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Just curious how the seasonality chart is calculated? I'd like to come out with my own.
Use crude as example, if I want to calculate the seasonality of December crude oil contract. What should I do? I downloaded the Dec-2017 data, and I found the contract actually started trading from 2008.
When I calculate 5 year seasonality, should I use the last 12 month data of Dec-2017, with last 12 month data of Dec-2016/2015/2014/2013 years, or something else?
Many thanks for your technical details. I will use excel to do this work. You inputs are highly appreciated.
Best Regards
David
Can you help answer these questions from other members on NexusFi?
I do not understand why you want to develop a system that can be bought at a reasonable price, if the quality of your system is not superior. And as you ask a very basic question I doubt you are able to beat the tools of MRCI or Seasonalgo.
Hi,
Rather than start a new topic I shall post my question here as its along the lines of the first question.
I am creating a seasonal indicator for the Sierra charts package and need help with the calculations too. Although seasonal charts are available on line and often free, I would prefer to have it displaying on my charting package.
I managed to get the same results as the MRCI website shows on their seasonality charts and my calculations are here to be viewed. the resulting chart is almost identical to MRCI's 5year seasonality of Crude oil chart. Here it is:
However, I would like to use a calculation like the one in Trading Navigators - Seasonal Trend indicator. Its a rolling seasonal index as far as I understand so that the value at 31 December = 1st January.
Here are two examples of it:
I'd appreciate any help as to the method and perhaps of an example of getting to a seasonal calculation like this.
If you're serious about measuring "seasonality", you have to use regression methods. This can be done by assigning "dummy" or "binary" variables to your datapoints.
I am not going to explain what regression, dummy/binary variables, or the millions of types of seasonality because it's too broad. You can do a simple dummy regression in excel if you are only looking at monthly seasonality (excel only let's you use up to 16 variables). The method to do this is fairly easily found using google, just search "binary dummy regression excel" or something.
Unfortunately, once you get the data to reflect seasonality and run a regression, interpreting the results takes more than just google searching and will likely take a lot of digging around for useful reference guides - unless you're already familiar with stats.
Studying seasonality and not including this type of study is like taking a soap box with rusty wheels to an F1 race.
