How to trade futures with high probability success: Recognize seasonal price patterns with seasonal charts.

How to trade futures? Seasonal trading can be one of the most effective trading methods. While other trading methods may have a strong theoretical backing, they have little empirical evidence of success. In contrast, the seasonal trading method may have almost no theory supporting it, but tends to perform the best empirically. This method operates on the assumption that certain markets tend to peak or trough at certain months of the year. This is especially true in commodities markets, where prices may fluctuate along with the seasons.

As Bernstein suggests, seasonal price tendencies can generate success rates of up to 80 percent in some markets.

## Three Main Types of Seasonal Tendencies

### Seasonals in Cash Prices

These seasonal tendencies tend to operate on a month-to-month basis, and should be analyzed as such.

### Seasonals in Futures Prices

Seasonal futures tendencies tend to be considered on a week-to-week or even a day-to-day basis because of the nature of futures; new futures are generated as previous ones expire, and different contract months will reflect different fundamental conditions.

A commodity spread is essentially the relationship between two different but related markets or between two different contract months in the same commodity. Sometimes called straddles, commodity spreads are another technical tool which exhibits seasonal patterns.

## Seasonal Chart

How to generate a seasonal chart? Seasonal price tendencies can usually be obtained from books or websites directly. But some of you might be interested in analyzing the data yourself. As Bernstein notes, here is a step-by-step method to calculate seasonal price tendencies and generate seasonal charts on your own:

1. Obtain monthly prices for the commodity you wish to analyze
2. List the monthly average cash prices in tabular form
3. Calculate the differences from one month to the next for the entire period of data
4. List the differences in columns according to month. That means indicating Jan to Feb differences, Feb to Mar, Mar to Apr, etc.
5. Add the month-to-month differences for each year back to the start of your data
6. Compute the average of the differences
7. Plot the first average, then add it to the second average of difference, and plot this figure. Continue until you have plotted all 12 months of differences
8. Calculate the percentage of time during the history of your data that prices are up or down in a given month.

## How to Trade Futures Price Patterns

As Bernstein notes, here are some examples of how this futures strategy can be applied.

Copper market – The price of copper tends to make a low in the Nov-Dec period. As builders begin to buy supplies, such as flashings and electrical wire, prices of copper begin to rise. This lasts until March, when the building season begins.

Corn and soybean markets – Prices in these markets tend to decline from July through October. By July, farmers are usually certain about the size and quality of their crop. And as harvest approaches, farmers often sell their crop to grain processing firms who will take delivery of the crop when it is harvested. The selling pressure usually causes prices to decline until harvest is over late in the year.

Heating oil markets – Home heating oil prices tend to reach a low in the summer, when demand is low due to the warm weather. Suppliers begin to buy heating oil at the low summer prices as they build up their inventories for the autumn and winter. This collective buying subsequently causes prices to rise.

These price patterns are similar year after year, so do learn how to trade futures according to them; this can be an extremely profitable way for you to time your investments.