Charl Botha retweeted
I think there’s a fundamental assumption here worth challenging: why should machine judgment resemble human judgment in the first place?
Human intuition is, in many respects, an evolutionary workaround for severe cognitive constraints. Limited working memory, finite attention, emotional attachment, confirmation bias and an inability to consistently reason probabilistically.
We seem to assume that the pinnacle of investment decision-making is the judgment of an exceptional human investor. But why should that be the ceiling?
A sufficiently capable AI could simultaneously evaluate thousands of competing hypotheses, continuously update probabilistic beliefs, identify causal relationships and dynamically allocate attention toward information with the highest expected value.
Crucially, it need not inherit the same cognitive limitations that make human judgment so fallible. Of course, machines can develop their own biases, but those need not resemble ours.
And today’s hedge funds are hardly a definitive test of machine intelligence. Most still use sophisticated technology within fundamentally human-designed investment frameworks.
Perhaps we’re asking the wrong question.
Instead of asking whether AI can replicate the intuition of a brilliant portfolio manager, we should ask whether that intuition is simply a computational shortcut developed by an intelligence with severely limited processing capacity.
The real opportunity isn’t to automate human judgment. It’s to discover forms of judgment that human cognition could never achieve.
Human intuition is, in many respects, an evolutionary workaround for severe cognitive constraints. Limited working memory, finite attention, emotional attachment, confirmation bias and an inability to consistently reason probabilistically.
We seem to assume that the pinnacle of investment decision-making is the judgment of an exceptional human investor. But why should that be the ceiling?
A sufficiently capable AI could simultaneously evaluate thousands of competing hypotheses, continuously update probabilistic beliefs, identify causal relationships and dynamically allocate attention toward information with the highest expected value.
Crucially, it need not inherit the same cognitive limitations that make human judgment so fallible. Of course, machines can develop their own biases, but those need not resemble ours.
And today’s hedge funds are hardly a definitive test of machine intelligence. Most still use sophisticated technology within fundamentally human-designed investment frameworks.
Perhaps we’re asking the wrong question.
Instead of asking whether AI can replicate the intuition of a brilliant portfolio manager, we should ask whether that intuition is simply a computational shortcut developed by an intelligence with severely limited processing capacity.
The real opportunity isn’t to automate human judgment. It’s to discover forms of judgment that human cognition could never achieve.
Think about how sophisticated today’s hedge funds have become.
Billions of dollars under management.
PhDs in mathematics, physics and computer science.
Massive data science teams.
Thousands of data feeds.
Alternative data.
Satellite imagery.
Machine learning.
Artificial intelligence.
High-frequency trading.
Thousands of GPUs.
Complex risk-management systems.
They can monitor markets, companies, supply chains and investor behavior at a level that was almost unimaginable 20 years ago.
And yet, some of the most sophisticated investment organizations in the world just suffered enormous losses.
That should make everyone stop and think.
If this level of technology, data and intellectual firepower isn’t enough to consistently produce good investment decisions, what exactly are we building?
The next generation will have even more data, faster computers, more powerful AI agents and increasingly complex models.
But will they have better judgment?
Or will we simply create bigger, faster and more sophisticated versions of the same mistakes?
The future of investing may not belong to whoever has the most data or the most computing power. It may belong to whoever knows what information to ignore.
Technology can process information.
It cannot guarantee wisdom.
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Charl Botha retweeted
This is a fascinating observation @futurewealthP, and I think you’ve identified perhaps the most important challenge in what I’m envisioning.
Connecting thousands of businesses, economic variables, hypotheses and potential causal relationships creates a search space that becomes computationally intractable remarkably quickly.
But I think your point about intuition is particularly interesting.
Perhaps much of what we call human judgement is actually a highly developed mechanism for allocating attention under conditions of extreme uncertainty.
We don’t consciously investigate every possible explanation for an observed outcome. Our intuition directs us towards a small subset of possibilities that seem worth exploring.
In other words, human intelligence doesn’t solve the combinatorial explosion problem through exhaustive reasoning. It solves it, imperfectly, through selective attention.
And perhaps that’s precisely the next frontier for autonomous research systems.
Imagine an interconnected investment knowledge graph where the system doesn’t attempt to investigate every conceivable relationship, but instead continuously estimates where additional research is most likely to improve its understanding or change an investment decision.
It could prioritise hypotheses according to their expected information value, economic materiality, uncertainty, existing evidence and computational cost.
But here’s the part I find particularly exciting.
What if the system could learn not only from the outcomes of its predictions, but from the success or failure of its decisions about where to investigate in the first place?
Then you’re no longer simply building a system that discovers relationships.
You’re building one that learns how to discover relationships more efficiently.
Its research process becomes endogenous and adaptive. An unexpected observation in one industry could trigger an investigation elsewhere, not because someone explicitly programmed that relationship, but because the system has learned that certain patterns of evidence warrant further attention.
Of course, this doesn’t eliminate the search-space problem. It introduces another difficult problem: how to distinguish genuinely promising research directions from attractive but ultimately spurious patterns.
That requires careful treatment of uncertainty, exploration versus exploitation, and the cost of pursuing the wrong hypotheses.
But it does suggest a very different architecture from simply deploying increasingly powerful agents against existing research workflows.
And I think your final philosophical observation is equally important.
If we eventually develop systems that are superior at determining how to achieve a particular objective, then deciding which objectives are worth pursuing becomes increasingly consequential.
In investing, we often treat maximising risk-adjusted returns as an obvious objective. But even that conceals questions about acceptable risk, time horizons, liquidity, externalities and what we’re ultimately trying to achieve with capital.
Optimisation is not the same thing as choosing what is worth optimising.
Perhaps the really interesting transition isn’t simply from human judgement to machine judgement, but from humans being primarily responsible for finding answers towards being increasingly responsible for deciding which questions and outcomes are worth pursuing.
I suspect we’re only beginning to appreciate the implications of that distinction.
Connecting thousands of businesses, economic variables, hypotheses and potential causal relationships creates a search space that becomes computationally intractable remarkably quickly.
But I think your point about intuition is particularly interesting.
Perhaps much of what we call human judgement is actually a highly developed mechanism for allocating attention under conditions of extreme uncertainty.
We don’t consciously investigate every possible explanation for an observed outcome. Our intuition directs us towards a small subset of possibilities that seem worth exploring.
In other words, human intelligence doesn’t solve the combinatorial explosion problem through exhaustive reasoning. It solves it, imperfectly, through selective attention.
And perhaps that’s precisely the next frontier for autonomous research systems.
Imagine an interconnected investment knowledge graph where the system doesn’t attempt to investigate every conceivable relationship, but instead continuously estimates where additional research is most likely to improve its understanding or change an investment decision.
It could prioritise hypotheses according to their expected information value, economic materiality, uncertainty, existing evidence and computational cost.
But here’s the part I find particularly exciting.
What if the system could learn not only from the outcomes of its predictions, but from the success or failure of its decisions about where to investigate in the first place?
Then you’re no longer simply building a system that discovers relationships.
You’re building one that learns how to discover relationships more efficiently.
Its research process becomes endogenous and adaptive. An unexpected observation in one industry could trigger an investigation elsewhere, not because someone explicitly programmed that relationship, but because the system has learned that certain patterns of evidence warrant further attention.
Of course, this doesn’t eliminate the search-space problem. It introduces another difficult problem: how to distinguish genuinely promising research directions from attractive but ultimately spurious patterns.
That requires careful treatment of uncertainty, exploration versus exploitation, and the cost of pursuing the wrong hypotheses.
But it does suggest a very different architecture from simply deploying increasingly powerful agents against existing research workflows.
And I think your final philosophical observation is equally important.
If we eventually develop systems that are superior at determining how to achieve a particular objective, then deciding which objectives are worth pursuing becomes increasingly consequential.
In investing, we often treat maximising risk-adjusted returns as an obvious objective. But even that conceals questions about acceptable risk, time horizons, liquidity, externalities and what we’re ultimately trying to achieve with capital.
Optimisation is not the same thing as choosing what is worth optimising.
Perhaps the really interesting transition isn’t simply from human judgement to machine judgement, but from humans being primarily responsible for finding answers towards being increasingly responsible for deciding which questions and outcomes are worth pursuing.
I suspect we’re only beginning to appreciate the implications of that distinction.
@uncovered_alpha@uncovered_alpha @uncovered_alphaus obstacle I see is combinatorial explosion: even for a super super super computer, the search space will be too large to search without some sort of choosing-where-to-search
Incidentally, this is what I think humans do with our “feelings” or “intuitions”)…these are our indicators of where to jump into the unfathomably large possibility space…This is all - or most - of what I think human judgement is - where to focus attention in the search space and our emotional/valence/hedonic reactions are the pointers or metal detectors if you will of this…what would this look like in AI…I think we are already seeing it…
Im no expert, but once AI agents approach models where they can have a model of where to direct their attention- and learn how to do so based on their vastly superior working memory and analytical resources, its game over for human judgment in terms of making “better”’decisions in arena’s where we aim for the same goal (better risk adjusted investment returns for example)…the most important is that we remain the masters of choosing values - that they are OUR values…
I think society is entering a phase where what used to be rarefied philosophical questions (what is valuable, what is meaning, what is good, etc)…will be much more important for many to work through, for many have built their identity and lives on their differential intellectual or analytical ability…we are entering the age of values and qualities imo (in short: in the trinity of Truth, Beauty, and Goodness, Beauty and Goodness is about to get a much needed positive re-valuation)….
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Charl Botha retweeted
Couldn’t agree more. It strikes me that most AI adoption in finance has focused on automating or accelerating existing workflows, rather than questioning whether those workflows are optimal in the first place.
As an analyst, I understand the appeal of getting to an answer more interesting question is whether AI can help us arrive at fundamentally better answers?
I’ve always been fascinated by the idea of an interconnected investment brain. Something akin to Obsidian, but purpose-built for investing, where companies, industries, themes, mental models, investment hypotheses and evidence exist within a continuously evolving knowledge graph.
I’ve actually started experimenting with a prototype of this concept, which I’m calling Labyrinth.
Imagine discovering something material about one business and being able to trace its implications across an entire network of companies, assumptions and investment theses. Rather than research existing in isolated notes, PDFs and spreadsheets, knowledge becomes interconnected, cumulative and increasingly useful.
Now combine that with probabilistic modelling.
Instead of a financial model producing a single target price based on point estimates, imagine one that represents a distribution of possible outcomes, understands the dependencies between assumptions and updates those probabilities as new evidence emerges.
The analyst’s role shifts from manually maintaining models and processing information towards challenging assumptions, evaluating evidence and exercising judgement.
I suspect Excel will eventually become less central to the investment process, replaced by something more dynamic, interconnected and probabilistic.
Perhaps the biggest opportunity for AI in investing isn’t helping us do the same work faster.
It’s fundamentally changing how we think, connect information and make decisions under uncertainty.
As an analyst, I understand the appeal of getting to an answer more interesting question is whether AI can help us arrive at fundamentally better answers?
I’ve always been fascinated by the idea of an interconnected investment brain. Something akin to Obsidian, but purpose-built for investing, where companies, industries, themes, mental models, investment hypotheses and evidence exist within a continuously evolving knowledge graph.
I’ve actually started experimenting with a prototype of this concept, which I’m calling Labyrinth.
Imagine discovering something material about one business and being able to trace its implications across an entire network of companies, assumptions and investment theses. Rather than research existing in isolated notes, PDFs and spreadsheets, knowledge becomes interconnected, cumulative and increasingly useful.
Now combine that with probabilistic modelling.
Instead of a financial model producing a single target price based on point estimates, imagine one that represents a distribution of possible outcomes, understands the dependencies between assumptions and updates those probabilities as new evidence emerges.
The analyst’s role shifts from manually maintaining models and processing information towards challenging assumptions, evaluating evidence and exercising judgement.
I suspect Excel will eventually become less central to the investment process, replaced by something more dynamic, interconnected and probabilistic.
Perhaps the biggest opportunity for AI in investing isn’t helping us do the same work faster.
It’s fundamentally changing how we think, connect information and make decisions under uncertainty.
This is so bang on, a lot of investing involves far too much false precision, and it's because it simplifies it for human understanding...this is why I'm excited about AI's use in investing
when you think from first principles, it seems crazy to be putting a precise number on something we know is uncertain...
analysts assign target prices, estimate “fair value” and forecast cash flows five years into the future. The model gives us an answer like $47.83.
but take a step back and think about what went into that number
we don’t know exactly how quickly revenue will grow. we don’t know what margins will be, how much the company will need to reinvest, or what return investors will demand in five years. Every assumption has a range of possible outcomes.
We choose one number for each, run the calculation, and end up with an answer that looks way more certain than anything we put into it.
We all know that investing is about gaining confidence that the probabilistic range of outcomes has a favourable skew
This is why I’m so excited about compute changing how we do this work.
Modelling is part of the problem, it's unfathomable for each cell in excel to have a probabilistic range of outcomes and for you to update those probabilities constantly as information emerges
But AI and newly written software will genuinely make this possible, not to mention the most advanced systems being able to ingest information and update those weights
of course, judgement still exists about the assumptions and their likelihood but I'm really excited to see how this evolves
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Few thoughts on AI in investment management and all fields where humans primarily use their conceptual/intellect ability to model/understand/predict the world (in a quantitative manner). The most serious obstacle I see to AI science at the moment is combinatorial explosion: even for a super super super computer, the search space will be too large to search without some sort of choosing-where-to-search algorhythim.
Incidentally, this is what I think humans do with our “feelings” or “intuitions”)…these are our indicators of where to jump into the unfathomably large possibility space…This is all - or most - of what I think human judgement is - where to focus attention in the search space and our emotional/valence/hedonic reactions are the pointers or metal detectors if you will of this…what would this look like in AI…I think we are already seeing it…
Im no expert, but once AI agents approach models where they can have a model of where to direct their attention- and learn how to do so based on their vastly superior working memory and analytical resources, its game over for human judgment in terms of making “better”’decisions in arena’s where we aim for the same goal (better risk adjusted investment returns for example)…the most important is that we remain the masters of choosing values - that they are OUR values…
I think society is entering a phase where what used to be rarefied philosophical questions (what is valuable, what is meaning, what is good, etc)…will be much more important for many to work through, for many have built their identity and lives on their differential intellectual or analytical ability…we are entering the age of values and qualities imo (in short: in the trinity of Truth, Beauty, and Goodness, Beauty and Goodness is about to get a much needed positive re-valuation)….
Incidentally, this is what I think humans do with our “feelings” or “intuitions”)…these are our indicators of where to jump into the unfathomably large possibility space…This is all - or most - of what I think human judgement is - where to focus attention in the search space and our emotional/valence/hedonic reactions are the pointers or metal detectors if you will of this…what would this look like in AI…I think we are already seeing it…
Im no expert, but once AI agents approach models where they can have a model of where to direct their attention- and learn how to do so based on their vastly superior working memory and analytical resources, its game over for human judgment in terms of making “better”’decisions in arena’s where we aim for the same goal (better risk adjusted investment returns for example)…the most important is that we remain the masters of choosing values - that they are OUR values…
I think society is entering a phase where what used to be rarefied philosophical questions (what is valuable, what is meaning, what is good, etc)…will be much more important for many to work through, for many have built their identity and lives on their differential intellectual or analytical ability…we are entering the age of values and qualities imo (in short: in the trinity of Truth, Beauty, and Goodness, Beauty and Goodness is about to get a much needed positive re-valuation)….
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Very important post @nealkhosla
As a reesult, I think much more government regulation incoming - the only player with enough power to counter this force…theres no putting the genie back in the bottle - when the power imbalance between consumers and producers stretch to breaking point, the producers (who are also the consumers in that they will have to pay wages etc from lower bargaining power) will respond: the only effective response I can see (as it is a collective action problem of note) is to come together in force, and the only actor that fits that bill is government (the Leviathan is about to be unleashed against Skynet in a big way)
As a reesult, I think much more government regulation incoming - the only player with enough power to counter this force…theres no putting the genie back in the bottle - when the power imbalance between consumers and producers stretch to breaking point, the producers (who are also the consumers in that they will have to pay wages etc from lower bargaining power) will respond: the only effective response I can see (as it is a collective action problem of note) is to come together in force, and the only actor that fits that bill is government (the Leviathan is about to be unleashed against Skynet in a big way)
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Charl Botha retweeted
It's a good week to be a centre-left kinda dude.
I believe that billionaires should be allowed to exist. Extreme talent and risk-taking should be rewarded.
I also believe that ordinary people with ordinary talents should be able to live a good life if they do honest work. It's completely absurd that people can't afford to have children, or to have basic healthcare.
These concepts aren't mutually exclusive unless you have idiots in power from either the far left or the far right.
I believe that billionaires should be allowed to exist. Extreme talent and risk-taking should be rewarded.
I also believe that ordinary people with ordinary talents should be able to live a good life if they do honest work. It's completely absurd that people can't afford to have children, or to have basic healthcare.
These concepts aren't mutually exclusive unless you have idiots in power from either the far left or the far right.
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(1) Suppose you were a real estate developer specialising in high-rise buildings or scyscrapers. And let's focus on Cape Town's CBD for the moment. Which high-rise building in Cape Town do you rate as the most beautiful? And all else equal, which building do you think made the most money for its investors?
Would you rather have built the most beautiful building or the most profitable? Would you ever rate beauty as more important than money in your project decision? Would your decision change if you only had one project left in your career?
Would you rather have built the most beautiful building or the most profitable? Would you ever rate beauty as more important than money in your project decision? Would your decision change if you only had one project left in your career?
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(2) And suppose you were an investor buying an apartment in a high rise building in Cape Town, or a firm considering renting office space? What do you think is the most beautiful building in Cape Town? How much of a premium would you be willing to pay to acquire or rent in this kind of building versus the average?
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Charl Botha retweeted
Does South Africa have too many malls? moneyweb.co.za/moneyweb-opini…
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Charl Botha retweeted
@blaiseaguerak@bigthink@blaiseaguera👌Do you thi@blaiseagueraes might depend on the substrate performing (certain) sorts of calculations at a certain min speed, so that a rock creature wouldn’t be conscious because its speed of “life” would be too low? Closely related, do you think consciousness happens at a certain “framerate” no matter the speed of the substrate if it reaches a certain min speed for consciousness to arise? I find in my own case that anxiety seems to increase the speed of my thoughts - and the urgency of the feel of my consciousness - but there still seems to be a background speed of feeling - the arena within which the events of consciousness happens or the objects change that is constant - or at least slower (and it happens when I realise that I am feeling anxious - that my thoughts are racing, but THAT thought-feeling is not itself “racing”.
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Charl Botha retweeted
I sat down with @bigthink to explore self-constructing computation, what defines a mind, why AI is humankind’s new symbiont, and how we can thrive together.
Watch the full conversation: bigthink.com/series/full-in…
Watch the full conversation: bigthink.com/series/full-in…
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Ive read and enjoyed the ‘Huisgenoot’ for many years - its the pulse of the nation.
I always start at the back. First there is ‘Heat South Africa’ - where you find out whether Steve has a new kid, then ‘Heat Global’ , where you see whether reasonably soon-to-be geriatric Leo has a new 25-year old girlfriend, or who is leaving whom for whom in Hollywood’s never ending ‘bollie-esque’ manner. Further to the front you find the feature articles which I particularly enjoy - the classic South African ‘Hugo-bel-die polisie’ type of real-life soap opera. Incidents which remind me why I find our country so special and endearing.
Yes, we have the bad, and the ugly, but we also have the good; the good of ordinary South Africans trying to make a living, and the self-deprecating humor that makes us such a warm and authentic people. And whether Hugo really managed to call - and reach! - the ‘polisie’, I can’t recall. What he and Marilise did manage was to remind us that most South Africans are probably not trying solve life, or diversify the human race to Mars, but just living…whether just trying to survive another day of funeral-policy-by-phone torture, or more seriously, just trying to make ends meet, or to simply be better. And yes; sometimes trying to reach the ‘polisie’. Have a great Friday everyone😊🙌
I always start at the back. First there is ‘Heat South Africa’ - where you find out whether Steve has a new kid, then ‘Heat Global’ , where you see whether reasonably soon-to-be geriatric Leo has a new 25-year old girlfriend, or who is leaving whom for whom in Hollywood’s never ending ‘bollie-esque’ manner. Further to the front you find the feature articles which I particularly enjoy - the classic South African ‘Hugo-bel-die polisie’ type of real-life soap opera. Incidents which remind me why I find our country so special and endearing.
Yes, we have the bad, and the ugly, but we also have the good; the good of ordinary South Africans trying to make a living, and the self-deprecating humor that makes us such a warm and authentic people. And whether Hugo really managed to call - and reach! - the ‘polisie’, I can’t recall. What he and Marilise did manage was to remind us that most South Africans are probably not trying solve life, or diversify the human race to Mars, but just living…whether just trying to survive another day of funeral-policy-by-phone torture, or more seriously, just trying to make ends meet, or to simply be better. And yes; sometimes trying to reach the ‘polisie’. Have a great Friday everyone😊🙌
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Charl Botha retweeted
There is a Hong Kong-based microcap multi-brand restaurant operator that compounds owner earnings at high teens (reinvesting half of annual cash flows at 40% ROI on new stores), pays a dividend yielding close to 10% and retains a fortress of unencumbered cash making up over a third of its market cap.
However, a material mismatch exists between the actual owner earnings the business generates and the accounting profits the company reports.
The discrepancy is due to something seemingly innocuous – despite adhering to the technical accounting standards, the annual depreciation/amortisation charge is materially inflated. Amortising the fixed fit-out costs, kitchen equipment and dining furniture (all one-off sunk costs of new store openings) over an arbitrary fixed period creates a material incongruence with the actual annual cash spent on periodic store refurbishments and the ongoing capital upkeep of its restaurant footprint.
The effect is that a company that is purportedly valued at 7x accounting EPS actually trades at 4x NTM owner earnings – a valuation dislocation of over 50%!
In security analysis, technical accounting expertise is one of the few remaining analytical edges in an investor’s arsenal. It is striking how often reported numbers obscure or distort the true commercial picture of a company. IFRS, US GAAP and other accounting frameworks aim to improve the quality of financial reporting, yet perversely they often have the opposite effect.
This case also highlights the deficiencies of quantitative screening as an idea generation tool, given its reliance on reported financial accounting data. To give yourself the best chance of uncovering hidden gems, you have to get into the nitty gritty – an exercise few are willing to do.
However, a material mismatch exists between the actual owner earnings the business generates and the accounting profits the company reports.
The discrepancy is due to something seemingly innocuous – despite adhering to the technical accounting standards, the annual depreciation/amortisation charge is materially inflated. Amortising the fixed fit-out costs, kitchen equipment and dining furniture (all one-off sunk costs of new store openings) over an arbitrary fixed period creates a material incongruence with the actual annual cash spent on periodic store refurbishments and the ongoing capital upkeep of its restaurant footprint.
The effect is that a company that is purportedly valued at 7x accounting EPS actually trades at 4x NTM owner earnings – a valuation dislocation of over 50%!
In security analysis, technical accounting expertise is one of the few remaining analytical edges in an investor’s arsenal. It is striking how often reported numbers obscure or distort the true commercial picture of a company. IFRS, US GAAP and other accounting frameworks aim to improve the quality of financial reporting, yet perversely they often have the opposite effect.
This case also highlights the deficiencies of quantitative screening as an idea generation tool, given its reliance on reported financial accounting data. To give yourself the best chance of uncovering hidden gems, you have to get into the nitty gritty – an exercise few are willing to do.
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Charl Botha retweeted
What a month. Depending on who you ask, I did something brave or borderline crazy: I launched a global deep value fund. And what a time to do it. That said, is there ever a good time to launch a deep value fund?
I’ve come a long way from my anonymous Deep Value Situations account days, tweeting about obscure setups behind a 90-year-old Walter Schloss avatar. Starting the account was probably the smartest thing I’ve ever done. I will forever be indebted to the FinTwit community – it opened more doors than I could have imagined and put me in touch with brilliant investors all over the world. It’s how I met Jan van Niekerk and Piet Viljoen, who gave me a shot to become a professional investor and sharpen my deep value DNA. Now, with RECM as my partners, I’ve launched the Maxia Value Fund – a Mauritius-domiciled “Expert” fund.
Over time, I will share more details about my journey, investment philosophy and the fund.
In a nutshell, I am running a highly concentrated portfolio of deep value situations that are more of the 70s Buffett persuasion than those of post-Depression Graham. The fund structure is quite simple. Despite full flexibility and an unconstrained mandate, my approach does not rely on leverage, shorting stocks, exotic derivative speculation, macro bets or chasing faddish themes and momentum.
Almost invariably, portfolio candidates are:
- Undiscovered and out-of-vogue businesses operating in boring industries.
- Industry leaders in emerging and frontier markets.
- Almost exclusively small or microcaps that often have no sell-side coverage.
- Collateral damage in a regional orindustry-wide crisis. When headlines scream “uninvestable” I really get to work.
Maxia is a small and nimble investment outfit – operationally very much like the original investment partnership setups of a young Buffett and Walter Schloss. With a one-man investment committee, I am a lone wolf and relish the ostensibly tedious work of combing through entire stock exchanges, A to Z – reading the filings and annual reports of businesses most investors have never heard of.
Virtually all of my net worth is invested alongside fellow investors. These are humble beginnings; however, I have no intention of becoming yet another institutional-like asset gatherer. I am also selective aboutwho I partner with – the right partners share my investment philosophy and think in years, not quarters.
More information and important disclaimers regarding Maxia Capital Management and the Maxia Value Fund are available on the website (link in bio). Fund information is restricted to expert and sophisticated investors as defined under Mauritian securities regulations and, in South Africa, to qualified investors.
I’ve come a long way from my anonymous Deep Value Situations account days, tweeting about obscure setups behind a 90-year-old Walter Schloss avatar. Starting the account was probably the smartest thing I’ve ever done. I will forever be indebted to the FinTwit community – it opened more doors than I could have imagined and put me in touch with brilliant investors all over the world. It’s how I met Jan van Niekerk and Piet Viljoen, who gave me a shot to become a professional investor and sharpen my deep value DNA. Now, with RECM as my partners, I’ve launched the Maxia Value Fund – a Mauritius-domiciled “Expert” fund.
Over time, I will share more details about my journey, investment philosophy and the fund.
In a nutshell, I am running a highly concentrated portfolio of deep value situations that are more of the 70s Buffett persuasion than those of post-Depression Graham. The fund structure is quite simple. Despite full flexibility and an unconstrained mandate, my approach does not rely on leverage, shorting stocks, exotic derivative speculation, macro bets or chasing faddish themes and momentum.
Almost invariably, portfolio candidates are:
- Undiscovered and out-of-vogue businesses operating in boring industries.
- Industry leaders in emerging and frontier markets.
- Almost exclusively small or microcaps that often have no sell-side coverage.
- Collateral damage in a regional orindustry-wide crisis. When headlines scream “uninvestable” I really get to work.
Maxia is a small and nimble investment outfit – operationally very much like the original investment partnership setups of a young Buffett and Walter Schloss. With a one-man investment committee, I am a lone wolf and relish the ostensibly tedious work of combing through entire stock exchanges, A to Z – reading the filings and annual reports of businesses most investors have never heard of.
Virtually all of my net worth is invested alongside fellow investors. These are humble beginnings; however, I have no intention of becoming yet another institutional-like asset gatherer. I am also selective aboutwho I partner with – the right partners share my investment philosophy and think in years, not quarters.
More information and important disclaimers regarding Maxia Capital Management and the Maxia Value Fund are available on the website (link in bio). Fund information is restricted to expert and sophisticated investors as defined under Mauritian securities regulations and, in South Africa, to qualified investors.
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Learnt something:
There is a real pleasure in “getting” an idea or “seeing” the connection between things. The intellectually curious will know the feeling I’m talking about well: here is one such connection that I “saw” recently…The etymology of the word “concept” literally means grabbing on to something (getting a hold of something or having a handle in it)…we form conceptions of things, or improve our concepts, or have better concepts, when they allow us to grab onto, or grasp, the nature of something (when we can hold the thing in our minds and play around with it - seeing it from this conceptual angle, or using that conceptual (handle) to get a better grip on it. The more touch points we have on the object, the better chance we have of understanding it…
So far obvious to those who know the elephant and perspectives metaphor. But the etymology of “concept” made me realize how closely our handles on things involve words that map to the senses in what seems to be somewhat proportional to their importance in our daily lives. For instance, we often say that we “see” what you mean, or I “hear” you, or I “feel” that this or that is true or right/wrong. Or this “smells” fishy. I struggle to find examples for taste🤔 Notice something: it seems that 3 of the senses - and especially sight and hearing, are the primary means by which we determine/grab a hold/come to propositional/factual knowledge, while taste and smell doesn't play much of a role here at all. I see that 1+1 is 2, I dont smell it or taste it- (perhaps other people do, but I certainly don’t. I wonder if one can practice smelling the truth of arithmetic🙈). Smell and Taste - but especially touch/feeling - play a much greater role in evaluative/normative judgement… “feels” wrong, leaves a bad “taste” in my mouth.
Its also interesting - although perhaps obvious - that most of our geometrical concepts are visual, and many of our semantic concepts are hearing related. Pictures and Words - sight and hearing. And feelings as a way of mentally touching something that often arrives via other senses but cannot really be touched anymore…I haven’t touched on our moving in the world - Ive “come to” the “insight”…and so on…what are some of the implications for learning or forming better concepts from this?
There is a real pleasure in “getting” an idea or “seeing” the connection between things. The intellectually curious will know the feeling I’m talking about well: here is one such connection that I “saw” recently…The etymology of the word “concept” literally means grabbing on to something (getting a hold of something or having a handle in it)…we form conceptions of things, or improve our concepts, or have better concepts, when they allow us to grab onto, or grasp, the nature of something (when we can hold the thing in our minds and play around with it - seeing it from this conceptual angle, or using that conceptual (handle) to get a better grip on it. The more touch points we have on the object, the better chance we have of understanding it…
So far obvious to those who know the elephant and perspectives metaphor. But the etymology of “concept” made me realize how closely our handles on things involve words that map to the senses in what seems to be somewhat proportional to their importance in our daily lives. For instance, we often say that we “see” what you mean, or I “hear” you, or I “feel” that this or that is true or right/wrong. Or this “smells” fishy. I struggle to find examples for taste🤔 Notice something: it seems that 3 of the senses - and especially sight and hearing, are the primary means by which we determine/grab a hold/come to propositional/factual knowledge, while taste and smell doesn't play much of a role here at all. I see that 1+1 is 2, I dont smell it or taste it- (perhaps other people do, but I certainly don’t. I wonder if one can practice smelling the truth of arithmetic🙈). Smell and Taste - but especially touch/feeling - play a much greater role in evaluative/normative judgement… “feels” wrong, leaves a bad “taste” in my mouth.
Its also interesting - although perhaps obvious - that most of our geometrical concepts are visual, and many of our semantic concepts are hearing related. Pictures and Words - sight and hearing. And feelings as a way of mentally touching something that often arrives via other senses but cannot really be touched anymore…I haven’t touched on our moving in the world - Ive “come to” the “insight”…and so on…what are some of the implications for learning or forming better concepts from this?
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Charl Botha retweeted
I live a lowkey private life. I rarely get bored. Like ever. A quiet room, a book, some music, a long walk, my own thoughts. That’s all I need. That’s all I want. What exhausts me is "performance". Small talk. Noise. Drama. Conversations with no depth. Having to act what I'm not. That shit drains my soul. So I disappear for a while. Just to breathe again. To hear my own thoughts. To feel my own emotions. To reconnect with myself. And honestly, it feels like therapy for the soul.
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