly used in calculating the RSI. To determine the average “up” value, we add the total
FIGURE 1.5 February 2004 Comex gold with RSI. ©2004 CQG, Inc. All rights reserved worldwide.
Dispelling Myths and Defining Terms
points gained on up days during the 14 days and divide that total by 14. To determine the average down value, we add the total points lost during the down days and divide that total by 14.15 Most traders define a market as overbought when the RSI closes above 70 and oversold when the RSI closes below 30.
Mathematical Technical Analysis
A Building Block for Mechanical Trading System Development
The general who wins a battle makes many calculations in his temple ere the battle is fought. The general who loses a battle makes but few calculations beforehand. Thus do many calculations lead to victory, and few calculations to defeat: how much more no calculation at all! It is by attention to this point that I can foresee who is likely to win or lose.
—Sun Tzu
Many excellent books on technical analysis provide readers with a comprehensive description of various mathematical technical indicators. This chapter does not attempt to duplicate their work but instead tries to address the essential facets of the most commonly employed indicators, including: an explanation of what the indicators are, why they work, and how they can provide system developers with ideal building blocks for mechanical trading systems.
Although I encourage readers to examine the various mathematical formulas behind these commonly employed indicators, I also freely admit that many traders successfully use these indicators without understanding the formulas on which they are based.
My choice of one indicator as opposed to another is almost exclusively dependent on that indicator’s popularity at the time I wrote this book. Again, I focus on the most widely used indicators because the more market participants focus on a particular indicator, the more likely that it will be useful in system development. I usually favor using the default parameters
designated by the indicator’s developer. Thus, for example, mechanical trading systems shown based on Wilder’s relative strength index (RSI) always use 9 or 14 periods.
Throughout this chapter I provide examples of indicators and trading systems that show profits. I could just as easily illustrate use of each indicator with losses, but I want to show why traders are drawn to a particular tool. Chapters 3, 4, and 5 discuss which technical indicators can be turned into successful trading systems. For now my goal is merely to explain what the most commonly used indicators are, why they are used, and how they form building blocks for comprehensive trading systems.

As stated in Chapter 1, there are two categories of mathematical technical indicators, those traditionally used to capitalize on the market’s propensity toward mean reversion such as oscillators, and those that profit from trending price activity, such as moving averages. Although many books on technical analysis treat these various indicators as if they worked exclusively in either trend-following or mean-reverting trading environments, this book will show how indicators can be successfully applied to either realm.
Trend-Following Indicators: Why They Work
I have already highlighted some of the psychology behind the success of trend-following indicators in the discussion of reference points in behavioral finance. In Chapter 1, I showed how emphasis on reference price points led traders to take small profits and large losses. If we assume that the majority of market participants lack the psychological fortitude to allow profits to run and take losses quickly, then successful traders use trend- following indicators that necessarily reinforce their ability to actualize disciplined profit and loss goals. As a result, such trend-following technicians often find themselves on opposite sides of the market from their less successful counterparts. This theme of successful trading as the systematic “fading” (buying whenever the indicator would sell and vice versa) of unsuccessful traders will be revisited throughout the text.
Because successful trend-following traders are both utilizing trend-following indicators and acting contrary to mass psychology, we have shattered another myth of technical analysis, namely, that following the trend and contrarianism are mutually exclusive. Instead, contrary opinion is often the epitome of trend trading.
One of the best-known examples of trend-following contrarianism occurred in November 1982 when the Dow Jones Industrial Average (the
Mathematical Technical Analysis
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