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The Art of Forecasting
Discover the secrets of Gann forecasting in this revealing report. A short content course by an expert in Gann's Theory.

Written by John Berends
A Commodity Trading Advisor
E-mail John at trade@gann.com for more information.


The art of forecasting is defined in its application. Most traders use an analyst's forecast as the end-all, be-all portion of their trading. This is absolutely the wrong approach. In this lesson we will discuss Gann's Master Time Factor and its correct application. You will find that even the great master Gann used forecasting as only a tool.

Gann stated in his stock and commodity courses that one should go back 10, 20, 30, 60, 90 and 120 years and determine when highs and lows were made in a particular stock and commodity. By lining up these days in the current year one obtains the forecast for the year. For example, look at the S&P 500 index. It made a high in August of 1987. Ten years later would be August 1997. Did we have a high in August 1997 and a low in October 1997? Well, yes we did. Note that the pattern did not repeat exactly as one would hope but herein lies the problem with such forecasts. Is it valuable to know that strength would be expected prior to August1997? Is it valuable to know there may be trouble ahead in the months of September and September 1997? Would you like to know that strength would be expected in November and December 1997? It is obvious that most traders can use this type of information. If one expected the cycles to repeat exactly one may have been shaken out of any short positions in the September to October run up.

Let's examine the construction of one of these forecasts. In order to mathematically compute a forecast one needs to normalize prices in each data set then average the two together. A similar method would be used using three, four, five or six data sets. In our example we will only use two. A simple spreadsheet program like Microsoft Excel or Lotus 1-2-3 is recommended for the calculations. We will use the 10 and 20 year cycles to build our forecast. First one needs to find the mid point of each set (year). Find the highest high and lowest low. Add these together and divide by two. From this mid-point number determine each closing price's percentage change. (Close-Midpt)/midpt. Once all prices are normalized into percentages change they should be added to the corresponding date in the other data set (year) and divided buy two. The resultant data points will be our forecast.




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CAUTION:

TRADING COMMODITIES, STOCKS AND/OR COMMODITY OR STOCK OPTIONS INVOLVES RISK. MONEY CAN BE LOST AND/OR MADE TRADING ANY SECURITY AND/OR OPTION. PAST PERFORMANCE OF A TRADING SYSTEM OR MARKET IS NOT NECESSARILY INDICATIVE OF THE FUTURE PERFORMANCE OF THAT SAME SYSTEM OR MARKET. MOCK TRADING AND ITS HYPOTHETICAL PERFORMANCE RESULTS ARE INHERENTLY LIMITED AND SHOULD ONLY BE USED AS A LEARNING TOOL AND NOT A MEASURE OF FUTURE PERFORMANCE. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL, OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE DISCUSSED WITHIN THIS SITE, SUPPORT AND TEXTS. OUR COURSES SHOULD BE USED AS LEARNING AIDS ONLY AND SHOULD NOT BE USED TO INVEST REAL MONEY. IF YOU DECIDE TO INVEST REAL MONEY, ALL TRADING DECISIONS SHOULD BE YOUR OWN.


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