Step 1: Understanding seasonal patterns
The purpose of this  analysis is to understand for a given market and commodity
combination the seasonal price trends.  By understanding these trends (done by explaining
unexpected behavior using the contextual information generated in Chapter 3) the analyst
will gain valuable insights that will facilitate analysis of  current prices.  Also, this process
can assist in identifying reference periods that will be useful comparisons for  current price
An example of the output from this analytical procedure illustrates the behavior of maize
prices in Nairobi, Kenya for each year over the period of 1993 to 1997 (Figure 5.2).  The
multiple year periods was selected to provide a historical perspective of the price behavior
of maize for those years.
Figure 5.2.  Example of intra year seasonal price behavior
Maize prices in Nairobi Market (Kenya): 1993   1997
The following insights explain the observed price behavior in the Nairobi Market.
During the first part of 1994, maize prices were well above normal.  The reason for these
high prices is that Kenya was just coming out of a severe drought. During the second half
of 1994, prices exhibited normal seasonal levels, following an exceptionally good July 
November long rains harvest and exceptional imports.  The price pattern in 1995 was
surprisingly flat.  The reason for this was the exceptionally good July   November 1994
long rains harvest and the staggered releasing of grain on the market by traders.  This
tempered the usual increases in prices during the January   June period that resulted in the
flat price curve.  A near total maize crop failure occurred during the October December
short rains season in 1996. Thus maize prices appreciated dramatically during 1997 and
remained comparatively higher than normal levels throughout 1997.   Also, the
unexpected price patterns in 1993 and 1996 are explained by uncharacteristic price
appreciation after May that resulted from an expectation of below normal long rains

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