Introduction

While the list of ideas with links to the latest articles for each is contained within the overall Idea Tracking page, a subscriber's question made me realize that this may not be the most convenient way to discover which investment opportunities or special situations have been covered in the past. The list below is the exhaustive set with links to the very first thesis and the latest update for each. This allows you to jump straight to the current status, though you can still daisy-chain backwards through previous updates if you prefer.

The Idea Inventory

The columns “Junior E&P”, “Special Situation”, and “Active” are boolean (i.e., 1=True, 0=False) and may help your browsing. I myself use them for performance analytics for the different categories.

TL;DR

Two years and 34 tracked ideas in, this review assesses whether my fundamental research process adds value — and where it falls short.

• The median idea reached a peak gain of over 40% since publication, with 20% becoming true multibaggers and another 30% approaching that threshold.

• Drawdowns were meaningful but asymmetric: the median idea declined ~20% at most, indicating a favorable skew.

• Current returns are far lower than peak returns, highlighting a structural reality of microcaps: value is often realized in bursts rather than through passive holding.

• Separating junior resource stocks from cash-flowing businesses does not appear to materially change the odds of identifying multibaggers, though it increases downside volatility.

• The primary opportunity for improvement lies not in idea generation, but in lifecycle and risk management after re-rating.

• To protect the integrity of the entry prices for my supporters, specific microcap ticker reveals will move behind the paywall in 2026.

These findings suggest that the research process is effective at identifying mispriced securities, while also underscoring the need for disciplined exit frameworks to preserve gains.

Introduction

This is my post of introspection for the second year of this Substack.

Granted, the first (general) post was already around Christmas of 2023, but the first company write-up idea was posted in the first days of 2024. This post is about three main things

1. Investigate the track record, now two years, of the blog’s ideas. As time progresses, this should help separate luck from skill.

2. Obviously, I hope to attract paying subscribers.

3. Deduce several conclusions and lessons, particularly on the portfolio management side, which is not part of the blog, but even more important to my own fortunes.

I track the performance statistics of published ideas via a Google Spreadsheet and use Datawrapper to provide up-to-date visualizations on the following page:

To discuss this post, I took a snapshot as of today, December 30, 2025, at 12:30 German time (not that it matters too much for the aggregate statistics).

I focus on the Total Shareholder Return statistics (i.e. dividends are added back) of when a company’s first article appeared on the blog until today (or the day when I announced stopping coverage). I focus mostly on the descriptive statistics, particularly the median of the Low, High, and Current Return. This way, the impact of outliers is minimized, which is what I want: are my write-ups not just time-consuming but actually providing genuine value?

Further, I segregate the more risky junior mining stocks from the “normal”, i.e. cash-flowing businesses.

I also segregate the write-ups by age cohorts, with the underlying intention to see if my aspiration to find good cash-flowing companies (whose friend is time, according to Buffett) is actually being met. If so, the returns in older cohorts should be higher than in younger ones, assuming the stock market is at least semi-efficient.

How do I handle stopped ideas? I freeze the return statistics since the time of publication on the day I stop the idea. This means two things:

1. Stopped ideas will still impact the statistics in the future, which I believe is as transparent as I can be, but

2. Their impact on the statistics will diminish as I publish additional ideas.

This analysis is not free from limitations. I exercise discretion in defining when coverage stops, in excluding ideas where I felt the work was insufficient, and in classifying companies as “junior” or “conventional.” While I attempt to minimize bias by freezing returns at the time coverage stops and by focusing on medians rather than means, these choices necessarily reflect judgment calls. The results should therefore be interpreted as indicative rather than definitive proof of skill.

General Observations

Google Sheet / Datawrapper issues: I have noticed that sometimes Google Sheet takes its time to update all the stock data. I speculate that this seems to throw the Datawrapper visualizations off when one accesses the tracking page, which is annoying. My own workaround is to first go to the raw data Google sheet, then “republish” the charts in Datawrapper, and finally access the live page. I am not sure if someone has encountered the same issue and knows a workaround, but for the time being, this is what it is.

Running the Substack is hugely rewarding: several posts received great feedback, particularly the free, more general ones. This is more rewarding than I originally thought. The free but investment process-oriented ones attract appreciation, but less feedback/enhancements, it seems. Which I am okay with, of course. Finally, this year I received kind suggestions for companies to seek out, which I appreciate, and one actually made it to write-up level and portfolio position.

Posting reasons why not to invest in a company hurts people’s feelings: Curiously, I was called nitpicky by a free subscriber whom I kindly shared my (paywalled) corporate governance concerns with, which may or may not come to bear in the future (I sure hope not, as I do not wish ill fortune on others). Let me, with all due respect, suggest: investors really should not feel attacked if someone else highlights a fact (as opposed to something misconstrued as in some short reports these days) and chooses to exit or not to invest in your favorite microcap due to that. It may just be a difference of opinion, risk tolerance, time frame, and independence of opinions is what makes a market. Along a similar vein, I received the irritating comment on X that selling a position at a loss (Cardlytics) makes only sense in tax loss season… well, to each their own.

Having standards can hurt performance (temporarily): Sometimes, having principles is expensive. I was tracking STSS and identified it as a potential multi-bagger. However, a governance maneuver regarding special voting rights for the CEO crossed my red line. Essentially, nanocap pulled what I believe is probably a legal but still kicking minority shareholder rights in the teeth:

I walked away. The stock subsequently tripled.

For me, there are two lessons in the above Yahoo Finance chart: While it hurts to see a +200% gain missed on the chart, this is a cost of doing business, and I am glad I did not suffer the 60% drawdown compared to when I posted the note. This solidifies that I would rather miss a winner than tolerate a management team that kicks minority shareholders in the teeth. Process over outcome.

Thoughts on Lifecycle Management: While I do not offer trading alerts, the divergence between the ‘Highs’ and ‘Current’ returns compels me to share how I intend to manage my own portfolio in 2026. The ‘Buy and Hold’ strategy works for compounding giants, but for the volatile and sometimes vulnerable microcaps I often cover, the data suggests we must be better at harvesting the crop we planted.

It is therefore important to distinguish between entry skill and exit strategy. This article primarily evaluates whether the research identifies mispriced securities, not whether a specific holding or trimming rule maximizes realized returns. The large gap between peak and current returns suggests that while entry selection is sound, portfolio management choices materially influence outcomes.

While I do not consider myself a technical analyst, the data suggests that some form of systematic de-risking may be beneficial after sharp re-ratings. One framework I am exploring for my own portfolio is a simple “weekly low” rule: when a stock that has appreciated strongly closes a Friday below the prior week’s low, it may indicate that the re-rating phase has ended. Note, I have not tested this rule systematically yet, and it may fail in both directions.

This is not presented as a prescription, but as a hypothesis informed by observed behavior in past ideas; it is an attempt to preserve asymmetry without prematurely capping upside.

The Statistics

High Level: Number of Articles, Idea Frequency, There Be Multibaggers?

I published a total of 233 articles and some Chats for brief company updates, and have 700+ subscribers (I pruned some inactive ones along the way). That’s more than two articles per week since starting the blog.

I track a total of 34 ideas (i.e. 17 per year, or roughly 1.5 per month), including five risky juniors, that were published and deemed tracked. From a performance perspective, it is unfortunate that I had decided to exclude $BABA and $HRBR stocks, but I felt I did not do too much work on them. And to be fair, I also excluded $ZOMD.V due to the governance concerns I mentioned above, and so far this has been good to me.

In the above snapshot, I focus on the stock highs since publication, and I defined

• Multibagger = since the initial post, the stock had a high, representing a gain of at least 100%

• “Almost Multibagger” = since the initial post, the stock had a high, representing a gain of at least 80%.

The insights over these two years are twofold. First, Approximately 20% of ideas reached multibagger territory at some point after publication. And second, surprisingly, excluding the riskier junior E&P companies does not change the statistics. I am as good or bad with juniors as with overall business ideas, at least from this perspective.

Teasing out the Value Add

The following shows a side-by-side comparison of the company write-ups’ descriptive statistics since the start of the blog. Left is all ideas, right is excluding junior companies, i.e., the cash flowing businesses, not the “lottery tickets”.

To answer whether this research is adding value, I focus on the Median High1, and, to a lesser extent, on the Median Low. I define my job as identifying mispriced companies before the market does. The ‘High’ metric tracks whether the market eventually, possibly only transitorily, agreed with my thesis. The ‘Low’ acts as an indicator of the chance and severity of drawdowns. Finally, since this newsletter provides ideas rather than active portfolio management, the ‘Current’ return assumes a passive ‘hold forever’ strategy, unless I explicitly stop an idea.

1. The Validation (The Highs): Since publication, the median investment idea rallied 41.3% at its peak. With 20% of ideas becoming true multi-baggers, the data suggests that the ‘Entry’ part of the equation—finding the value—is sound.

2. The Validation (The Lows): Since publication, the median investment idea fell 20% (or less) at its trough. The data suggests an asymmetric skew of published ideas to the upside.

3. The Reality of Microcaps (The Current): The median current return is significantly lower (roughly +2% to +5%, depending on the exclusion of juniors). This disparity highlights a structural reality of small-cap investing: Value is often realized in bursts, and you need to be active to lock in some of the gains.

Since publication:

1. The median high exceeds 40%. This means half of my investment ideas gained more than 40%. Even the first quartile of the highs is 20%, i.e. 75% of ideas at least reach a 20% gain.

2. At the same time, half of the stock ideas had a drawdown of -20% at most (and less than that when excluding the juniors). The first quartile of the lows suggests that there are 25% of ideas that see very painful drawdowns in excess of -25% or -30% (right vs left chart).

3. Over the entirety of published ideas since the start of 2024, the first quartile High is about 20% for both populations. That means three-quarters of ideas exceeded a 20% return at some point. This is remarkable as at the same time, the Russell 2000 increased by 29%. There is a really high chance that 50%-75% of the stock ideas I published exceeded the two-year buy-and-hold return of what I consider a reasonable benchmark.

   

4. The current return median is positive, but much lower than the high.

5. The means of the highs and of the current returns are much higher than the respective medians; thus, there are outperformers skewing the distribution. This also demonstrates the well-known fact that investing is skewed to the upside.

While a two-year performance is not yet really a long-term track record, I would say that there is a genuine value add from my stock picks. Particularly, when you consider that it is commonly said that in investing, you need only to be right less than 50% of the time because the upside is typically unlimited and the downside is capped at zero (if you diversify), I am pretty happy with the medians, as the high and low medians imply that my picks are strongly skewed to the upside and present subscribers with the opportunity to diversify into my picks and possibly lock in gains along the way.

One implication of the strong positive skew in these results is that entry price matters disproportionately. Because a minority of ideas drive a majority of outcomes (the returns are power law-distributed), unrestricted ticker disclosure allows readers to benefit from the research without bearing any of the cost, while potentially even degrading entry conditions for others (although my readership is still small).

For that reason, and to align incentives between readers and research effort, new microcap ticker reveals will move behind the paywall in 2026. This is not a claim that paid subscribers will outperform, but rather an attempt to preserve the integrity of the idea-generation process and reward those who fund the work.

Is Time a Friend?

If the companies I pick are good companies, based on my assumption of the weak market efficiency hypothesis, the market should reward them over time with higher share prices as they execute. To investigate this, I created four age cohorts of the ideas (excluding the juniors, thus called “conventional”), strictly on days elapsed since publication. As I freeze the return statistics when I stop following an idea, I also freeze its age. The following shows the age distribution of age quartiles (where A=cohort 4, D= cohort 1):

The following charts show the statistics from youngest (D, cohort 1) to oldest (A, cohort 4):

• Particularly when analyzing the Highs, there is a nice validation of my thesis: the cohorts’ statistics get better with increasing age. Admittedly, the current return medians for cohorts 2 (C) and 3 (B) are counterintuitive when compared to cohort 1. Also, the median of the cohort 1 Highs outperforms cohort 2, but this can also be due to a short-term event that I reacted to when writing up the recent stocks.

• In the spirit of my argument in the previous, more general section: The medians of the Highs and Lows show a strong (and increasing) skewedness in favor of investors (despite the fact that an increase in time also increases the amount of time a stock can mark a new low).

• I am pleasantly surprised that three of my four cohorts show a first-quartile current return of -3.3%, -8.1%, and -2.1%. This means that of each of these cohorts, 75% of stocks are currently less than 10% down (even after just undergoing tax loss season). Differently put: far more likely than not, the stock picks of these cohorts are at least about break-even, or, more likely, in positive territory.

• Analyzing the stocks in cohort 2, my worst-performing cohort of age 169-249 in days (i.e. still less than one year old; also note that the first quartile of the Highs shows that 75% of this cohort actually reached a high of over 20%) shows me:

  • Two of these companies are not microcaps (Idea 21: IWG, and Idea 25: DEC), both of which I am not concerned about the near term price movements

  • On one idea, I acted on a bold CEO statement, but I believe the company might actually accelerate its growth again.

  • For another idea, I did a misinterpretation regarding the CEO’s SBC package being suspended, but the overall prospects should still be good. However, I scaled back my investment a bit due to my misinterpretation.

  • A nanocap that just needs more time to gain from the defense industry’s tailwinds and its recent diversification.

  • And the final non-junior microcap in that cohort is GlobalX, which depends on airplane delivery (with the exact timing beyond their immediate control), and sometimes weather conditions. I am not concerned about the overall prospects and acknowledge that microcap investor Bruce Galloway recently increased his stake.

The Stopped Ideas

• OCI NV, as the company intends to be acquired and relisted in a stock exchange, which my broker does not support

• Cardlytics, as the thesis was broken, at least for the time being

• EMERGE Commerce after a nice, quick gain because the overall social media sentiment surrounding this stock is very bullish, and I still have no clarification on some of my questions regarding the fundamentals.

The Winners (so far)

Overall, the blog saw some huge winners (at their highs)

• Idea 10: PharmX Technologies Ltd, published already last year, reached this year a high of +300%

• Idea 27: SenSen Networks Ltd, published this year, saw a gain of +225%, despite my initial skepticism

• Idea 24: Brazilian Iron Ore Play, published this year, reached a gain of +357%

That means, and this circles back to the first chart, that of the seven multibaggers of this blog, there were a 3-bagger, a 4-bagger, and a 4.5-bagger. The remainder were nice doubles at their highs:

• Idea 3: Rave Restaurant Group Inc

• Idea 4: nano-cap SaaS Gem (pulled back significantly in recent months)

• Idea 8: OCI NV (stopped, see above)

• Idea 11: Garrett Motion Inc

Importantly, for each of the winners (except for the stopped OCI), I believe the respective thesis is still intact. Of course, I am biased and could be fooling myself by hanging on to stocks that (rightfully) retraced from their highs.

Conclusions

The original intent of this Substack was to slow down my own investment process and improve the quality of my fundamental work. Two years of data suggest that this goal is being met, with the important caveat that the sample size remains limited and the time horizon short.

The dominant takeaway is that the research process appears effective at identifying securities that the market later re-rates, often sharply but unevenly. The primary challenge is not idea generation, but lifecycle management: harvesting gains without sacrificing the asymmetric upside that defines successful microcap investing.

Governance standards, while occasionally costly in foregone upside, remain non-negotiable for me. I accept the missed upside as the cost of avoiding governance structures that historically lead to an increased risk of permanent capital impairment.

Writing publicly has sharpened my thinking, exposed blind spots, and generated feedback of a quality I did not anticipate. The discussions and exchanges with readers have meaningfully improved both my process and my enjoyment of investing.

Going into 2026, my focus will be on refining risk-management frameworks while continuing to publish deep, fundamentals-driven research. I welcome thoughtful input, especially on exit discipline in small- and microcap investing, and I thank all readers, free and paid alike, for engaging with the work. For free readers interested in the full company write-ups and ongoing tracking, please consider upgrading to a paid subscription.

Introduction

I do not spend too much time tracking performance and do not like the ritualized performance check on certain dates (recently, the cadence has switched to monthly, it seems). I am ambivalent about this, because…

• At best, I am more right than wrong. But that may create hubris and overconfidence on my side (bad for future performance) and establish me as an authority (bad for the readers who blindly take in what an authority opines). Moreover, as I aspire to be more of a long-term investor (or speculator), it will take time for my ideas to play out - with approximately 21 months since positing the first idea on this blog, this can hardly be considered a long-term track record.

• I do think one should honestly check the published ideas and theses, and also track performance somewhat loosely to assess where and how to approve.

Hence, I established the live tracking page, where anyone can check the performance and not rely on stale snapshots over time:

Performance

Looking at the live-tracked performance of posted ideas today (a random day since posting the first idea in January 2024) shows:

28 ideas posted, including 5 junior resource E&P (Exploration & Production) companies that are inherently riskier.

Historical Chances of Multi-bagging

I define an idea as

• a multi-bagger, if it achieved a total return high of +100% or more since the date of the initial post;

• an “almost” multi-bagger, if its high was in excess of +80%.

Interestingly, the same share of ideas multi-bagged when comparing the ideas with and without the junior resource companies: 17-18%. The share of “almost” multi-baggers is roughly one-third for both populations.

Of course, it is hard to know when to exit…

Current Returns of Ideas (ex-junior E&P), Overall

I exclude the junior E&P companies as they are not cash-generative businesses and thus more volatile and inherently more risky. Ultimately, junior E&P ideas will only be a small fraction of the over ideas on this Substack.

Overall, the median current return of +5.9% is satisfactory in that 50% of stock ideas gained. Thus, if the market gods flipped a coin deciding whether when an idea is posted on this substack, chances are the idea will be a positive.

Current Returns of Ideas (ex-junior E&P), Per Age

Pleasingly, the age cohort statistics support the thesis that time helps good ideas, indicating my focus on cash-generative businesses is sound.

• Oldest quartile: median total current return +46.7%

  

• Second-oldest: median total current return +34.7%

  

• Youngest quartile cohort: median total current return +6.5%

  

However, the second youngest quartile cohort disappoints: median total current return -13.6%. This is caused by ideas between 119 and 331 days of age, i.e. Innovative Food Holdings, Greggs, Covalon, Flow Traders, Cardlytics, and IWG.

• Cardlytics (CDLX) and Innovative Food Holdings (IVFH) are the largest detractors (-73% and -48%),

• Flow traders (+6%) and IWG (+3%) are positive,

• Covalon is at -5%, and Greggs at -22%.

Discussion

Overall, I am pleased. Some multibaggers, positive median return, and the age cohorts mostly behave as they should: better returns over time (and significantly so).

However, the second youngest cohort has issues in that CDLX was an idea that was not earning a profit, and IVFH, while at breakeven, had sizable operating cash outflows.

• For Cardlytics, the mental models I applied painted a bright future, but I should have waited for cash flow or profit inflection. Furthermore, the envisaged catalyst arrived, but had less of an impact than I anticipated. I pulled out of CDLX due to a lack of operational progress on the key metrics, but I have not removed it from idea tracking, so it may serve as a constant warning and detractor to the track record. Over time, with more ideas, the effect will diminish.

• For IVFH, the uplisting catalyst has been postponed, and I am still waiting for the business to gain operational traction. Maybe I am wedded too much to the (admittedly visually improvable) concept art of mine about the acquisition/marketplace flywheel, but if execution kicks in, the idea will turn. Remember, the performance tracker is just that, and so far, I have not removed performance statistics of ideas when I sell out.

Conclusion

This substack is still young, and I am continually expanding my tool belt. Therefore, it is too early for definitive conclusions, and as the investing landscape changes over time, nothing is cast in stone, anyway.

That said, I think this review of performance since inception has been a valuable exercise. The results are encouraging: a positive median return, the emergence of several 'multibaggers,' and data that support the core thesis that good, cash-generative ideas improve with time.

However, the analysis is just as valuable for highlighting weaknesses, such as the underperformance of the second-youngest cohort driven by cash-burning businesses like Cardlytics and Innovative Food Holdings. These instances serve as crucial lessons in patience and the importance of waiting for a clear inflection in cash flow. They are not failures, but rather tuition paid to the market. For IVFH, I am more optimistic that it will turn for the better than for CDLX, but this may be my bias speaking.

Looking ahead, the goal is to continue this process of transparent reflection. The next evolution of this performance tracker may be to distinguish between 'active' and 'inactive' ideas. This would not only show the performance of the active idea portfolio but also preserve the lessons from sold positions, offering a clearer, more complete record. Ultimately, this blog is a journey in public. The performance, with all its successes and setbacks, is part of that journey, and I am committed to sharing it honestly.

Honestly, I am a bit torn about year-end performance posts. The quality of write-ups and analyses should at some point show up in the stock performance, but on the other hand, who knows what time frame. Especially if Mr Market is the maniac depressive that Ben Graham portrayed him to be. Also, “past performance is not a predictor of future returns” as the disclaimer goes… and analysts or bloggers with a good track record will probably establish a sort of authority bias in their readers…

Due to that I have the running post that should do live updates at:

With all that being said, here is a summary statistics snapshot taken right now (December 30, 2024, 12:38 German time). Note that I simply add back dividends to the stock prices seen to get a total return measure.

Aggregate Statistics

The Hi-Low Spread & Current Return

The following provides a snapshot of the trading range of the ideas since posting, sorted by the observed High. Interestingly, the trading ranges of the bottom half (from Wickes and below) are lower than those of the upper half - I am not clear what to make of that.

Discussion & Conclusion

Most ideas were only published during the year, i.e. their age is lower than what I consider a period where the quality of an analysis can truly show itself - unless you consider investing for particular situations, catalysts, or technicals.

That said, figure 3 shows the sobering fact that about half of the 15 ideas are currently in the red. However, I think that the overall current return (including dividends) statistics are satisfactory as the median is 11.6%, see figure 1. Also, note that I cover two junior E&P companies (Canada Nickel and Elixir Energy) without revenues whose future depends on attracting financing/deals (which I believe they will manage to do). Due to these ideas, the median is notably higher than the mean (~8.3%). Both companies are currently in the red detractors and particularly punishing the mean. Furthermore, I still think that Cardlytics has chances to turn to profitability but choosing to publish prior to earnings hurt the statistics instead of waiting until after earnings.1 All in all, had I played it safe and excluded the high-risk posts on companies with no imminent profitability (Cardlytics, Canada Nickel, and Elixir Energy) half of the bottom half of stocks in figure 3 would be removed with a profound impact on the overall statistics. Despite the drag on the performance statistics, I am fine with these three picks - otherwise, I would post that I stop considering these companies.

Looking for multi-baggers in figures 2 I see that one stock that clearly crossed the +100% mark and two stocks that topped at +92%, i.e. that almost doubled.

Finally, looking at the historical high of ideas published in figure 1, probably a profitable trading strategy would be to flip the ideas after say 50% gains (i.e. the median). I have to think more about that, though.

So far so good. Happy New Year.

Disclaimer

I own shares in some of the companies mentioned and stand to benefit if they rise in price. I may decide to purchase or sell shares at any time without prior notice. Do your own research and size positions appropriately if you invest. Nothing here is meant to be understood as investment or financial advice or as a solicitation to purchase or sell securities. Historical performance is not a predictor of future performance.

Introduction

This article uses Datawrapper to track the Investment Opportunities that I write about and Google Sheets to allow up-to-date tracking. For all calculations, I use the ideas’ “native” stock exchange prices and currencies as provided by Google Finance.

Aggregate Statistics: Including and Excluding Junior E&P

The following table provides:

• The current count of ideas per type to provide context to the above and the below, i.e., how many junior ideas are excluded from the age cohorts’ performance statistics, for example.

• The share of total ideas that, since initial publication, exceeded 80% (i.e. “almost a multi-bagger”) or 100% total return.

Next, the aggregate statistics for all published investment opportunities from first publication to when I stop following the idea (none stopped so far).

As junior resource exploration is risky and time-consuming, it affects the overall performance statistics. If I exclude those, the statistics look as follows. Make no mistake, I am still convinced of each of these juniors I picked. But they are naturally more risky and their prices are more volatile due to being exposed to the whims of Mr Market.

Age Cohorts

As I am not necessarily interested in very short-term performance (although I don’t mind good, fast performance), I am interested in the distribution of performance over time. I stratified into four age cohorts: based on the initial articles’ ages, I created four quartiles. This may not be the best way to do it - please feel free to provide suggestions for improvements. Because the number of ideas is still small, the aggregate statistics per cohort are less expressive at the time I introduce these first. As more ideas get added, the statistics’ expressiveness should grow1.

Age Distribution

The following plot shows the age of the initial articles of each of the ideas in chronological order:

Excluding the junior E&P ideas from the analysis, I get the following age quartile limits.

Cohort Performances

From youngest to oldest.

To scorecard my performance, I focus on the Median Current Return. If positive, 50% of my ideas in that cohort to have a positive current return. In addition, if the Current Return third quartile + first quartile value > 0, then all the better. The winners certainly more than offset the detractors. As I aspire to write about ideas that I expect to generate compounding value over time, I expect (at the time of writing this) that older cohorts have higher median values and interquartile performance for Current Return.

Again, I would expect the statistics to become more meaningful as I publish more ideas over time. But so far, my scorecard seems to be going in the right direction: for businesses that are not junior resource E&P, the median return is positive except for the youngest cohort, and the median seems to increase over time. As the number of ideas in each cohort is still limited, expect swings even for the median (which is more robust to strong outliers than the mean) - this should reduce as more ideas make it into my corner of the internet.

Other Interesting Statistics

The following is a visualization of the current % and the high % return since the first publication on the opportunity.2

The next chart visualizes the spread of high % and the low % relative to the first date of publication on the opportunity. In case you wonder why a low % can be above 0: to track total return, I include dividends collected since publication…

And finally, a graph and a table of the raw data for you to peruse, e.g. annualized CAGR, days since publication, links to latest updates, etc.

Please provide feedback in case there are some metrics that I should add to the visualization.

Disclaimer

I own shares in some of the companies mentioned and stand to benefit if they rise in price. I may decide to purchase or sell shares at any time without prior notice. Do your own research and size positions appropriately if you invest. Nothing here is meant to be understood as investment or financial advice or as a solicitation to purchase or sell securities. Historical performance is not a predictor of future performance.

Appendix: EDIT History

• September 2025

  • I noticed that the chart “current % and the high %” was actually showing CAGR vs current. I corrected the figure as CAGRs distort the graph too much for young ideas.

• July 2025:

  • Added a Datawrapper way to provide the numbers discerning between the “normal ideas” and the “juniors”.

  • Added statistics about how many of the total ideas touched a high of 80% and 100%, i.e. that were close to multi-bagging, or even multi-bagged.

• June 2025:

  • I just realized that Datawrapper stops updating charts after 30 days, then one needs to ‘republish’ the charts. Possibly, the data shown in the past was sometimes stale. I will now regularly republish charts to keep this page up to date.

• May 2025:

  • Added a distinction of aggregate performance statistics to separate out speculative junior E&P vs conventional businesses.

  • Structured more clearly via Headlines

  • New subtitle

• December 2024: Fixed a Type-O

• October 2024: I now manually track dividends collected. I do so by simply adding dividends back to the share price High, Low and Current.

• Added Aggregate Statistics Mean, Median, and first and third quartile