Navel gazing Alert: How to improve my investment process by incorporating “Momentum”
Management summary:
“Navel gazing” alert: This post doesn’t contain any actionable investment ideas but rather explores how I can enrich my own investment process in the future by incoprorating some measures of Stock price and fundamental momentum.
Excursion: My secret hobby
First I have to admit that for a few months now, I do have a secret hobby: I am watching on a regular basis a Wikifolio (Wikifolio is a German/Austrian platform where everyone can set up a “fund” and other investors can participate) from an Austrian trader with the name Richard “”Ritschy” Dobensberger.
Not only has he managed to attract 160 mn EUR in investments into his portfolio but he has averaged 33% CAGR over the last 13 years, resulting in an overall performance of around 4000% which is really really remarkable and puts him into the top of any trader I know.
Ritschy’s strategy is relatively simple: He has a universe of a few dozen well known, relatively volatile/high beta stocks and buys them when they seem go up. If they continue to go up, he keeps them or even adds, if they go down he sells them extremely disciplined.
Once in a Podcast he said something along the lines: “It’s like in football. A football coach selects the players that are currently in great shape, not the ones who are out of shape”.
Not every trade works, but those that work well (like Rheinmetall) move the portfolio big time.
To give Ritschy some credit, although it sounds simple, it is clearly not that easy to execute, but it clearly shows one thing: Momentum as a factor works quite well, especially since around Covid.
Don’t worry, I won’t turn into a momentum investor anytime soon because I think I don’t have the mental set up to run such a strategy, but I think I have ignored stock price momentum in my investment process for too long.
Ignoring momentum so far despite some noble intents
For the longest path of my career I have either ignored momentum or actually invested against (negative) momentum. In the past, this has overall worked quite well, but I think I left a lot of return on the way.
I had pondered introducing momentum into my investing process several times. Here for instance is a dedicated post from 2012 (13 years ago !!!).
This was my summary back then:
That was a decent insight, but unfortunately I never followed up. I rather did the opposite, such as documented in this post from 2016:
So after pondering that I was always selling too early, I sold the GTT position which became a multi-bagger (~5x) and reinvested into a stock that turned out to be a value trap.
Why didn’t I follow up on it ? To be honest, I do not know for sure but the main reason is most likely that I outperformed my benchmark anyway for another 6 years until 2019. Why change a system that works ?
However, including 2025 YTD, I have now underperformed in 4 out of the last 7 years.
The current market seems to be extremely momentum driven, which clearly is one factor of the recent underperformance of my portfolio as I have ignored it maybe for too long.
Weaknesses in my current process:
Looking at my more recent actions, I identified the following issues:
- risk of ending up in value traps
- adding mostly to positions on the way down
- not adding to position that work well
- selling too early
- wrong prioritization of watchlist by only focusing on “cheapness based on historic numbers)
- missing out on a diversification angle
.
What does academia / statistics say
There is a lot of evidence that momentum is a strong “factor” in explaining stock returns and especially “alpha”. i.e. positive outperformance.
Here is a summary table generated form ChatGPT when I asked about the 10 most important studies:
What measure exactly is usually used as a proxy for momentum ?
The “Quant literature” usually mentions 6 month or 12 month momentum, often in the form of “6 month -1 momentum” or “12 month -1 momentum” which excludes the most recent month, i.e. looking at the 6 or 12 Month performance 1 month ago.
Why is this ? It seems that the most recent month is statistically “noise” or even negatively correlated with subsequent stock returns. So ignoring the returns of the last month in determining momentum seems to improve results in these studies.
There was a recent interesting post on Klement on Investing that showed that using both time periods, i.e. 6 & 12 months momentum seem to be even better.
Depending on the study, positive momentum is then confirmed if the 6M or 12M price return is either positive or positive AND greater than the risk free rate of return. Most studies than invest into the best decile momentum stocks and short the bottom decile of the stocks with the worst momentum.
Time horizons
Typical momentum strategies require quite frequent rebalancing in order to achieve their alpha, which is clearly not my goal.
Under German Tax law, frequently realizing gains is also not the best strategy to maximise after tax returns. This aspect is often not covered in academic studies.
To be honest, even if a mechanical system would yield better results, I still enjoy being a stock picker and I am actually prepared to sacrifice some performance for the joy of analyzing single companies.
Nevertheless I think I can improve my process by including some aspects of stock price momentum.
How to include stock price momentum into my investment process going forward
As mentioned in my Q2 Performance review, I want to include stock price momentum on a more systematic basis into my investment process.
My main tool for this is a spreadsheet which around ~100 most interesting stocks (including all my portfolio holdings) that I will compare to each other based on quality (measured by some criteria), valuation (i.e. discount to my “fair value) and momentum.
The factors quality and valuation can reach a maximum of 14 points. Momentum gets accounted for in the following way:
I defined a momentum score that will be added to or subtracted from the total score.. The Momentum Score can go from -2 to +2 in increments of 1.
As a first step, I will assign a score of +1 if the 6-1 month performance is >5%, -1 if performance is <-5%, else 0
In a second step, I will add +1 if the 12-1 month performance is >5%, -1 if <5%, else zero.
So depending on momentum, a stock can get a max of +2 added or max -2 deducted. This score is clearly not based on rigorous back testing, it is more a kind of “gut feeling” and it serves one main purpose:
Assuming that all other aspects are equal (Quality, valuation) I will prioritize higher momentum stocks to lower momentum stocks. This applies to both, stocks I want to analyze more deeply and stocks I want to add to or that I want to sell for increasing liquidity.
Fundamental momentum
In addition, I also reflect the fundamental momentum in my qualitative score. I will give a point if the last observable EPS number went up, zero points otherwise (no negative values here).
This is how it looks in practice:
This is an abbreviated snapshot form my sheet that shows how this works in principles with just my portfolio companies:
I do not use this sheet to slavishly follow the ranking but rather as a starting point for further analysis. For instance, some people asked me if I would add to TFF. If I look at my model, adding to TFF is clearly not my top priority. Rather the opposite.
GESCO for instance doesn’t score that well at the moment, but I see some potential for future improvement. But still, I sized the position small as the score is not that good.
But I also would still add (cautiously) to a negative momentum stock like Novo Nordisk if quality and valuation seem to be attractive enough.
Am I 100% sure if this will improve my (relative) results ? I do not know, but I do think that adding this additional perspective could help me in the mid- to long term.
What ChatGPT thinks of my approach
I uploaded this document to ChatGPT (5) and asked it what it thinks about my approach. This is the result:
The overlay strategy that it suggested in the subsequent step however is too complicated for my simple stock picker mind. But the criticism as such is clearly valid.
Therefore I asked it for a simpler set of rules manage the issues which it provided:
To be honest, I found these rules quite helpful and will try to implement them going forward as well as it mirrors my own thinking quite nicely.
When asked about the risks of adding a momentum overlay to fundamental stock picking however, ChatGPT came up with a few points that are also worth considering:
Final thought:
While I don’t like to use LLM’s to create content, I find the conversation with these models often helpful if I ask them about the opposite case or risks. This really enriches an article in my opinion.
To be continued…..
value and opportunity 
I don’t know how it happened, probably the luck of the innocent unpretentious amateur investor, but this year I am up 28% YTD. I wonder how „smart“ investors have miserable performances, and simple joe’s like me had 28%. And no crypto involved, as I am not into religions or faiths…
Congratulations. May I ask how your portfolio looks like ?
It is a no brainer: Alphabet, Allianz, ASRNL, Amazon and Microsoft. These gave 20%. Remaining 8% comes from two traditional businesses (IT/CAN) that I am still builfing positions and can’t disclose. And thinking to rebalance half my insurers to another chip (undisclosed).
Congrats. Now what is your 15 and 30 year performance p.a. ?
I only have a 12 y track record, 11.4% pa.
Looking at the list of stocks, your portfolio at year end 2024 must have looked different. Alphabet and Amazon for instance are up a lot less less than 20% YTD in EUR terms.
When I want to discuss my portfolio, I value more the opinion of my building’s albanian janitor than that of ChatGPT. Or is he Kosovar ? Can’t remember….
Same here. My janitor is from Bangladesh, and his investment insights definitely better than the V&O automata.
Just answer me this question: why do you waste your time here ?
I really like this blog…
[Comment slightly adjusted by blog owner]
This is probably one of the best posts on investing I have read this year. Thanks! It also focuses on some mistakes that I have made repeatedly. Personally I think that adding points to the quality- and valuation-rating makes a lot of sense. It seems that a “buy the dip” strategy for companies that generally meet your criteria could be mad more difficult (neg. momentum) at least if the “dip” lasts longer than one month or the recovery is not very quick.
The “simple momentum rules” are probably quite helpful, because they point to issues, that you already had to deal with (no falling knife, letting winners run, concentration in negative momentum etc.) anyways. So rules over instinct.
It might mean extra work on the watchlist, because this probably needs to be even larger to end up with candidates that either improve operationally and stay cheap (but not negative!) over 12 months, or that have brief “crash” with a very quick recovery so you stay above the 6-1 momentum line and don´t end up trimming after just buying.
Check also his Gain History, a very very huge amount of his gains comes frome Tesla, Moderna and Rheinmetall.
A gain is a gain I would say.
My Point is based on a single stock strategy (or very few) the variance is huge, there will always one guy who picks a 100 Bagger…
I followed a very well known german youtuber „Unge“ and he made a video showing his portfolio ( he is a gaming youtuber). He bought 100% Tesla because he loved the car, he sold right at the top and bought TESLA 2013 sold in 2018 made 1000% and bought beyond meat and made 400%.
I if you had Tesla with 10%+ in your portfolio your performance is insane.
Performance is impressive. I followed a german youtuber „Unge“ (Gaming), he showed his portfolio a few years ago. Went more or less allin with Tesla in 2013, sold with perfect timing around 2018 1400% Profit… Bought Beyound Meat and sold at peak 400%, went big into Tesla again…
Regarding performance he would be even better than Ridschy.
My point is, in a very small stock basket 1-4 variance is insane. There will always be a few guys out of 1000 who did everything right…
I guess every portfolio with at 10%+ Tesla the last ten years will outperform you like this.
I doubt he can repeat that story in his fund.
Very good point. I had not thought of that at first myself. The outperformance can simply be explained by statistical probability. Of course, it is very low for such a case, but in the sea of wikifolios and losers, one of them has reached a lottery prize.
This explanation is more compelling than Ridschy’s expertise or technique.
This seems to me a very good and pragmatic approach to incorporating a momentum factor into a value strategy. I have personally learned my lesson. I often sold the well-performing stocks too early and then, with a new investment idea, bought right at the falling knife. Looking back on my investments over the past years, I believe that consistently applying momentum checks at purchase and sale would have significantly improved my returns. Thanks for the excellent, well-founded contribution! One practical question: Do the 6-1 or 12-1 values have to be calculated by oneself? Or can they be found somewhere?
Thanks for the comment. I do calculate the numbers myself, not sure if there is a service where you can calculate this.
I use Koyfin. There, you can easily create your own formulas, so you can have a 6-1 or 12-1 column for your watchlist.
Very nice post and thought provoking… In particular I liked the short mentioning of:
>AND greater than the risk free rate of return
I do not remember having read that in the past although it should be a “no brainer” to check for. Maybe it was not mentioned anymore because of the low interest environment. But for the time being you might as well look at it to get an idea of the extra return above the risk free rate of return.
Curious if you can provide an example calc (maybe even use a company with the actual data?)
A few quetions:
A few questions again, like you did for the AI scorecard example, it would be great to see 1-2 “worked out” examples with the calcs. Especially if you look at total return? And absolute return only vs. relative return to market? If if amount of outperformance matters vs. only the sign?
Another question: the most recent/current month of performance is ignored in the analysis correct? What happens if a stock falls 25% on an earnings print? Do you “ignore” that and still purchase or add if the 6/12 month momentum (as measured) is still positive? Or do you acknowledge that the 25% decline will kick it out of the momentum bucket in a month?
Hi, i will do an example in a later post. But I keep things really simple. Only price performance and I compare only with a “hard” 5% minimum.
It is also important that this does not constituate an automatic trading algorythm. I just use it as a starting point. With regard to the -25% drop: I would try to understand where that comes from. According to literature, for the last monht, momentum is negatively correllated with the 1 month return. So a company with very good longer term momentum and negrativ 1M returns could be interesting if the other factors are positive as well.
This is a great article that helps delineate where momentum investing fits in the whole quantitative space. https://atstradingsolutions.com/built-for-purpose-why-every-trend-follower-has-a-different-mission/
Ritschy now gets his own investment fund!
There is a great line up of fund managers that started with a Wikifolio. I think of Mr. Spang (great value destroyer) and Mr. Haas (great value destroyer). Welcome Ritschy to the club!
Ritchy staid humble and did not start a fund……
https://www.fundview.de/posts/2025/08/2025-08-06-galerie-exklusiv-wikifolio-startet-eigenen-fonds-future-fundstars.html Of course he does.
Didn’t know that. Thank you.
The performance of Mr. Spangs Fond is not so great to be friendly. One hit wonder.