Taming the Market Hours: Adding a Session Day Range Filter in TradingView

The foreign exchange (forex) market and many other instruments operate across different geographical locations, leading to distinct trading sessions. Market behavior can vary significantly between these sessions, with some known for higher volatility or specific trading patterns. This is where a session day range filter in TradingView comes in. This filter allows you to focus your analysis on specific timeframes within a session, potentially leading to a more targeted understanding of price movements.

Why Filter by Session Day Range?

Here are some key reasons to consider using a session day range filter:

• Tailored Analysis: Different sessions can attract different types of traders, leading to unique market dynamics. Filtering by session day range allows you to analyze price action within the context of a specific session and its typical behavior.

• Reduced Noise: Overnight sessions, for example, can be less liquid and prone to erratic price movements. Filtering out these periods can help you focus on periods with more consistent trading activity.

• Strategy Optimization: If your trading strategy thrives on specific session characteristics, a session day range filter allows you to backtest and refine your strategy within those parameters.

TradingView Doesn't Have a Built-in Filter (But There's a Script for You!)

While TradingView doesn't offer a dedicated session day range filter, Pine Script, its powerful scripting language, allows you to create your own. Here's how to accomplish this:

Building a Session Day Range Filter with Pine Script

1. Open the Chart: Launch TradingView and pull up the chart you want to analyze.

2. Add a New Indicator: Click the indicator icon (plus sign) on the top toolbar and select "New Indicator."

3. Name Your Script: Give your script a descriptive name like "Session Day Range Filter."

4. Write the Pine Script Code: Here's the basic code for a session day range filter:

Pine Script

//@version=5
indicator("Session Day Range Filter", overlay=true)

// Define session open and close times
sessionOpen = input(8 * 60, title="Session Open Time (GMT)")  // Adjust for your desired session
sessionClose = input(16 * 60, title="Session Close Time (GMT)")

// Calculate current bar time in minutes since midnight GMT
currentTime = time_convert(time(), timeframe.period, timeframe.timezone)

// Check if current time falls within the session range
isSessionTime = currentTime >= sessionOpen and currentTime < sessionClose

// Highlight bars within the session range
color = if isSessionTime
    color.green
else
    color.gray
plot(close, color=color, linewidth=2)

Explanation of the Code:

• sessionOpen and sessionClose: These define the opening and closing times of your desired session in minutes since midnight GMT. You can adjust these values based on the specific session you're interested in (e.g., London open at 3 AM GMT would be 3 * 60).

• currentTime: This calculates the current bar time in minutes since midnight GMT.

• isSessionTime: This conditional statement checks if the current time falls within the defined session range.

• color: This defines the color of the bars on your chart. Green bars represent periods within the session range, while gray bars are filtered out.

• plot: This plots the closing price with the color determined by the isSessionTime statement.

5. Customize Your Filter:

• You can adjust the sessionOpen and sessionClose values to target specific sessions.

• Modify the color scheme using the color variable.

• Consider adding additional conditions to the if statement to filter based on other factors like price movements or specific session times within the overall session range.

6. Save and Apply the Script: Once satisfied with your script, click "Done" to save it. Select the newly created "Session Day Range Filter" from the indicator list and apply it to your chart.

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Benefits of Using a Session Day Range Filter

• Targeted Analysis: Focus on price movements within a specific session's context, potentially leading to more accurate interpretations.

• Reduced Noise: Eliminate potentially misleading data from less liquid periods, allowing for cleaner analysis.

• Strategy Backtesting: Fine-tune your trading strategy by backtesting within the timeframe of your chosen session.

Remember:

• A session day range filter is a tool to complement your analysis, not a replacement. Combine it with other technical indicators and price action analysis for a comprehensive approach.

• Be mindful of potential session overlap depending on the instruments you trade and your chosen session.