Important: There is no guarantee that ATS strategies will have the same performance in the future. I use backtests and forward tests to compare historical strategy performance. Backtests are based on historical data, not real-time data so the results shared are hypothetical, not real. Forward tests are based on live data, however, they use a simulated account. Any success I have with live trading is untypical. Trading futures is extremely risky. You should only use risk capital to fund live futures accounts and if you do trade live, be prepared to lose your entire account. There are no guarantees that any performance you see here will continue in the future. I recommend using ATS strategies in simulated trading until you/we find the holy grail of trade strategy. This is strictly for learning purposes.
As a quick reminder, we’re on the hunt for the holy grail of automated trading strategies. If you have any questions, start with the FAQs and if you still have questions, feel free to reach out to me (Celan) directly at AutomatedTradingStrategies@protonmail.com.
Just a quick update on three things:
Q1 2026 Forward Test
Live Test #2
APM Battle
Q1 2026 Forward Test
The Forwrad Test started last week. This is the smallest portfolio I’ve ever run. It consists of approximately 7 strategies.
Here’s a look at the equity curve:
In total, the portfolio is up $46K on 661 trades. Here’s a daily breakdown:
Now let’s talk about the Live Test.
Live Test #2
Live Test #2 started last week as well. To read more about the first Live Test (196% return), click here.
No trades were made last week. Analysis from 2025 showed that Week 2 is the best performance week of the month and it appears to be fairly persistent. The first week is very important because it determines your drawdown. Best case scenario, this week will fund the rest (read: future drawdowns won’t ever dip below Week 1 profit).
The Great APM Race
An APM is a meta-strategy that sits on top of your underlying trading strategies and makes real-time decisions on each trade signal.
How it works: Your base strategies (Strategy 3, Strategy 6, Strategy 9, etc.) generate trade signals. Instead of blindly executing every signal, an APM evaluates each one against its specific criteria. Each APM uses a different methodology. A strategy might have a 1.2 profit factor trading every signal. But if an APM can identify which 40% of signals are high-quality and filter out the rest, that subset might have a 2.0+ profit factor. You’re trading less, but making more.
The best part (at least to me) is that these APMs aren’t static filters. They’re designed to learn and adapt. As they accumulate more trade history, their models recalibrate. Cecil refines his prediction. Tomas updates his state probabilities. Usha adjusts her weights. The expectation is that performance should improve as each APM builds a larger sample of what works and what doesn’t in current market conditions.
How long until we see meaningful learning? Honestly, I don’t know. It could take weeks to accumulate enough data for statistical significance, or months before the adaptive mechanisms show clear improvement over baseline. Some APMs may converge quickly while others need more runway. This is uncharted territory.
Currently, Tabitha (Tobacco Lite), is the only APM I’ve published. She finished Week 1 at ($8,075), which actually makes her the 2nd best performer in the Tobacco family, behind only Tomas (V5), which was up $13K. I will share the V5 and V6 APMs with you the first week in February. Meanwhile, if you haven’t done so already, start creating your forward test portfolio. You need at least 10 strategies that trade on a regular basis for this to work. You can run the same strategy, ie, Strategy 3, on 10 different instruments.
Week 1 Winners:
🥇 Cecil: +$17,332
🥈 Tomas: +$13,394
🥉 Maryam: +$10,082
Here’s a bar race showing the race from day-to-day:
This is the first time I’m running 34 APMs head-to-head in live forward testing. And I still have about 10 that have yet to make a trade.
This little experiment could be a complete failure or we might be on the heels of discovering a truly novel approach to portfolio management. I know as much as you do at this point. We’re watching this experiment unfold together in real-time.
Week 1 gave us Cecil in the lead, but one week proves nothing. The real story will emerge over months of data. That’s what makes this interesting. We’re not backtesting hypotheticals, we’re running a live tournament and letting the results speak for themselves.
If you have any questions feel free to reach out directly:
Contact AutomatedTradingStrategies@protonmail.com
I will be away from my desk until February so response times might be delayed. All subscribers have been comped for one month.