Mid-2026 Portfolio Update: Up 23.6% so far, but here’s how I nearly blew it. (Myfxbook Verified Results)

Free_Butterscotch_86 · 2026-07-03T20:28:43+00:00

=== SUMMARY === - The author shares a mid-2026 portfolio update of CFD algo strategies, up 23.6% YTD, but details two costly lessons: a code bug causing excessive risk on Japanese index trades, and the necessity of tick‑data backtesting over 1‑minute bars. - The core thesis is that rigorous validation (auditing live executions and tick‑data cross‑checks) dramatically improved strategy performance, raising the rolling Sharpe above 2.0. - Quality assessment: This is a well‑researched, transparent post with verified Myfxbook results, but it is more of a meta‑lesson on risk management and backtesting methodology than a specific investment thesis. Not pure noise, but not actionable DD for a specific asset. === SENTIMENT === BULLISH === TRADE IDEAS === No actionable trade ideas in this post.

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The author shares a mid-2026 portfolio update of CFD algo strategies, up 23.6% YTD, but details two costly lessons: a code bug causing excessive risk on Japanese index trades, and the necessity of tick‑data backtesting over 1‑minute bars.
The core thesis is that rigorous validation (auditing live executions and tick‑data cross‑checks) dramatically improved strategy performance, raising the rolling Sharpe above 2.0.
Quality assessment: This is a well‑researched, transparent post with verified Myfxbook results, but it is more of a meta‑lesson on risk management and backtesting methodology than a specific investment thesis. Not pure noise, but not actionable DD for a specific asset.

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I've run a portfolio of CFD strategies generated with StrategyQuant X for over 2 years, and I publish my results publicly.

I’m halfway through the year and sitting at a **23.6% return** on my master account. It’s been a great run since March, but the first three months were essentially a flatline, punctuated by a massive, heart-attack-inducing spike that I definitely didn’t intend.

I learned two massive lessons the hard way, and I figured I’d share them in case anyone else here is building their own algo systems.

# 1. Triple-check your live trade executions

I hit a weird spike in early March because of a bug in my code. I run my strategies with a strict **0.25% risk per trade**, but for my Japanese stock index strategies, the code was accidentally firing at **2-3% risk**. Instead of my usual $500–$600 per trade, I was suddenly risking $3,000–$4,000. It worked out to the upside initially, but it was pure luck, followed by a brutal dip. If you’re trading, audit your MT5 backtests—I would’ve caught the math error immediately if I’d actually paid closer attention to those logs.

# 2. Tick data testing is mandatory

My performance for the first quarter of the year was just going sideways. However, when I backtested the strategies, I should've been up. So the backtests and the live results weren't matching.

Here's the thing: for a long time, I was only running my backtests on 1-minute resolution data. My logic was that because these are intraday breakout strategies with trade durations of a few hours, the resolution wouldn't matter. I was wrong.

When I finally forced all my strategies through a **tick data test**, the ones that weren't matching my backtests showed massive performance degradation. I made tick data cross-checking a mandatory part of my workflow, and once I cut the strategies that failed that test, my performance smoothed out and my rolling monthly Sharpe ratio jumped above 2.0.

Overall:

June was my best month yet at **13.39%**, and I'm feeling a lot more confident now that my backtests actually reflect live conditions. This portfolio has been running for over 2 years, and I'm trying to be as transparent as possible.

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