Date Range: 5, 10, 15 years
Perform the analysis using the last 5, 10, or 15 years of data.- The more depth of information the stronger the relationships will be.
- However, if fundamental changes are taking place in the industry/economy you might consider using the most relevant, (less) amount of information, time frame.
- While the industry is undergoing a change, if the relationship found in the shorter period of data yet still exists in the longer periods of data, it would be indicative of a reliably reoccurring relationship (very strong relationship).
- You may spot strength or any undergoing shifts in a trend by looking at multiple time frames.
Data Period Division Method:
Data is divided into periods of months, quarters, and years. A bullish/bearish period refers to a bullish/bearish quarter for instance.Example #1:
Suppose your data is divided in quarters. Your seasonal chart in the month of April (1st month in the 2nd quarter) will be referring to:
- What usually happens in April (ALL)
- What path did it usually take in April when the 2nd Quarter finished up (bullish period case)
- What path did it usually take in April when the 2nd Quarter finished down (bearish period case)
Data Division period: Annual
Seasonal Chart will be reffering to the following:
- What usually happens in April (ALL)
- What path did it usually take in April when the year finished up (bullish period case)
- What path did it usually take in April when the year finished down (bearish period case)
Data Series: All.
Filter: None
This data series will refer to all data in the month of April, for instance.
Filter: None
This data series will refer to all data in the month of April, for instance.
Data Series: Bullish.
Filter: Bullish Periods
This data series refers only to the data in the months of April, for instance, whose period finished up.
Filter: Bullish Periods
This data series refers only to the data in the months of April, for instance, whose period finished up.
More specificly, if your data is divided into periods of:
- Years: The data searies uses only the data for the month of April, for instance, whose year finished positive.
- Quarters: What path does it usually take in April, for instance, when the (2nd)Quarter finishes up.
- Months: What path does it usually take in April, for instance, when the Month of April finishes up.
Data Series: Bearish.
Filter: Bearish Periods
This data series refers only to the data in the months of August, for instance, whose period finished down.
Filter: Bearish Periods
This data series refers only to the data in the months of August, for instance, whose period finished down.
More specificly, if your data is divided into periods of:
- Years: The data searies uses only the data for the month of August, for instance, whose year finished negative.
- Quarters: What path does it usually take in August, for instance, when the (3rd)Quarter finishes down.
- Months: What path does it usually take in August, for instance, when the Month of August finishes down.
Data Series: Current Prices.
Filter: None
The actual prices of the month you are examining, April for instance.
You may find conformance of actual prices to their bullish and bearish historical tendencies.
How similar is it tracking to the bullish path?
Is it trading as it does when the month finishes up?
Filter: None
The actual prices of the month you are examining, April for instance.
You may find conformance of actual prices to their bullish and bearish historical tendencies.
How similar is it tracking to the bullish path?
Is it trading as it does when the month finishes up?