<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multi-Timeframe on FX Backtest Diary</title><link>https://etherpoc.com/en/tags/multi-timeframe/</link><description>Recent content in Multi-Timeframe on FX Backtest Diary</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 24 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://etherpoc.com/en/tags/multi-timeframe/index.xml" rel="self" type="application/rss+xml"/><item><title>A +33.8% backtest fell to -3.0% in walk-forward: all three roads to complexity failed</title><link>https://etherpoc.com/en/posts/indicator-stacking/</link><pubDate>Fri, 24 Jul 2026 00:00:00 +0000</pubDate><guid>https://etherpoc.com/en/posts/indicator-stacking/</guid><description>&lt;p&gt;Over the full test period the numbers read +33.8% with a PF of 1.15. For a moment I thought I had finally found it. Then the walk-forward test came back: -3.0% overall, profitable in one year out of five. Gone.&lt;/p&gt;
&lt;p&gt;This article merges five studies (research notes 34, 44, 45, 47 and 61) into one story about complexity. I attacked the market from three directions that every trader eventually tries: let machine learning dig through a mountain of features, stack indicators on top of each other (a fractal base, fractals plus filters, then a multi-timeframe combo), and shrink the timeframe for more trades. All three roads ended in rejection. But the five studies failed in exactly the same shape, and that shape is worth more than any single result.&lt;/p&gt;</description></item></channel></rss>