MAIK + 2 ML September 19, 2018 TIME SERIES ANALYSIS & SEASONALITY A process for the definition of prevailing trends in the time context is the SEASONALITY METHOD. According this method the value of a magnitude lets say the evolution of the average price of Crude Oil is the product of 3 elements : A. The Long Term Value (L) B. The Seasonality Coefficient (S) C. The Random Coefficient (R) where R =1, on an average basis. S is an Index, taking values around to 1. If S<1 then we know that we are in a Month with low seasonality, instead of S>1 where we are in a Month with high seasonality If S=1 then there is no Seasonality, in other words taking the 8.33% (1/12) of an Annual Value (Annual Sales) this will be equal with the sales per month every month... Total view of S indices, is the the main stream pattern, created from the past, that explains how is expected to be allocated Monthly an Annual Value.... S is also the expected change of an average value of a variable vs. the average value of the previous month. An example of a Seasonality Diagram for CRUDE OIL WTI is the following case : Quote Share this post Link to post Share on other sites
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