Day of Week - Volatility Report

21 thg 3, 2023

█ OVERVIEW

The indicator analyses the ⁣volatility⁣ and reports statistics by the days of the week.


█ CONCEPTS

On business days and weekends, different market participants get involved in the markets. How does this affect the markets during the week?

Here are some ideas to explore:

• When are the best days for trading?
  
• Which day of the week is the market the most volatile?
  
• Should you trade on business days? Is it worth trading during the weekend?
  
• How does this relate to your most profitable trades?
  
• Is there a confluence with the days having the highest win rate?
  
• Which days of the week should you stop trading?
  

Ethereum


USDCAD


NZDUSD


█ FEATURES

Configurable outputs
Output the report statistics as mean or median.


█ HOW TO USE

Plot the indicator and visit the 1D, 24H, or 1440 minutes timeframe.


█ NOTES

Gaps
The indicator includes the ⁣volatility⁣ ⁣⁣ from gaps.

Calculation
The statistics are not reported from absolute prices (does not favor trending markets) nor percentage prices (does not depict the different periods of  volatility  that markets can go through). Instead, the script uses the prices relative to the average range of previous weeks (weekly ATR).

Trading session
The indicator analyses weekdays from the ⁣daily⁣ ⁣chart⁣, defined by the exchange trading session (see Symbol Info).

Extended trading session
The indicator can include the extended hours when activated on the chart, using the 24H or 1440 minutes timeframe.

Overnight session
The indicator supports overnight sessions (open and close on different calendar days). For example, ⁣EURUSD⁣ will report Monday’s ⁣volatility⁣ from Sunday open at 17:00 to Monday close at 17:00.


This is a PREMIUM indicator. In complement, you might find useful my free Time of Day - ⁣Volatility⁣ Report.

24 thg 8, 2023

Phát hành các Ghi chú

v2.0

• Added new modes of comparison (weekly distribution and comparison to an average day)
  
• Allowed the range selection for analyzing the data over a defined period
  
• Fixed an error related to `str.format_time()`
• Added minor improvements