Seasonality Table - [JTCAPITAL]

Seasonality Table - [JTCAPITAL] is a modified way to use monthly return aggregation across multiple assets to identify seasonal trends in cryptocurrencies and indices.

The indicator works by calculating in the following steps:

1. Asset Selection
   The user defines a list of assets to include in the seasonality table. By default, the script allows up to 32 assets, including popular cryptocurrencies like BTC, ETH, BNB, XRP, and others. Each asset is identified by its symbol (e.g., "CRYPTO:BTCUSD").
   
   
   
2. Monthly Return Calculation
   For each asset, the script requests monthly price data using request.security. Specifically, it retrieves the monthly open, close, and month number. The monthly return is calculated as:
   
   Return = (Close - Open) / Open
   
   This step provides a normalized measure of performance for each asset per month.
   
   
3. Data Aggregation
   The script stores two key arrays for each asset and month combination:
   
   sumReturns: The cumulative sum of monthly returns
   
   countReturns: The number of months with valid data
   
   This allows averaging returns later while handling months with missing data gracefully.
   
   
   
4. Table Construction
   
   Rows representing months (January–December)
   
   Columns representing each asset
   
   An additional column showing the average return for all assets per month
   
   A final row showing the yearly average return for each asset
   
   
5. Filling the Table
   The table cells are filled as follows:
   
   Monthly returns are averaged for each asset and displayed as a percentage.
   
   Positive returns are colored green, negative returns red.
   
   Missing data is displayed as a gray “—” placeholder.
   
   Each row’s values are normalized for the color gradient to show relative performance.
   
   
6. Averages Computation
   The script calculates two types of averages:
   
   Monthly Average Across Assets: Sum of all asset returns for a month divided by the number of valid data points.
   
   Yearly Average Per Asset: Sum of all monthly returns for an asset divided by the number of months with valid data.
   These averages are displayed in the last column and last row respectively, with gradient coloring for visual comparison.
   
   

Buy and Sell Conditions
This indicator does not generate explicit buy or sell signals. Instead, it provides a visual heatmap of historical seasonality, allowing traders to:

Identify months where an asset historically outperforms (bullish bias)

Identify months with weak historical performance (bearish caution)

Compare seasonal patterns across multiple assets for portfolio allocation

Filters can be applied by adjusting the asset list, changing the color mapping, or focusing on specific months to highlight seasonal anomalies.

Features and Parameters

Number of assets: Set how many assets are included in the table (1–32).

Assets: Input symbols for the assets you want to analyze.

Low % Color: Defines the color for the lowest monthly returns in the gradient.

High % Color: Defines the color for the highest monthly returns in the gradient.

Cleaned asset names for concise display.

Gradient-based visualization for easier pattern recognition.

Monthly and yearly averages for comparative analysis.

Specifications

Monthly Return Calculation
Uses the formula (Close - Open) / Open for each asset per month. This standardizes performance across different price scales and ensures comparability between assets.

Arrays for Storage

sumReturns: Float array storing cumulative monthly returns.

countReturns: Integer array storing the number of valid data points per month.
These arrays allow efficient aggregation and average calculations without overwriting previous values.


Data Retrieval via Security Calls

Requests monthly OHLC data for each asset using request.security.

Ensures calculations reflect the correct timeframe and allow for historical comparison.

Color and Text Assignment

Green text for positive returns, red for negative returns.

Gray cells indicate missing data.

Gradient background shows relative magnitude within the month.

Seasonality Analysis

The table visually encodes which months historically produce stronger returns.

Useful for portfolio rotation, risk management, and identifying cyclical trends.

Scalability

Supports up to 32 assets.

Dynamically adapts to the number of assets and data availability.

Gradient scales automatically per row for consistent comparison.