OPEN-SOURCE SCRIPT
已更新 Seasonality Chart [LuxAlgo]

The Seasonality Chart script displays seasonal variations of price changes that are best used on the daily timeframe. Users have the option to select the calculation lookback (in years) as well as show the cumulative sum of the seasonal indexes.
🔶 SETTINGS
🔶 USAGE
Seasonality refers to the recurrent tendencies in a time series to increase or decrease at specific times of the year. The proposed tool can highlight the seasonal variation of price changes.

It is common for certain analysts to use a cumulative sum of these indexes to display the results, highlighting months with the most significant bullish/bearish progressions.

The above chart allows us to highlight which months prices tended to have their worst performances over the selected number of years.
🔹 Note
Daily price changes are required for the construction of the seasonal chart. Thus, charts using a low timeframe might lack data compared to higher ones. We recommend using the daily timeframe for the best user experience.
🔶 DETAILS
To construct our seasonal chart, we obtain the average price changes for specific days on a specific month over a user-set number of years from January to December. These individual averages form "seasonal indexes."
This is a common method in classical time series decomposition.
Example:
Pine Script®
Seasonal variations are often highlighted if the underlying time series is affected by seasonal factors. For market prices, it is difficult to assess if there are stable seasonal variations on all securities.
The consideration of seasonality by market practitioners has often been highlighted through strategies or observations. One of the most common is expressed by the adage "Sell in May and Go Away" for the US market. We can also mention:
These are commonly known as calendar effects and appear from the study of seasonal variations over certain years.
🔶 SETTINGS
- Lookback (Years): Number of years to use for the calculation of the seasonality chart.
- Cumulative Sum: Displays the cumulative sum of seasonal indexes.
- Use Percent Change: Uses relative price changes (as a percentage) instead of absolute changes.
- Linear Regression: Fits a line on the seasonality chart results using the method of least squares.
🔶 USAGE
Seasonality refers to the recurrent tendencies in a time series to increase or decrease at specific times of the year. The proposed tool can highlight the seasonal variation of price changes.
It is common for certain analysts to use a cumulative sum of these indexes to display the results, highlighting months with the most significant bullish/bearish progressions.
The above chart allows us to highlight which months prices tended to have their worst performances over the selected number of years.
🔹 Note
Daily price changes are required for the construction of the seasonal chart. Thus, charts using a low timeframe might lack data compared to higher ones. We recommend using the daily timeframe for the best user experience.
🔶 DETAILS
To construct our seasonal chart, we obtain the average price changes for specific days on a specific month over a user-set number of years from January to December. These individual averages form "seasonal indexes."
This is a common method in classical time series decomposition.
Example:
To obtain the seasonal index of price changes on January first we record every price change occuring on January first over the years of interest, we then average the result.
This operation is done for all days in each month to construct our seasonal chart.
Seasonal variations are often highlighted if the underlying time series is affected by seasonal factors. For market prices, it is difficult to assess if there are stable seasonal variations on all securities.
The consideration of seasonality by market practitioners has often been highlighted through strategies or observations. One of the most common is expressed by the adage "Sell in May and Go Away" for the US market. We can also mention:
- January Effect
- Santa Claus Rally
- Mark Twain Effect
- ...etc.
These are commonly known as calendar effects and appear from the study of seasonal variations over certain years.
版本注释
- Set the overlay to false- Minor changes
开源脚本
本着TradingView的真正精神,此脚本的创建者将其开源,以便交易者可以查看和验证其功能。向作者致敬!虽然您可以免费使用它,但请记住,重新发布代码必须遵守我们的网站规则。
Get access to our exclusive tools: luxalgo.com
Join our 150k+ community: discord.gg/lux
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
Join our 150k+ community: discord.gg/lux
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
免责声明
这些信息和出版物并不意味着也不构成TradingView提供或认可的金融、投资、交易或其它类型的建议或背书。请在使用条款阅读更多信息。
开源脚本
本着TradingView的真正精神,此脚本的创建者将其开源,以便交易者可以查看和验证其功能。向作者致敬!虽然您可以免费使用它,但请记住,重新发布代码必须遵守我们的网站规则。
Get access to our exclusive tools: luxalgo.com
Join our 150k+ community: discord.gg/lux
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
Join our 150k+ community: discord.gg/lux
All content provided by LuxAlgo is for informational & educational purposes only. Past performance does not guarantee future results.
免责声明
这些信息和出版物并不意味着也不构成TradingView提供或认可的金融、投资、交易或其它类型的建议或背书。请在使用条款阅读更多信息。