Seasonality & Cyclicality

Understanding the background of a market will greatly enhance your understanding long-term market direction and reduce the likelihood of surprises when trading. These background influences should be thoroughly researched every weekend while some should also be updated daily before trading. This entry can be classified under Weekend Research and Preparation. What is being covered will rarely effect your trading, but could be the reason for major losses if your pre-trading preparation is not thorough.

Seasonality vs. Cycles

In most cases, seasonality is restricted to one production cycle (the period of time that passes between one production event and the next). For most of the principal field crops produced in the U.S., seasonality occurs over a 12-month period (stretching over all four seasons—hence the name “seasonality”). Seasonality should be distinguished from other cycles. Seasonality is related to the calendar, such as months or seasons, and is usually based on changes in supply and demand. Cycles can last any length of time (from minutes to decades). While there is ample statistical evidence (and a sound theoretical explanation) for seasonality in crop markets, there is only limited evidence that other types of “cycles” affect the markets for most of the principal U.S. field crops.

Unlike price cycles, which may have a “technical analysis” explanation, the few fundamental crop “cycles” that have been identified are widely believed to be triggered by external events that have an unusual impact on the market. These market shocks (often associated with droughts), in turn, trigger production, demand, and even policy reactions. The effects of such market shocks gradually dampen over time and do not continue indefinitely.

I’m not going to get into the Keynesian macro economic theory of business cycles, except to say an awareness of them could be helpful when trading. I will, however, hit on the the impact of the four-year Presidential Election Cycle developed by Yale Hirsch which apparently comes from presidential canidate promises and the actuality of their term in office:

The first year of a presidency is characterized by relatively weak performance in the stock market. Of the four years in a presidential cycle, the first-year performance of the stock market, on average, is the worst. The second year, although better than the first, is also is noted for below-average performance. Bear market bottoms occur in the second year more often than in any other year. The third year or the year preceding the election year is the strongest on average of the four years. In the fourth year of the presidential term and the election year, the stock market’s performance tends to be above average.

Then comes seasonality and some other quirkslike Black Friday, the Santa Claus Rally, and the January Effect which I’ll go into breifly. Black Friday comes the day after the U.S. Thanksgiving, celebrated on the fourth Thursday in November. The strategy is to but the Dow industrials at the beginning of the week (Nov. 23), then sell on Black Friday.

The Santa Claus Rally begins on Dec. 23 and runs into the first two days of January. The so-called January Barometer, devised by Hirsch, says that if the Santa Claus Rally extends through January there will be a good year ahead. “As January goes, so goes the year,” is one of the market’s most-cited seasonal trends.

The January Effect is the period from mid-December through the following January, when the Small Caps supposedly outperform the Blue Chips. A weak January Effect is a bad omen, and could be a negative for the next 12 months because Small Caps “are more sensitive to the domestic economy, while larger companies or multi-nationals tend to be more sensitive to the global economy.”

The Dogs of the Dow strategy was popular in the early 1990s. It started when a few insiders recognized that the 10 highest-yielding Dow stocks outperformed the market indexes. Later, a book was published about this strategy and then all the major brokerage firms started offering Dogs of the Dow managed accounts. The strategy doesn’t work anymore, but it does show what an understanding and open mind to what seasonality might accomplish. For instance:

  • After dropping 50 points from its high during September 2003, the S&P 500 rallied over 115 points through December 31, 2003.
  • In October 2004, the S&P 500 dropped 52 points from its October high before rallying 127 points through December 31.
  • From its September 2005 high, the S&P 500 fell nearly 75 points just prior to a sharp 107 point rally into December.
  • In 2006, the S&P 500 did not drop during September or October as it had in 2003, 2004 and 2005. Instead, the market rallied 165 points from its July 18 low to its October 26 high without a meaningful pullback along the way. In percentage terms, the S&P 500 rallied over 13% during this period, a performance that has only occurred three other times since 1980 during the same calendar period (1982, 1984 and 1996).
  • In August 2007, the S&P 500 dropped from a high of 1553 to 1406 before rallying 159 points through October.

Don’t use seasonal data in isolation. Seasonal data should only be a part of a trading strategy. Of course it has more immediate trading relevance with certain commodities and other industries affected by the seasons. One such industry, construction, shows how seasonal data can be useful when trading futures indexes when certain economic announcements are due. When an economic calendar shows Existing Home Sales where the previous release showed x and the forecast is down. it might not be so bad – maybe even good. Say its the fourth quarter. Well, with winter setting in and the kids in school, there’s just never as many home buyers as there are in the third quarter. This could be a very profitable insight.

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