WD Gann Methods – Seasonal Studies

“To everything there is a season,” and the seasonal trends that commodity prices follow make them actually much easier to forecast than stocks.

The problem with conventional seasonal analysis is that analysts look at an average seasonal price curve covering the previous 20 years, ignoring the overall context in which a market is trading.

You Need an Extensive Historical Database

Conventional seasonal analysis lack the unique perspective obtainable only by using a much more extensive historical database to carefully catalog price moves by formation and stage. And context is the key to maximizing the value of seasonal market forecasts because a market customarily displays different seasonal tendencies depending on where it stands in its life cycle.

For example, 25 of the 30 major lows in wheat since 1880 hit bottom between June and October. Whenever wheat prices continue sliding to new bear market lows after October, you could probably stay short with confidence at least until June.

After a final low in any commodity, the intensity of an initial bull market leg up tends to vary dramatically depending on its point of origin in the season, which can provide invaluable insight in projecting its extent.

Classifying Turning Points

Our massive proprietary database enables us to classify every turning point in history based on its month of occurrence, and then further narrow our focus according to the specific stage of the market at the turn, promoting even more accurate commodity market forecasts.

Market Forecasting – Contact Gann Global

Learn more about Seasonal Studies and how they relate to market forecasting. Seasonal Studies is one of five WD Gann Forecasting Methods, reviewed in detail in the “Essential Course” by Gann Global Financial (available to subscribers and Insiders).

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