Usually, it is to raise cash to pay back bank loans for seed, fertilizer, equipment, and other supplies, and/or because they lack the storage for their entire crop.  This glut of supply causes commercial buyers to step back and patiently wait for prices to fall before buying.  Thus, every fall we tend to see grain prices drop.  This is a seasonal occurrence.

Another one is in the live cattle market.  Every spring, livestock producers take feeder cattle off of winter pasture, put them in feedlots, and finish them.  This is done more frequently in the spring because the heat of the summer tends to dry up the pastures and it is more economical to finish the cattle in feedlots over the summer and bring them to market in the fall.  Thus the fall tends to see a bulge in cattle coming to market, and October futures prices usually trade cheaper than the summer month futures and the following winter month prices.  This is a seasonal effect on prices.

There are companies like Moore Research Center, Inc. that evaluates seasonal tendencies for all the various commodity markets.  Using a computer search algorithm, they look for starting and ending dates of seasonal trades over the most recent 15 years. 

Some of their findings I believe are true seasonal patterns like those described above.  However, I believe some are simply statistical anomalies that have no basis in fundamental facts.  Why, for instance, would the Canadian Dollar have a seasonal from July 12 to July 31 where in 14 of the last 15 years the price has fallen?  I know of no fundamental reason to justify such a claim.  I would bet that if you looked at the 15 years prior to the last 15 years that you might find a very different result.  And going forward, we might see that market go higher more often than down in the next 15 years.

Therefore, just because a seasonal occurred and worked over the past 15 years, doesn’t mean it will work this year.  So what do you do with this knowledge?

I still think the numbers are interesting, and if enough people believe in it, then it may happen because people make it happen (the self-fulfilling prophecy).  Therefore, there is value to these numbers whether the seasonal is fundamentally real or just an anomaly.

So how do you invest in a seasonal?  What I use is the stochastic to help me know when to enter the trade.  Stochastic is a study whose readings are from 0-100%.  It is used as an overbought/oversold market indicator much like relative strength.  Anytime a stochastic reading gets over 80% it is considered overbought, and under 20% it is considered oversold.  I like to use over 90% for my overbought, and under 10% for my oversold.

A seasonal is a slice of time, every year over some historical period.  But that doesn’t mean that each year the prices start moving in the direction of the seasonal exactly on the beginning date of the seasonal, and that prices reverse on the day the seasonal ends.  In fact, I doubt that any of the price trends of a seasonal start and end on those dates for any given year.  Since it is an average of all the years, we can assume that some years start going in the directional sooner and some years later than the average start date.

What I do is start looking for a bottom 30 days before an up seasonal starts (I look for a top 30 days before for a down seasonal).

If I see a stochastic reading under 10 percent within 30 days of the start of an up seasonal, I believe I have improved my chances for a successful trade. Here is a perfect example.  There is a down seasonal in corn from June 2nd until June 29th.  The chart below shows this with the green down arrow as the start of the seasonal and the green up arrow as the end of the seasonal.  30 days prior, which would start May 2nd, I start looking for an overbought market condition.  On May 17th, the blue vertical line highlights a stochastic reading over 90%.  On this day I would be a seller of corn futures, or a buyer of puts, or a seller of calls.

Any or all of these strategies apply, depending on your tolerance for risk. Be aware that I selected this chart because it represented what I believe the optimum result.  They don’t all work this nicely, nor is there any guarantee that in the future any of these will work at all.  To give you the other side, here is a chart of the Australian Dollar, a seasonal that didn’t work.  This buy seasonal started on June 2nd and lasted until June 21st.  An oversold condition occurred on June 7th, after the seasonal started.

Had you bought on the day the seasonal started (June 2nd) you would have never been profitable.  If you bought on June 7th, then you did see a little gain right away, but that faded quickly, and this trade loses money if held to the end of the seasonal.

So even though this trade didn’t work, if you use a reasonable stop or purchase an option, which defines your risk, then you would limit your loss. All-in-all I like this strategy for seasonal trading because it gives you well defined parameters.  Shows you how much time you need for your option.  That way you don’t pay for time you don’t need.  Also, it gives you an exit strategy using stochastic or the end date of the seasonal.  For example, if you use the stochastic again for the above corn trade, you might have bought back your short corn futures when the stochastic reading went under 10%, indicating an oversold condition.

This would have occurred on June 15th, two weeks before the seasonal would have ended.  The exit price would have been 233 at the close. Some profit would have been left on the table since the low of this move was made on June 26th at 221, but on June 29th the day the seasonal ended, the market closed at 228 ½, not much worse than the 233 oversold exit price. 

You can look for the seasonal dates that are up coming under each of the individual listed commodities within our website.  Good luck and best wishes always.

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