First X Days Of A YearFirst X-Day Indicator
Overview
The "First X-Day Indicator" is a powerful tool to visualize and analyze market sentiment during the crucial first trading days of each new year. It provides immediate visual feedback on whether the year is starting with positive or negative momentum compared to the previous year's close, a concept often related to market theories like the "January Effect" or the "First Five Days Rule."
The indicator is designed to be clean, intuitive, and fully customizable to fit your charting style.
Key Features
Yearly Baseline: Automatically draws a horizontal line at the previous year's closing price. This line serves as a clear 0% reference for the current year's performance.
Dynamic Background Coloring: For a user-defined number of days at the start of the year, the chart background is colored daily. Green indicates the close is above the previous year's close, while red indicates it's below.
Final Performance Symbol: At the end of the analysis period (e.g., on the 5th day), a single summary symbol (like 👍 or 👎) appears. This symbol represents the final performance outcome of the initial trading period.
Settings & Customization
You have full control over all visual elements:
Analysis Period: Define exactly how many days at the start of the year you want to analyze (e.g., 3, 5, or 10 days).
Line Customization: Fully control the yearly baseline's appearance. You can change its color, width, and style (Solid, Dashed, or Dotted) or hide it completely.
Symbol Customization: Choose any character or emoji for the positive and negative performance symbols. You can also adjust their size (Small, Normal, Large) or hide them.
Background Control: Enable or disable the daily background coloring and select your preferred custom colors for positive and negative days.
FIVE
Rolling summaryStatistical methods based on mean cannot be effective all the time when attributed to financial data since it doesn't usually follow normal distribution, the data can be skewed or/and have extreme values which can be described as outliers.
In order to deal with this problem it is appropriate to use median-based techniques.
The most common one is called five-number summary/box plot, which plots median of the dataset, 25th (Q1) & 75th (Q3) percentiles (the medians of lower & upper parts of the original dataset divided by the original median), and whiskers calculated by taking range between Q1 and Q3, multiplying it by 1.5 and adding it to Q3 and subtracting it from Q1. The values which are outside the whiskers are considered outliers. Default settings of the script correspond to the classic box plot.
Seven-number summary can be also plotted by this script, by turning on 4 additional percentiles/Bowley’s seven-figure summary by turning on first 2 additional percentiles and changing their values to 10 and 90 respectively.
P.S.: Mean can be also turned in just to check the difference.
