Linear Regression Signals for FTSE 100 and UK Gilts

Summary

This article presents an MQL5 Expert Advisor that combines UK gilt and FTSE 100 market data in a linear regression model. It describes conventional gilts and inflation-linked gilts, and outlines the common tendency for investors to move between equities and government bonds as risk appetite changes. The model uses recent OHLC inputs from both markets to forecast a future FTSE 100 closing value, with an intercept included in the regression.

The implementation standardizes the input features because gilt and index prices are on different scales, then estimates coefficients using a pseudo-inverse. The model’s direction is combined with technical analysis: a trade is considered only when the indicators agree, and a forecast reversal can prompt position closure. The article argues for using recent data because market regimes change, while noting that larger samples require more computation. It offers an implementation walkthrough rather than rigorous performance analysis. The concluding claims of self-optimization and time-frame flexibility are not supported here by detailed test statistics, and the description provides no quantified evidence of profitability.

Key ideas

• The model uses recent gilt and FTSE 100 data to forecast a future index value.
• An intercept and pseudo-inverse estimation are used in the linear regression implementation.
• Input features are standardized to account for different price scales across the two markets.
• Technical indicators must agree with the model’s direction before the system enters a trade.
• The article provides an implementation description but no quantified evidence of profitability.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.