Beating The SP500 > Winning The NBA Title

76ers GM Daryl Morey is one of the pioneers who brought Moneyball-type thinking to basketball during his tenure with the Rockets.

His interview with Patrick on Invest Like The Best is insightful and entertaining. I want to zoom in something Morey says:

You are weighing championship odds. And generally, we look over a three year time horizon with that. You could really pick any time horizon, but three years seems to work best with the data. And we basically do a sharp ratio like you would in investing, which is like here’s how championship odds increase, here’s the variance of that move.

Is it on the efficient frontier of return to risk basically and Shane [Battier], obviously, fit that for us.

None of our information is anywhere as good as the financial models. Actually, our underlying data is more predictive, quite a bit predictive. I talk to a lot of quants on Wall Street, and I tell them our signal to noise ratio using whatever measure you want….And they go like — yes, they go like, whoa, you guys are — that’s incredible. And I’m like, yes, but you remember, we have to be best of 30. You guys just have to beat the S&P by 2% and you are geniuses. So each industry has its own challenges.

We’re like a pure play. It’s the lifeblood of our business, whereas in other businesses, I’d say execution probably matters a lot more. In all aspects, including coaching, a well-executed, slightly suboptimal strategy generally will be the best strategy poorly executed. I mean you know that.

That’s generally true in basketball as well. But I would say in our realm of decision-making, it’s really almost a pure decision-making thing. This draft pick beats that draft pick. This free agent for $5 million beats that free agent for $5 million. It’s more of a pure play.

Sports is actually way simpler than most of the people you talk to, way simpler. Our sport, it changes, but not much. Our data is pretty good. Our competitors aren’t coming out with new products. Our competitive dynamics are known.

They’re hard, but they’re — no, we don’t have the Rumsfeld problem of unknown unknowns, like some start-up in stealth mode that might emerge, like, that’s why academics have done more and more papers about sports.

Because if you’re trying to isolate how to make good decisions, sports is really the right area to do that in

This is a great section because it highlights how different domains just have different size error bars. Sports signals are stronger than investment signals. The counterbalance to that fact is when Morey says:

I talk to a lot of quants on Wall Street, and I tell them our signal to noise ratio using whatever measure you want….And they go like — yes, they go like, whoa, you guys are — that’s incredible. And I’m like, yes, but you remember, we have to be best of 30. You guys just have to beat the S&P by 2% and you are geniuses. So each industry has its own challenges.

Umm, beating the SP500 by 2% consistently is rarified air even if that number sounds small. Morey admits that only a handful of teams have the requisite talent to even compete for the title. So your probability of winning the championship is either 0 or likely much better than a professional fund manager beating the SP500 by 2%.

Asset managers win by being good salespeople (a friend called this the Matt Levine model — being a good hedge fund is about gathering assets when you get hot and keeping them when you get cold. It’s a scheme for getting rich that has a lot less to do with returns than the industry will admit. Come to think of it, being a valuable sports franchise probably has more to do with the logo and stadium than actually winning…it’s not that winning and returns don’t matter, it’s the gap between how much they matter and how much we think they matter).

I’m guessing Morey threw the 2% number out there without much thought. He was actually making a deep point that if an adversarial game is technically easier (say checkers vs chess) the competition enjoys the same low-difficulty advantage and you are in the same place of having a low chance of winning. But I was curious…how hard is it to beat the SP500 by 2%?

I’ll admit a question like this is in my friend Nick Maggiulli’s wheelhouse so when he reads this he’ll almost certainly have a more complete answer. But I decided to take a quick stab at it.

I pulled up the portfoliovisualizer.com fund screener and filtered for US equity large-cap funds with at least a 5-year history benchmarked to the SP500 total return (this is an appropriate benchmark for a large-cap US equity fund.)

My criteria for beating the SP500 without getting lucky was the fund needed an information ratio (IR) of .50 or greater. An information ratio is outperformance normalized by tracking error. Tracking error is the standard deviation of the difference in returns between the fund and the SP500. If a fund outperforms by 2% per year but the tracking error is 10% (ie an IR = .2) that feels like noise vs a fund that outperforms by 2% with only 4% tracking error [I realize I’m using a simple, satisficey method for separating signal from noise, so if you are an allocator who just threw up in their mouth, brush your teeth then email me with an education so I can learn too!].

What did the screen turn up?

  • 45 out of 677 funds had IR of .5 or greater (caveat: the IRs use a 3-year lookback)
  • 8 funds out of 677 had at least .5 IR AND outperformed the SP500 total 3-year returns by 200 bps
  • Only 3 funds outperformed by 200 bps for 5 years (the IR ratio is still a 3- year lookback)

Daryl your point is well-taken but beating the SP500 by 2% with skill is 90s Bulls-level for public fund managers.

If You Wait For All The Info You’ll Be Too Late

In the past few days, I’ve been getting around to the feedback and follow-ups from last week’s StockSlam sessions. Here’s a reaction and my response worth sharing widely.

Attendee:

Just wanted to shoot you a quick note – loved the game last week, thanks for putting it on!

I had a hard time playing the game because I didn’t have intuition for the odds of the game… I’m way more of a Quant- the only thing I could think of was trying to execute the optimal strategy.

To figure out the optimal strategy I’d run a Monte Carlo simulation – play the game 100,000 times (programmatically using python or something) and see the distribution of outcomes as well as figure out some conditional probabilities (like what are the odds of last place winning given current relative location). Getting a sense of this would help price different bets – not a sure thing all the time, but better odds!

Generally, I ended up playing the game buying out-of-the-money “horses” (i.e. last place)… I figured with the mean reversion built into the game combined with behavioral biases to dump losers would be a winning strategy… and I ended up with a positive PnL so maybe I was into something!

I don’t know how you did that for a career for so long… so stressful and I was wound up all night from it, haha…

My reply:

An anecdotal observation — I’ve noticed that quants and accountants actually get a bit paralyzed sometimes and it highlights the fact that crunching the numbers to perfection isn’t the core skill of trading.

It really is handicapping how wrong you could be and then acting with a margin of safety commensurate with the possible reward. Basically, if you wait to have the best info you’ll be too late. So the constraint is “how do I act optimally subject to being fast?” Everyone is in the same boat. That’s a key point. The game would be different if everyone had infinite time to crunch the numbers. Trading is playing the game at hand — and that has a speed component. This is inescapable. It’s also true in reality even if the form varies. Buffet might wait for a fat pitch, but when it comes the bat speed still needs to be fast.

Whatever your game, you ultimately get a feel for it by being able to hold your attention on what matters and tuning out the rest. There’s some visualization…being ready to pounce on an incorrect market that you’ve been studying. In StockSlam, you really get a sense of what consensus is for a color in a certain relative position and then your antennae is up for aberrations. You are gathering and measuring data via listening and memory while in real-life the same functions are performed in code. But they are the same functions. And both are downstream from “what do I need to be paying attention to?” That will vary by the time horizon of your strategy.

[The attendee also mentioned that the penalty for not executing the game’s “broker cards” was too low.

My response:

As far as the penalty we are actually thinking to ditch it anyway and use carrots for doing things on your card rather than punishments. But I hear you on the $5 not mattering much but it remains a useful part of the game by letting us examine if players can find the least expensive way to execute the card. You are effectively benchmarking a trade not to “does this have edge” but “is this better than negative $5”.


This is a critical concept in real life. Broadly, satisficing is often better than making perfect the enemy of the good. Also, there are some strategies that are not profitable if you have to cross a spread but are profitable if the benchmark is “it saved me from crossing a spread” (very relevant for an org that has to make many hedging trades per day). Academic papers are notorious for finding strategies that underappreciate indirect transaction costs. But you may be able to repurpose such strategies to warehouse risks instead of crossing bid-asks to shed them. That’s a lower bar than a strategy that needs to cross a spread. In a world of rebate liquidity this is especially true. The cost/rebate structures for taking/ supplying liquidity is like a 4-point swing in a basketball game.]

Related reading (as an exercise you can think of why these posts are so related to what I described above):

  • If You Make Money Every Day, You’re Not Maximizing (28 min read)
  • The Paradox Of Provable Alpha (1 min read)

GPT Stuff

A college buddy texted me:

The link referenced is totally 🤯. My friend just scratched the surface of what’s possible!

Enjoy:

  • How to Use ChatGPT on Google Sheets With GPT for Sheets and Docs

    What Can You Do With GPT-Powered Google Sheets?

    Step-by-step walkthrus in the article on how to do the following GPT functions en masse in a spreadsheet:

    1. Generate Text

    2. Translate Text

    3. Summarize text

    =GPT_SUMMARIZE(C44) will summarize the content of cell C44 into the active cell.

    4. Extract data

GPT-4

OpenAi released GPT-4 this week. Here are some buzzworthy examples:

This thread includes a similar example as well as prompts asking GPT-4 to create videogames, a link about Khan Academy building on the tech to create an assistant for teachers, and more.

I’m far too stupid to pontificate on what any of this means. Every day substacks, articles, papers, interviews, and videos comment on AI, alignment, the meaning of creativity, and the future of jobs from writing to coding. I just see a useful tool to use until the day I’m deleted from the simulation in favor of a paperclip.

Moontower #185

GPT Stuff

A college buddy texted me:

The link referenced is totally 🤯. My friend just scratched the surface of what’s possible!

Enjoy:

  • How to Use ChatGPT on Google Sheets With GPT for Sheets and Docs

    What Can You Do With GPT-Powered Google Sheets?

    Step-by-step walkthrus in the article on how to do the following GPT functions en masse in a spreadsheet:

    1. Generate Text

     

    2. Translate Text

    3. Summarize text

    =GPT_SUMMARIZE(C44) will summarize the content of cell C44 into the active cell.

    4. Extract data

GPT-4

OpenAi released GPT-4 this week. Here are some buzzworthy examples:

This thread includes a similar example as well as prompts asking GPT-4 to create videogames, a link about Khan Academy building on the tech to create an assistant for teachers, and more.

I’m far too stupid to pontificate on what any of this means. Every day substacks, articles, papers, interviews, and videos comment on AI, alignment, the meaning of creativity, and the future of jobs from writing to coding. I just see a useful tool to use until the day I’m deleted from the simulation in favor of a paperclip.

Money Angle

In the past few days, I’ve been getting around to the feedback and follow-ups from last week’s StockSlam sessions. Here’s a reaction and my response worth sharing widely.

Attendee:

Just wanted to shoot you a quick note – loved the game last week, thanks for putting it on!

I had a hard time playing the game because I didn’t have intuition for the odds of the game… I’m way more of a Quant- the only thing I could think of was trying to execute the optimal strategy.

To figure out the optimal strategy I’d run a Monte Carlo simulation – play the game 100,000 times (programmatically using python or something) and see the distribution of outcomes as well as figure out some conditional probabilities (like what are the odds of last place winning given current relative location). Getting a sense of this would help price different bets – not a sure thing all the time, but better odds!

Generally, I ended up playing the game buying out-of-the-money “horses” (i.e. last place)… I figured with the mean reversion built into the game combined with behavioral biases to dump losers would be a winning strategy… and I ended up with a positive PnL so maybe I was into something!

I don’t know how you did that for a career for so long… so stressful and I was wound up all night from it, haha…

My reply:

An anecdotal observation — I’ve noticed that quants and accountants actually get a bit paralyzed sometimes and it highlights the fact that crunching the numbers to perfection isn’t the core skill of trading.

It really is handicapping how wrong you could be and then acting with a margin of safety commensurate with the possible reward. Basically, if you wait to have the best info you’ll be too late. So the constraint is “how do I act optimally subject to being fast?” Everyone is in the same boat. That’s a key point. The game would be different if everyone had infinite time to crunch the numbers. Trading is playing the game at hand — and that has a speed component. This is inescapable. It’s also true in reality even if the form varies. Buffet might wait for a fat pitch, but when it comes the bat speed still needs to be fast.

Whatever your game, you ultimately get a feel for it by being able to hold your attention on what matters and tuning out the rest. There’s some visualization…being ready to pounce on an incorrect market that you’ve been studying. In StockSlam, you really get a sense of what consensus is for a color in a certain relative position and then your antennae is up for aberrations. You are gathering and measuring data via listening and memory while in real-life the same functions are performed in code. But they are the same functions. And both are downstream from “what do I need to be paying attention to?” That will vary by the time horizon of your strategy.

[The attendee also mentioned that the penalty for not executing the game’s “broker cards” was too low.

My response:

As far as the penalty we are actually thinking to ditch it anyway and use carrots for doing things on your card rather than punishments. But I hear you on the $5 not mattering much but it remains a useful part of the game by letting us examine if players can find the least expensive way to execute the card. You are effectively benchmarking a trade not to “does this have edge” but “is this better than negative $5”.


This is a critical concept in real life. Broadly, satisficing is often better than making perfect the enemy of the good. Also, there are some strategies that are not profitable if you have to cross a spread but are profitable if the benchmark is “it saved me from crossing a spread” (very relevant for an org that has to make many hedging trades per day). Academic papers are notorious for finding strategies that underappreciate indirect transaction costs. But you may be able to repurpose such strategies to warehouse risks instead of crossing bid-asks to shed them. That’s a lower bar than a strategy that needs to cross a spread. In a world of rebate liquidity this is especially true. The cost/rebate structures for taking/ supplying liquidity is like a 4-point swing in a basketball game.]

Related reading (as an exercise you can think of why these posts are so related to what I described above):

  • If You Make Money Every Day, You’re Not Maximizing (28 min read)
  • The Paradox Of Provable Alpha (1 min read)

Money Angle For Masochists

76ers GM Daryl Morey is one of the pioneers who brought Moneyball-type thinking to basketball during his tenure with the Rockets.

His interview with Patrick on Invest Like The Best is insightful and entertaining. I want to zoom in something Morey says:

You are weighing championship odds. And generally, we look over a three year time horizon with that. You could really pick any time horizon, but three years seems to work best with the data. And we basically do a sharp ratio like you would in investing, which is like here’s how championship odds increase, here’s the variance of that move.

Is it on the efficient frontier of return to risk basically and Shane [Battier], obviously, fit that for us.

None of our information is anywhere as good as the financial models. Actually, our underlying data is more predictive, quite a bit predictive. I talk to a lot of quants on Wall Street, and I tell them our signal to noise ratio using whatever measure you want….And they go like — yes, they go like, whoa, you guys are — that’s incredible. And I’m like, yes, but you remember, we have to be best of 30. You guys just have to beat the S&P by 2% and you are geniuses. So each industry has its own challenges.

We’re like a pure play. It’s the lifeblood of our business, whereas in other businesses, I’d say execution probably matters a lot more. In all aspects, including coaching, a well-executed, slightly suboptimal strategy generally will be the best strategy poorly executed. I mean you know that.

That’s generally true in basketball as well. But I would say in our realm of decision-making, it’s really almost a pure decision-making thing. This draft pick beats that draft pick. This free agent for $5 million beats that free agent for $5 million. It’s more of a pure play.

Sports is actually way simpler than most of the people you talk to, way simpler. Our sport, it changes, but not much. Our data is pretty good. Our competitors aren’t coming out with new products. Our competitive dynamics are known.

They’re hard, but they’re — no, we don’t have the Rumsfeld problem of unknown unknowns, like some start-up in stealth mode that might emerge, like, that’s why academics have done more and more papers about sports.

Because if you’re trying to isolate how to make good decisions, sports is really the right area to do that in

This is a great section because it highlights how different domains just have different size error bars. Sports signals are stronger than investment signals. The counterbalance to that fact is when Morey says:

I talk to a lot of quants on Wall Street, and I tell them our signal to noise ratio using whatever measure you want….And they go like — yes, they go like, whoa, you guys are — that’s incredible. And I’m like, yes, but you remember, we have to be best of 30. You guys just have to beat the S&P by 2% and you are geniuses. So each industry has its own challenges.

Umm, beating the SP500 by 2% consistently is rarified air even if that number sounds small. Morey admits that only a handful of teams have the requisite talent to even compete for the title. So your probability of winning the championship is either 0 or likely much better than a professional fund manager beating the SP500 by 2%.

Asset managers win by being good salespeople (a friend called this the Matt Levine model — being a good hedge fund is about gathering assets when you get hot and keeping them when you get cold. It’s a scheme for getting rich that has a lot less to do with returns than the industry will admit. Come to think of it, being a valuable sports franchise probably has more to do with the logo and stadium than actually winning…it’s not that winning and returns don’t matter, it’s the gap between how much they matter and how much we think they matter).

I’m guessing Morey threw the 2% number out there without much thought. He was actually making a deep point that if an adversarial game is technically easier (say checkers vs chess) the competition enjoys the same low-difficulty advantage and you are in the same place of having a low chance of winning. But I was curious…how hard is it to beat the SP500 by 2%?

I’ll admit a question like this is in my friend Nick Maggiulli’s wheelhouse so when he reads this he’ll almost certainly have a more complete answer. But I decided to take a quick stab at it.

I pulled up the portfoliovisualizer.com fund screener and filtered for US equity large-cap funds with at least a 5-year history benchmarked to the SP500 total return (this is an appropriate benchmark for a large-cap US equity fund.)

My criteria for beating the SP500 without getting lucky was the fund needed an information ratio (IR) of .50 or greater. An information ratio is outperformance normalized by tracking error. Tracking error is the standard deviation of the difference in returns between the fund and the SP500. If a fund outperforms by 2% per year but the tracking error is 10% (ie an IR = .2) that feels like noise vs a fund that outperforms by 2% with only 4% tracking error [I realize I’m using a simple, satisficey method for separating signal from noise, so if you are an allocator who just threw up in their mouth, brush your teeth then email me with an education so I can learn too!].

What did the screen turn up?

  • 45 out of 677 funds had IR of .5 or greater (caveat: the IRs use a 3-year lookback)
  • 8 funds out of 677 had at least .5 IR AND outperformed the SP500 total 3-year returns by 200 bps
  • Only 3 funds outperformed by 200 bps for 5 years (the IR ratio is still a 3- year lookback)

Daryl your point is well-taken but beating the SP500 by 2% with skill is 90s Bulls-level for public fund managers.

From My Actual Life

My music school does a class where you form a band for 5 weeks then perform. It’s a great way to accelerate learning. I’m on guitar duty for the show tonight.

Here’s the setlist:

  1. Can’t Let Go by Robert Plant and Alison Krauss
  2. Far From Any Road by The Handsome Family
  3. Fake Plastic Trees by Radiohead
  4. Plush by STP
  5. Stop Draggin My Heart Around by Stevie Nicks and Tom Petty

Ben and Kathryn handle vocals and the harmonies are why 3 of these songs are duets.

[In the Moontower survey this year many of you fretted (pun intended) about imposter syndrome. Well, in this group, 2 out of the other 4 musicians have albums out and a 3rd busked his way singing and playing guitar through Europe in his youth. Fck it…I’m gonna have fun and definitely not worry about my skills (desperate chuckle)]

 

Ok, talk to you all in mid-April. Until then stay groovy (and not like these 2 terrors 👇)

A Walrus Opens Networth.xlsm

Internet hygiene demands you mark listicle content as spam and move on.

Except when it comes from

Nat Eliason’s Newsletter

who wrote a banger list of 40 lessons to celebrate his 30th birthday. I feel like a mental decade behind this guy. I guess I could feel 2 decades behind. Better late than never.

40 Lessons From 30 Years

Here were my favorites, sometimes with a comment:

✔️It’s never the right time: Any time you catch yourself saying “oh it’ll be a better time later,” you’re probably just scared.

✔️Bad things happen fast, good things happen slowly

✔️Beware of shadow careers: via Steven Pressfield “Sometimes, when we’re terrified of embracing our true calling, we’ll pursue a shadow calling instead. The shadow career is a metaphor for our real career. Its shape is similar, its contours feel tantalizingly the same. But a shadow career entails no real risk. If we fail at a shadow career, the consequences are meaningless to us.”

  • [Kris: This is one of my favorite ones. It echoes something my friend
    Paul Millerd

    wrote to me once:

    You’re doing the thing everyone does at the beginning of a solo path — you’re looking to be saved. No company, no other person’s playbook, or metric of success will save you. The only thing that matters is coming back to the thing you are meant to do. You must do it on your terms. Men waste years trying to avoid this.]

✔️Standing events are the best way to regularly see friends: Constantly having to schedule outings, dinners, etc. makes it hard to regularly see people. Create standing events. Invite people you want to spend more time with. It’s the easiest way to get more friend time in your week.

  • [Kris: My close college friend Brook just calendered a bi-monthly standing get-together with our old school crew. We had our first one 2 weeks ago (we played pickleball and ate some delicious Thai at a hole-in-the-wall in Palo Alto). The beauty of standing meeting was immediately obvious. It was fun and felt needed. His initiative is appreciated. You could be that person in your group.]

✔️Remote relationships cost you real relationships: Every minute you spend cultivating relationships with people through a screen is a minute you’re not deepening relationships with people you can actually see and touch and smell.

  • [Kris: This one dovetails with the preceding one. I’m as guilty as anyone]

✔️ No one is thinking about you very much: So don’t worry about looking stupid or embarrassing yourself or whatever. No one cares.

  • [Kris: Maybe the most important lesson my mother ever taught me. And I’m still more inhibited than I want to be.]

✔️The time will pass anyway: Maybe it’ll take you five or ten years to succeed at whatever you want to do. Well, those ten years will pass anyway. In ten years you can either have made progress on your goals, or still be whining about how long things take.

  • [Kris: This was nearly verbatim what I thought about when I decided to quit my job. Once I knew I wasn’t going to be happy doing it for another 20 years I decided I’d rather be closer to wherever I wanted to be than if I started the clock later on a new life. If your time horizon is long, a step backward is a smaller percentage of the time remaining. If you try to play prevent defense until you hit your number, you’re still rolling the dice. Snake eyes and the doctor calls “You’re bloodwork came back…we’d like to do more tests”. You don’t have forever to start living. GoTo: Shadow Career ]

✔️Money is a tool for freedom: The best reason to accumulate wealth is to buy yourself freedom from anything you don’t want to do, and the freedom to do the things you do want to do. Money is not an end in itself. If you sit on it and never use it, you’ve wasted your life.

  • [Kris: The ratio of people who agree with this but don’t act upon it looks like a walrus on a pogo stick]

✔️Many of the best changes in life are unknown until you make them: Feeling “fine” is a dangerous attitude. You might have no idea how much better you could feel, how much happier you could be, how much fuller your life could be.

✔️Get physical: Buy real books. Print photos. Write cards. Buy vinyl. Space is how you show yourself and others what you value. Minimalism is a horrible, dull trend. Fill your life with totems to what you care about.

  • [Kris: This is the one I’m most torn about. I like being free of stuff but the minimalist aesthetic feels soulless.The older I get the less I like modern. My IG is basically an homage to the 60s and 70s, especially in CA. The treadmill of cleaning after the kids has given some leniency to having art supplies, books, boardgames and stompboxes strewn about. An old Boogie Nights-esque house that’s both tidy and warm wouldn’t have been on my Bingo card but it’s cheaper and feels more inspiring than the prior house that we renovated down to the studs in a conventionally tasteful way. That said, it would be nice to have a master closet. The luxe amenities around here are trapped in the 70s — tile countertops with grout lines😐 ]

✔️Money can absolutely buy happiness. So long as you spend it on upgrading and expanding the things that make you happy, instead of using it to play status games or on fleeting experiences.

  • [Kris: The less time you spend thinking about money the happier you’ll be. We are naturally wired to think of how things could be better. If you think about money a lot you’ll automatically think of how you can get more of it. This is adaptive over some range of savings. And once you’re safe (not rich) the value of those thoughts nosedives faster than your thoughts about money taper (assuming they do at all). You can count your expiring breaths in the widening gap between the value of those money thoughts and the time spent thinking about networth.xls. Oh yea, if that file is called networth.xlsm — you’re doomed. Sorry, I don’t make the rules.]

✔️Advice only works in retrospect. You usually have to have experienced a failure or loss to understand the relevant advice. Hearing some piece of advice will rarely stop you from making the related mistake.

✔️The whiners are the loudest. Happy people are off enjoying their lives, not complaining about them on social media.

✔️No one is crazy: They just have different values and information than you. If you had their life experience, you’d probably think the same. The sooner you embrace this, the sooner you can empathize with people you disagree with instead of pretending you’re superior.

  • [Kris: Big Morgan Housel energy here. That’s a compliment.]

✔️You find what you like by trying it, not by thinking about it

✔️You don’t have to make money back where you lost it: If something in your business or life is losing money, you don’t have to plug the hole right there. Often it’s easier to make the money back elsewhere.

  • [Kris: This is adjacent to a bit of advice I give dealing with the ups and downs of trading — have other places in your life to get wins. Bad runs are inevitable. Have outlets. Your deadlift PR doesn’t care about your p/l. ]

✔️Trust your negative gut, not your positive gut: If you have a great feeling about something, you might just be excited or gullible or not thinking it through, so take your time. But if you have a bad feeling about something, you’re almost certainly right about it.

✔️Stressing about a problem rarely fixes it: Try to bias towards improving things instead of whining about them. Or if you can’t fix them, forget about them.

  • [Kris: Another adjacent thought…my friend Steiner never complains unless he has ideas for how to fix a problem. We’re human. Sometimes we need to vent. So Steiner’s principle is aspirational. But one thing I’ll quickly sort a new acquaintance on is — “does this person suck the life energy out of the air we share?” I don’t know how Piglet hung out with Eeyore so much.You’re a donkey that CAN TALK. Have some perspective you mopey ingrate.]

Mock Trading

We played StockSlam after dinner. The kids (well not the 1st grader) and adults were all into it.

There are 8 colors or shares that take a random walk over 10 rounds. The shares of the color that climb the highest are worth $100 at expiration. The rest of the shares are worthless. So you are trading a derivative contract (a future) not the share prices directly.

Purple is in the lead:

The rules are simple. You are mock trading in an open outcry environment. You start with 4 shares of each color and cash. It’s a free-for-all where you can trade with anyone at any price. You can bid, offer, or make 2-sided markets. It’s exactly what we did when we trained although simpler since we aren’t using options (although depending on the audience we will also trade options as side bets…”what’s your offer on the blue 150 call?”— if you get lifted, you can buy blue shares to delta hedge and isolate the vol).

The game is a deeply layered experience. You can just play for fun. It’s wildly energetic — we make sure everyone gets involved and there are gentle ways to do that, different personalities manifest in so many ways…some sling from the hip, some are shy or don’t want to open their mouths until they think they know the value of everything but then it all changes and you realize that approach won’t work.

But what attracted me to the game, beyond the fun, was how it bursts with trading lessons. Based on the audience we modulate the experience up and down. We give homework leading up to the event and bridge the rationale of the questions to insights embedded in the game. We connect real-life investing and trading concepts to the game (and honestly we don’t even get to them in these 2+ hour events…everyone wants to play not listen to lecture).

The single most powerful lesson though is one I harp on all the time — trading is about measurement not prediction. In the game, prediction is not even possible. The walk is random. But skill expresses itself strongly! Your ears pipe in pricing data so you can triangulate fair value and find aberrations. The visceral feel of playing skillfully is well-matched to the feeling of trading effectively in real life. When I pull you aside and ask why you did X or Y, a good answer will take the same form of sound trading rationale — “well, I bid 17 for green because red which is in the same position just traded 20 and I know Sam bought a bunch of green last round for 12 and is looking to flip a quick profit”. Your transacting like crazy but you can kind of tell without stopping to count if you are making or losing money when you get into the flow.

Getting In The Trading Headspace

Let’s pose some questions and entertain some scenarios.

At the start of the game, all the colors start at 100. I might start by just throwing out a 14 bid for red or a 9 offer in yellow just to see or a 16 offer in green, etc to get a read of the thought processes when the game is a blank slate.

Let’s look at a scene futherer along:

Suppose the following montage represents the situation in the pit:

Purple: 28-32

Green: 20-24

Blue: 20 bid

Gray: 10 bid

Jane yells “Pink/orange 1×3…even bid for the pink. I’ll buy pink, sell 3 orange for even”

What do you do?

If you sell the 1×3 you will get long 3 orange and short 1 pink. You can then turn around and lift the 1 green at 24 while hitting the 10 bid in the gray 3x.

What’s your net position:

+3 orange

-1 pink

+ 1 green

-3 gray

Chunking the risk:

  • You’re long 3 orange and short 3 grays (they are worth about the same, as they are 96 and 95 respectively in the race).
  • You are long 1 green and short 1 pink (again worth similar amounts based on their race position)

The risk on these positions is basically a wash…but you collected $6!

[You sold 3 grays at $10 each and bought 1 green for $24. The pink/orange 1×3 traded premium neutral]

If you keep doing positive expectancy trades and manage to not get too unbalanced in your positions you will have a high Sharpe and be profitable by expiration. If you just try to load up on the color you think will win, that’s a zero expectancy strategy that’s high risk/high reward and will have a garbage Sharpe over many games.

As we play the game I might come over and nudge you:

  • “Hey, do you think the gray bid had any room? If you can squeeze an 11 bid out of them then you would have collected $9 instead of $6.”
  • “What if the gray bid was thin and you could only sell 2 on the 10 bid? Do you see how liquidity and gauging the size on the bid/offer is important? You are now ‘hung’ on 2 grays that you couldn’t offload. Is the trade still worth doing if you have to hit a 9 bid on the remaining 2 lot for an average price of 9.33?”
  • “The green bid was only 20, you could have bid 22 and maybe the 24 offer would have stepped down and offered 23s or better yet just hit your mid-market bid.”
  • “Blue is 20 bid…maybe those oranges and grays were kinda cheap relatively and the good side of the trade was just buying the orange 3x via the first ratio trade but not locking it in by selling the grays. Don’t do a trade good by $5 and then do a trade bad by $2 to lock it in if you don’t have to…you have to maximize when you have the best of it because you may find yourself needing to give up edge sometimes to manage risk”.
  • “With the green offered at 24, maybe you can dangle a 22 offer in the blue…if you get lifted turn around and take the greens. You’ll have legged the spread for 2…maybe you try to offer out the pink/blue spread at 7 fishing for a 5 bid. Paste those and your net position is long green/short pink for a $3 credit!”

This is trading.

Replace colors with option strikes/maturities and all the many combinations of vertical spreads, synthetics, straddles, and underlying… churn all day, and let the chips fall where they may.[see Mock Trading Options With Market Makers]

If you trade enough with a positive edge the expiration results are just noise — you win some, you lose some. The p/l over time converges to your edge.

Knowing the arbitrage relationships in options is the same as knowing that the field of colors can’t be worth less than or more than $100. Today we measure fair value from liquid consensus using machines — in the game we gather consensus by listening. In the pit, it’s loud and busy and orders are flying around everywhere. You learn to focus attention on what matters. And that changes depending on the context. The same is true in modern trading.

Today we enter trades with code or mouse clicks not vocal cords but the concepts are the same. That’s why prop firms still use mock trading to train. The arena is a Socratic forum that opens up conversations about practical scenarios. It’s like having a poker coach press you on “Why did you call that bet? What did you think they were holding? With what odds? If you think they just caught a 2 pair with that Jack of clubs on the river, do you think they really would have called the big bet on the turn with a low pair and no draw?”

Mock trading in the presence of an experienced trader is an opportunity to debug your thinking.

This was Friday night:

And then Saturday night with the family:

rea events ranged from 10 to 25 people. I’m still in awe of a 6th grader who could just see the Matrix. The kid was fast and a total shark, preying on people that were still getting their bearings. After the game, he had opinions about shifting some of the probabilities in the algo and adding skew. I asked his mom if he was coding or using Excel and she said “no, not yet”.

”Umm, give him to me”. With some tools for expression he’ll be off to the races!

Otherwise, with respect to the game, I will share more as appropriate. We did have a videographer at all the sessions so at some point there will be more to see. In the meantime, if you are interested in having us do a team-building or educational seminar at your office, conference, or school hit me up and we’ll figure something out. By the way, the game shown above is just one of several games we actually trade on. The attendees will remember their favorite “bunny” I’m sure.]

Financial Literacy

In a recent interview with Tim Ferriss, VC Bill Gurley admits:

If there was a scale of financial sophistication between one and 10, and you would say a really smart person in New York is an 8.5, the average Silicon Valley person on financial literacy is a two.

And it’s funny because they make fun of Wall Street, but it’s just out of ignorance, they don’t know anything.

Bill said it, not me (the transcript is worth reading for the full context but I’m not twisting him… those words are the spirit). I don’t know enough to have an opinion on this but I do find it surprising. Financial literacy starts at home and VCs don’t strike me as a cohort that rose from the gutter so either I’m wrong about the source of financial literacy or maybe poor kids play lacrosse after all.

Either way, the workings of money are abstractions like code. It touches almost every decision since it prices time (interest rates function as an exchange rate between time and money). It’s a basic life skill in an increasingly abstract, financialized world. Teaching our kids about it is basic hygiene.

Last night, we had our regular family dinner with my wife’s sister’s fam (4 adults, 4 kids — grades 1, 4, 5 and 7 plus another 4th grader who was spending the night). We usually go around the table asking each person about something they were grateful for that week or what’s something they tried at and failed (I know, I know it’s a bit cliche. These prompts do lead to provocative discussions and serve to put kids and adults on the same level).

But this time we did something different.

Yinh wanted to use the Silicon Valley Bank run as a learning moment. She started by explaining how banks invest deposits in longer-dated loans to earn a yield. To nudge the kids towards understanding the risk, she said the bank invests in loans that only pay back once a year. While not mechanically true, the point was to have them recognize the liquidity mismatch between the long-dated loan and the deposits that can be withdrawn anytime.

I taught them how rising interest rates cause the value of the loans to fall. But I also dispensed with mechanical accuracy in favor of intuition. I told Zak he plays the role of the bank. He loans me $100 and I promise to repay him $110 in one year. But then, immediately, mom asks to borrow that $100 from me but she’ll pay me back $120 in a year.

How should Zak feel? Well, sad. He’s going to get $110 in one year but since his mom is willing to pay $20 for a loan he could have lent her only $90 and still known he’s going to get back $110 in a year. Of course, this isn’t accurate interest rate math, but save that for a 7th grader. For a 4th grader, this delivers the point intuitively. [And for adults who think buying individual bonds instead of a bond fund somehow is less risky because they know how much nominal money they’ll get back, think through Zak’s position here — he is still getting $110 back but he’s definitely sad even though the counterfactual universe where he invests in a bond fund that gets marked down to $90 is optically worse.]

I was fortunate that my mother taught me about money. I can still remember my brain hurting when she explained a mortgage to me. It took a while to get my head around it. Remembering that keeps me patient — I’m grateful she persisted until it got through my dense skull. She didn’t push, she just repeated herself calmly every time I was frustrated “how does this work again?”. It sinks in eventually. If anything, the exposure will prime them to learn faster when they do encounter it down the line when the stakes are higher in school or real life.

[If you think my difficulty in understanding a mortgage was stupid, I got a better one for you. When I was about 12 or 13 an older kid told me a prostitute is “someone that gets paid to have sex with you”.

Sit down for this.

My mental model for “someone gets paid to X with or at you” was…a hitman.

I now believed that there was a person whose career was to have someone pay them to have sex with a 3rd party. Until then I had the impression that sex was a desirable activity but then hearing it connoted as something that is delivered as revenge or assault made me wonder if sex might actually be a gross punishment.

Dazed and confused is a fitting description of my existence so I’ve got that going for me and this blog.]

Brain Plug-In

Friends,

Wednesday’s Moontower Munchies, Mondegreen Minds, was a celebration of computational thinking. I shared a quote by Montessori instructor Matt Bateman in reference to math:

It matters for your soul. Math is the realm of precision, exactitude, quantity, measurement, and logic. If that’s the realm you’ve populated with secondhand incantations, that will invariably transfer to areas of life in which those things are cognate. (Which is every area.) The exactitude of the mind, the quality of judgment of the mind, and the independence of the mind are interrelated.

He quotes Maria Montessori herself:

When you say “There goes a man of vague mentality. He is clever but indefinite,” you’re hinting at a mind with plenty of ideas, but lacking in the clarity which comes from order period of another you might say, “He has a mind like a map. His judgments will be sound” in our work, therefore, we have given a name to this part of the mind, which is built up with exactitude, and we call it “the mathematical mind.”

Bateman asks:

Is your mind made of routines that are alien incantations that you mysteriously “work”? Or is it understood, made up of independently cognized algorithms, which you can mull and interrelate, and in which you have earned confidence?

The reason I write anything on any particular day is usually opaque to me. Most of my alien incantations come from the mind-cleansing bombardment of a hot shower whose snippets I can sometimes reassemble into a cohesive message. I don’t ask why any particular topic occurs to me but this week my urge to promote computational thinking had a few sparks.

I’ll mention 2 here and another in Money Angle.

  • This was StockSlam week.Steiner had a vacation in the Bay Area so we used the opportunity to host the pit trading simulation in SF and Walnut Creek. I love doing these sessions to meet people, play games, foster in-person connections, and help participants viscerally feel the concepts I write about.The world of finance, trading, and betting is an amazing laboratory to improve your thinking and decision-making. Being forced to put a price on a belief sharpens fuzzy thinking.
  • A meeting with a local friendWhere I live in CA nobody talks shop (this is probably not true on the peninsula or showbiz land). Here folks people are obsessed with skiing (Tahoe this and Tahoe that and best season ever, yadda yadda) and mountain biking. I’m no adrenaline junkie and my Egyptian blood hates the snow.So I was surprised a) that a friend was actually in town and b) that they wanted to talk shop (kinda). This person invests in pre-IPO companies today but spent the past 20 years in software sales and the 90s as a software engineer. They reached out because they wanted to learn more about options. Not because they wanted to devote themselves to trading, but because they thought dabbling in options would help them be more methodical in their thinking.A few points they mentioned:
    • They felt that their computational thinking muscle had atrophied since their engineering days, especially with a life in sales. While they had developed strong pattern recognition and business acumen, they felt gaps in how they synthesized those inputs into decisions.
    • The founder of their fund seems to think in terms of options but uses a different language to describe scenarios. This reinforced my friend’s sense that this was a place they should improve.
    • They wanted to take a more hands-on role in helping their kids (who incidentally take chess lessons at my house) think rigorously and thought directing their own attention in that direction would help.

My responses:

  1. The grass isn’t greener. I was jealous of their experience.Those pattern-recognition inferences are inputs and can only be gathered by decades of reps. The reasoning part can be taught much faster. If you spent just a year in a trading/arbitrage environment you’d have a useful lens to carry with you for life. Acquiring a practical mental catalog of business models takes much longer. I believe I can take my brain and stick it in someone else (provided they had some minimum aptitude, desire, and work ethic). I can’t acquire the equivalent fraction of what they know in the same amount of time.[Obvious alert: this is why you try to assemble complementary teams. In Gauntlet, you want the long-range Archer, the healing Wizard potions, the Barbarian to deliver damage, and the Valkryie’s armor for protection.]
  2. We all get rusty.Despite years of trading and writing, when I read Agustin Lebron’s Laws Of Trading (my notes) I realized how lazy my own thinking had gotten. It put me right back in the culture and mind habits of prop firms in a way that reminded me that weeds of lossy heuristics were growing in my mental garden.
  3. I promised to send a list of posts to get the gears turningAs I sat down that afternoon to compile the list, I figured I should make it available to anyone who felt the same.

With that enjoy a new portal:

🧠Moontower Brain Plug-In

📖Learn

🏋🏾Practice

Moontower #184

Friends,

Wednesday’s Moontower Munchies, Mondegreen Minds, was a celebration of computational thinking. I shared a quote by Montessori instructor Matt Bateman in reference to math:

It matters for your soul. Math is the realm of precision, exactitude, quantity, measurement, and logic. If that’s the realm you’ve populated with secondhand incantations, that will invariably transfer to areas of life in which those things are cognate. (Which is every area.) The exactitude of the mind, the quality of judgment of the mind, and the independence of the mind are interrelated.

He quotes Maria Montessori herself:

When you say “There goes a man of vague mentality. He is clever but indefinite,” you’re hinting at a mind with plenty of ideas, but lacking in the clarity which comes from order period of another you might say, “He has a mind like a map. His judgments will be sound” in our work, therefore, we have given a name to this part of the mind, which is built up with exactitude, and we call it “the mathematical mind.”

Bateman asks:

Is your mind made of routines that are alien incantations that you mysteriously “work”? Or is it understood, made up of independently cognized algorithms, which you can mull and interrelate, and in which you have earned confidence?

The reason I write anything on any particular day is usually opaque to me. Most of my alien incantations come from the mind-cleansing bombardment of a hot shower whose snippets I can sometimes reassemble into a cohesive message. I don’t ask why any particular topic occurs to me but this week my urge to promote computational thinking had a few sparks.

I’ll mention 2 here and another in Money Angle.

  • This was StockSlam week.Steiner had a vacation in the Bay Area so we used the opportunity to host the pit trading simulation in SF and Walnut Creek. I love doing these sessions to meet people, play games, foster in-person connections, and help participants viscerally feel the concepts I write about.

    The world of finance, trading, and betting is an amazing laboratory to improve your thinking and decision-making. Being forced to put a price on a belief sharpens fuzzy thinking.

  • A meeting with a local friendWhere I live in CA nobody talks shop (this is probably not true on the peninsula or showbiz land). Here folks people are obsessed with skiing (Tahoe this and Tahoe that and best season ever, yadda yadda) and mountain biking. I’m no adrenaline junkie and my Egyptian blood hates the snow.

    So I was surprised a) that a friend was actually in town and b) that they wanted to talk shop (kinda). This person invests in pre-IPO companies today but spent the past 20 years in software sales and the 90s as a software engineer. They reached out because they wanted to learn more about options. Not because they wanted to devote themselves to trading, but because they thought dabbling in options would help them be more methodical in their thinking.

    A few points they mentioned:

    • They felt that their computational thinking muscle had atrophied since their engineering days, especially with a life in sales. While they had developed strong pattern recognition and business acumen, they felt gaps in how they synthesized those inputs into decisions.
    • The founder of their fund seems to think in terms of options but uses a different language to describe scenarios. This reinforced my friend’s sense that this was a place they should improve.
    • They wanted to take a more hands-on role in helping their kids (who incidentally take chess lessons at my house) think rigorously and thought directing their own attention in that direction would help.

My responses:

  1. The grass isn’t greener. I was jealous of their experience.Those pattern-recognition inferences are inputs and can only be gathered by decades of reps. The reasoning part can be taught much faster. If you spent just a year in a trading/arbitrage environment you’d have a useful lens to carry with you for life. Acquiring a practical mental catalog of business models takes much longer. I believe I can take my brain and stick it in someone else (provided they had some minimum aptitude, desire, and work ethic). I can’t acquire the equivalent fraction of what they know in the same amount of time.

    [Obvious alert: this is why you try to assemble complementary teams. In Gauntlet, you want the long-range Archer, the healing Wizard potions, the Barbarian to deliver damage, and the Valkryie’s armor for protection.]

  2. We all get rusty.Despite years of trading and writing, when I read Agustin Lebron’s Laws Of Trading (my notes) I realized how lazy my own thinking had gotten. It put me right back in the culture and mind habits of prop firms in a way that reminded me that weeds of lossy heuristics were growing in my mental garden.
  3. I promised to send a list of posts to get the gears turningAs I sat down that afternoon to compile the list, I figured I should make it available to anyone who felt the same.

With that enjoy a new portal:

🧠Moontower Brain Plug-In

📖Learn

🏋🏾Practice

Money Angle

In a recent interview with Tim Ferriss, VC Bill Gurley admits:

If there was a scale of financial sophistication between one and 10, and you would say a really smart person in New York is an 8.5, the average Silicon Valley person on financial literacy is a two.

And it’s funny because they make fun of Wall Street, but it’s just out of ignorance, they don’t know anything.

Bill said it, not me (the transcript is worth reading for the full context but I’m not twisting him… those words are the spirit). I don’t know enough to have an opinion on this but I do find it surprising. Financial literacy starts at home and VCs don’t strike me as a cohort that rose from the gutter so either I’m wrong about the source of financial literacy or maybe poor kids play lacrosse after all.

Either way, the workings of money are abstractions like code. It touches almost every decision since it prices time (interest rates function as an exchange rate between time and money). It’s a basic life skill in an increasingly abstract, financialized world. Teaching our kids about it is basic hygiene.

Last night, we had our regular family dinner with my wife’s sister’s fam (4 adults, 4 kids — grades 1, 4, 5 and 7 plus another 4th grader who was spending the night). We usually go around the table asking each person about something they were grateful for that week or what’s something they tried at and failed (I know, I know it’s a bit cliche. These prompts do lead to provocative discussions and serve to put kids and adults on the same level).

But this time we did something different.

Yinh wanted to use the Silicon Valley Bank run as a learning moment. She started by explaining how banks invest deposits in longer-dated loans to earn a yield. To nudge the kids towards understanding the risk, she said the bank invests in loans that only pay back once a year. While not mechanically true, the point was to have them recognize the liquidity mismatch between the long-dated loan and the deposits that can be withdrawn anytime.

I taught them how rising interest rates cause the value of the loans to fall. But I also dispensed with mechanical accuracy in favor of intuition. I told Zak he plays the role of the bank. He loans me $100 and I promise to repay him $110 in one year. But then, immediately, mom asks to borrow that $100 from me but she’ll pay me back $120 in a year.

How should Zak feel? Well, sad. He’s going to get $110 in one year but since his mom is willing to pay $20 for a loan he could have lent her only $90 and still known he’s going to get back $110 in a year. Of course, this isn’t accurate interest rate math, but save that for a 7th grader. For a 4th grader, this delivers the point intuitively. [And for adults who think buying individual bonds instead of a bond fund somehow is less risky because they know how much nominal money they’ll get back, think through Zak’s position here — he is still getting $110 back but he’s definitely sad even though the counterfactual universe where he invests in a bond fund that gets marked down to $90 is optically worse.]

I was fortunate that my mother taught me about money. I can still remember my brain hurting when she explained a mortgage to me. It took a while to get my head around it. Remembering that keeps me patient — I’m grateful she persisted until it got through my dense skull. She didn’t push, she just repeated herself calmly every time I was frustrated “how does this work again?”. It sinks in eventually. If anything, the exposure will prime them to learn faster when they do encounter it down the line when the stakes are higher in school or real life.

[If you think my difficulty in understanding a mortgage was stupid, I got a better one for you. When I was about 12 or 13 an older kid told me a prostitute is “someone that gets paid to have sex with you”.

Sit down for this.

My mental model for “someone gets paid to X with or at you” was…a hitman.

I now believed that there was a person whose career was to have someone pay them to have sex with a 3rd party. Until then I had the impression that sex was a desirable activity but then hearing it connoted as something that is delivered as revenge or assault made me wonder if sex might actually be a gross punishment.

Dazed and confused is a fitting description of my existence so I’ve got that going for me and this blog.]

Money Angle For Masochists

We played StockSlam after dinner. The kids (well not the 1st grader) and adults were all into it.

There are 8 colors or shares that take a random walk over 10 rounds. The shares of the color that climb the highest are worth $100 at expiration. The rest of the shares are worthless. So you are trading a derivative contract (a future) not the share prices directly.

Purple is in the lead:

The rules are simple. You are mock trading in an open outcry environment. You start with 4 shares of each color and cash. It’s a free-for-all where you can trade with anyone at any price. You can bid, offer, or make 2-sided markets. It’s exactly what we did when we trained although simpler since we aren’t using options (although depending on the audience we will also trade options as side bets…”what’s your offer on the blue 150 call?”— if you get lifted, you can buy blue shares to delta hedge and isolate the vol).

The game is a deeply layered experience. You can just play for fun. It’s wildly energetic — we make sure everyone gets involved and there are gentle ways to do that, different personalities manifest in so many ways…some sling from the hip, some are shy or don’t want to open their mouths until they think they know the value of everything but then it all changes and you realize that approach won’t work.

But what attracted me to the game, beyond the fun, was how it bursts with trading lessons. Based on the audience we modulate the experience up and down. We give homework leading up to the event and bridge the rationale of the questions to insights embedded in the game. We connect real-life investing and trading concepts to the game (and honestly we don’t even get to them in these 2+ hour events…everyone wants to play not listen to lecture).

The single most powerful lesson though is one I harp on all the time — trading is about measurement not prediction. In the game, prediction is not even possible. The walk is random. But skill expresses itself strongly! Your ears pipe in pricing data so you can triangulate fair value and find aberrations. The visceral feel of playing skillfully is well-matched to the feeling of trading effectively in real life. When I pull you aside and ask why you did X or Y, a good answer will take the same form of sound trading rationale — “well, I bid 17 for green because red which is in the same position just traded 20 and I know Sam bought a bunch of green last round for 12 and is looking to flip a quick profit”. Your transacting like crazy but you can kind of tell without stopping to count if you are making or losing money when you get into the flow.

Getting In The Trading Headspace

Let’s pose some questions and entertain some scenarios.

At the start of the game, all the colors start at 100. I might start by just throwing out a 14 bid for red or a 9 offer in yellow just to see or a 16 offer in green, etc to get a read of the thought processes when the game is a blank slate.

Let’s look at a scene futherer along:

Suppose the following montage represents the situation in the pit:

Purple: 28-32

Green: 20-24

Blue: 20 bid

Gray: 10 bid

Jane yells “Pink/orange 1×3…even bid for the pink. I’ll buy pink, sell 3 orange for even”

What do you do?

If you sell the 1×3 you will get long 3 orange and short 1 pink. You can then turn around and lift the 1 green at 24 while hitting the 10 bid in the gray 3x.

What’s your net position:

+3 orange

-1 pink

+ 1 green

-3 gray

Chunking the risk:

  • You’re long 3 orange and short 3 grays (they are worth about the same, as they are 96 and 95 respectively in the race).
  • You are long 1 green and short 1 pink (again worth similar amounts based on their race position)

The risk on these positions is basically a wash…but you collected $6!

[You sold 3 grays at $10 each and bought 1 green for $24. The pink/orange 1×3 traded premium neutral]

If you keep doing positive expectancy trades and manage to not get too unbalanced in your positions you will have a high Sharpe and be profitable by expiration. If you just try to load up on the color you think will win, that’s a zero expectancy strategy that’s high risk/high reward and will have a garbage Sharpe over many games.

As we play the game I might come over and nudge you:

  • “Hey, do you think the gray bid had any room? If you can squeeze an 11 bid out of them then you would have collected $9 instead of $6.”
  • “What if the gray bid was thin and you could only sell 2 on the 10 bid? Do you see how liquidity and gauging the size on the bid/offer is important? You are now ‘hung’ on 2 grays that you couldn’t offload. Is the trade still worth doing if you have to hit a 9 bid on the remaining 2 lot for an average price of 9.33?”
  • “The green bid was only 20, you could have bid 22 and maybe the 24 offer would have stepped down and offered 23s or better yet just hit your mid-market bid.”
  • “Blue is 20 bid…maybe those oranges and grays were kinda cheap relatively and the good side of the trade was just buying the orange 3x via the first ratio trade but not locking it in by selling the grays. Don’t do a trade good by $5 and then do a trade bad by $2 to lock it in if you don’t have to…you have to maximize when you have the best of it because you may find yourself needing to give up edge sometimes to manage risk”.
  • “With the green offered at 24, maybe you can dangle a 22 offer in the blue…if you get lifted turn around and take the greens. You’ll have legged the spread for 2…maybe you try to offer out the pink/blue spread at 7 fishing for a 5 bid. Paste those and your net position is long green/short pink for a $3 credit!”

This is trading.

Replace colors with option strikes/maturities and all the many combinations of vertical spreads, synthetics, straddles, and underlying… churn all day, and let the chips fall where they may.[see Mock Trading Options With Market Makers]

If you trade enough with a positive edge the expiration results are just noise — you win some, you lose some. The p/l over time converges to your edge.

Knowing the arbitrage relationships in options is the same as knowing that the field of colors can’t be worth less than or more than $100. Today we measure fair value from liquid consensus using machines — in the game we gather consensus by listening. In the pit, it’s loud and busy and orders are flying around everywhere. You learn to focus attention on what matters. And that changes depending on the context. The same is true in modern trading.

Today we enter trades with code or mouse clicks not vocal cords but the concepts are the same. That’s why prop firms still use mock trading to train. The arena is a Socratic forum that opens up conversations about practical scenarios. It’s like having a poker coach press you on “Why did you call that bet? What did you think they were holding? With what odds? If you think they just caught a 2 pair with that Jack of clubs on the river, do you think they really would have called the big bet on the turn with a low pair and no draw?”

Mock trading in the presence of an experienced trader is an opportunity to debug your thinking.

This was Friday night:

And then Saturday night with the family:

rea events ranged from 10 to 25 people. I’m still in awe of a 6th grader who could just see the Matrix. The kid was fast and a total shark, preying on people that were still getting their bearings. After the game, he had opinions about shifting some of the probabilities in the algo and adding skew. I asked his mom if he was coding or using Excel and she said “no, not yet”.

”Umm, give him to me”. With some tools for expression he’ll be off to the races!

Otherwise, with respect to the game, I will share more as appropriate. We did have a videographer at all the sessions so at some point there will be more to see. In the meantime, if you are interested in having us do a team-building or educational seminar at your office, conference, or school hit me up and we’ll figure something out. By the way, the game shown above is just one of several games we actually trade on. The attendees will remember their favorite “bunny” I’m sure.]

Mondegreen Minds

There are some domains that select against “fuzzy” thinking. Coding instructions for a stupid box of transistors to carry out. Pricing an arbitrage down to a 1/2 penny. Building a literal bridge.

The opposite of fuzzy thinking is computational thinking. Google sponsors a course by the International Society for Technology in Education (ISTE) called Introduction to Computational Thinking for Every Educator.

From the description:

Computational thinking (CT) is an essential skill for students and educators alike. This systematic approach to solving problems is at the foundation of not just computer science, but many other subject areas – and careers – as well…Through this course, you’ll increase your awareness of CT, experiment with CT-integrated activities for the subject areas you teach, and create a plan to incorporate CT into your curricula.

I’m not steeped in educational pedagogy, so I’m taking liberties when I say computational thinking is a sub-category of what I’d just call “rigorous thinking”. One of the defining attributes of said rigor is being methodical in your thought process. The code, the argument, the theoretical price, the ruling — they should all be laid out in steps that lend themselves to debugging. From this perspective, good writing is as much a child of rigorous thinking as computation is.

The merit of such thinking shouldn’t need much support. You are able to read this on a phone or computer because ingenuity employs rigor. But if your day job isn’t in a STEM field you may think it’s impertinent. Judging from the sludge that spills from the mouths of politicians or partisan hacks (and then gets repackaged into memes), it’s pretty clear their reasoning brains are intentionally shut off out of convenience. They’re hacking humans, not computers. And the nature of success means there are enough blind squirrels finding nuts that one might conclude vision is overrated.

But if you care about calibration and making decisions with a tighter link between input and output (life is such that it will never be as tight as the artificial world we grow up in where grades dictate your “ranking”) rigorous or computational thinking is a useful skill. If anything, to help neutralize bullshit.

In Place Value As Soulcraft Montessori advocate Matt Bateman writes:

Interestingly, in Montessori math, the target of mastery is decimal place value. The whole Montessori math curriculum is geared towards developing a cognitive, habitual, almost physical understanding that going past 9 means that something changes (similar to Alpha math emphasis on physical). Is your mind made of routines that are alien incantations that you mysteriously “work”? Or is it understood, made up of independently cognized algorithms, which you can mull and interrelate, and in which you have earned confidence?

It matters for your relationship with the world, a world that is increasingly mathematical. Even if your life’s work isn’t particularly mathematical, being alienated from math means being alienated from progress. Montessori writes of the increasing importance of math, in a passage that could have been written today:

“Mathematics are necessary because intelligence today is no longer natural but mathematical, and without developing an education in mathematics it is impossible to understand or take any part in the special forms of progress characteristic of our times period a person without mathematical training today is like in illiterate in the times when everything depended on literary culture. But even in the natural state human mind has a mathematical bent, tending to be exact, to take measurements and make comparisons, and to use its limited powers to discover the nature of the various “effects” that nature presents to man while she conceals from him the world of causes.”

It matters for your soul. Math is the realm of precision, exactitude, quantity, measurement, and logic. If that’s the realm you’ve populated with secondhand incantations, that will invariably transfer to areas of life in which those things are cognate. (Which is every area.) The exactitude of the mind, the quality of judgment of the mind, and the independence of the mind are interrelated.

Montessori again:

When you say “There goes a man of vague mentality. He is clever but indefinite,” you’re hinting at a mind with plenty of ideas, but lacking in the clarity which comes from order period of another you might say, “He has a mind like a map. His judgments will be sound” in our work, therefore, we have given a name to this part of the mind, which is built up with exactitude, and we call it “the mathematical mind.”

I love the expression “alien incantations”.

The last few years have been a bull market in alien incantations. Fuzzy thinking, Cathie Wood-math and crypto word salad (my favorite was listening to normie tradfi rent-seekers in neckties slither up next to believers and regurgitate their incantations but forget everything past the first stanza).

Not to overextend a finance metaphor but maybe things really do get that weird near the zero bound.

Stay groovy!

[Afterthought: misheard lyrics like the oft-chopped chorus to “Smells Like Teen Spirit” are called mondegreens. Modern discourse, not just crypto, feels like mondegreens having sex with each other. It’s funny to think of their children as mule-thoughts that will then be trained on by large language models. Like an extended game of Buzzfeed telephone where the substance is long lost.

A flood of written “content” is coming. The value of rigorous thinking is going to increase on a relative basis because smart-sounding, but ultimately pattern-matched writing will cost nothing to produce.

Ted Chiang’s ChatGPT Is a Blurry JPEG of the Web is worth your time. It’s a clever analogy and well-written.]