Poor Ash’s Almanack (Welcome To The Best Free Mental Models Resource)

“You don’t have to be brilliant… only a little bit wiser than the other guys, on average, for a long time.”

 – Charlie Munger


Welcome to Poor Ash’s Almanack, the best free mental models resource on the internet.

What’s a mental model and how will it make you better at life, business, and pretty much everything?  If you don’t know the answer, that’s okay – start here.

If you already know what mental models are, read on: with three types of content spanning ~half a million words, created by someone who’s spent years learning and applying the lessons from hundreds of category-defining books, Poor Ash’s Almanack will make you happier, more successful, and more interesting at a cocktail party.  (Well, maybe.  No guarantees on that last one.)

Intelligent, highly educated readers from L.A. to New York to Brisbane to Hong Kong have provided rave reviews.  Here are nine of my favorites, verbatim:

– “Poor Ash’s Almanac[k] – wow – thanks.  superbly done – love the way you express counterintuitive ideas so simply.” (Talmudic scholar)

– “love your work and your writings – keep it up[,] it[‘]s very unique!” (wealth management executive from Australia)

– “Poor Ash’s Almanack is probably the most insightful and well written set of mental models I have ever come across.  We would like to congratulate you on pulling this off and are grateful to you for sharing it openly. This must have taken an incredible amount of time and dedication to put together.” (investors from New York)

– “I had been looking for a resource like this for a while and I get the feel[ing] that there are a lot of people who were.  Everyone talks about the latticework but [I’ve] never seen much of anything that actually goes into decent detail about each one.” (family office analyst from the East Coast)

– “the quantity of output is making me feel bad about my productivity.  Impressive.” (hedge fund analyst from Tennessee)

– “Fabulous… I love the notes and the way you’ve tied everything together.  I think I speak for the entire value investing community when I say: thank you.” (Managing Director of Investments at a large publicly-traded insurance company renowned as a “compounder.”)

– “I’m blown away.” (hedge fund manager from New York)

– “Samir, this is one of the most insane things I’ve ever seen in my life. (In a good way.)” (hedge fund manager from Texas)

– “THANK YOU.  That’s as big as gmail will let me type, but it’s still an understatement of my appreciation.  I (shamelessly) spent my entire workday exploring PAA yesterday (and will likely do the same today.)” (college student from Utah)

Follow in these readers’ footsteps and turbocharge your happiness and productivity by exploring our three types of content and joining our mailing list (below) for infrequent, thoughtful nudges to make wiser decisions.


100+ important concepts that’ll make you dramatically more effective at life, condensed into 37 pages that are easy to read and understand.  Some of my favorites: structural problem solvingculture / status quo bias, cognition / intuition / habit / stress, luck vs. skill, and salience.


Effective Thinking (Incl Psychology / Neuroscience)

Science, Engineering, Math, Medicine

Business / Finance / Entrepreneurship

History / Biography

Not sure what to read next?  Our book reviews provide detailed insights on what you can expect to learn from any given book – and our notes and analysis highlight the mental models, tying in related concepts from other books to enrich your learning and provide you with logical next steps.

Our three favorites:

Misbehaving (M review + notes)

The Design of Everyday Things (DOET review + notes)

Why We Sleep (Sleep review + notes)


If you’re feeling overwhelmed, I’ve put together a few suggestions on how to group content in a thematic manner.  The most useful is probably the 80 / 20 Mental Models Learning Journey – 17 books in 17 weeks to get you through 80% of the value on this site.

MAILING LIST (~16 emails per year – 4 Askeladden Investor Letters, 12 monthly “mental models memos”)

Are you, like many other high-caliber thinkers – incl. managers at $1B+ AUM shops – subscribed to our mailing list yet?

If not, you’re losing out on occasional “nudges” to get wiser!
You can sign up for our email list below, and/or you can follow us on Twitter (we’re old-fashioned and don’t Tweet, but new posts on the website are automatically tweeted out.)

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About / Contact

Hi.  I’m Samir Patel.  I run a concentrated, unlevered, long-only small/micro-cap hedge fund and separately managed accounts (SMAs).  My strategy is pretty simple: I wait patiently for high-quality businesses to trade down to attractive valuations.  

If you want to get in touch with me: samir [at] askeladdencapital {dot} com

Below (after some legal disclaimers) is a really long (apparently 33-page / 16,000 word) FAQ about Askeladden.  For your convenience, it’s collapsible, so you can click on only the questions which are interesting / pertinent / amusing to you, and ignore the rest.

Please note, importantly, that THIS FAQ DOES NOT SUBSTITUTE FOR ASKELADDEN CAPITAL’S FORM ADV, ADVISORY AGREEMENT, OR OTHER LEGAL DOCUMENTS.  THIS IS NOT AN OFFERING OF SECURITIES.  This FAQ was last updated in September 2018 and important information may have changed in the interim.  As of this writing, Askeladden Capital owns shares in Franklin Covey and LGI Homes, which are mentioned in the below discussion.  Other companies mentioned are either former portfolio positions, or watchlist companies we never invested in but have followed and watched for a while.


General Info + Investing in Askeladden Capital

Founded in 2016 and located in the suburbs of Dallas-Ft. Worth, Texas, Askeladden Capital Management is the investment advisor to a limited partnership (Askeladden Capital Partners) as well as separately managed accounts ("SMAs") which, subject to certain exceptions, are typically allocated equivalently to the limited partnership.

Askeladden runs a highly concentrated, unlevered, long-only strategy (typically 8 - 15 positions, with the top positions sometimes exceeding 20%) focusing on small and micro-cap stocks, predominantly in the U.S. Askeladden is closing to new investors at ~$50 million in fee-paying AUM to ensure we have a long runway for being able to profitably execute this strategy.

We do not use portfolio margin or options or short-selling, nor do we have macro views or proprietary quant algorithms - what we do here is plain-vanilla, fundamental, old-fashioned bottom-up stock picking based on extensive reading and research.

Briefly, we try not to outsmart ourselves: we’re looking for six-inch rather than six-food hurdles; if an idea isn’t obvious, it’s probably not for us. We’re not splitting hairs on valuation and our models rarely have decimal points or detailed line-item calculations.

We’re looking for good to great businesses with good to great management at great to good prices (respectively). Generally and directionally speaking, we want to buy businesses worth 15 - 20x+ their free cash flow / NOPAT at 10 - 16x, with, of course, occasional exceptions.

We generally initiate new positions when we believe we’re underwriting 20% annualized returns over a three-year period with our base case assumptions, recognizing that mistakes on our end and bad luck / bad execution for companies can and will reduce that return in many instances. A margin of safety is thus built in, such that even in bad outcomes, we hope to earn at least a modest return on capital. Please see the next section of the FAQ for more details.

Although we’re comfortable with reasonable leverage in circumstances where appropriate, our portfolio companies tend to have strong balance sheets; the majority of our positions over time have had sub-2x net debt to EBITDA (often sub-1x) and many have had no leverage or, in fact, substantial cash balances.

With occasional exceptions, we tend to avoid businesses that are extremely cyclical, commodities-driven, or difficult to understand (for example, we typically do not invest in semiconductors, biotech / pharma, and so on.)

Please note that any usage of "we" is simply the "royal we" because using "I" all the time sounds kind of egotistic. Askeladden is a one-man shop; I am the sole owner and employee of Askeladden Capital Management, although we do use outsourced service providers for fund administration, fund audit, compliance advisory, and legal advisory services.
Investment in Askeladden-managed separately managed accounts (SMAs) is open to the general public. Investment in Askeladden Capital Partners, LP (the partnership) is limited to accredited investors, who will be required to verify their accredited status with relevant financial documents.

Investors can choose either alternative. With certain exceptions, SMAs are generally allocated equivalently to the fund, with minor tracking error. Interactive Brokers’ platform enables synthetic trade aggregation and pari passu allocation; essentially, I am typically trading one giant pool of capital, with the fund and individual SMA accounts receiving pro rata allocations of trades at the same cost basis as everyone else.

Prospective clients who prefer transparency and liquidity generally tend to favor SMAs. Having an SMA is just like having any other brokerage account, except Askeladden has trading authority within the account. Conversely, those who may have compliance restrictions of their own may favor the pooled nature of the fund.

Although we make no explicit recommendations given that we’re not financial planners, given the highly concentrated nature of our investment approach, we generally feel it would not be suitable for clients to invest more than 10 - 20% of their net worth in Askeladden (with a few exceptions, such as young professionals with extremely long-term horizons, limited short-term capital needs, and high future earnings power.)
Askeladden Capital makes sense for long-term, value-oriented investors who are looking for a growth-mindset manager applying a multidisciplinary, qualitatively-focused investment approach in some of the less-traveled corners of the U.S. stock market. Specifically and somewhat uniquely, we do so without wasting time, money, or effort on non-value-added activities. Examples of such non-value-added activities that we avoid:

attempting to predict near-term stock price movements and endlessly scrutinizing every near-term data point,

having opinions on “macro” market topics which we have no chance of understanding such as the Fed’s balance sheet,

maintaining a traditional M - F, 9 - 5 workweek,

dressing up and commuting to an office,

otherwise creating and presenting an inauthentic brand image for marketing purposes.

We reinvest the time freed up by not doing these things into reading and research that create actual value, even if they don’t look as impressive in a client meeting. (See the “product vs. packaging” mental model.) Our investment and business approach is very idiosyncratic and is not for everyone; I do my best to vet prospective clients to make sure they’re a good fit for our approach before they contribute capital. Depending on the size of the account, this usually involves multiple emails and, often, a phone call (or a few) prior to reviewing and signing legal documents, funding the account, and initiating the advisor-client relationship.
Excluding copious cash that I keep around to ensure that me and my firm can handle unanticipated expenses, about ~70% of my net worth is invested directly in Askeladden Capital Partners alongside other investors. I get monthly statements just like everyone else does.

The remaining ~30% is split between a Roth IRA and a taxable brokerage account held elsewhere. The Roth stays there because I’m too lazy to port it over to IB for such a small account; the brokerage account stays there so I have easy access to capital if I need it for something (future down payment, business expense, unanticipated personal or family health expense, etc) without having to withdraw from the fund. Notably, these two accounts are very infrequently traded and hold only two securities, both of which are large positions of the fund.

Meanwhile, my dad is 69 and retired, and is in a similar situation: ~70% (+) of his IRA balance is invested in an SMA (non-fee-paying) with ACM. The remaining IRA balance is held in cash, as well as the same two securities mentioned previously.

The SMA is utilized rather than the fund because of his age and need to take RMDs. along with additional regulations around IRA clients inside of limited partnerships; it is simpler to avoid that and also to not have to handle withdrawals from the fund.

Other than our home and checking/savings accounts, my dad does not have any assets (he is not a wealthy man - he was laid off a number of times while I was growing up - to be frank, I always felt like, and in most ways was, the “poor kid” in the well-to-do D/FW suburb I grew up and still live in. We were always solidly middle-class, but contrast bias kicked in against my largely upper-middle-class and wealthy friends.)

I would strongly recommend against any other client allocating such a significant portion of their assets to Askeladden. But that’s what I and my family do.
A lot of reasons. Broadly speaking, I didn’t see a lot of opportunities in terms of working corporate jobs to do intellectually stimulating work that adds value for clients, while providing an upper-middle-class income for myself and my future family, while allowing me to live my life in the way I wanted to (prioritizing sleep and health, having time for family and personal interests).

Several of my friends and mentors helped me realized that if this was what I wanted to do with my life, it made more sense to start young - when I had no family or mortgage to support - rather than when I was older. Gaining more experience wouldn’t have eliminated prospective clients’ desire to see a track record, so it made sense to get the track record going.

As for the existential reasons I’m doing this: investing is a field where productivity and value creation is disintermediated from time and location: my job is to read a lot of stuff and think about it. I can work just as well from a 4G connection in a cornfield as I can from a fancy office.

As such, while investing necessarily requires many hours of work on a consistent basis, to learn about and stay apprised of promising investment candidates, it doesn’t necessarily require you to be in any given place at any given time - providing a lot of flexibility for simultaneously pursuing personal interests, or being an active and present member of your family.

As such, I often work on weekends and bank holidays (does anyone actually celebrate Columbus day?) At the same time, I usually see the latest Marvel movie at 2 PM on a Tuesday when nobody’s in the theater, rather than a weekend or weeknight evening when the theater’s packed.

Most of the time I work from my bedroom with a three-monitor setup and a standing desk; sometimes I work on my laptop at a coffeeshop, or a friend’s place… or on my phone while I’m standing in line at Chipotle or waiting for commercial breaks during Cowboys games to end. As long as the research gets done, it’s completely irrelevant when or where it gets done.

If I wanted to maximize my lifetime earnings, I’d be doing something else. You can run the math on my fee structure and my eventual firm size: it’s high by conventional standards, but absurdly low by finance-industry standards relative to what I’d make in most higher-level jobs.

But I think that money has low marginal utility beyond enough to comfortable live an upper-middle-class lifestyle. So I’m not pursuing it. I’m much more focused on other factors.

This allows Askeladden to pursue the unique approach of closing very small ($50MM FPAUM) and focusing heavily on research rather than on non-value-added marketing activities designed to increase the size of the firm. I have to spend some time on functions like compliance, trading, and business development, of course, but the proportion of that time is explicitly structured to be far lower than at many small firms, by the nature of the way I’ve set up and run Askeladden, and the way I plan to grow it.

This maximizes value for clients by ensuring that my time is spent on research, that we have a long runway to exploit that research… simultaneously, it minimizes the amount of time I spend on stuff I don’t enjoy.

I generally like to think that my edge is roughly equally split between two components: the attractiveness of the opportunity set in small and micro-caps, which we will be able to exploit given our plan to close at $50MM AUM, coupled with a concentrated, research driven, value-oriented approach that puts a lot of thought into process and temperament. I explore this approach in significant depth in the next section of FAQ.

“Talent” is hard to pin down. I have the empirics to suggest that I’m capable of performing high-level analytics: I’ve scored in the 99th percentile of every standardized test I’ve ever taken (2370 SAT, 770 GMAT).

However, I’m also aware of two important factors that more than outweigh that. First, investing is generally a business where approach is more important than IQ, exemplified by the failure of Long-Term Capital Management (LTCM), although there are of course numerous other examples. As such, it’s easy to get too cute and outsmart yourself - to use our first obligatory genuflection to Bunger and Muffett (I mean, Munger and Buffett), great investing is typically about finding six-inch hurdles… not six-foot ones.

Second, it’s often behavioral factors - particularly hubris / arrogance / overconfidence - that sinks many promising investors. Counterintuitively, believing you’re worse at something can make you better at it. For example, I try to start every road trip by assuming that I’m a below-average driver with no special reflexes or talent at maneuvering a moving vehicle.

Thus, I assume that I have to take precautionary measures to maximize my base rate of getting to my destination safely. I never text and drive, I never drink and drive (I never drink in the first place), I try to stay within 5 - 7 miles of the speed limit, I try to avoid driving during rush hour and other dangerous times, and so on.

Paradoxically, by starting with the assumption that I’m not a particularly talented driver, and thus applying the appropriate margin of safety to compensate, I probably end up being a better driver than those who are texting while going 15 miles over the speed limit.

I believe a similar phenomenon applies in the investing world: starting by assuming you have the least insight and information can lead you to a process where you end up with the most, whereas starting by assuming that you and your team are the smartest guys in the room usually ends up with… well, that story ends without a cash flow statement, or much of anything else.

Askeladden’s fee structure is significantly more client-friendly than most similar funds we encounter. Qualified clients pay*:

A management fee of 1.5% of AUM (charged as 0.125% monthly in arrears).

Importantly, there is no nickel-and-diming here: while many funds charge investors for routine business expenses such as audit, fund administration, and research, the only expenses at ACM not typically covered by the management fee are trade commissions. (Please see our Form ADV for more details.)

A performance allocation of 30% of any outperformance vs. the S&P 1000 Total Return Index, calculated every three years from the date of a client’s contribution, subject to high-water-mark and carry-forward of any underperformance vs. this index.

Although I don’t aim to track or beat any benchmark over any given timeframe, I recognize that investors always have a (nearly) zero-cost alternative via index funds - so I feel it is only appropriate to charge performance allocations on performance that exceeds that hurdle rate, as that is (in my mind) the value which I am creating over time. Additionally, as a value investor who underwrites positions with a three-year investment horizon, it doesn't seem appropriate to measure incentive compensation on an annual basis.

*Please note that per SEC regulations, investment managers such as Askeladden cannot legally charge non-qualified clients a performance allocation. Therefore, any non-qualified clients (i.e., those with a net worth, excluding equity in primary residence, of $2.1MM or below) pay a flat 1.95% management fee, with no performance allocation.
Not typically for small accounts; larger accounts ($1MM+) are potentially negotiable.

Some of Askeladden’s early clients pay less than the stated fee structure; however, now that Askeladden has established more of a track record, and given the fact that the fund will close at $50MM to preserve runway for executing our strategy, I intend to be more stringent on not giving up economics. Our fee structure is already very client-friendly, and fees are merely one part of the value equation.

While the performance allocation may be negotiable in these instances, the management fee is almost certainly not - it is difficult to run a business (or a personal checkbook) without reasonable visibility into cash flow, and my management fee at scale will only support reasonable business expenses and a reasonable living for myself.

I believe management fees are often unfairly vilified: there’s a reason why most jobs pay salaries rather than pure commissions. It’s behaviorally very challenging and stressful to focus on long-term value creation when you’re more worried about where your next meal is coming from. As such, I believe performance-allocation-only fee structures, such as the “Buffett Partnership” or “25 over 6” structure, create significant and undesirable conflicts of interests between the manager and the client. From my perspective, these structures are well-intentioned but ultimately misguided for both the manager and client. They aren’t really pay-for-performance, because managers can’t control market valuations.
Typically $100K. However, I have made exceptions in certain situations. So if you’re extremely interested and aligned with our philosophy but $100K is more than you have liquid, please reach out and we can discuss possibilities.
Actually, no - SMAs are much less of a burden to manage than the fund.

Years ago, overseeing separately managed accounts required placing trades in individual client accounts, and rotating the order in which these trades were placed to avoid some clients consistently achieving better execution and some clients worse. This is where the perception of administrative burden comes from.

However, new technology has done away with those concerns. ACM uses the Interactive Brokers platform for both the fund (ACP) and separately managed accounts. Most of the time (with occasional exceptions), I'm placing trades for one synthetic "pool" of capital that includes the partnership as well as all SMAs. Interactive Brokers then allocates these trades pro rata to all accounts based on each account's percentage of the total pool.

For example, say that a manager has $1MM at IB, split between one account with $500K and five accounts with $100K each. The manager places a trade for $20K, or 2% of the entire pool of capital.

As the trade executes, IB would assign each account its pro rata share (2%) at the same cost basis as everyone else - so if the entire $20K trade order executes at an average cost basis of $10, the $500K account will have $10K worth of stock (2% of the account size) at an average cost basis of $10, while all the $100K accounts will have $2K worth of stock (2% of the account size) at an average cost basis of $10. Typically, other than infrequent rebalancing to correct minor tracking error, I'm only trading individual client accounts when money is added/withdrawn, or if there are account-specific requirements that need to be taken into account.

As such, there is actually significantly *more* administrative burden in managing the limited partnership: I have to approve monthly statements, coordinate with the fund administrator every time there is a new client (or a new client deposit). I also have to serve as an intermediary for client deposits/withdrawals, providing banking information and so on. Additionally, every year, I have to prepare financials for the auditors and review K-1s before they are distributed, and so on.

In SMAs, all of these functions are either nonexistent, or handled by Interactive Brokers directly, so I save time, as do clients (ex. they can check their statements at any time on their own, rather than waiting for us to finalize them and send them out. They can also add/withdraw money without me having to serve as an intermediary.)

Finally, as ACM scales, liquidity management will become an important concern - many of our mentors have impressed upon us the difficult of managing client redemptions and additions, particularly when dealing with illiquid portfolio positions. Having SMAs means that when a client chooses to add or withdraw money, only that client's account (rather than the entire fund) is affected by the change.
Here is the really abbreviated version of my bio:

Homeschooled K - 12 (and planning to homeschool my kids) for academic reasons. (My family isn’t religious.) Spent a lot of time in elementary/middle school pointlessly memorizing a bunch of obscure and useless words; this is something people still care about for reasons I really don’t understand.

Started community college at 13, graduated high school at 17 with an associate’s degree and 4.0 GPA, graduated magna cum laude with a bachelor’s in biochemistry at 19, graduated with an MBA (4.0 GPA) at 20.

While still a full-time undergraduate student, started working full-time as an editor for Seeking Alpha Pro at 18.

Became an analyst for a small/micro-cap hedge fund in Dallas at 19

Launched Askeladden Capital at 21

I will someday be a published novelist.

See? You’re all caught up. Wasn’t that easy?
I’m 24. I’m a native Texan with the Texas flag tie to prove it (y’all).

I try not to take myself too seriously, although people tend to tell me that I'm very intense, so I guess that's an interesting combination. A thing I'm good at is dogsitting.  Another thing I'm good at is listening. (Think, James, what's more important - your potato, or your friend?) A thing I suck at, as you can probably tell, is web design. Another thing I suck at is drawing.

If I’m not responding to your emails, there’s a good chance I’m carrying a stupidly heavy backpack up a stupidly large mountain for reasons largely incomprehensible to people who prefer roofs to tents.

Random other stuff: my idea of a good Friday night (or really, any other day/time of the week) involves staying at home with a book and some (quiet) music. I’m really boring. The most exciting thing I do on a regular basis is cooking really foodie things (which I greatly enjoy).  But in terms of conventional excitement, there's not much.  Other than going skinny-dipping in the middle of nowhere, everything I do is probably pretty grandma-approved.

One of my longtime best friends, Clayton, also insists I mention that if I pay more attention to your dog than you, it’s nothing personal… I just feel about dogs the way most people feel about, well, dogs.

I like people just fine 1x1 or in small groups… I’m singlehandedly bringing back the long email. And I’m fine speaking to crowds (I was a high school debater). I just don’t like being in crowds, parties, New York City, or other places where there are lots of people all at once. (This explains why my vacations involve stupidly-heavy backpacks and stupidly-remote places, if you were wondering.)

Notably, I don’t consume alcohol unless I’m cooking with it and it’s mostly cooked off (ex. a half-cup of white wine when making a pot of risotto). Seriously, I’ve had exactly half of an alcoholic beverage in my life, and that was only because I accidentally ordered a house-made lemonade at a nice restaurant that I didn’t realize was “hard” lemonade (it wasn’t explicitly specified on the menu!)

On the other hand, I am the sort of person who owns a sous vide and a Chemex… both of which changed my life. Foodie is soft-selling it. If you want to do the Dale Carnegie thing and listen to me blather on for about three hours, ask me about my cooking or my favorite coffee from a ridiculously narrow region within Ethiopia. I’ll food-nerd out on you.

I work out 3x/week, usually a mixture of cardio and weightlifting.  I am not particularly athletic.  Also, despite the best efforts of many of my friends, I do not run.  This roughly sums up how I feel about running:

Strategy + Process Deep Dive

Generally, the companies we look for tend to have several, and hopefully many/most, of the following characteristics.

Differentiated business model or best-of-breed product.

This is not always associated with market share - sometimes companies with strong products corner the market (as in the case of Zix or Kadant), while sometimes they intentionally and purposefully serve the highest-value customer segment rather than attempting to be everything to all people (as in the case of DMC Global).

Oftentimes, it can in fact be profitable to own the “small disruptor” that can grow by gaining market share largely regardless of overall market conditions (as in the case of, again, DMC Global.)

Sometimes, of course, a product can be totally commoditized, but a company with a structural business model advantage can still be extremely lucrative over time. Berkshire Hathaway’s GEICO is the classic value investing example; car insurance is essentially a complete commodity with only very modest differentiation potential, but GEICO’s low-cost agentless structure enabled it to pass along lower costs to consumers and gain material market share over time.

In our current portfolio, we believe LGI Homes (LGIH) is an example of this - homebuilding is an industry where product differentiation is extremely difficult (and perhaps impossible), but LGIH has demonstrated a structural advantage in its margins and returns on capital due to its unique and differentiated approach to homebuilding (standardized no-option spec building combined with active demand generation via direct mail, resulting in much higher sales velocity than the vast majority of peers) that, while not impossible to replicate, would be difficult to execute for many/most of its competitors due to the need to rebuild their operating processes and culture from the ground up.

Strong customer value proposition and strong margins (or strong margin potential).

While many investors focus on “pricing power,” we prefer to focus on what drives pricing power over the long term - the customer value proposition. Peter Thiel presents a simple “X | Y” model that distinguishes value created by a company from value captured. I reference this in the disaggregation mental model.

Some industries can destroy or not create value while capturing plenty for themselves (for example, most multi-level marketing companies, and perhaps timeshares), while others can create tremendous value while failing to capture much for themselves (for example, public school teachers, parents, or airlines.)

An important and true tautology is that unsustainable things cannot be sustained - companies that abuse their pricing power eventually piss off their customers, and things tend to end badly (see: Valeant and other pharma companies that consistently raised prices on lifesaving drugs.) MBA-trained executives who solely focus on the rational classical-economics angle fail to understand the mental model of fairness: oftentimes, even if you’re creating tons of value, there’s an upper limit on what people are willing to pay.

If you’re already charging customers as much or more than they think is fair, you don’t have a long runway for increasing prices. On the other hand, if you’re providing customers with a great deal - and constantly finding ways to make the value proposition better, as with our portfolio holding Franklin Covey with their All Access Pass subscription - then you have a strong base for long-term revenue growth and margin expansion potential.

As such, we attempt to consider business economics from not only shareholders’ point of view, but also from the point of view of other important stakeholders - especially customers. If customers don’t win in the long-term, neither will shareholders.

Nonetheless, from the point of view of the shareholder, we also want to see companies that are being run for profit, rather than for revenue maximization, or as engineering playhouses. Higher margins offer more “cushion” in bad times; the combination of operating deleverage and low margins can be deadly. We are generally enthused by margins that are stronger than those of peers (and sustainable), or situations in which there is a clear and obvious path to higher margins over time (such as a company gaining scale by consolidating a fragmented market).

A high mix of recurring revenue, and/or “selling opex, not capex.”

The benefits of recurring revenue are obvious - it is much easier to grow or maintain your business when you start on January 1st with 70, 80, or 90% of last year’s revenue already in the till. You are much less subject to the whims and vagaries of market forces, and much more in control of your own destiny.

More broadly, “selling opex, not capex” is our internal shorthand for companies that sell things that are routine components of their customers’ operating budgets, often with a short operating life or high need for replacement, rather than one-time, project-based capex.

As a completely hypothetical example, consumers don’t enter annually recurring contracts to purchase lightbulbs or toothpaste, but nonetheless, these are small-peanuts, relatively frequent, replacement-demand purchases that are unlikely to be heavily scrutinized or delayed by external macroeconomic circumstances.

Conversely, large appliances or machines like lawnmowers, washing machines, and refrigerators tend to be somewhat more discretionary (and scrutinized) purchases.

Strong balance sheets.

Balance sheets often don’t matter until they’re the only thing that matters… despite the easy credit environment and generally robust economic circumstances, we’ve seen bad balance sheets permanently wipe out material amounts of shareholder value in the blink of an eye (Essex Rental, Team Inc).

As such, although it has become popular in the current easy-money environment for many companies to use “appropriate leverage” (read: as much as they can borrow) to reduce their cost of capital and maximize their returns on equity, we tend to prefer companies that take a somewhat more conservative approach - after all, as value investors, we prize margin of safety, especially multiple levels thereof.

We have found that highly-levered companies, tautologically by definition, have high leverage / gearing to external events: what would be merely modest speedbumps for a conservatively-capitalized companies can be existential threats for companies leveraged to the hilt. As such, it is much harder for us to ascertain an appropriate margin of safety for such companies, and as a general rule of thumb (with, of course, occasional exceptions), our approach tends to be simply leaving those for other people who are better suited to handle those situations.

As a general rule of thumb, the vast majority of our portfolio exposure will have sub-2x debt-to-EBITDA, often sub-1x, and we especially enjoy investing in companies with very low debt, none at all, or meaningful cash balances, which provide downside protection as well as optionality to jump on attractive opportunities when they present themselves.

Limited exposure to commodities or other extremely volatile / unpredictable macro factors.

You’re not going to see Askeladden owning gold miners anytime soon (probably ever.) We tend not to make directional bets on commodities or macro factors.

When we do take commodity risk, it is typically in an indirect fashion - for example, we’ve owned small positions in several companies selling differentiated, high-margin “technical products” for use in drilling oil wells.

Although these companies did of course have oil price exposure, we felt that they were set up well to deliver solid results in most environments other than a further collapse of oil prices - even with flat or modestly lower oil prices and drilling activity, we believed their ability to create value for customers would allow them to create value for shareholders, while offering a lower-risk, higher-reward way to benefit from an oil recovery (which eventually materialized).

We were never taking bet-the-ranch type positions here (our total oilfield products exposure was mid-high single digits at its peak), but viewed them as an appropriate risk-reward in context of our portfolio.

Low capex needs, or high returns on capital.

Most of the companies we invest in tend not to need a lot of capital to grow their businesses; even if they are industrials, they’re usually selling high-value, IP-driven products, where most of the heavy manufacturing of low-margin components is outsourced to others. In many cases (such as software and professional services), our preferred companies have capex budgets limited to routine computer systems and office buildouts.

In the case of companies that do need capital to grow, we of course are focused on returns on capital. Fogo de Chao had best-in-class unit economics, returning more 4-wall EBITDA per dollar invested in a new restaurant than the vast majority of its peers. LGI Homes has a similar position in the homebuilding sector.

In all cases, we don’t focus as much on reported ROIC as most value investors - a perhaps surprising statement. However, we find that many people use ROIC mechanically, allowing it to be an overinfluencing arbiter of whether a business is “good” or “bad” or “capital intensive” or “not capital intensive,” without considering the circumstances and what really drives growth.

For example, if a company operates in a saturated market, ROIC could be infinite and it would be completely irrelevant - if the company can’t grow because there’s no demand for additional product, then its value is constrained to its current free cash flow rate. On the other hand, a company with a low current ROIC but high demand for incremental product that doesn’t require additional capacity expansion can transform its economics in a very short period of time.

Thus, we’re more focused on fundamental drivers of metrics than metrics themselves. We try to think like business owners, not OPMI investors.

--- This is a representative but non-exhaustive list of the qualitative factors we consider. Of course, it’s important to note that you can never bat a thousand - only very rarely will you find a “perfect company” at a “perfect price,” and perhaps the most value-added component of my job is determining how much to weight each of the preceding factors, in light of a company’s current valuation and other relevant circumstances.
ACM approaches idea generation meaningfully differently from many firms. Typically, when looking at new companies for the first time, I’m more focused on finding interesting companies with strong business models that deserve to be followed closely over the long-term, and less focused on near-term valuation (though for obvious reasons, I typically don’t spend a lot of time studying companies that currently trade at patently absurd valuations.)

I find that taking a longitudinal approach and following companies over time allows me to glean more insights than trying to learn all I can in one go; similarly, having a list of interesting companies and waiting for the valuations to come to us is behaviorally sound because it reduces the incentive to “massage the numbers” to make an idea actionable. Defining “success” as “adding something to the watchlist” or “updating something on the watchlist” rather than “adding something to the portfolio” helps us be more objective in our assessments.

When we identify a company that has the characteristics we look for, and isn’t trading at a completely absurd valuation, we spend anywhere from a few hours to a few weeks digging into the company’s investor information, depending on how interesting the company is. Unlike many value investors, we tend to start with conference call transcripts - specifically, company presentations at sell-side / industry conferences, or company Investor Day presentations, rather than securities filings.

We find that, unfortunately, 10-Ks tend to be written by lawyers, for lawyers (risk factor: our stock price might decline if global warming kills all our customers, or, even better, risk factor: the future is uncertain and we don’t know what’s gonna happen.)

While company filings are undoubtedly critical sources of due diligence information, they tend not to present as much helpful color on the qualitative aspects of the business as less formal, more story-oriented management presentations.

We typically start by reviewing up to the past three years’ worth of conference calls, contextualizing the takeaways by identifying what peers or public industry sources (such as trade magazines) have to say on similar topics, or going back farther in the company’s history to better understand specific issues (for example, we like to understand, if possible, how the company performed through the 2008 - 2009 financial crisis, and we also like to see if targets / initiatives set in the past ended up panning out - or if management has changed their tune.)

We then perform due diligence and financial analysis by consulting company filings - including, of course, footnotes and important sections such as segment reporting. Our results are collated into research documents (see “research document” question below) that may range from “briefs” (not boxers) of a few paragraphs to thorough, 20 - 50 page deconstructions. The point of this documentation is to avoid the pitfalls of memory: months or years after looking at a company, hastily-scribbled notes might as well be written in Serbian.

Documenting our findings and conclusions in as much detail as possible allows us, in the future, to pick up where we left off and avoid re-work. My research documentation process was developed with the help of my friend and mentor Zeke Ashton, whose firm Centaur Capital Partners has delivered risk-adjusted returns significantly in excess of appropriate benchmarks over a 16 year plus track record.

When this research document is completed, we add the company to our watchlist, along with a “fair value” estimate that we set to compound at 10% annually (our assumed / underwritten equity cost of capital for substantially all companies), allowing us to track which companies may be trading at reasonable valuations at any given point in time, and also allowing us to determine over time whether or not the company’s value creation matches, exceeds, or underperforms our expectation (hopefully assisting us in making more accurate judgments in the future).

Importantly, this process may occur all at once, or over time, depending on our level of interest, the company’s valuation, and other demands on our time (we focus heavily on utility and opportunity costs). We aim to add 40 - 50 new companies to the watchlist each year (gross), but will have fewer additions on a net basis, as we often lose companies to M&A or, less frequently, eventually decide they’re no longer worth our time to follow. We would like to eventually grow the watchlist to somewhere in the neighborhood of ~300 names.

In many cases, we eventually follow up by speaking to company management / IR, or that of peers, to more deeply understand specific issues. However, we only very rarely do “primary research” such as channel checks - we tend to find that if such work is necessary, the opportunity is probably not obvious enough.

We revisit companies already on the watchlist due to some combination of:

1) Time passing

2) Some interesting event (like an acquisition or meaningful new product launch) occurring.

3) The stock price being in the neighborhood of or meaningfully below our underwritten fair value, suggesting that an opportunity might be present (with further consideration required).

Our research process is, of course, a work in progress rather than set in stone: we’re always looking for ways to improve.
Our philosophical approach to valuation is that a company’s intrinsic value is the sum of its future cash flows. Of course, most people agree on this fundamental tenet of finance. How they put it into practice is the key.

Our valuation approach is what I’ll call “DCF-inspired.” Although DCFs are theoretically defensible, there are a few problems with them, in my view.

First, traditional three-statement DCFs often imply a false degree of precision when approaching the necessarily probabilistic question of what a company is worth. Unfortunately, analysts have a tendency to forget this and rely on the precision of the model as a substitute for the quality of the thinking - falling prey to the “garbage in, garbage out” phenomenon. Just because the model says something doesn’t make it gospel truth.

Second, while traditional DCFs involve forecasting a lot of individual line-items, the truth is that usually only a handful of variables (revenue growth and margins) drive the majority of company value. Being directionally right on these important factors is often far more important than being precise about rounding errors like swings in accounts receivable. Good ideas tend to be relatively clear and obvious and rarely does the success or failure of an investment thesis hinge on a 0.1 vs. 0.2 in cell EF52 on the balance sheet six years from today.

Third, much of the forecasting of individual line items ends up being trivial, as the majority of value in medium-term DCFs (and much of the value in long-term DCFs) is captured in the “terminal value” piece.

Given these factors, what I’ve found after three years of professional investing is that a much simpler “back of the envelope” approach seems to appropriately capture a reasonably conservative fair value estimate. I basically just move the “terminal value” piece of the DCF back to the present, determining a fair EV/NOPAT multiple based on what I expect the company’s medium-to-long-term earnings growth rate will be.

I tend to focus on NOPAT rather than earnings given our sensitivity to leverage; I tend to give companies only partial credit for debt-driven capital structure efficiency. Equity cost of capital is almost always underwritten at 10% (I won’t bother explaining why CAPM and beta are idiotic); cost of debt is usually underwritten at 4 to 6% depending on the company (and in substantially all cases, this is well in excess of what the company is actually paying on the debt). Moreover, I typically don’t assign full value to the tax shield created by debt.

Meanwhile, I start by assuming most companies will grow at a GDP-like 2% rate. Companies with obvious secular growth challenges - say, a company producing freesheet paper for printers - would obviously be valued at a growth rate of 0, or even perhaps a negative growth rate. (This is mostly hypothetical, as I don’t spend much time working on these sort of “deep value” cigar butts.)

On the other hand, higher-quality companies that have opportunities to gain market share, expand margins, or participate in GDP-plus markets are typically assigned growth rates of anywhere from 3 to 5% depending on various factors (the attractiveness of the company and market, its historical performance, the level of recurring revenues and competitive defensibility of the business, etc).

Assuming a debt-free company, this then equates to the following valuation rules of thumb:

Undifferentiated company (GDP-like 2% growth): ~12- 13x EV/NOPAT

Company with modest growth prospects. (somewhat GDP-plus growth, say 3%): ~14 - 15x EV/NOPAT. (KFY was in this bucket.)

High-quality company with solid growth prospects. (meaningfully GDP-plus growth in earnings, say 4%): ~16 - 18x EV/NOPAT.

Very high-quality company with strong growth prospects. (5%+ growth): ~20x EV/NOPAT, or potentially even higher. (FC and ANSS are in this bucket.)

Of course, we typically attempt to purchase these companies at a ~20% or greater discount to fair value, which equates to a ~20% three-year forward IRR (assuming 10% per year compounding from our fair value estimate). In the case of companies with a debt balance, P/FCF substitutes for EV/NOPAT in the discussion above, with companies getting modest credit for the lower cost of capital via debt - although I typically don’t underwrite in excess of ~20x EV/NOPAT in the vast majority of situations.

There are plenty of places you could poke at my methodology, and there are plenty of other ways one could reasonably approach valuation. The above discussion is obviously just the abbreviation of a meaningfully more nuanced analytical process. But here’s what I like about it.

1) It’s generally more conservative than how most people (in the current market environment) value companies, and generally maps well to long-term intrinsic value creation.

2) It keeps me focused on the important variables (i.e. the drivers of NOPAT growth over the long term - i.e. revenue growth and margins), and keeps me away from big risks (secularly declining industries and leveraged balance sheets.)

3) What it gives up in precision, it gains in tradeoffs / opportunity costs: by not wasting time building (and maintaining) models with a false degree of precision, I’m free to spend more time thinking hard about the qualitative drivers of the inputs into the model.

Of course, there are exceptions. For example, this discussion primarily applies to companies which need little capital to grow. More capital intensive companies where growth is necessarily linked to reinvestment (like AerCap) are often valued by using ROE and an assumed growth rate to determine an appropriate multiple to book value per share. In other instances (like Fogo de Chao), they might be valued on a DCF that does incorporate unit-economic assumptions.

Indeed, I do sometimes use DCFs when situations aren’t well-captured by the model above - and I occasionally also play around with DCFs just to help me understand the range of values that could be possible long-term under different scenarios.

Finally, I use relative valuation mostly as a negative filter. I will rarely justify a valuation by saying “X was bought for Y” or “Y historically has sold for Z,” and I never make investments based on “greater fool theory” (well, this is overvalued, but it’s gonna get even more overvalued.) Nonetheless, in some instances, relative valuation can be helpful - for example, I had successful outcomes buying two home security companies (ADT, in its previous public-company iteration prior to the Apollo buyout, and Alarmforce) that were trading meaningfully below long-term EV/RMR transaction averages despite strong fundamental outlooks.

In most cases, though, I simply try to ascertain that my fundamentally-derived valuation is not out of whack with what the market has been willing to pay over a long time horizon for the business in question, or for similar businesses - if my valuation is meaningfully above that, it’s a warning sign to stop and think about what I might be missing, or whether the market will eventually see what I see.
With some exceptions discussed below, we generally tend to use management as a negative rather than positive filter: very rarely will we assign a “management premium” to a company over and above what we believe the business merits, but more frequently will we assign a “management penalty” to a company that routinely makes idiotic decisions (for example, Monotype’s stupid acquisitions of stupid companies in stupid sectors at stupid prices, with a completely stupid strategic rationale. I am really keeping my thoughts on that company’s actions close to the vest here.)

The most important characteristic we assess in management is character - we’ve learned through our own experience (as well as read from the eminent dead) that you simply can’t make a good deal with a bad person. While much bad behavior is private (as exposed by, for example, the #MeToo sexual harassment movement), thankfully, for our purposes, most corporate bad behavior tends to be relatively visible: management teams who enrich themselves at the expense of shareholders, or generally seem to deal in bad faith, are usually visible from a mile away.

Capital allocation is perhaps the next most important factor we assess, although - importantly - we don’t care about capital allocation with regards to buybacks, but rather only with regards to M&A. This is a heretical point of view for a value investor, but I believe it’s perfectly logical. Paying too much for share buybacks is a reflexive risk; i.e., it requires the stock price to be above a reasonable estimate of intrinsic value.

Thus, if a company’s share price is below the company’s fair value, it is really completely irrelevant whether or not management would buy back shares above fair value: if the stock gets to fair value or beyond in the future, and then management buys back stock, shareholders who buy at the current price have very little to be sad about.

The only situation in which such management activity would be of concern is if it correlated to bad capital allocation decisions elsewhere, but we find that management conception of share buybacks and M&A is often strangely uncorrelated: very thoughtful and disciplined acquirers who won’t pay more than ~8x post-synergies EBITDA for a deal may often buy back their own shares at any price to “offset dilution.” (it’s dumb, but it’s the way the world works, and we’ve learned to just roll with it - we’re covered because we treat stock comp as a cash cost anyway.)

Finally, we generally like to see management teams make good operational decisions, although we’re cautious in remembering that, first, generalist investors with limited experience of the industry often vastly overestimate their own ability to assess the sensibility of companies’ actions - running a company is a nontrivial task. Second, management teams’ actions must be weighed in context of the competitiveness of the industry and the cheapness of the valuation - an inexpensive company in a sleepy backwater niche competing against mom and pops running lifestyle businesses obviously doesn’t require management with the same level of sophistication as a highly-priced global multinational in extremely competitive markets.

Historically, while we would penalize (or entirely avoid) a company that made bad capital allocation decisions, we wouldn’t assign any premium to companies that consistently made good ones. Part of this is premised on base rates and my lack of confidence in my own ability to assess management teams other than directionally: my understanding is that most employers generally tend to overweight face-to-face interviews vs. past performance (i.e. the paper track record - an employee’s historical accomplishments.)

With limited data, it is extremely difficult to ascertain just how good management is; oftentimes, as discussed in Phil Rosenzweig’s The Halo Effect (Halo review + notes), today’s stars are tomorrow’s duds. Valeant’s J. Michael Pearson is perhaps the most recent example - many value investors (not us) lauded him as a revolutionary, game-changing “outsider” CEO; a few years later, well, everyone knows how that turned out. So, while we’re generally confident in our ability to determine where managers fit in broad buckets - i.e. “terrible,” “okay,” “good,” or “really good” - we’re careful not to put too much weight on that assessment.

Investing is, of course, an evolutionary process, and with five years of professional investing experience under my belt, I’ve grown modestly more confident in my ability to identify managers who, in specific situations and in the right circumstances, can add meaningful value through operational improvement or accretive M&A.

For example, particularly in the industrials sector, executives with big-company experience coming into smaller, historically-undermanaged companies in not-terribly-competitive niches can often execute a combination of internal margin improvement, new product development, and accretive tuck-in acquisitions that can boost the company’s value dramatically beyond that which could be reasonably underwritten on a purely as-is, organic basis.

Having missed out on a few of these situations, I’ve since learned that if I feel like that’s the sort of situation I’m dealing with, it’s OK to accept a somewhat more modest margin of safety than I would have done historically - and/or hold onto the stock a bit longer, even if it trades to or above my conservatively-underwritten estimate of fair value.
There are a number of reasons. First of all, my understanding of the empirical research is that small and micro-caps tend to outperform their larger peers over time; there’s also more opportunity for mispricing in the smaller, less-traveled corners of the market, because big funds can’t or won’t waste time looking at them, and small funds that exploit them successfully tend to rapidly grow too large to do so. This is one of the reasons that I am closing Askeladden to new clients at $50MM in FPAUM.

I openly acknowledge that there are many good arguments for investing in large caps as well, and I’m not dogmatic about only investing in tiny companies: some of the companies on our watchlist (and, historically, in our portfolio) have been well-known household names. For example, we owned home-security giant ADT prior to its buyout by Apollo. If someone told me Google was trading for 5x free cash flow, I’d obviously take a look.

However, even if there are opportunities in stocks like Google, Amazon, Facebook, and so on, I don’t feel that my point of view would add enough unique value to be worth my fee structure. There are many low-cost (index fund) or costless (direct position ownership) ways for investors to own these securities.

Additionally, there are many far larger investment firms with sector specialists and vast research budgets who dedicate a significant amount of time and resources evaluating these situations. It is unclear what advantage I would have over them. So I don’t spend much time assessing large, well-known, well-covered situations.

On the contrary, assessing small and micro caps requires a bit more know-how and unique insight that I feel like I’m well-positioned to provide. It often requires some digging to find interesting companies in the first place, and far more digging (and in-depth thought, based on years’ worth of pattern recognition mental database) to come to appropriate conclusions.

Even within the small-cap world, our portfolio tends to look very different than that of many small-cap managers; with occasional exceptions, we tend not to focus on popular “hedge fund hotels” and instead look for truly under-the-radar opportunities that few other high-caliber investors are really looking at deeply and thoughtfully.

While there are of course no guarantees and past performance is no indication of future results, I feel that this differentiated insight will add long-term investment value in excess of my fee structure, enabling me to create value for clients relative to their opportunity cost (small/mid-cap index funds.)
Some value investors like to hold huge amounts of cash; some think the opportunity cost of holding any at all is too high. I have friends on both ends of the spectrum and believe that both sides have valid reasoning.

As with the previous question, it really boils down to less of a theoretical argument for me and more of a practical, what makes my life easiest and me likely to do my personal best type answer.

Since I’m a human, not an econ, having enough cash available at all times to buy a new compelling position - or add to positions that are falling - removes me from the behaviorally challenging position of having to rob Peter to pay Paul, i.e. choosing favorites among my portfolio. (Objectively, if you own two equally undervalued stocks, and one falls by 20% while the other falls by 50%, you should be willing to sell the first to buy the second.

But loss aversion, status quo bias, and other behavioral factors make this more challenging than it sounds; it’s easy to make the right decision as a Monday morning quarterback, and much harder to do so when you’re in the game with adrenaline flowing.)  Cash is essentially the structural problem solving solution to these behavioral challenges.  If I'm Linus, then a little cash is my safety blanket.

On the other hand, to the extent that I usually have sufficient investment opportunities available with a mid-teens three-year IRR that I believe is reasonably conservatively underwritten, it is difficult to justify holding monstrous amounts of cash. From a mathematical standpoint, I’d have to believe in a high likelihood of a near-term market correction to justify holding a lot of cash.

Here’s the rough and simple math: if you earn even a modest 10% on invested capital for two years, it takes an 18% market correction for you to “break even” on the decision; if you earn 15%, it takes a correction of 25%+.

Given my belief that I have no particular insight on if or when market valuations will go down (or up, or sideways, or do the hokey-pokey and turn themselves around), I’ve decided that it’s intellectually inconsistent to hold large piles of cash in the face of reasonably strong investment opportunities. Clients can do that on their own without paying me fees to do so, and I am, similarly, very conservative in the way I run my own personal finances (I’d rather not risk what I have, and need, for what I don’t have, and don’t need.)

As such, I’ve lowered the target Askeladden cash balance from a higher level at inception and in the early days of the fund to 10 - 15%.

However, again, as with everything else on this page, this is a general guideline rather than a rule set in stone: if there are can’t-miss investment opportunities, we will go to 0% cash (although I do not plan to use leverage.) Conversely, if there are no opportunities whatsoever and the market is uniformly insanely overvalued, we could be content to sit in 100% cash until that wasn’t the case.
One difference between Askeladden and many other investment firms, in addition to not doing complex things for the sake of sounding smart, is that I also am not interested in maximizing my total achievable return. I’m more interested in my ability to maximize the amount of potential return in my strategy that I can capture.

To go back to the Peter Thiel X | Y metaphor: say that the maximum achievable return of some given investment strategy is 20% per annum. The investment manager, being human, only actually achieves 15% per annum.

Now, his friend comes up and tells him, “hey, psst. If you incorporated some quantitative AI-driven macro trading on the virtual reality blockchain, your maximum achievable returns would increase to 25% per annum.”

Let’s assume this is true. The problem, however, is that the manager only has so much time available - tradeoffs - and he only has certain skillsets and interests - trait adaptivity. Perhaps he could learn to be a macro-blockchain-whatever star. On the other hand, much more likely is that attempting to learn that new skillset would take up a long time, and not be terribly suited to his temperament, and what would actually happen is that the opportunity cost of spending time on such things would lead to his actual returns dropping to 12%.

The moral of the story is that it’s irrelevant how much return you could potentially achieve in a perfect world. We’re humans, not econs. What’s relevant is what returns we can actually realistically achieve given our constraints.

I’m always interested in expanding my circle of competence, but I want to do so in ways that have a high base rate of potential success, without many tradeoffs. Thus, I find that certain specialized industries - like clinical-trial stage biotechs - are best left to the experts in those fields; similarly, I believe that far more people think they’re good at macro and shorting than actually are.

So I have no macro views (other than obvious sensibilities to risks - i.e. if housing starts are well above their long-term average and everyone and their dog is becoming a mortgage broker, maybe it’s not the best time to buy a house.) I also don’t short - I don’t have any unique arguments; it boils down to the standard ones. Shorting decreases vol and improves Sharpe but doesn’t really increase real returns; I’m not catering to that client base anyway. Shorting has unlimited risk and limited upside, the reverse of being long. Timing matters for shorts; it requires a totally different paradigm than going long. Twice a stupid price isn’t twice as stupid. Etc.

The point is, I do only what I think I can do well, and I’m okay knowing that there are many potentially profitable opportunities outside of my wheelhouse. To put it another way, I’m 5’7 (5’8 on my driver’s license) - I’m not trying out to be an NBA power forward anytime soon.
Askeladden executes a concentrated strategy with a target of 8 - 15 positions in the portfolio, although this is a guideline rather than an ironclad rule and we might hold more or less at our discretion.

Some concentrated funds equal-size positions; we do not. We believe that exceptional opportunities deserve exceptional allocations of capital, and are willing to take 20%+ positions when we believe it is warranted (our largest position, as of this writing in September 2018, is around 34% of AUM, and we have had larger positions in the past. It is worth noting that one of our large clients likes our strategy but is uncomfortable with that level of concentration, so we set up specific position size limits for their account - and are happy to discuss the same for any sufficiently large account.)

On the other hand, we also believe that some situations may - despite being attractive risk-rewards - not merit, for whatever reason, a large position. For example, companies with customer concentration risk, or meaningful cyclical / commodity exposure, could be perfectly reasonable investments at the right price, but the position needs to be sized thoughtfully relative to the worst-case scenario for the risk factor.

As one example of this, in the case of the oilfield products companies discussed earlier, I assumed that in the worst case (if the oil market truly collapsed, permanently), they could lose 80%+ of their value. This helped inform the ~7 - 8% maximum portfolio allocation for the aggregate "bucket" of all companies in this arena - in light of the strong upside potential, in the worst-case scenario, I would have been willing to tolerate a meaningful but not fatal loss at the portfolio level.

This certainly constrained our returns and it’s easy to justify taking larger positions with hindsight bias now that things have worked out - the risk likely wasn’t as big as we underwrote - however, we’d rather be laughed at for being overly cautious than put out of business for being wrong or unlucky.

In general, then, of course with some exceptions, our position sizing looks roughly like the following.

spec / initial position: 0 - 300 bps (0 - 3% of the portfolio)

"core" position: 300 - 700 bps (3 - 7% of the portfolio)

"conviction" position - 700 - 1200 bps (7 - 12% of the portfolio)

"high conviction" position - 1200 bps + (12%+ of the portfolio)

We do, of course, think about positions in context of correlated risks to what we already own - for example, if we already own a few companies that are above our comfort level with regards to their level of debt, we’re unlikely to take a meaningful position (or perhaps a position at all) in a new company that is meaningfully indebted, because the risks are of course correlated: even if the companies are in dramatically different industries, a deep recession and the accompanying credit crunch would be meaningfully adverse for all companies with that common risk factor.

It’s also worth tying this in with our watchlist approach. I’ve found that “familiarity risk” is underweighted by many investors: I always find that my first time assessing a new company or a new industry, there are usually a few small nuances that I miss. Sometimes these are irrelevant; sometimes they can have a material impact on the company’s valuation or the fundamental attractiveness of its business model.

In general, the longer I follow a company (or companies like it), the more confident I am in my ability to accurately assess and underwrite the situation. Finally, from a behavioral standpoint, an understanding of models like hyperbolic discounting also suggests the wisdom of waiting for the “honeymoon period” to end: you may have a crush on the stock after the first date, but how will you feel about it after you’ve been cramped in a small Miata with it for twelve hours, getting all up close and personal with its undeodorized armpits?

As such, beginning around the second year of Askeladden’s existence, I meaningfully slowed down the pace of my position entry. If I determine that a new prospective position is suitable for a given position size, I will only take a modest portion of that position size - typically no more than about 300 - 400 bps, and often smaller (my starter positions are often 200 bps plus or minus some). With every quarter that goes by that nothing implodes, and assuming the valuation gap is still appropriate, I increase the position size toward its target.

Obviously, this guideline doesn’t apply to companies which I’m very familiar with (ex. I’ve owned them before or followed them for a long time), and applies less in industries which I’m very familiar with. There are still times when I’m willing to go big fast to take advantage of what I believe may be a transitory opportunity. However, in general, I’ve found that it helps me make better and more thoughtful decisions.

One additional point here: I’ve learned over time that it’s intellectually inconsistent to believe that I can’t predict short-term market movements (which has been proven - repeatedly), and to also believe that I should only buy stocks that are down from recent levels, or that at least haven’t run up significantly.

In fact, I’ve found that some of our best investments have been stocks where we ignored (often significant) recent run-ups in the stock price and focused on the large gap between the stock price and intrinsic value; conversely, historically, some of my worst mistakes have been when I allowed big price declines to invoke transactional utility (see Thaler) and cause me to frame the situation more in terms of the “discount” I’m getting to recent or historical stock price or valuation than in terms of the actual underlying utility (i.e., the underlying value).

Similarly, like many value investors, we’re naturally inclined to excitedly buy dips and gloomily not buy run-ups in stocks we already own. Over time, thanks to whiffing on much of the gains from situations like KMG Chemicals and DMC Global / Dynamic Materials, while doubling down on fundamentally worsening situations (Essex Rental prior to Askeladden’s inception), we’ve learned to be judicious about not anchoring too closely to our initial valuation and purchase price.

Price is only half the value equation: if intrinsic value is increasing faster than price, taking a bigger position might well be warranted; conversely, if intrinsic value is falling faster than price, trimming may be in order even if the stock is down from where we bought it.
As is often the case late in a bull market, it is currently popular to espouse the “buy and hold forever” strategy - i.e. identify a great business, purchase it, then never (or rarely) re-evaluate whether it still deserves a spot in the portfolio, so long as it fundamentally continues chugging along.

While this strategy has merits such as tax-efficiency, we’re a bit more old-school around here: we’re fairly valuation-sensitive, and when a stock approaches our fair value, we typically begin to trim our exposure. Depending on the stock’s exact valuation, the level of predictability of its business model, and optionality / other factors, we will sometimes continue to hold stocks even if they trade modestly above what we believe is fair value - especially for particularly exceptional businesses.

In general, we tend to have a two-bucket approach here:

“Businesses with a price.” These are the businesses we invest in that are still perfectly reasonable businesses, but aren’t “special” - we own them because they are trading at very attractive valuations relative to their merits, and thus need to sell them when that is no longer the case. We tend to aggressively trim these positions as valuation increases, and generally entirely exit the position when it meets or exceeds our fair value estimate - we are playing for the easy money, not trying to squeeze out every last dime. Examples include: ZIXI, FOGO, KFY.

“Great businesses.” These are the businesses that we believe have significant long-term value creation potential, which we are willing to hold onto longer than we would with businesses in the previous category. Examples include: FC, BOOM, KMG.

Historically, we have found that we tend to sell stocks too soon. On the one hand, this is a common trait among value investors over the long-term, both historically and in the experience of some of our mentors with decades of market experience. So we’ve attempted to get a little more patient and realize that once market sentiment changes on a stock, we often underestimate how conservative our underwriting standards are relative to those of other investors.

On the other hand, it’s also worth considering that the current market environment - with constantly-rising multiples, for the most part - has been very favorable to buy-and-hold strategies, and very unforgiving to extremely valuation-sensitive investors. As such, we’re careful not to “overlearn” from a limited data set, and generally intend to stick to our policy of being disciplined on valuation on the sell-side.

Since inception, given the generally favorable environment, we’ve found that most holdings have positively rerated dramatically faster than we had underwritten, resulting in our strong returns. We do not believe that this would occur in all market environments, and continue to believe that a 3-year underwriting horizon is appropriate. We anticipate that, over time, our turnover will decrease, along with returns, if the market takes longer to revalue our portfolio positions.
For obvious reasons (protection of proprietary intellectual information on which our business is based), I’m not going to publicly share every name on the list. However, I can provide some high-level details. As of early September 2018, the watchlist contains ~120 companies, broken down as follows:

113 listed on domestic U.S. exchanges

7 listed on foreign exchanges (all developed countries - 2 UK, 1 AU/NZ, 1 Vienna, 1 Sweden, 2 Canada)

Here is the segmentation by market cap:

21 are <$300MM market cap (~18%)

14 are $300MM - $500MM market cap (~12%)

29 are $500MM - $1B market cap (~24%)

15 are $1B - $2B market cap (~13%)

15 are $2B - $5B market cap (~13%)

16 are $5B - $10B market cap (~13%)

10 are $10B+ market cap (~8%)

To summarize the numbers, 30% of the companies we follow are $500MM or less in market cap, ~55% are $1B or less in market cap, and ~67% are $2B or less in market cap. Additionally, our portfolio exposure tends to skew to a lower market cap than our watchlist due to (in our experience) the higher prevalence of bargains among the smaller companies on our list: although it of course varies over time, as of early September 2018, our portfolio exposure is heavily skewed toward sub-$1B - and, in particular, sub - $500MM companies:

~ 31% sub-$300MM market cap

~ 33% $300 - $500MM market cap (of which, interestingly, all started out as sub-$300MM and earned its way higher based on solid performance)

~ 11% $500MM - $1B market cap

~ 8% $1B - $5B market cap

~5% $5B + market cap

(~11% cash)

I spend roughly half of my time reading broadly, or, in other words, not engaging in what would classically be considered “investment research.” Why?

I address the question in depth in my Q2 2018 letter. However, briefly, to rip off Charlie Munger, attempting to go through life all hedgehog-like, with only One Big Idea that drives all of your thinking, is “like being a one-legged man in an ass-kicking contest.”

As I discuss in the Q2 2018 letter, I think that data availability is rarely the bottleneck for good decisionmaking. There are, certainly, plenty of instances in which data insufficiency is a problem, and I’m not saying that more data couldn’t help solve many problems.

However, oftentimes, the bigger problem is simply getting people to respond appropriately to the data that’s already available: we all know, for the most part, what we should be doing to improve our health (eat right and exercise), and yet there are many medical doctors in America who smoke cigarettes. Hint: it’s not because of a lack of data on the carcinogenic effects of cigarette smoke.

To the extent that it’s my job to collect, analyze, and interpret data on whether or not specific public companies are interesting investment prospects, data collection is rarely the bottleneck. Even in the cases of investment mistakes, when I look back, it wasn’t a lack of information (in most cases) that led to the mistake - it was my failure to interpret the information appropriately.

Utilizing a multidisciplinary approach broadens my schema and helps me understand the base rates that might apply in a given situation. Investors are often criticized for seeing the whole world through the lens of a DCF model spreadsheet; I try to take the opposite approach and understand the world through many different lenses to build a more complete mental picture.
It’s a good question. In classic high school debate stype, I have three responses.

A) Fully-dedicated internal resources are not the only way to counterbalance overconfidence or impulsive decisionmaking.

As someone with a growth mindset and a deep appreciation of the critical importance of approaching problems from multiple perspectives (see: schema mental model), I routinely seek outside perspective on many issues, ranging from business decisions (such as whether or not to retain a certain service provider) to research (i.e aspects or angles of an investment thesis that I might be missing).

I’ve attempted to cultivate a broad range of resources for accomplishing this. First, I have a few very close relationships with other investment managers - all of whom have substantially more experience than I do - and these relationships have influenced my analytical and portfolio management decisions to what I believe is an appropriate degree. I am always the one and only decisionmaker, but soliciting perspectives from these trusted resources is almost always helpful (even if I end up disagreeing).

Second, I have a broader - but still highly selective - group of investors with whom I occasionally share ideas. The investors I choose to touch base with depend on the idea; one of my emerging fund manager friends loves industrials as much as I do, while another will never look at them because he finds them boring. However, there’s almost always a handful of smart investors I can share research with if I feel like I need a sharp additional set of eyes.

Third, I occasionally utilize mass-audience platforms like Seeking Alpha or SumZero, or ACM letters to publish investment research and reference ideas; although I plan to do this more selectively in the future, it can still be helpful.

B) Fully-dedicated internal resources are often not the best way to counterbalance overconfidence or impulsive decisionmaking.

Internal politics issues can arise when disagreements between colleagues may affect compensation or job security: I’ve heard of many instances (both within and outside of the investment industry) when larger team sizes actually magnified the echo chamber effect.

Conversely, truly independent third-parties whose compensation and livelihood is not tied to their opinion can often provide more objective, more insightful critique. When I share ideas with other investors I know, it’s no skin off their nose if we ultimately come to completely different understandings of the situation.

C) Approach and process before a conclusion matter as much as the sanity-checking after a conclusion. See the “temperament” section. If you approach research with the mindset that you’re God’s gift to the public equity markets, it is unlikely that any amount of feedback from any number of third parties will help you come to a more objective conclusion.

On the other hand, I always try to remain humble and cognizant of the fact that I have limited resources relative to many other larger generalist funds, limited experience relative to many other investors, and plenty of past goof-ups.

Although I’m only human and undoubtedly still continue to be subject to human traits such as overconfidence and desire bias, I try to approach the world with an open-minded, growth mindset perspective: I’m more interested in learning than proving myself right. I always try to change my mind when the overwhelming preponderance of data suggests that my existing beliefs are inaccurate or maladaptive.

So I’m often playing devil’s advocate with myself throughout the research process - if I want to jump to the conclusion that “this is a great business,” I often try to stop and ask myself “okay, but what are the points that suggest it might not be as great?” This helps me avoid confirmation bias and narrow framing.
Well, okay, but you have to promise you’ll show me yours after, so we can compare whose is - uh - never mind.

Before proceeding, please note three important factors:

A) This research has not been modified from its internal counterpart other than to redact certain portions - for example, long excerpts from news articles / industry reports, or notes from 1x1 management meetings, that for obvious reasons I do not feel is appropriate to (re)publish in a public forum.

B) Some of my research documents are typed using voice dictation, so please excuse any typos.

C) Most importantly, obviously, I’m sharing research pieces that I’m proud of, which tends to mean that either they resulted in a good outcome for me, or they were just exceptional pieces of research. Not all of our research is this presentable or actionable or useful. I don’t want you to think that all of our research looks like this, or that what I’ve posted here is exactly what all of our research looks like. The point is to help interested parties learn more about the general thought process that goes into the Askeladden approach.

Be aware (generally speaking) of issues with cherry-picking / selection bias: since inception, we’ve been extremely fortunate to have the vast majority of positions work out very well. Conversely, I made plenty of mistakes in my personal account prior to launching Askeladden - such as bad decisions in levered, cyclical / commodities driven companies, in some cases with bad management. I learned a lot from these mistakes, but they’re unfortunately not documented as thoroughly as more recent research.

With that in mind, here’s a sampling of Askeladden research, ranging from “briefs” or idea writeups (before we stole our research documentation approach from Zeke) to full-out, longitudinal research documents (in the post-Zeke era, excluding some companies we’ve followed for a long time). KFY/FOGO/FC are old-style notes; ZIXI/PFIE/EEX/ASPN are new-style research documents.

Something we (are) invested in with extremely high conviction:

Franklin Covey (FC). There’s not much to say here that hasn’t already been said in various writeups. Here’s our initial take; here’s a later update from a letter. The story has continued to get better; FC is now signing clients to multi-year deals, which is a complete transformation from the completely discretionary nature of client purchases merely a few years ago.

Something we invested in with conviction:

Fogo de Chao (FOGO) and Korn Ferry (KFY). Both were similar stories in that they were uncomplicated business models with attractive attributes we felt were underappreciated by the market; both had their own risks and flaws but not enough to offset their very inexpensive free cash flow valuations. Both ended up being high single to low double digit positions that we exited profitably once the market valuation reflected our base case expectations. (In the case of FOGO, we actually managed to own it twice.)

Something we invested in in a small way:

Profire Energy (PFIE) and Zix Corp (ZIXI). Profire was a small oilfield technical-products company with very attractive financial characteristics and a leading position in a very niche market, offset by the obvious risk of oil prices. As a small position established before sentiment on North American shale drilling had reached its current level, it worked out well for us, although given the commodity risk we don’t regret not owning more.

Meanwhile, Zix Corp (ZIXI) is a small software company, conveniently headquartered right here in Dallas, that we had followed for about a year and a half. We had met with the new CEO and liked the story quite a bit, but were never comfortable with the valuation, primarily because the company had a large balance of NOLs/DTAs (net operating losses / deferred tax assets) that meant it was paying very low to no cash taxes. The conceptually correct way to value these is on an NPV basis - they do not last forever, and at some point in the future the company will have to pay cash taxes - but many investors, including those on prominent value investing sites, very lazily and inappropriately simply capitalized the company’s current FCF stream, resulting in a valuation that was always out of reach for us.

Subsequently, two things happened: first, the tax cuts significantly reduced the materiality of the NOLs to the valuation; second, Zix encountered some modest exogenous headwinds that we viewed as likely transitory and, in any event, not fatal to the business model. The stock traded down to a valuation that we viewed as extremely attractive, and we pounced. Sadly, it didn’t stay there long enough for us to build up the position size we would have liked, but we won’t complain about a quick and strong return on capital with what we feel was minimal fundamental risk borne, given the company’s strong product offering, recurring revenue, and very strong, cash-rich balance sheet with thoughtful / capable management.

Something we have yet to invest in:

Emerald Expositions (EEX) [updated document with September 2018 additions coming soon]. Emerald is an operator of trade shows that we’ve now followed for a year and a half - our watchlist told us it was worth looking at again recently. It’s a phenomenal business model, with 40%+ EBITDA margins, minimal capex needs, great cash dynamics (exhibitors typically book and pay for booths months or years in advance of the show), and a seemingly strong consumer value proposition with a network effect - if you own the biggest trade show in a space with all the important exhibitors and attendees, it is hard for a newcomer to replicate that advantage.

Offsetting these very attractive characteristics, the industry appears to be somewhat cyclical (attendance in NAM is just now recovering to pre-2008 levels), Emerald has >3x debt-to-EBITDA (manageable, but on the high end), and the company’s exposure to the challenged retail end-market has depressed its organic growth since its IPO. Although the stock price seems reasonable, it’s not quite attractive enough for us to get involved, so we remain in wait-and-learn mode.

Something we invested in that didn’t really work out:

Aspen Aerogels (ASPN). Although we had an “okay” stock price outcome, fundamentally, this story just wasn’t playing out the way I expected; the product didn’t seem to be gaining traction quickly enough to offset the risk of the company’s balance sheet continuing to whittle away. After a year or so of involvement, I decided that our capital (and my brain cells) were better spent elsewhere. It may yet work out very well - or it may implode. I don’t feel like I have a reasonable foundation on which to make that assessment at the current time - and therefore, I don’t own it anymore.

In retrospect, the position was probably sized a little too large relative to the quality of the underlying business.
Historically, I’ve been relatively public (via forums like Seeking Alpha, SumZero, as well as ACM investor letters) about our portfolio holdings. It’s no secret that as of September 2018, Franklin Covey is the largest position in Askeladden’s portfolio.

Going forward, however, I intend to be more selective about such disclosure, to protect the proprietary nature of the work we do. Prospective clients are welcome to ask about current ideas, and I will likely answer, depending on the discussed account sizing - but I’m also increasingly careful about ensuring that I’m able to monetize the work that I do.

You’re Still Here? Oh, for the Post-Credits Scene. (Miscellaneous Questions I Often Get)

No - sorry. It’s nothing personal, I promise.

I've tried it several times, and what I've learned is that my investment approach is so hands-on that it's very difficult for me to derive value from interns without merely assigning data collection type grunt work (which I don't want to do). I can’t find a way to utilize internal resources without incurring too much overhead, so I’ve stopped trying - it’s a different skillset from investing and not one I need to develop given ACM’s long-term business plan.

I am, nonetheless, always happy to be a sounding board for questions / thoughts / investment ideas / etc; I have a soft spot in particular for people from nontraditional backgrounds or non-target schools. I cannot guarantee a detailed response (or a response at all) depending on how busy I am and how interested I am in the topics you bring up. But I'm usually pretty responsive, even if it sometimes takes a while - it never hurts to email and you're encouraged to do so.
I wasted way too much time reading investing books when I was a beginning value investor. Most people do the same. The truth is that value investing is like learning any physical skill like hitting a tennis serve: you can read all you want about the physics of it, but you’re only going to get better at it by actually going outside and doing it.

Value investing theory is relatively straightforward and merely three books, with the supplement of Warren Buffett’s annual letters and perhaps his biography Snowball, contain all you need to get started:

The Most Important Thing (Illuminated) by Howard Marks The Manual of Ideas by John Mihaljevic The Art of Value Investing by Heins/Tilson

If you want to become a better value investor, spend more time actually working on value investing. It’s amazing how many people I run into who’ve read tons of value investing books but can’t translate the theory into a brief, thoughtful writeup on a company of interest. It’s nontrivial and takes practice, so get to it!
You may have noticed that I have an e-mail handle (and twelve t-shirts) that say “Maximum Effort.” It’s a catchphrase from Deadpool, a superhero who’s not so super. Deadpool likes to mess around and not take things too seriously… he is a bit, but not quite, like Richard Thaler, whose greatest trait (according to Danny Kahneman) is being so lazy that he only works on really interesting problems. I’m Thaler in this analogy.

Anyway, Deadpool occasionally encounters a situation where he has to stop messing around, be serious, and give “maximum effort” - not all that often, but once in a while. It kind of captures or resonates with my personality in some ways: I somehow manage to be both the person who’s never doing much most of the time, and the person who gets more done than most anyone I know (in brief spurts of intense focus).

Anyway, it’s a little “nudge” to not take things too seriously most of the time, but show up ready to fight when it counts...
My history with the character is longstanding. When I was tiny (maybe six or seven, and always small for my age), my mom would take me to the big library in the next suburb over and let me spend afternoons reading books that were bigger than me. Some of my favorites, at the time, were Norse mythology.

Anyway, in middle school, playing a video game called RuneScape (which taught me more about supply and demand than anything in B-school), I re-encountered the character under the name “Askeladden,” which reintroduced me to the character’s history. Askeladden - often actually called “Boots” - is the youngest of three brothers and the runt of the litter, but ends up besting the troll or winning the princess through his wits rather than through brute force or connections.

Per Wikipedia: Ashlad (Norwegian "Askeladden") is the main character in many Norwegian folktales. In some ways, he represents the small man who succeeds where all others fail. He always wins in the end, often winning the princess and half the kingdom.

… In many folk tales, the Ash Lad is portrayed as the youngest of three brothers. Early in a typical tale, the older brothers appear to have much greater chances of success in life. … In contrast, the Ash Lad is looked down upon as a seemingly drowsy ne'er do well, perhaps even as a loner or misunderstood eccentric, who spends too much time sitting by the fireplace lost in thought as he is poking the ashes.

… The two older brothers, who are tied to conventional thinking, typically fall flat on their faces. In contrast, it is the Ash Lad who comes up with creative solutions. He is smarter, more tactical, more receptive and more aware of the needs of others. He outwits trolls, dodges charging unicorns or gets a magic Viking ship to transport him where he ultimately saves the princess.

… “In modern parlance, the Ash Lad is an individualist, free-thinker, and nonconformist who is capable of deep abstract, analytical thinking “outside the box”, or who can create a scientific paradigm shift. He is capable of acting as a true visionary or innovative early adopter.”

Being a teenager and thus prone to make inexplicable decisions, I decided that I was going to call myself “Ash” instead of “Samir,” and did so for several years in certain contexts. Various email addresses I used to have included “the ash lad” in some form or another.

Years later, when I decided to start my hedge fund, I found empirical proof that there are too many hedge funds: it’s damn near impossible to find a name for one that someone else hasn’t already taken. My initial preference was Texan-themed names (cowboy, lone star, etc) - all taken.

I thought “Roark Capital” would be iconic, and it turns out that is already a private equity firm. “Patel Capital” seemed presumptuous since, A, Mr. Patel is my dad, and B, there are like a trillion Patels in the world (don’t run the math on how that’s possible given the global population is orders of magnitude lower - just accept it as a strange but true fact.)

And then Askeladden came to mind - and the Askeladden character description and story arc seems to pretty much fit what we’re trying to do around here. So there ya go.
[in my best Morgan Freeman voice]

Let me get this straight: you think that your employer, one of the richest and most powerful men in the world, spends his nights beating criminals to a pulp with his bare fists… and your plan is to blackmail this person?

Well, good luck.
Richard Thaler, Don Norman, and Laurence Gonzales.

No comment on whether or not I would torment Thaler with an illusory bowl of cashews (or a real bowl of cashews that magically refilled itself and floated a few inches in front of Thaler's nose, throughout dinner and even after). Or whether or not I would torment Norman by hosting the party in a building filled with horrible, terrible, no-good, very-bad Norman Doors. Unfortunately, Gonzales seems un-tease-able, so I don't know how I'd make him feel at home...
Nope! None since high school, and not planning to go down that road for… like, several years, at least. I was on dating apps for about a month one time and it was an unmitigated disaster. (I was far more interested in long-form bios and educational/work attainment than pictures, which seemed only of tertiary importance given their profound lack of predictive ability of relationship success or interpersonal chemistry.

My guy friends just laughed at my naivete. But I was so confused as to why anyone did this swiping nonsense. Clearly these apps were not designed with me in mind.)

There is a time and place for everything and I’m too focused on long-term outcomes to have any interest in short-term distractions that are statistically unlikely to lead where I want to go (see: base rates mental model).

Honestly, at the moment, I would much rather have a dog. (Dogs always love you and will never leave you. There is no drama or emotional volatility with a dog. Just pure, unadulterated affection.)

If you’re planning to convince me that I should be dating, just FYI, my parents, best friend(s), and mentor have already tried and failed. Your base rate ain’t very good 🙂
See the previous question. I have no reason to do otherwise. I like my family and would be lonely living on my own; they like me back and would miss me. Why pay rent in exchange for disutility on both sides? I manage my dad’s IRA free of charge (the economic value of which far exceeds reasonable rent on a room), I cook half the food (which I always pay for), and I just generally try to be a helpful person, so I’m not the typical boomerang Millennial. I’ll move out when I have someone else to move in with. That’s not gonna be soon.

There’s also a bit of cultural gap here that you have to understand: as Texan as I am (there’s literally a Texas flag above my bed), there are still some aspects of Asian-American culture that have rubbed off on me, one of them being the somewhat different conception of family. In India, it’s not uncommon for kids to live with their families until they get married; it’s also very common for elderly parents to subsequently move in with their children. (Given that I’m an only child, we’ll see how my future wife feels about that one.) We’re not in Kansas - I mean India - anymore, but some of the values still persist.
Well, maybe. I have empirics, sort of: https://www.hbs.edu/faculty/Pages/item.aspx?num=45809

But really, I’m just not interested in changing who I am for the sake of monetary gain. Most of my friends think I’m crazy for deciding that I’m going to close ACM to new clients at $50MM in FPAUM. It’s a pretty easy decision if you understand my life goals, which have very little to do with maximizing my personal wealth. Marginal utility is an important model here; beyond enough income to support a family at an upper-middle-class lifestyle, other factors tend to become much more important in personal happiness (per empirical research).

Autonomy tends to be one of those factors, and it’s particularly one for me. If I wanted to let other people tell me what to wear, how to talk, and when to wake up in exchange for throwing large checks at me, I could do that much more efficiently working for someone else. I didn’t start my own shop to do that.

Askeladden clients tend to appreciate that I’m authentic and honest about who I am, as well as who I’m not. (I am a kid in the suburbs in a bedroom; I am not a Big Institutional Investor and I’m never gonna be - so why bother acting and talking like one?)

I plan to win on performance, not pedigree. Investors who want Midtown offices and Hermes ties and wingtips and so on can get that somewhere else - and there’s a tradeoff (see the GSElevator twitter feed).

I really care about doing a good job; I don’t much care about looking like I’m doing a good job - and I’m much more interested in clients looking for the former rather than the latter.
If you are on this site looking for recipes, you are either exceptionally lost or Google is exceptionally broken.

Nonetheless!  I eat pretty much everything except blue cheese, cardamom, and more than a tiny bit of cilantro (I’m one of those people who is super sensitive to cilantro, which is amusing because I grew up eating not one but two cuisines that prominently feature cilantro).  I also don’t do raw fish other than in small quantities (I can eat sushi rolls and tuna towers… tried and failed to eat sashimi once, and won’t even bother with ceviche.)  Other than that, I’m pretty adventurous - I’ve tried and liked squid-ink spaghetti al mare, for example.  (I didn't make it myself.  I just ate it somewhere.)

I’m not a vegetarian - I grew up in Texas, for crying out loud, although I had a dalliance with Kansas City style BBQ that I may tell you about depending how much trust we’ve built up and how nicely you ask - but I’m moderately obsessed with vegetables, and tend to cook/eat vegetarian a lot of the time.  I’m a bit of a protein skeptic and my diet tends to be heavy in complex carbs, vegetables, and unsaturated fats (i.e. loads of real extra virgin olive oil, sometimes walnuts) with some meat maybe every other day.

I’ve made friends with pretty much every veggie in Sprouts except turnips and radicchio.  Turnips just suck, and I had a really bad experience with radicchio once (horribly bitter) that I haven’t yet overcome. <

Favorite things I’ve made:

(regular basis)

Risotto, usually with either mushrooms, or with this kale puree (kale puree is a total winner on everything)

Farro is awesome any way you cook it.  Just cook it in broth with some aromatics and sautee some vegetables and you’re good.

So is pasta… particularly in unexpected presentations, like this (heavily modified to be more flavorful / spicy).  Also this, minus the ricotta.  Also, do yourself a favor and toast some panko with a few diced garlic cloves, a little good butter (Kerrygold or the like), a little high quality olive oil, some aromatics (sage / rosemary), and salt/pepper.  Then toss it on pasta with nothing more than high quality EVOO and parmesan. If you’re feeling fancy, caramelize some lemon slices (blanch first in salted water, then cover in sugar and cook on low until nicely browned) and put those on there too.

Wild rice + brown rice with shiitakes, onions, lemon, and garlic.  Dried shiitakes seriously changed my life. Thanks to John for saving me from flavorless grocery-store mushrooms…

Greens - swiss chard, lacinato kale, broccoli rabe, random South Indian green sorrel-ish stuff that one of my mom’s friends gave us, even spinach in a pinch.  I’ll take them all. often with walnuts/parm/evoo/lemon/garlic/chile, or same minus the walnuts and parm. Still looking for another reliable standby.

Chicken paprikash.  This, directionally.  One of the first chicken dishes I’ve liked enough to want to make again over and over.

Roasted Cauliflower hummus - no really, you have to try it.  Cauliflower does NOT make a crust (sorry, paleo folks) but it does make a really good hummus.  Eat fresh (doesn’t taste as good once it’s sat, sadly).

Muhammara.  This stuff’s high end restaurant-level, and you can do it at home pretty quickly.  More red pepper, more aleppo, no cayenne, more pomegranate molasses, a tad more than half the lemon.

Maple-lemon-smoke glaze (grade B or really dark grade A maple syrup, fresh squeezed lemon juice, liquid smoke) - reduce until tacky. I put it on sous vide turkey and it was AWESOME but really it would probably go on a lot of things. My maple syrup budget just went through the roof, I think...

Roasted vegetables - often brussels sprouts (these, directionally - the lemon-garlic-yogurt sauce is winner; plan to make about a million times as much as the recipe calls for), broccolini (this, directionally), or carrots (with fennel/etc over coffee beans), sweet potatoes (my own recipe - I infuse EVOO with lots of fresh rosemary + sage, diced garlic, cracked pepper, and some form of spice, i.e. red chile flakes or grated homegrown serranos, and then I strain out the spices, toss the sweet potato cubes in oil and salt, and bake at 375 convection until they mush easily.)


(special occasions)

Dean Fearing’s Texas Red chili.  I will FIGHT YOU if you put beans in my chili.

Chicken enchiladas with tomatillo-sour cream sauce.  (this, directionally; I forget what modifications we make)

Seared halloumi cheese with blackberry-balsamic reduction, wrapped in hatch chiles.  As good as it sounds… if only halloumi cheese weren’t stupidly expensive.

Brisket, served refrigerated rather than hot.  I know that sounds weird. I don’t smoke my own brisket… there are plenty of people around here who do that way better than I ever could.  I just came up with the idea of eating it cold.  

The Latticework of Mental Models

Poor Ash’s Almanack > The Latticework of Mental Models

Below are links to pages containing 100+ critically important mental models I’ve gleaned after years of reading hundreds of books.  I’ve condensed them into 37 highly interlinked pages, because association enhances learning, and because the models are more powerful when they’re interacting.

The sidebar on page 55 of Poor Charlie’s Almanack quotes Charlie Munger:

“I’ve long believed that a certain system – which almost any intelligent person can learn – works way better than the systems that most people use.

What you need is a latticework of mental models in your head.  And, with that system, things gradually get to fit together in a way that enhances cognition.

However, my particular approach seldom seems to get through, even to people of immense ability.  Things usually die after going to the ‘Too-Hard’ pile.”

Lots of people talk about mental models; few have built an actual latticework.  It’s easy to see why: building this latticework – comprising over half a million words in total – was the hardest thing I’ve ever done in my life.  And I’ve done some pretty hard things.  No kidding on the “too-hard” pile.

I read two books a week.  I’ve structured my life so that reading and learning can be primary priorities.  Most people, unfortunately, don’t have that kind of time or cognitive capacity after all their other professional and personal commitments.  As one Poor Ash’s Almanack reader put it,

“One thing that’s really difficult for me is that there isn’t enough time in the day to attack everything I want to read […] my list of things to read is way too long and not shrinking quickly […]

sometimes I can’t bring myself to [sacrifice near-term performance measures] so I can read something that will be more useful down the line.” 

The sidebar on page 55 of Poor Charlie’s Almanack goes on to mention:

“Simplicity is the end result of long, hard work, not the starting point.”

Nothing substitutes for your own reading, thinking, and application.  But I hope this latticework of mental models – spanning the models, their interactions, and many of the books in which you can find them – makes that hard work a little easier for you.

The Poor Ash’s Almanack Latticework of Mental Models

Psychology / Neuroscience Mental Models

The Multidisciplinary Rationality Mental Model

This mental model is where you should start if you’re not familiar with the mental models approach – it covers sub mental models like man-with-a-hammer, circle of competence, and mapmaking, helping you to understand exactly what you are trying to accomplish in the process of enhancing your cognition.

The Sleep / Chronotypes Mental Model

When you’re sleep-deprived – like 70% of adults and anyone who wakes up with an alarm clock – you may be the equivalent of “legally drunk,” and neuroscience finds your prefrontal cortex – the home of rational decisionmaking – may be in an “offline, disabled state.”  Sleeping 8+ hours a night – at the right time of day, as determined by your individual genetically-determined chronotype – rather than society’s demands – is critical to your productivity and health.

The Cognition / Intuition / Habit / Stress Mental Model

Very few people have a full understanding of how our decision-making process actually works.  It’s critical to understand the disparate (but interlinked) systems of cognition and intuition, how the former modifies the latter via habit/conditioning, and how stress can dramatically distort our decisions – plus, of course, how we can combat that amygdala hijack, both in the moment (short-term) and through longer-term approaches to life.

The Culture / Status Quo Bias Mental Model

Many brilliant thinkers point out that much of what we do has no fundamental purpose or prevailing reason.  Much human activity, on the contrary, is shaped by “status quo bias” or “culture” – our tendency to do what we (and others) have historically done.

This is generally adaptive, but can lead to some crazy outcomes.  Understanding sub-models like default options and opt-in vs. opt-out can help us make more effective decisions – and “nudge” others to do the same.

The Overconfidence / Intellectual Humility / Scientific Thinking Mental Model

Overconfidence is a powerful human trait – one that is adaptive dose-dependently, but quite dangerous in many situations (whether we’re hiking or making business decisions.)

It shows up in many contexts – understanding the sub-models like fundamental attribution error, the planning fallacy, and desire bias can help us avoid bad decisions.  Meanwhile, by inversion, shifting to more of a cautious, scientific thinking process can also enhance our cognition.

The Schema / Selective Perception Mental Model

Everyone’s heard of the “confirmation bias” mental model, but few people actually understand the important psychological and neurological mechanisms that underlie it.  Before we ever even perceive information; our brain automatically filters out some of it (selective perception) – which can be dangerous; pilots have missed planes on runways and radiologists have failed to notice missing clavicles in X-rays.

Once whatever’s left gets to our brain, we actively filter out some of the rest of it – using our schema, or worldview.  It’s critically important, then, for us to make sure we have a worldview that avoids ideology and lets the right stuff through while keeping the wrong stuff out – while also developing structural solutions to prevent missed perceptions.

The Fairness / Loss Aversion / Endowment Effect Mental Model (Deprival Superreaction Syndrome)

Humans do not like things being taken away from us.  The esoteric, technical scientific jargon for our behavior when we’re deprived of something we believe we have a right to is “batsh*t !@#$ing crazy.”  Charlie Munger calls it the deprival “super” reaction tendency because it can even trump incentives.

Yet whether as business managers, parents, or individuals, we routinely fail to account for this scientifically-demonstrated cognitive bias in others – as well as ourselves – and it dramatically shapes our behavior, often in maladaptive ways.  Sub-models include “loss aversion” (that we feel losses 2x as much as equivalent gains), “the endowment effect” (our curious tendency to value things we have more than we would if we didn’t have them), and “fairness” (our surprising tendency to reject offers that are good for us if we deem them “unfair.”)

The Contrast Bias Mental Model

We’re biologically wired to notice changes – but only above a certain threshold.  Those below this threshold might fly below the radar – to our detriment – unless we do something about it.

Contrast bias drives sub-models like self-justification (the process by which we rationalize our bad behavior) and anchoring (our tendency to make judgments in relation to already-known quantities).  An interaction between contrast bias and mindfulness is also an easy, scientifically proven way to make ourselves happier.

The Salience Bias / Availability Heuristic / Recency Bias Mental Model

Stuff that sticks out vividly in our minds – and thus is more “available” to our cognitive processes – disproportionately drives our decisions, for better or worse.

Understanding how these related cognitive biases of salience, availability, and recency work can help us enact structural problem solving solutions that ensure more accurate information is available to us for making decisions.  It can also help us communicate more effectively with others, by conveying information in a way that they’ll remember.

The Human Memory Mental Model

Our memories have hard biological constraints that we cannot escape – yet we frequently, and foolishly, rely on them for critical short-term and long-term functions.

Developing a thorough understanding of the workings of our memory can help us avoid decision-distorting sub-models like hindsight bias – and will also encourage us not to engage in multitasking, scientifically proven to be an ineffective way of getting things done

The Planner-Doer (Hot-Cold Empathy Gap / Hyperbolic Discounting / Present Bias) Mental Model

One of the greatest lies of human existence is the myth that if we don’t feel like doing something today, we’ll magically feel like doing something tomorrow… or this time next year.

We experience life as a series of moments, thus dramatically overestimating our self-control and willpower at future points in time, and dramatically underestimating how much specific circumstances (like hunger, exhaustion, stress, arousal, or craving) will affect our decisions.  Understanding this “present bias” mental model allows us to make better decisions – as both individuals and organizations – that maximize our long-term utility.

The Product vs. Packaging Mental Model

When we purchase a product or service, we only get to consume that product or service – not the irrelevant “packaging” we’re just going to throw away.  Yet we often let this irrelevant “packaging” – like someone’s appearance or educational background, or whether something looks like what we expect or want it to look like – distort our cognition by substituting for the real “product” information that’s important.

Sub-models include busyness vs. productivity – hard work, it turns out, is not only not always effective, but sometimes it can actually kill you – as well as precision vs. accuracy, which explains a lot of low-utility professional activity.

The Sunk Costs / Consistency Tendency and Commitment Bias Mental Model

There’s no use crying over spilt milk – but we do anyway.  Perhaps no tendency of human cognition is more paradoxical and destructive than our penchant for throwing good after bad – wasting precious time, money, and emotional energy trying to “get back” past expenditures which simply cannot be recouped.

This tendency is powerful, particularly when it interacts with other models like incentives – as we’ll see, it can even lead honorable and upstanding citizens to kill innocent civilians and then celebrate their deaths, even though we have no justification for doing so.

The Probabilistic Thinking and Storytelling Mental Model

We tend to jump to absolute conclusions on the basis of limited data; this leads us to make decisions based on beliefs that can’t be justified by rational analysis.  Thankfully, there is a counterapproach – albeit a nonintuitive one: probabilistic thinking.

Becoming a “many-handed economist” and starting to say things like “it depends” and “it could be that, but it might also be” isn’t going to score us any points with friends (or employers), given humanity’s desire for certainty.  But if you want to make effective decisions, probabilistic thinking is absolutely crucial.

The Agency / Willpower / Growth Mindset Mental Model

“Belief behavior matters” is one of the foremost data-backed predictors of professional success and emotional / personal well-being.  Determinism and nihilism should be uniformly rejected by any rational thinker in favor of agency – the belief that we have control over our future, that no matter what happens, we always have the power to choose our response.  One important sub-model is the “growth mindset” – treating failures as an opportunity to reflect, learn, and bounce back stronger, rather than succumbing to defeat and learned helplessness.

Too much of a good thing isn’t always better, though – some immature and irrational people advocate “willpower” (sometimes known as “grit”) as the solution to all of life’s problems, despite the fact that research indicates that willpower is usually the least effective way to solve any problem.

The Social Connection and Social Proof Mental Model

Peer pressure ain’t just for teenagers – decades of rigorous research demonstrate that humans have a powerful need for social connection, which in turn drives our tendency to do things because other people are doing them.  This tendency is often subconscious, but is an extraordinarily powerful mental model that can turn our brains into mush: many intelligent, rational people will pick an obviously wrong answer to an easy question if everyone around them is doing so.

Important sub-models here including the “liking bias” and “reciprocity bias” – when we like people, or when they do nice things for us, we tend to view and treat them more favorably than we otherwise would.  This has clear applications for professional success: make other people like you, and the world is yours.  But be mindful that others can exert this same influence on you, too.

The Empathy / Empathic Listening Mental Model

The drive to be understood is so powerful that the simple act of listening to a friend discuss their challenges can dramatically boost their mental and physical health – per scientific research.  In a professional context, empathy is equally important as well: solving problems (whether our own, or those of others) often requires us being able to see the world from another person’s point of view – even if we disagree with that point of view.

The Mindfulness / Cognitive Behavioral Therapy / Happiness Mental Model

Why do many of us go through life unhappy despite a constant stream of enjoyable experiences?  Why do many of us find it difficult to abandon cherished beliefs, even as mounting evidence demonstrates their lack of validity?

Answers to these questions can be found in the practice of mindfulness; I personally use a less passive, more “active” / aggressive approach called “cognitive behavioral therapy.”  Sub-models here include “hedonic adaptation” – the tendency of our emotional well-being to remain at a relatively stable baseline (over the long-term) despite positive or negative external circumstances – and specific, psychologically-validated approaches for more accurately processing the world, and feeling happier to boot.

Effective Thinking / Problem-Solving Mental Models

The Structural Problem Solving / Choice Architecture Mental Model

What’s the easiest way to deal with a problem?  Don’t have the problem in the first place.

This approach should be intuitive to many people – it’s an underlying principle behind everything from oil changes to contraceptives – but altogether too often, as individuals or organizations, we stubbornly try to willpower our way to success, moving sand from here to there with our bare, bleeding palms rather than doing the smart thing and renting a bulldozer.

Asking, demanding, or begging people to make good decisions in a bad structure is like asking your neighbor’s Chocolate Lab to guard your steak – it’s just not gonna work.  In contrast, powerful results can be achieved using “choice architecture” to create systems where people are influenced – subtly or not-so-subtly – to make the right choices.  Structural problem solving, as we’ll explore, helped people retire with 10x the savings they would otherwise have had, without making a single lifestyle sacrifice along the way.

The Nonlinearity Mental Model (Critical Thresholds, Exponential Growth, Dose-Dependency, Power Laws)

The world looks pretty linear up close – but, just like we live on a sphere that looks flat from our vantage point, many of the phenomena we interact with on a daily basis are profoundly nonlinear in nature.  We can’t deal with this nonlinearity mentally, and often abstract it into an easier-to-understand linear framework.

Specific sub-models include dose-dependency – more of a good thing is not always better; in many cases, like Tylenol, it can be much, much worse, or even deadly.  Critical thresholds are also important – sometimes nothing interesting (or dangerous) happens until you hit a certain point, and then bam – nuclear explosion.  Exponential growth is also very hard to intuit, but has important implications for our decisions as individuals and organizations.  Finally, power laws underlie much of biology and society, and are an intriguing (rarely-studied) area to explore further.

The Trait Adaptivity Mental Model

Like many people, I used to have a naive conception of the world based upon strengths and weaknesses that I viewed as absolute – I’m good at X.  I’m bad at Y.

The truth is that strengths and weaknesses are always context-dependent: what makes a company the dominant industry player of its era can (and often has) led to challenges when the environment changes.

Observable in nature / biology as well as the world we’ve created, trait adaptivity is critical to understand for three reasons.  First, today’s strengths can be tomorrow’s weaknesses.  Second, by selecting “for” one trait, we often unintentionally select “against” others.

Third and finally, how do you beat LeBron James?  By playing anything other than basketball – understanding your traits as an individual (or organization) is critical to “game selection” and thus success.

The Inversion Mental Model

The more perspectives from which we approach a problem, the better our chances of finding a solution.  Often, starting with the end and working backwards can yield new and unusual insights not available by working forward.

Two specific sub-models here are selection bias and survivorship bias – often, when we evaluate data, we’re only seeing a small fraction of the actual sample size.  By working backwards from the present set of data to that from whence it came, we can make better and more accurate decisions.

The Incentives Mental Model

You get what you pay for – it is hard to convince someone of something when their salary depends on them not understanding it.  This pops up literally in many contexts throughout the world; incentives are easy to understand but phenomenally powerful.

The Multicausality / Disaggregation / Correlation vs. Causation Mental Model

We like to think of the world as neat and simple; the reality is that it’s complex and nuanced.  Just because two things often happen together doesn’t mean there’s any causal relationship; moreover, we often “satisfice” for one cause of a given phenomenon, when in reality there may be more than one – whether we’re talking about structural failure or a medical condition.

Learning to break the world apart and analyze its constituent components is a process used by most successful entrepreneurs and investors.  Sub-models include “emergence” (from complexity theory) and the “Swiss Cheese model” of causality (describing how accidents happen.)

The Priors / Bayesian Reasoning / Conditional Probabilities Mental Model

In beloved teen flick The Perks of Being A Wallflower, freshman English teacher Mr. Anderson encourages his bright student, protagonist Charlie Kelmeckis, to “be a filter, not a sponge.”

Mr. Anderson’s talking about the delicate balance between remaining open to new ideas – necessary for progress – without letting our heads fill up with junk and nonsense.

It’s a tricky proposition.  Thankfully, there’s an approach – Bayesian reasoning and “priors” – that allows us to bridge this gap, either qualitatively or mathematically.

The Base Rates / Inside View / Outside View Mental Model

Oftentimes, we make decisions only based on the “inside view” – the view of the world we can see from where we stand.

Even if we do our best to incorporate all the necessary information, we’re missing an important view – the “outside view” – which refers to the long-term statistical frequency, or probabilistic likelihood, of a given condition, outcome, or other factor.  These are often called “base rates.”

Combining “base rates” with the aforementioned Bayesian reasoning can be a powerful decision tool – yielding completely nonintuitive outcomes about how much (or how little) to react to incremental datapoints.

The Zero-Sum vs. Win-Win Games, Arms Races + Relative vs. Absolute Skill Mental Model

I’m fond of deconstructing all the reasons why hard work is overrated.  One of the key ones is that in certain types of games – known as “zero-sum games” – for one person to win; another person has to lose.  Think of predator and prey: for the lion to eat, the antelope has to perish.

These sorts of games often turn into “arms races” – a mental model for situations in which each side works harder and harder but receives absolutely no benefit for doing so.  Key to reaching this understanding is appreciating the dynamics of absolute vs. relative skill – even as we get better and better at a given task, if our competitors are getting better too, our “relative skill” – i.e. the difference in ability between that and our competitors – may narrow.

What’s the solution?  Win-win games – where one person doesn’t have to suffer for the other person to succeed – are much easier to win at, and yield much more positive outcomes for everyone.

The Opportunity Costs / Tradeoffs / Return on Investment Mental Model

Every dollar, or unit of time, that we spend on X is one that we can’t spend on Y, Z, or the rest of the alphabet.  A powerful decision tool is thus to be aware of a small set of the best “opportunities” available to us – whether for financial capital, time, or emotional energy – and ruthlessly compare every opportunity that comes along against that one.

It’s a powerful mental model, and one that too few people apply despite knowing the concept theoretically.

The Local vs. Global Optimization Mental Model

Everyone learns about “silos” in business school, but few people fully appreciate the real-world applications.  Often, individuals and organizations face tradeoffs (discussed above) with respect to time, or with respect to a certain segment of their lives (or organizations) at the expense of the rest.

For example: if you want to be happy, at any given infinitesimally small moment, the best thing you can do is take a near-lethal dose of hard drugs.  That’s “local optimization.”  It is in obvious and irreparable conflict with “global optimization” – the more sensible goal of having a happy life, over the long term, for which end taking hard drugs is possibly the absolute worst decision you can make.

Usually the choices aren’t this clear and dramatic: but many businesses forego long-term investment opportunities to maximize this quarter’s earnings, and many individuals make decisions (with regards to friends, career, and otherwise) that are pleasant in the short-term but carry long-term consequences.  It’s a mental model always worth considering.

The N-Order Impacts (Unintended Consequences) Mental Model

Actions have repercussions – and you have to consider those repercussions, those unintended consequences, whenever you make a decision.

For example: what could be more desirable than paying doctors based on performance, measured by whether or not their patients get better?  It certainly sounds better than paying them based on the number of procedures or tests they do – which incentivizes volume, not utility – but on the other hand, by inversion, if you’re paying doctors for patients getting better, you’re also not paying, or punishing, them for patients not improving or getting worse.

This, paradoxically, might lead doctors to engage in the sort of “selection bias” we previously discussed – i.e., refusing to treat the sickest or most challenging patients, who arguably need medical care the most.

This mental model shows up everywhere.  Sub-models include reflexivity and network effects.

The Feedback Mental Model (Autocatalysis, Decision Journaling)

Systems respond to feedback – but only in certain forms.  If feedback is inconsistent, unclear, or unavailable, strange outcomes can emerge.

Two particularly important sub-models here are “autocatalysis” and “decision journaling.”  Autocatalysis refers to “virtuous circles” or “vicious cycles” where good begets good and bad begets bad.  An example on the downside is stress and substance addiction: stress is a known trigger for bad, locally-optimizing behaviors (like drinking) that create bad global consequences (like depressed REM sleep, decreased performance, lost friendships, etc.)

That, of course, leads to more stress – which leads to hitting the bottle even harder – which leads to more stress.  Thankfully, this sort of process can be inverted, and used to form positive “flywheels” that spin faster and faster with their own momentum as time goes on.

Decision journaling also eliminates hindsight bias – discussed earlier in the “memory” mental model – thereby allowing us to receive more accurate and appropriate feedback.

The Utility Mental Model (Including Transactional Utility)

What could be simpler than the mental model of doing things that are good for us – whether measured in dollars, units of happiness and joy, or otherwise?

It turns out that many people fail to consider utility in making their everyday decisions, and if they do, they focus on irrelevant “packaging” rather than useful “product.”  For example, consumers are often disproportionately influenced by “transaction utility” – the quality of the deal – and a “good deal” can lead us to purchase things we don’t want and won’t use, while a “bad deal” can prevent us from consuming experiences that will provide us great joy.

The Activation Energy Mental Model

There aren’t a lot of free lunches – but activation energy is one.

Profoundly modest and seemingly unnoticeable increases or decreases to the energy required to engage in a certain behavior can have profound impacts.

For example, making healthy foods merely a little bit easier to reach – and unhealthy foods merely a little bit more difficult to reach – can dramatically improve our eating patterns, without preventing us from making bad food choices if we want to!

It’s not just about our waistlines: activation energy can be used to save lives and help people save for retirement, as we’ll explore.

The Bottlenecks / Weakest Links Mental Model

Oftentimes, the performance of an entire system can be derailed by its weakest link.  If you have a flat tire, it doesn’t matter that 99% of your car is functioning fine – you ain’t getting anywhere.

This applies to mindsets as well as physical systems: often, the way we see the world can be a “bottleneck” between us and success.  This isn’t something that education and intelligence exempt us from, either – as we’ll explore, even Nobel prize-winning nuclear physicists faced bottlenecks in their schema.

The Luck vs. Skill / Process vs. Outcome / Sample Sizes / Averages / Path-Dependency Mental Model

You still here?  Because I saved some of the best models for last.

Experience usually benefits us and allows us to make better decisions.  Except when it doesn’t: as one survival expert quipped, “experienced” can mean “someone who’s gotten away with doing the wrong thing for far longer than you have.”

It’s important to differentiate between luck and skill when evaluating outcomes.  If you drive across the country three times not wearing a seatbelt, going double the speed limit, and live to tell the tale, you’ve learned some profoundly maladptive lessons.

Particularly in cases like this where bad outcomes are infrequent but severe, focusing on a validated “process” (wearing your seatbelt) helps us make the right decisions, when “outcomes” (like not dying) can mislead us.

Important sub-models here are sample sizes – what they do for us and what they don’t – as well as path-dependency, or the way that luck can accumulate over time in a manner that’s dependent on previous events.

The Humans vs. Econs Mental Model

“Why won’t they read (the instructions / consent form),” moans every engineer ever – and, for good measure, South Park’s fictionalized version of Steve Jobs.

Well, the answer is: we don’t read the instructions, or the consent form, because we’re humans, not econs.  We’re not omniscient.  We don’t have unlimited attention.  And we certainly don’t have unlimited willpower.

In fact, if you want to apply a margin of safety (see below), it’s probably best to assume that we have no willpower whatosever, and the attention span of a toddler who’s been given a free espresso while Mom wasn’t looking.

Funny?  Sort of – it can be tragic, too.  When we design products or systems for idealized, fictional “econs” rather than real, messy “humans,” things can go south in a hurry – and good design will always taken into account the reality of humanity, not the way we would like humanity to be.

The Margin of Safety Mental Model (Including Resiliency / Redundancy)

You can take the boy out of value investing, but you can’t take the value investing out of the… never mind, that sounded better in my head.  Well, I am a value investor, after all, and our patron saint concept – margin of safety – was shamelessly stolen from engineering.

But, like many mental models, margin of safety is applicable far beyond its original concept and purpose: putting a whopping margin of safety between us and bad path-dependent events is one of the easiest ways to live a happy and successful life.

Eat More Tomorrow: Nutrition Through The Lens of Mental Models (New as of summer 2019!)

Most of us eat badly. How can we improve our health without sacrificing taste?

Our new 50K word mental model – Eat More Tomorrow – combines insights from David Katz on nutrition, Richard Thaler on behavior,  and Samin Nosrat on flavor.

Book Reviews

Poor Ash’s Almanack > Book Reviews

The premise of book reviews on this site is the interaction of the marginal utility and opportunity cost mental models.  Books are judged primarily on how much learning potential they offer you, per unit of time invested – so a book with 10 arbitrary “units” of learning in 500 pages would be ranked much lower than a book with 8 units in a more concise 200 pages.  Consideration is given to writing style; i.e., fun, enjoyable books that are easier (and faster) to read are rated more highly than dry, dull, academic books (which we try to avoid at all costs.)

Reviews are separated into four categories:

Effective Thinking (Incl Psychology / Neuroscience)

Science, Engineering, Math, Medicine

Business / Finance / Entrepreneurship

History / Biography

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