Great article on the power of combining factor investing with a systematic momentum overlay. It’s rare to see a strategy that effectively mitigates the decade-long underperformance periods often seen in pure factor plays.
Have you tested how sensitive the CAGR is to the specific look-back period—for instance, does using a 6-month vs. a 12-month momentum window significantly change the drawdown protection results?
I have tested every possible look-back period with the monthly data. The CAGR stays significantly above market level, regardless of the lookback period, but the alpha gradually declines the further I move away from the selected monthly intervals, as you would expect.
So, it seems the system would do well with most settings, but I optimized it for the most consistent outperformance based on the 2000-2020 data.
I’ve been following MarketFighter’s site pretty much since the early days — mostly just reading quietly and trying to understand the logic behind the strategy. Over time, the consistency of the updates and the transparency really kept me coming back.
One thing I was curious about was whether the returns in USD would match the EUR version. After checking it myself, the USD performance is basically similar, and in some periods even a bit higher. That gave me enough confidence to stop watching from the sidelines.
So I ended up buying the suggested ETF strategy myself — and yes, the returns are real. Not backtests, not theory. Actual results in my own account.
Big thanks to MarketFighter for putting the work into this. I have decided to subscribe because it’s rare to find something that’s both simple and actually holds up when you test it on your own.
Just sharing this for anyone else who’s been quietly observing like I was.
You can feel the years of trial and patience behind this. The discipline to stick with a system is what most people struggle with. It’s a steady approach that seems to value consistency over excitement.
It does require discipline to stick with a system.
And yes, my main priority was to build a system with high consistency in the returns. There are lots of trading systems available that deliver higher CAGRs but with much higher volatility. Personally I don't have the risk profile to stick with these, so I had to invent my own.
Really enjoyed reading this because it focused on something many investors overlook: the importance of having a repeatable process. Outperformance rarely comes from chasing every market trend or constantly reacting to noise. More often, it comes from having a clear framework, staying disciplined, and sticking to it through different market cycles.
What stood out to me is that good investing often looks boring from the outside. It is patience, consistency, and sound decision making under uncertainty repeated over time. That is where the real edge usually comes from. Great breakdown.
Well said, and thanks, I appreciate it! 🙏 You’re absolutely right. Patience, discipline, and consistency can take you far, and that combination seems to be underrated.
You should execute the trade after you receive the monthly trade signal in your inbox. Ideally on the first day of the month, but the sooner the better.
The whole back-test and my five years of trading the system in real life have been based on trades executed at the turn of the month or on the first trading day of the month.
I haven’t, because we don’t have access to these as retail investors in the European Union. But historically, they would most likely have performed better in the crisis years but also introduced more volatility.
A very interesting approach, which may actually work for me.
The shown results look really good! The one disadvantage I can see to this approach is that it makes you realize gains much earlier vs a buy and hold approach, so the capital gains taxes paid early leave less money to be invested and reduce the compounding effect over time.
Can you share your thoughts and/or data on the taxes effect due to constant gains realization?
Capital gains tax is definitely worth considering, but it’s also a highly individual matter, depending on the country you live in.
I have paid subscribers from all over the world, but I always recommend consulting with a local tax expert if you have any doubts, as I only know about the Danish tax system myself.
I've been reading for a while and find the approach genuinely interesting. Combining sector and factor momentum into a single monthly rotation is a clean idea, and you're more transparent about the mechanics than most people selling signals. Credit for that.
Before I allocate seriously to it, four things I'd like to understand:
1. Benchmark construction — is the MSCI World column price return or net total return? Compounding your annual figures gives roughly 3.8% p.a. over the period, which is about two points below MSCI World's actual net total return. If the strategy column includes dividends and the benchmark doesn't, a meaningful slice of the reported alpha would be a measurement artifact.
2. Live vs. backtested — can you break out performance from the date you started publishing signals, separately from the simulated history? An out-of-sample record is the only part that can't be optimised in hindsight.
3. 2008 — the strategy shows -10.24%. Consumer staples, the strongest global sector that year, fell roughly 15-20%. A long-only rotation between sectors and factors shouldn't be able to beat its own best available holding, so I assume there's a cash or moving-average filter in the model. Could you describe it?
4. Investability pre-2013 — most of the major factor ETFs didn't launch until 2012-13, and several factor indices were backfilled. How much of the 2000-2012 record is simulated on index data rather than tradeable instruments, and does it account for spreads and TERs?
Not trying to be difficult — these are the questions I'd ask any manager, and clear answers would make me more confident rather than less. Thanks.
1. The data I used to build this was based on price returns, so I decided to stick with this for all data to make a fair apples-to-apples comparison. You're right that net totals are higher. This applies to the benchmarks as well as the strategy returns.
3. Yes, there's a drawdown protection layer, also based on relative price momentum. I have tested this part on data back to 1871, and it kicked in last time in 2008-2009. It is described in this article.
4. It's not based on specific ETF implementations as they vary across the globe. It's based on the underlying indices and not accounting for spreads, TERs, or taxes, as all of this varies upon execution.
Thanks for the article, and the effort. Looks like it will pay back the time you have put in. For investors in Spain, there is a deferred tax mechanism that consists in the use of investment funds, in lieu of etfs, as there is a tax provision that lets investors transfer funds directly between investment funds without any tax withholding. Taxes are due when you redeem the funds for the investment fund. I guess the answer is no if it’s of no use for the majority but, have you backtested the method with investment funds that can be comparable to the etfs you’ve used? Of course bigger costs but also less taxes would need to be factored in to be able to compare apples to apples.
That sounds like an attractive deal with the funds! As you guessed, I haven't backtested this. Most funds are actively managed, which means you can't really use their historical track record for anything, and I would never use them for systematic trading.
If you have access to passive index funds that track the same or similar indices, then it's a different story. As long as their fees are not exorbitant, I would definitely go for that solution. Feel free to send me a DM if you want to pursue this.
Great article and I love the simplicity of the strategy. I have noticed that the MSCI World annual performance figures on your Distribution of Returns table are not accurate. Most years are either too high or too low. MSCI World returned 21% in 2025 for example, 15% more than your figure. I just wondered where this error came from?
My guess is you compared with MSCI World in USD? 😉 All the numbers I provide are in EUR. It’s not an error, it’s simply the MSCI World Index in EUR. If you live in the US or in any country with another currency, you will see fluctuations matching the currency movements :)
Good work, look forward to studying it further. I have been testing a similar approach but only once every three months and not thought through sector-wise as systematically as you have done. Kudos. That said, would like to see comparison equity curves between the major US indices such as Russell, NQ, ES, not just the World Index.
I'm actually planning on a US-specific article some time in August, as other US-based subscribers have requested more US-specific content. Then I will look more into this.
Maybe you already noticed, but I included S&P 500 for comparison in some of the charts in this article 😊
Really enjoyed this — the honesty about your 15-year journey before finding what actually worked is refreshing. Most people only share the wins.
The psychological point resonates deeply: knowing a factor works over 20 years means nothing if you capitulate during a 3-year drawdown. That's where most retail investors (and honestly, some institutional ones too) fall apart.
As a former institutional portfolio manager, I used sector dispersion within the S&P 500 extensively - and during periods like the COVID crash, exploiting those gaps allowed me to generate meaningful outperformance for my clients' portfolios.
Curious -when you're rotating between ETFs, how do you handle sectors where the factor signal conflicts with the macro backdrop? For example, Value has screamed "buy" on certain Financials for years, yet macro headwinds kept suppressing returns. Do you follow the signal mechanically, or is there a qualitative override in your system?
The system is entirely based on monthly price levels and the relative momentum of these. It does not take macro backdrop, fundamental data, personal opinions, emotions or any other qualitative parameters into account.
Eliminating all of this noise and emotions and simply relying on the academically proved factors of excess returns is what has caused the results you see :-)
Thanks for the article. As a fellow computer scientist I loved reading this and your approach. I've downloaded the stock data for the last few years, calculating all the technicals for each stock and running various queries with a view to something similar in an individual sock basis, but your approach is so elegantly simple (appreciate the work to get there wasn't!). Will definitely give this a try.
Thanks, I really appreciate your comment! I've been down that road with individual stocks as well, attempting to build a similar system, but I didn't manage to find the same consistency as I did with the ETF setup. It was too volatile for me :-)
The quality factor section resonates most. The reason quality outperforms over long periods isn't random. It's because businesses with high ROIC and consistent profitability have structural advantages that compound the same way the returns do.
The psychological challenge you describe is real. Most investors abandon quality factor strategies during underperformance because they don't understand why quality works. The fundamentals tell you why.
That's what makes it possible to hold through the difficult periods.
Factor investing is academically credible and practically humbling. Value was dead for a decade. Momentum crashes violently. Low volatility underperformed in the longest bull run in history. The factors work — on a timeline most investors can't emotionally survive.
Action: Look up the maximum drawdown and longest underperformance period for each factor cited — then decide honestly if your patience actually matches the strategy's requirements
Exactly. Investing in individual factors is practically impossible to hold on to during the inevitable bad periods. That's what my strategy aims to solve by rotating into the recently strongest factor and abandon the rest. But you are absolutely right regarding the use of individual factors.
Great article on the power of combining factor investing with a systematic momentum overlay. It’s rare to see a strategy that effectively mitigates the decade-long underperformance periods often seen in pure factor plays.
Have you tested how sensitive the CAGR is to the specific look-back period—for instance, does using a 6-month vs. a 12-month momentum window significantly change the drawdown protection results?
Thank you! Appreciate your comment 🙏
I have tested every possible look-back period with the monthly data. The CAGR stays significantly above market level, regardless of the lookback period, but the alpha gradually declines the further I move away from the selected monthly intervals, as you would expect.
So, it seems the system would do well with most settings, but I optimized it for the most consistent outperformance based on the 2000-2020 data.
Thank you for the knowledge 👏
I’ve been following MarketFighter’s site pretty much since the early days — mostly just reading quietly and trying to understand the logic behind the strategy. Over time, the consistency of the updates and the transparency really kept me coming back.
One thing I was curious about was whether the returns in USD would match the EUR version. After checking it myself, the USD performance is basically similar, and in some periods even a bit higher. That gave me enough confidence to stop watching from the sidelines.
So I ended up buying the suggested ETF strategy myself — and yes, the returns are real. Not backtests, not theory. Actual results in my own account.
Big thanks to MarketFighter for putting the work into this. I have decided to subscribe because it’s rare to find something that’s both simple and actually holds up when you test it on your own.
Just sharing this for anyone else who’s been quietly observing like I was.
That’s great to hear, thank you so much for sharing this! 🙏
You can feel the years of trial and patience behind this. The discipline to stick with a system is what most people struggle with. It’s a steady approach that seems to value consistency over excitement.
Thanks for the words! 🙏 You are absolutely right.
It did take many years to reach this point.
It does require discipline to stick with a system.
And yes, my main priority was to build a system with high consistency in the returns. There are lots of trading systems available that deliver higher CAGRs but with much higher volatility. Personally I don't have the risk profile to stick with these, so I had to invent my own.
Really enjoyed reading this because it focused on something many investors overlook: the importance of having a repeatable process. Outperformance rarely comes from chasing every market trend or constantly reacting to noise. More often, it comes from having a clear framework, staying disciplined, and sticking to it through different market cycles.
What stood out to me is that good investing often looks boring from the outside. It is patience, consistency, and sound decision making under uncertainty repeated over time. That is where the real edge usually comes from. Great breakdown.
Well said, and thanks, I appreciate it! 🙏 You’re absolutely right. Patience, discipline, and consistency can take you far, and that combination seems to be underrated.
I love this! This is exactly the kind of edge I’ve been looking for 🙏 Subscribed and looking forward to follow!
When exactly are the trades supposed to be executed?
Thank you so much, I really appreciate this!
You should execute the trade after you receive the monthly trade signal in your inbox. Ideally on the first day of the month, but the sooner the better.
The whole back-test and my five years of trading the system in real life have been based on trades executed at the turn of the month or on the first trading day of the month.
Have you ever backtested a short ETF when you go to cash ?
I haven’t, because we don’t have access to these as retail investors in the European Union. But historically, they would most likely have performed better in the crisis years but also introduced more volatility.
Having trouble with subscribing on substack .. please send me a link.
Try this url in a web browser: https://www.marketfighter.com/subscribe
A very interesting approach, which may actually work for me.
The shown results look really good! The one disadvantage I can see to this approach is that it makes you realize gains much earlier vs a buy and hold approach, so the capital gains taxes paid early leave less money to be invested and reduce the compounding effect over time.
Can you share your thoughts and/or data on the taxes effect due to constant gains realization?
Thanks Leonid, appreciate the kind words!
Capital gains tax is definitely worth considering, but it’s also a highly individual matter, depending on the country you live in.
I have paid subscribers from all over the world, but I always recommend consulting with a local tax expert if you have any doubts, as I only know about the Danish tax system myself.
I've been reading for a while and find the approach genuinely interesting. Combining sector and factor momentum into a single monthly rotation is a clean idea, and you're more transparent about the mechanics than most people selling signals. Credit for that.
Before I allocate seriously to it, four things I'd like to understand:
1. Benchmark construction — is the MSCI World column price return or net total return? Compounding your annual figures gives roughly 3.8% p.a. over the period, which is about two points below MSCI World's actual net total return. If the strategy column includes dividends and the benchmark doesn't, a meaningful slice of the reported alpha would be a measurement artifact.
2. Live vs. backtested — can you break out performance from the date you started publishing signals, separately from the simulated history? An out-of-sample record is the only part that can't be optimised in hindsight.
3. 2008 — the strategy shows -10.24%. Consumer staples, the strongest global sector that year, fell roughly 15-20%. A long-only rotation between sectors and factors shouldn't be able to beat its own best available holding, so I assume there's a cash or moving-average filter in the model. Could you describe it?
4. Investability pre-2013 — most of the major factor ETFs didn't launch until 2012-13, and several factor indices were backfilled. How much of the 2000-2012 record is simulated on index data rather than tradeable instruments, and does it account for spreads and TERs?
Not trying to be difficult — these are the questions I'd ask any manager, and clear answers would make me more confident rather than less. Thanks.
Thanks for the kind words, I appreciate it!
Let me try to answer your questions:
1. The data I used to build this was based on price returns, so I decided to stick with this for all data to make a fair apples-to-apples comparison. You're right that net totals are higher. This applies to the benchmarks as well as the strategy returns.
2. Fully agree, the out of sample data is the most important part. I displayed a chart for this in my latest article here: https://www.marketfighter.com/p/i-switched-my-strategy-to-usd-and
Performance since I started publishing on Substack in March can be found here:
https://www.marketfighter.com/p/performance-update-august-2026
3. Yes, there's a drawdown protection layer, also based on relative price momentum. I have tested this part on data back to 1871, and it kicked in last time in 2008-2009. It is described in this article.
4. It's not based on specific ETF implementations as they vary across the globe. It's based on the underlying indices and not accounting for spreads, TERs, or taxes, as all of this varies upon execution.
I hope this answered your questions :)
Great article, one follow-up
MTUM/VLUE/QUAL/SIZE launched around 2013, How are you able to get pre 2013 behavior?
Thanks 🙏 Those are US-listed ETF representations. My data is based on the underlying indices, most of which date back to the 90s :)
Thanks for the article, and the effort. Looks like it will pay back the time you have put in. For investors in Spain, there is a deferred tax mechanism that consists in the use of investment funds, in lieu of etfs, as there is a tax provision that lets investors transfer funds directly between investment funds without any tax withholding. Taxes are due when you redeem the funds for the investment fund. I guess the answer is no if it’s of no use for the majority but, have you backtested the method with investment funds that can be comparable to the etfs you’ve used? Of course bigger costs but also less taxes would need to be factored in to be able to compare apples to apples.
That sounds like an attractive deal with the funds! As you guessed, I haven't backtested this. Most funds are actively managed, which means you can't really use their historical track record for anything, and I would never use them for systematic trading.
If you have access to passive index funds that track the same or similar indices, then it's a different story. As long as their fees are not exorbitant, I would definitely go for that solution. Feel free to send me a DM if you want to pursue this.
Great article and I love the simplicity of the strategy. I have noticed that the MSCI World annual performance figures on your Distribution of Returns table are not accurate. Most years are either too high or too low. MSCI World returned 21% in 2025 for example, 15% more than your figure. I just wondered where this error came from?
Thanks, I’m glad you like it!
My guess is you compared with MSCI World in USD? 😉 All the numbers I provide are in EUR. It’s not an error, it’s simply the MSCI World Index in EUR. If you live in the US or in any country with another currency, you will see fluctuations matching the currency movements :)
Good work, look forward to studying it further. I have been testing a similar approach but only once every three months and not thought through sector-wise as systematically as you have done. Kudos. That said, would like to see comparison equity curves between the major US indices such as Russell, NQ, ES, not just the World Index.
Thank you for the kind words!
I'm actually planning on a US-specific article some time in August, as other US-based subscribers have requested more US-specific content. Then I will look more into this.
Maybe you already noticed, but I included S&P 500 for comparison in some of the charts in this article 😊
Hi, have you posted the drawdown of the strategy anywhere?
Hi! You can find some more detailed return data in my latest post here: https://www.marketfighter.com/p/behind-the-scenes-of-a-502-excess
Really enjoyed this — the honesty about your 15-year journey before finding what actually worked is refreshing. Most people only share the wins.
The psychological point resonates deeply: knowing a factor works over 20 years means nothing if you capitulate during a 3-year drawdown. That's where most retail investors (and honestly, some institutional ones too) fall apart.
As a former institutional portfolio manager, I used sector dispersion within the S&P 500 extensively - and during periods like the COVID crash, exploiting those gaps allowed me to generate meaningful outperformance for my clients' portfolios.
Curious -when you're rotating between ETFs, how do you handle sectors where the factor signal conflicts with the macro backdrop? For example, Value has screamed "buy" on certain Financials for years, yet macro headwinds kept suppressing returns. Do you follow the signal mechanically, or is there a qualitative override in your system?
Thanks, I appreciate your comments!
The system is entirely based on monthly price levels and the relative momentum of these. It does not take macro backdrop, fundamental data, personal opinions, emotions or any other qualitative parameters into account.
Eliminating all of this noise and emotions and simply relying on the academically proved factors of excess returns is what has caused the results you see :-)
Thanks for the article. As a fellow computer scientist I loved reading this and your approach. I've downloaded the stock data for the last few years, calculating all the technicals for each stock and running various queries with a view to something similar in an individual sock basis, but your approach is so elegantly simple (appreciate the work to get there wasn't!). Will definitely give this a try.
Thanks, I really appreciate your comment! I've been down that road with individual stocks as well, attempting to build a similar system, but I didn't manage to find the same consistency as I did with the ETF setup. It was too volatile for me :-)
The quality factor section resonates most. The reason quality outperforms over long periods isn't random. It's because businesses with high ROIC and consistent profitability have structural advantages that compound the same way the returns do.
The psychological challenge you describe is real. Most investors abandon quality factor strategies during underperformance because they don't understand why quality works. The fundamentals tell you why.
That's what makes it possible to hold through the difficult periods.
Factor investing is academically credible and practically humbling. Value was dead for a decade. Momentum crashes violently. Low volatility underperformed in the longest bull run in history. The factors work — on a timeline most investors can't emotionally survive.
Action: Look up the maximum drawdown and longest underperformance period for each factor cited — then decide honestly if your patience actually matches the strategy's requirements
Exactly. Investing in individual factors is practically impossible to hold on to during the inevitable bad periods. That's what my strategy aims to solve by rotating into the recently strongest factor and abandon the rest. But you are absolutely right regarding the use of individual factors.