NTAP
NetApp, Inc
stock NASDAQ

I've spent the last 49 days running my custom momentum strategy with a $20K live account on the S&P 500 and Nasdaq 100. It is a long term play with weekly rebalancing and designed to ride the biggest winners among top momentum stocks
Obviously seven week trading lacks of statistical significance, but here are my numbers for this short run:

**The numbers:**
\- Trading period: June 2, 2026 - July 21, 2026 (49 days, 7 weeks)
\- Return on deployed capital: 17.19%
\- Return on total account: 4.45% - (average market exposure was only approx. 28% - more on that below)
\- Trades: 8 stocks traded, 5 winners, 3 losers -> 62.5% winrate
\- Profit factor 3.18
\- Biggest winner: MRVL + $428 in 2 weeks
\- Biggest loser: FIX -$288
My weekly retunrs ranged from - 2.49% to +12.95% (MRVL rally). 5 out of 7 weeks were green. Here is how the deployed capital perfomed week over week. The strategy actually tracked right in line with my backtests (backtested CAGR: 42.4% p.a. vs. live annualized approx. 42.3%).
It also navigated the tech sector rotation quite well - it rotated out of semis and into cybersecurity, healthcare and industrials quite early, catching a 25% move on Panw in 3 weeks.

**My 5 takeaways from 7 weeks of live trading:**

**1. Less is more for the universe selection.**
I tried adding the Russell 2000 and other Indices in my backtests - it just led to a worse Sharpe and a deeper max. drawdown. The S&P500 plus Nasdaq100 combo was the sweet spot.
**2. Staggered deployment was a mistake.**
I originally planned to scale in over 5 weeks (stretching out to September). In reality one of my filters keep blocking new entries meaning my average exposure was only \~28% and max. \~38%. I still pulled 4.85% on the total account - imagein if I had been fully deployed the whole time. Lesson: deploy fully from day one.
**3. Manual execution introduces errors**
I thought I made a "trading error" which actually turned out to be my trailing stop working perfectly, but I did accidentally skip to rebalanceing trades. The impace was minimal this time, but the operational risk is real. Lesson: for me as a reminder - the strategy needs to be fully automated!
Manual execution does not scale and just adds behavioral noise.
**4. Trading costs are small but...**
... they compound. Since I am using IB - IBKR commissions feel negligible on a per-trade basis. But factor in weekly rebalancing over several years, and that drag adds up fast. So my lesson is: lower turnover isn't a flaw - it's probably a feature.
**5. Cash drag from filters is real**
One of my entry filters sidelined me from the absolute highest momentum names like Dell, HPE, DDOG, NTAP and it's frustrating in the moment to watch them run, but that filters earns its keep on downside protection.
**What’s next?**
I'll drop a separate post covering my tech stack soon, and I'll keep sharing these performance updates from time to time if you guys find them helpful.
Tomorrow, I’m rolling out a new and improved strategy. The biggest change? Shifting to monthly execution instead of weekly to keep the system leaner. Assuming I set everything up correctly and the TWS API actually does what it's supposed to do, it will be fully automated. Let's see.
How has your momentum strategy been running these last few weeks? Curious what universe and rebalance frequencies you are using.

I've spent the last 49 days running my custom momentum strategy with a $20K live account on the S&P 500 and Nasdaq 100. It is a long term play with weekly rebalancing and designed to ride the biggest winners among top momentum stocks
Obviously seven week trading lacks of statistical significance, but here are my numbers for this short run:

**The numbers:**
\- Trading period: June 2, 2026 - July 21, 2026 (49 days, 7 weeks)
\- Return on deployed capital: 17.19%
\- Return on total account: 4.45% - (average market exposure was only approx. 28% - more on that below)
\- Trades: 8 stocks traded, 5 winners, 3 losers -> 62.5% winrate
\- Profit factor 3.18
\- Biggest winner: MRVL + $428 in 2 weeks
\- Biggest loser: FIX -$288
My weekly retunrs ranged from - 2.49% to +12.95% (MRVL rally). 5 out of 7 weeks were green. Here is how the deployed capital perfomed week over week. The strategy actually tracked right in line with my backtests (backtested CAGR: 42.4% p.a. vs. live annualized approx. 42.3%).
It also navigated the tech sector rotation quite well - it rotated out of semis and into cybersecurity, healthcare and industrials quite early, catching a 25% move on Panw in 3 weeks.

**My 5 takeaways from 7 weeks of live trading:**

**1. Less is more for the universe selection.**
I tried adding the Russell 2000 and other Indices in my backtests - it just led to a worse Sharpe and a deeper max. drawdown. The S&P500 plus Nasdaq100 combo was the sweet spot.
**2. Staggered deployment was a mistake.**
I originally planned to scale in over 5 weeks (stretching out to September). In reality one of my filters keep blocking new entries meaning my average exposure was only \~28% and max. \~38%. I still pulled 4.85% on the total account - imagein if I had been fully deployed the whole time. Lesson: deploy fully from day one.
**3. Manual execution introduces errors**
I thought I made a "trading error" which actually turned out to be my trailing stop working perfectly, but I did accidentally skip to rebalanceing trades. The impace was minimal this time, but the operational risk is real. Lesson: for me as a reminder - the strategy needs to be fully automated!
Manual execution does not scale and just adds behavioral noise.
**4. Trading costs are small but...**
... they compound. Since I am using IB - IBKR commissions feel negligible on a per-trade basis. But factor in weekly rebalancing over several years, and that drag adds up fast. So my lesson is: lower turnover isn't a flaw - it's probably a feature.
**5. Cash drag from filters is real**
One of my entry filters sidelined me from the absolute highest momentum names like Dell, HPE, DDOG, NTAP and it's frustrating in the moment to watch them run, but that filters earns its keep on downside protection.
**What’s next?**
I'll drop a separate post covering my tech stack soon, and I'll keep sharing these performance updates from time to time if you guys find them helpful.
Tomorrow, I’m rolling out a new and improved strategy. The biggest change? Shifting to monthly execution instead of weekly to keep the system leaner. Assuming I set everything up correctly and the TWS API actually does what it's supposed to do, it will be fully automated. Let's see.
How has your momentum strategy been running these last few weeks? Curious what universe and rebalance frequencies you are using.