Download Linear Regression Value for MetaTrader 5

Linear Regression Value

Linear Regression Value

This software component for MetaTrader 5 is built to enhance the capabilities of your trading environment. This technical indicator acts as a specialized analysis tool designed to visualize market data. It helps traders identify emerging trends, momentum shifts, and key support or resistance levels by plotting statistical calculations directly onto price charts.

How to Setup and Use Linear Regression Value

1. Installation: Place your file in the MQL/Indicators folder via "Open Data Folder" and restart your terminal.

2. Loading: Find the indicator in the Navigator, drag it onto your chart, and configure the input parameters in the popup window.

3. Customization: Press Ctrl+I to open the indicator list, select your tool, and click "Properties" to change colors, levels, or visual styles.

4. Updating: Replace the old file in the Indicators folder with the new version and restart the platform to apply changes.

Frequently Asked Questions

Q: Why is my indicator not showing? A: Verify the file is in the MQL/Indicators folder, or try right-clicking the "Indicators" tree in the Navigator and clicking "Refresh."

Q: Do custom indicators slow down the platform? A: Too many complex indicators can impact performance; remove unused ones via the "Indicator List" (Ctrl+I).

Q: Can I use MT4 indicators on MT5? A: No, MQL4 and MQL5 are distinct languages; ensure the indicator is compiled specifically for your platform version.

Description & Settings


In the "good old days" coders were trying to optimize all the code that could be optimized. One such example was the optimization of Liner regression calculation. Coder that was coding by the name "mathemat" (if I remember correctly, if I am wrong please correct me) came up with a simplified formula for linear regression value : 3*lwma - 2*sma
And, since both lwma and sma can be optimized to a so called "loop less mode", it was adopted as the optimal way to calculate it and it produces correct values. But that calculation lacks what the "normal" linear regression value calculation has as intermediate values :

linear regression intercept

and the slope of the linear regression line
So, here is one different way of calculating linear regression (optimal : uses the so called "loop less mode") but that has both the intercept and slope

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