The seasonality widget is a powerful feature from TrendSpider that allows you to visualize seasonal trends for any symbol. Seasonality is a characteristic of a time series whereby the data experiences regular and predictable changes that recur every calendar year. With the help of this widget, you can easily collect valuable insights into how the symbol has performed historically.
You can use these data points and observations to strategize your trades or when setting limits for option strategies, among many other things.
In this documentation, we will explore how to:
Add Seasonality Widget
Interpret Seasonality Data
Let’s get started 🚀
Add Seasonality Widget
Step 1: Click on the Sidebar button from the top right corner of the interface.
Step 2: Select Add or Remove Widgets from the dropdown list.
Step 3: Click on the Add New Widget Here button at the bottom of the side panel.
Step 4: Select the Seasonality from the dropdown list.
Step 5: Click on Done and the widget will be added to the sidebar.
You can customize the seasonality chart to view and analyze the data points for a specific time period by managing the time settings options below the chart legends.
Select any of the following time units for which you want to analyze the seasonality on the charts :
- Week of the Year
- Day of the Week
- Hour of the Day
In addition to selecting the time unit, you can also use the date picker to fetch and measure seasonality data falling after a specific date. You can select this particular date either by using the dropdown menu or by manually entering it in the field.
The dates available within the date picker vary based on the aggregation (time unit) selected. For example, the traders shall have comparatively more dates to select from the date picker if the monthly time unit is selected over an hourly aggregation.
Filter Seasonality Data
You can filter the seasonality data appearing in the charts to exclude outliers, such as the 2008 financial crisis or the 2020 COVID-19 outbreak, or anything else of your choice by simply clicking on the filter icon.
By excluding these periods, you may be able to create a more accurate picture of how security behaves during normal times. You can exclude an entire year (i.e., “2008”) or specific months (i.e., “May 2008”).
You can also have more than one exclusion by separating values by commas. For example, if you wanted to exclude the 2008 crisis and the first months of the COVID panic, you could use "2008, 2009, 2010, Mar 2020, Apr 2020, May 2020".
Interpreting Seasonality Data
Navigate to the chart in the Seasonality widget to view and interpret the seasonality for the following data points:
- Winning Periods (Green Columns)
- Median Change (Violet Line)
- Mean Change (Blue Line)
- P25% / P75% (Pale Blue Cloud)
- Raw Data
Tip: You can full-screen the chart by clicking on the full-screen button at the top-right corner of the chart 💡
Toggling to the full-screen mode makes it easy to read and interpret the data points:
Winning Periods (Green Columns)
Toggle on the Winning Periods from the chart legend at the bottom. Winning periods on the chart reflect the percentage of aggregation periods (days, weeks, months, hours) that closed higher than they opened. For example, in the chart below you can observe the reading for the first month of the year where 78% of the first month periods closed higher than they opened.
Median Change (Violet Line)
Toggle on the Median Change % from the chart legend at the bottom. The median change on the chart reflects the median percentage change of a time series for the selected time period. For example, in the chart below you can observe the reading for the first month of the year where the median change percentage was 9.53% The median is the “middle” value in an ordered list of values.
Mean Change (Blue Line)
Toggle on the Mean Change % from the chart legend at the bottom. The mean change on the chart reflects the mean (average) percentage change of a time series for the selected time period. For example, in the chart below you can observe the reading for the first month of the year where the mean change percentage was 6.34%. The mean is equal to the sum of all values divided by the number of values.
P25% / P75% (Pale Blue Cloud)
Toggle on the P25% / P75% from the chart legend at the bottom. The 25% percentile to 75% percentile range is shaded on the chart widget to show where “most” of the percentage changes or volatility took place.
The minimum and maximum mean percentage changes are shaded on the chart to show the absolute highs and lows over the time series.
The raw data in the seasonality chart reflects the distribution of outcomes. For example, if you are looking at the Monthly data for 10 years, then there will be 10 dots for each month with raw data, where each dot would represent the outcome of one of the months in the sample.
Vertical Dashed Line
Every Seasonality chart has a vertical dashed line called "Now", which illustrates what's the corresponding period on your Seasonality chart for the "Now" moment. It's not very useful for Monthly charts, but helps a lot for the Week of Year, for example.