Moontower #269

Friends,

I’m driving to Costco Friday morning with mom. She’s telling me that she’s waiting on a friend who is going to help her sell some of her dresses on FB Marketplace. I offered to help but wrapped it in “let me show you how I do it”.

Of course, I was just going to have ChatGPT write the copy, format it for whatever sites she wants to put it, etc. I’ve shown her LLMs before but it’s not part of her routine so I have to remind her that there’s this useful thing out there.

[Aside: This week — I gave it a video of my son’s bike not switching gears to have it help us troubleshoot. And it worked. I feel like I give it 50 screenshots a day but I’m behind on the video thing.]

Anyway, she said something that was both sad — and totally predictable:

A defeated: “If I can have this GPT thing do everything for me what’s the point of talking to people?”

Let me say something before I continue — acceleration might be so destabilizing that we regret it. But the regret will be empty because regret implies you could have chosen differently. AI safetyism suggests we can. But as long as innovation is distributed enough (nebulous word but it’ll do) coordination is fighting a formidable anniversary — the “Guinness book impulse”. Me — I’m long resigned to locally optimizing til the end of humanity, I’m just gonna use the useful stuff.

Back to my mom. I disagreed as agreeably as I could.

In 1990, you could have a discussion about how many wives Henry VIII had. Today, someone goes “why are we arguing about facts?” when Siri is listening. A whole style of conversation went away. Only someone who longs for Crystal Pepsi misses arguing about facts.

AIs are going to make things as complex as drafting and posting an ad as simple as Googling the definition of “ad”. I mean this is the seat of the whole LMGTFY joke. But as AI improves it will encompass so much — including some people’s entire job description.

If we dash into the future as we have with prior transformative GPTs (general purpose technologies not “generative pre-trained transformer”), automation will free us to move up the task complexity ladder. But when intelligence itself, in all its recursive acceleration, is the technology — how human-speed needs adapt to sci-fi capability is anyone’s guess (and if you’re into that sort of thing, there’s plenty of guesses out there).

But yea, if most of your questions start with “How do you…”, before the words hit another’s ears your phone will interrupt — let me AI that for you, until you are trained to only talk about — whatever else there is to talk about.

My mom is still wondering about that one but the answer is obvious even if she isn’t aware.

🔗Further reading

Terms of Centaur Service (9 min read)
Venkatesh Rao

Venkat is one of my favorite writers. He has been co-writing with LLMs in a series called Contraptions under his main substack. He’s also documenting his prompting strategy and techniques. It’s like watching a child discover how to use an unfamiliar toy except the child is a genius and nobody else knows how to use the toy either. You are watching someone tinker on a frontier. This post lays out his case for this and it’s absolutely worth reading.

But, the piece I enjoyed more is an example of this tinkering called The Poverty of AbundanceThe article is a critique of the book Abundance by Ezra Klein and Derek Thompson but it’s voiced via a 3rd person device — the setup is:

a Venkat’ subscriber response to the question ‘Should I read Abundance?’

The writing is strong, the argument resonates, and I just found it enjoyable (although I’ll admit it was a bit repetitive when I read it again, controlling for the fact that I read it, well, again).

Some quotes I snipped:

  • For the better part of two decades, they have constructed and defended a style of procedural liberalism that demoted imagination, displaced conflict, and outsourced moral complexity to the aesthetics of clarity and competence.
  • But the wound cannot be closed by the hand that inflicted it. What follows is not a conventional review. It is an accounting.
  • Before we can understand the shape of Abundance, we must first study its echo. The reception of this book is not merely a collection of opinions—it is a map of allegiances, a soft launch of an ideological bloc. The chorus of voices praising it are not simply impressed readers; they are participants in a long-running effort to refurbish the liberal project through the idioms of competence, optimism, and post-ideological pragmatism.
  • Its very reception reveals its function—not as a proposal for change, but as an aesthetic rebranding of a liberalism in retreat.
  • there is no real vision of the goodAbundance offers motion, not destination. It presents politics as tempo, not telos. It cannot say what we are building for, only that we must build faster…It takes the tempo, but not the stakes. It lifts the vocabulary—builders, abundance, speed—but re-instruments it for procedural liberalism. The result is a rhetorical uncanny valley: liberalism in cosplay, moving fast and healing things, in theory.
  • This is mimicry, not convergence. The authors do not join the techno-right’s program. They do not defend wealth, capital, or founding myths. But neither do they clearly break with them. Instead, they aestheticize their urgency—appropriating momentum while disavowing ideology.
  • Abundance cannot imagine a world. It can only imagine more throughput. More houses, more energy, more bandwidth. But more is not a theory of the good…The liberal imagination, as represented here, has decayed into optimistic logistics—a moodboard of acceleration absent any cosmology.
  • And the political imagination this produces is impoverished. Democracy becomes performance. State capacity becomes project management. The future is rendered not as possibility but as a better-run present. This is the endgame of procedural liberalism: aesthetic pacing instead of moral theory. A tone of competence in place of public morality. Abundance does not rebuild the foundations of liberal belief—it rebrands the ruins.
  • Abundance is not worth your time—not because it lacks intelligence, but because it lacks courage…It is a strategy, not a vision. A memo dressed in urgency. And you, I suspect, are not in the market for memos…ou are looking for what Abundance cannot offer: a theory of change that begins with conflict and ends with meaning.

Insofar as this is Venkat behind a curtain and I know he is a fan of James C. Scott whose Anarchism essays I finished recently, the critique tracks 😛


Money Angle

Good time to re-surface Harel’s gem:

The Realized Volatility Puzzle (9 min read)
Harel Jacobson

This one is a bookmarkable dictionary of various realized volatility measures.

Realized vol computations are on my mind because as we’ve been upgrading our data pipelines in the moontower app we are discussing enhancements to our realized vol infra to leverage the upgrades.

I won’t go into our details here but the recent rally holds a clue as to why many classic measures of realized vol struggle — they are too slow to reflect the present.

This is my custom list in the app as of Friday’s close. I point you to the 30d VRP (“volatility risk premium”) column…all those negative numbers mean the 1-month implied vols are trading at a large discount to the 1-month realized vol. In other words, the options market expects the next month to be much calmer than the Vitamix-on-max-speed market Liberation market of April 2025.

It’s a bit like looking at VRP after earnings — it’s “low” because they divide a large price move into a volatility that anticipates a more normal environment.

A manual adjustment to our VRP calcs in the app is to look at our vol cone chart. This is TSLA. You can see that the current 30d realized vol (green line is current daily RV readings of various lookback) is way above the 30d IV…but the 1 week IV has vol premium to the 1-week realized vol…in other words, realized vol has crashed (also obvious from the green line):

Traditional VRP measures struggle both ahead of known events (that’s why pro’s “extract”) and after a period of insanity that the market feels is at least partially resolved. We are working on enhancements to automate the adjustments you should make coming out of high vol periods.

SD from 200d MA column

In the screenshot above I drew a box around the SD from 200d MA column. We added it recently to the Cockpit view.

The definition:

ln(price/200d MA) divided by 6m IV to normalize

It’s not a signal just a useful way to get your bearings after a lot of movement with a meaningful comparison. The ln() is basically the same as “the % difference from the current price to the 200d MA”

We divide by 6m IV which is a stable enough ruler to compare across names. If TSLA and SPY are both 5% lower than their 200d MA, TSLA is much “closer” once you adjust for its volatility.

Money Angle for Masochists

I saw this on Kalshi back on 4/25:

Do you interpret that as bullish?

Simmer on it a bit.

I’ll come back to it in a sec but before that I want to point out that it reminds me of this tweet:

In both the Kalshi market and the tweet a normal person sees a delta bid.

In both cases, I (and most option traders probably) see a vol bid.

For the tweet, it’s all explained in one-touch.

Why does the Kalshi market look like a vol bid to me?

Look at my gut reflex to the Kalshi quote in this tweet. The answer lies is in the first thing I asked Grok.

I’m exhaustingly repetitive in trying to advocate for seeing the world with a vol lens because at its core it’s a prompt to think about risk and its price.

But ya know, maybe also just ignore it — BTFD and carry on is an American birthright. Anything that keeps you from interpreting information as bullish should be burned for warmth so feel free to print a stack of moontowers like this one and light a match. Don’t worry, I am pathologically unable to take offense anyway.

From My Actual Life

My reason for my mom’s visit, as she does every year at this time, is for my little guy’s birthday.

Of the kids in our wider family he’s known for long phases. My wife misses his Avengers phase which lasted 2 years, which handed off to a car phase where he would check if every Dodge Challenger on the road was a Hellcat or Demon, but his longest phase has been otters which is going on 2.5 years.

I’m doing my best to influence the next phase — I’m taking him to see Jack White in 2 weeks to follow up on our recent pilgrimage to see Angus.

He’s pretty stoked in light of his first performance last week (that outfit was picked out of his closet at 11pm the night before as he wanted to have a White Stripes look. I feel uncomfortable in front of an audience — he’s made of a different substance than me):

And if you’re wondering…the gift wrapped on the table in the pic above is a Bambu Lab A1 3D Printer recommended by my avid hobbyist friend Dave Nadig. My first request is some 1mm guitar pics.

I’ll report back on how 3D printing projects work out.

Stay Groovy

☮️


Moontower Weekly Recap

Posts:

Moontower #254

Friends,

It’s been a heavy week. I wrote more up top here so Money Angle is just one section today.

First, here’s one small thing you can do to not feel helpless.

Khe lives in LA (not in the fire regions) and our families both have seen too many pics from friends in affected areas.

Living in the Bay Area you hear your share of fire anecdotes ranging from the Oakland Hills fires in the early 90s to the fires in recent years north of SF. A friend of mine was a top official in Contra Costa County Fire and I’ve listened to some harrowing stories including a time he called his wife from a fire battle on a local mountain with the “I want you to know I love you and the kids”. CA firefighters are a badass breed knowing full well what they’ve signed up for.

There’s a lot of finger-pointing already and the fires aren’t even close to being contained. Getting to the bottom of the pile to find the ball when this is over (sorry to even minimize the current moment with a “when this is over”) is gonna be an ugly mess of scratching, eye-gouging, and nut punches.

If you live here with your eyes open you can see how CA is a devil’s bargain. When I sold my house in 2020 it was under a red sky. PG&E was in the news. Large chunks of people’s net worths being uninsurable just didn’t strike me as sustainable. I was wrong because all home prices did was go up since then.

[Contradicting that thought is my simultaneous hunch that a major natural disaster would super spike the prices of remaining homes when the demand to build devours supply. I thought a widespread disaster in the congested area would have come from a faultline.]

Nothing’s changed. Insurance math ain’t gonna math unless the kindling is cleared. This is a good thread on some ground truth. It’s comforting because physically there are possible solutions. Realistically, it’s TBD. To be doubted.

California’s troubles run generations deep.

1988’s Prop 103 kneecapped the insurance market’s ability to find clearing price for the risk. So the risk is socialized. And when risk is socialized it’s there’s less incentive for its true owners to internalize it. If “crabcakes and football is what Maryland does”, California is sunny weather and price distortions.

Prop 13, enacted the year I was born basically granted landowners a call option on inflation while wage earners were left short convexity via state income taxes required to feed the beast effectively subsidizing landlords. This is not “unintended consequences.” These were obvious second-order effects. Great job all around, direct democracy.

[A side note: I’m not unsympathetic to seniors who don’t want to be displaced because of property taxes but there can be targeted programs for freezing taxes beyond a certain age. But even absent that, you have to look at the problem holistically and in the counterfactual. If you don’t have Prop 13 distorting the cost of living here, people would be forced to plan better. Ya know, like they do in other states. I don’t know enough about what I’m about to say but my guess is the closer the tax receipts are to where people actually live the better aligned elected officials are to the constituents. That compliance usually prohibits hedge fund employees from donating to local officials but not national candidates affirms that intuition. In compliance’s case, the stronger influence is a bad look. In general governance though, it’s better.]

In any case, it’s hard to focus on what happens once the patient is no longer in shock. It’s easier to just fall into the loop…what would you do if you lost your home, your kids lost their school, maybe you didn’t have insurance?

Even if you have insurance it must feel overwhelming. I was chatting with someone yesterday about how 8 years after the Sonoma fires there is so much that is not rebuilt. And that’s not even an urban area.

What if your house is still standing but your neighbors’ houses are gone? At that point you might want to start over somewhere else but your put option didn’t pay out. It makes me think of this dark bit of humor. “My family!!!!”

5 years ago we were, without knowing it, heading to a lost year or more. The fire victims are staring down a similar barrel. The New Year’s resolutions scribbled a week earlier. Literally gone. What’s the difference, no time for that now. Got a full plate for the next million hours just to get back to stable.

[As a matter of commiseration it’s not helpful to relate a story back to yourself. I have no idea how these people really feel. But I’ll share that my apartment burned down in college. Thankfully a roommate noticed the smell and quickly got us to knock on doors…realizing that nobody knew where the smell was coming from we evacuated across the street not knowing what was going on. Until I saw the flames burst out of my bedroom window on the second floor. The fire was in the walls, starting from the take-out joint’s oven below us.

We were fortunate because both the university and Red Cross were able to quickly get us cash and concessions on due dates. And most importantly a friend housed and fed a bunch of us for days as we tried to secure apartment leases elsewhere. Despite the experience, I can’t fathom what it’s like to go through anything like this with your own home and when it happens to everyone around you. But I suspect even small gestures will go a long way.]

I can’t find the link now but someone who lost their house in Hurricane Milton wrote a good thread about how confusing it is. It can take a while to be allowed back to your site (I still remember the day we went back to the building and it does stay with you. And again that was small potatoes). The person explained how you collect little bits of info from everyone as nobody can see the whole picture.

Embodying what it must be like every day for the foreseeable future will hopefully focus the rest of us on being useful right now. But yeah, we are going to need to learn from it.

I hate to say it, but I’m not optimistic.

I don’t wanna be a drag every week in this letter so maybe I just get it all out now so I can get back to sharing educational things.

An unpleasant musing

The “algorithm” knows you can’t hate someone so vastly different from yourself.

Our deepest hate is reserved for those similar enough to remind us of ourselves. You find the Taliban, serial killers, and cartel bosses disgusting but they are too far to hate. They didn’t betray you. You were never on the same team.

If 9/11 were to happen today, would we unite?

Not if the algorithm is in charge.

This leads to a haunting question: is Twitter/X or whatever social media you look at real life? The line feels blurry even when I’m “touching grass” with people in meatspace. I’m increasingly noticing convergence between socials. Which makes sense. If the meme works there, copy it here. (Related: playing video games with my son has made me more aware of Twitterisms that are really gamerisms because there’s no way he would know them otherwise). The “memes” start as compressed thumbnails of an idea until they gradually terraform its host’s personality.

Luigi as a vigilante is a meme. That arsons might plausibly be flaming the original fire feels like it’s coming from a similar place. The Joker is here. I’m not here to point fingers because as wrong as the Joker is, as unjustified as his actions are they start with pain. Explaining the source of pain will never justify the evil it produces, but pretending it’s gonna just go away is begging for the spiral to accelerate. And we are so far from addressing that pain.

Hey, but I hear SPX earnings are expected to grow 15% this year.

Is Twitter real life? Elon says it is. He says it’s the media now. The truth. Ok, do you know what the “truth” is telling us? It’s telling us you have two years to get rich because capital, not labor, will be all that matters. That soon enough as quickly as you can imagine it an AI army will build it. You just need enough capital to pay the electric bill.

For people who still put gas in their car, this sounds like a death sentence. And if you shrug and say, “Well, it’s the truth,” then okay—Jokers everywhere. Don’t be shocked.

Positional Scarcity and the Human Condition

The accelerationist dream of post-scarcity is a fantasy. It sells itself on utopian visions without addressing the reality of positional scarcity. Status, sorting, and competition are zero-sum. They don’t vanish, even in a world of abundance. These instincts are baked into the human condition.

Nature reminds us of these instincts. My kids have been home sick much of the past week as the plague gets traded in our house like Pokemon cards (this is also weighing on my mood. Sick kids are not themselves and it’s sad, pathetic sight). TV has been on a lot. We were watching a nature vid of male humpback whales chasing a female trying to protect her calf. The males all wanted to do the “humpty dance,” but the mom wasn’t interested in Irish twins. The eventual victor was the male who escorted her to safer waters, perhaps hoping she’d “repay” the favor. The narration projected human motives onto the whales, and as awkward as that felt, it refreshed my sense that our capacity to trade, to make mutually beneficial exchanges, is what holds us together.

To situate this capacity truthfully we acknowledge the tense contexts. There’s social Darwinism. Life is competition. As I alluded to earlier, this remains even if we solve hunger. But we also cooperate at least at the tribal level. “Tribe” encompasses many scopes. “America” itself is a tribe that contains many tribes. And one tribe that encompasses even “America” is civility. A tribe that believes in inherent human dignity. It’s an ideological tribe. It’s from that tribe that we sense the trade-off between equity and efficiency. Efficiency means it’s important that our surgeons have proven their steady hands and sound minds. Equity means we don’t throw handicapped babies in Lake Tahoe. These are the outer boundaries of the tribe’s beliefs. Within the boundaries, “reasonable people can disagree”.

What’s happening right now is confusion about the boundaries and whether being part of the civility tribe is even desirable. The tribe is very large. Almost everyone starts within it. But the Joker is outside it by choice. Because of the betrayal of either boundaries or usefulness.

This is colliding with another human impulse.

Just Because

Humans do bizarre things. Flip through the Guinness Book of World Records, and you’ll see countless examples of this: we set records “just because.” Why did you climb the mountain? Because it’s there. Why do you want to go to the moon? Or Mars? Why not?

There are instrumental answers to these questions. Justifications or rationalizations depending on your own leaning. But they are beside the point. It’s gonna happen because humans gonna human.

Injecting some chaos and mutation into an evolutionary system is natural. If we survive it, it will turn out to have been species-level adaptive. We stand on the cusp of great acceleration. People trying to literally cure death. The stakes feel massive. Like humanity forking. The rhetoric sounds like something someone committed to the tribe of civility would say. We “need” to do this.

But today and increasing so…

…when the speaker says “we” the listener doesn’t trust the “we” includes them.

At least not a version of them that is dignified.

The lack of trust doesn’t come because the speaker is evil. It’s because we know from experience that humans will do things just because they can. Steve-O is the kinda guy that would have been a Jackass for free. Curiosity drives us forward. But poison is the dose. Morbid curiosity is what we call an overdose.

Society is looking at a group of people at a party and thinking, “Should you be taking that much?” Some dude in the corner funneling beer is egging them on and the normies who have to wake up early to go to work say “You know it’s getting late, I’ve had a bit to drink and if I wait any longer I won’t be able to catch an Uber?”

Huh?

Bruh, don’t you know that Waymo never sleeps?


A thought that didn’t fit

“Just because” isn’t always “just because”. Doing anything unusual has an algorithmic incentive. My kids watch YouTube basketball channels constantly. I saw an episode where they were record-book maxxing. Just trying to set records for various things like “dunks in a minute”. These videos get tons of views, but I find something deeply unsettling about them.

Making money is a reasonable proxy for “created value”. But you’d have to be pretty far up your own rear to think that there aren’t people who have gotten rich destroying value via deception, excessive rent-seeking, or simply getting away with crimes.

But there’s a wide swath of activity (think legal grifts) that always has at least a few redeeming stories that end up whitewashing the whole enterprise in the eyes of its few satisfied customers. (The rest of the customers churn because grifts are usually short-sighted, constantly hungry for new marks).

And then you have things stuff like Mr. Beast videos.

I just don’t know. It feels really dark in the same way I couldn’t watch more than one episode of Squid Games.

Sure, people point out all the good he does, but here’s my problem: attention is zero-sum. Every minute watching him is at the expense of another entertainer who will recycle that income through the economy or charity. At a macro level, there’s no additional good being done here. It’s just more noticeable when it’s a single ticket.

Maybe this is my “old man yells at clouds” moment. There’s always been nonsense content. But when I see these videos, I feel like I’m staring into Palpatine’s horrific face: “Oh I’m afraid the deflector shields will be quite operational when your friends arrive.”

We’re entertaining ourselves to death.

Related reading


Money Angle

On Friday I tried a little experiment.

I opened a voice channel in our Discord called The Moontower Subscriber Hoot.

[Back in my floor days it was common for traders on the floor wear a headset to be on continuous conference with the traders streaming quotes upstairs in the office. At the fund, we also had an open conference line on our turrets to be able to talk to other traders on the team. I don’t know the origin of the term in the industry, but these conferences are called “hoots”.]

I wasn’t writing or working on something that needed deep attention so I figured why not open the hoot and chat while I tried to sell some TLT puts. [I didn’t get filled because I was cheeky with a limit a penny above the bid.]

I narrated what I was doing which I though could be a nice “over-the-shoulder” way to explain what I’m thinking as I do it plus enjoy the banter, something I miss from the old job.

Regarding TLT, I decided to toe into some bond delta with TLT being down more more than 2 st devs over the past month, more than any other liquid name in the Cockpit view.

I decided to express the delta through short vol as TLT vols in the belly of the term structure look attractive enough to sell on both our DASHBOARD and REAL view.

I chose a 35d put…skew is a bit elevated and the strike vol on the options were up a lot that morning.

ATM vol relationship to realized vol history

We talked about several other trades on the hoot and I got to explain a juicy rev/con trade that turned out to not be a real opportunity but people came away with a better understanding of how synthetic futures work!

In narration, the group was able to see how I use greeks to make sense of what’s going on in real-time. Makes a topic that seems abstract super practical and useful. For example, if I sell .30d puts at $1.85 vs stock at $65 and buy them back at $1.88 when the stock drops to $64.50 why that’s a big winner if I traded them delta-neutral.

You can also use greeks to discuss vol changes from tick to tick.

“See how the option is offered at $1.80 again 20 minutes later even though stock is a dime lower? The option only has a penny of theta, so it wasn’t erosion. It has a .30 delta and .15 vega so that means IV is down .2 clicks”

Overall a great experiment that I’ll make a trend. Not committing to a schedule but when I host them it will be on a Thursday and/or Friday.


A few weeks ago Nick Pardini had me on his podcast Analyzing Finance.

I know Nick from his days as a researcher for Parallax, we sat a few desks from one another.

It was fun to catch up. We cover options, volatility, and how options theory principles are found in all kinds of life or business decisions. The options stuff is really perfect for people trying to learn, it’s not heavy, and touches on a lot of practical questions around when you should consider using them or not and why volatility behaves the way it does.

Stay Groovy

☮️


A Visual Primer For Understanding Options

Note:

This is a guest post by @KeyPaganRush. You can find the origin of this collaboration here.


 

If you’re a normal civilian like me, who at the very most took vector calculus as an undergraduate, you’d probably look at a differential equation like this and have the following reaction:

It doesn’t help that most people in finance who work in the volatility space are mathematically adept and don’t necessarily know how to simplify this for mathematical muggles.

I’m not that great at mathematics myself and although I use statistics and probability on a regular basis for my non-finance day-job, most of this is stuff covered in the 2nd year of an undergraduate course.

Concepts become more intuitive when I can visualize them, which has helped me scrape together just enough mathematical literacy to be decent at my job. Applying the same thinking to options, I decided to give up on trying to interpret options from the standpoint of differential equations, and instead lean into my already existing intuition of probability and statistics.

Conveniently, both approaches get you to the same answer.

I expect this approach can help other civilians finally make sense of the vol space.

An intuitive understanding of options

Probability distributions

When looking at the price of a stock, there are only 3 results that can occur next: Go up, go down or stay flat. If we make a big assumption that the chances for each are all the same, you can simulate a price chart as just being a long series of up, downs or flats.

The Galton Board shows that repeating the simulation many times over, you will find that the final price of a stock (each ball) forms a bell-like distribution, the normal distribution. Even if the probability is not equal, this is a starting point to model price movements.

Option prices as segments of distributions

You might have heard that options represent the full distribution of the market and are thus the real underlying. Sure you can argue, in the literal sense, that they are not the underlying, but that viewpoint is useless for making money, where the underlying stock price is a blunt representation of what the market expects. To illustrate, think of a stock as having a probability of having an ending price, represented by the graph below.

 

The market probabilities assigned to each of these prices is influenced by the buying/selling supply/demand of options. The peak of the distribution is typically the ATM. When you buy a call option at strike K, you are paying for the probability (The shaded green area) on the right side of K.

 

Conversely when buying a put option you are paying for the probability on the left side of K. This area of probability you buy is what you pay for an option.

 

When you sell your call, whatever probability is still existing to the right side of K is your payoff. Larger area of probability = more expensive the option is. So what can influence how much this option will end up costing?

When long a call option, if the price of the stock goes up, this shifts the entire distribution to the right. Each time the distribution moves to the right, because the stock goes up in price, you are gaining more area of probability and thus increasing the price of the option.

 

Delta and Gamma

When playing around in your mind with these graphs, you can normalise the amount of area  you have, as a ratio of the entire distribution.
The area that is moving past your strike, as a ratio of the entire distribution, is Delta1.

Notice however, that the change in delta gets bigger as the price of the stock gets closer to your strike. It then begins to scale down as you get past your strike and start moving further away from your strike. This means your delta is changing as a function of price. This ratio between the change in delta and the change in price, is gamma.

 

Vega

The area of that call option can get bigger (more expensive) even if the price of the stock stays completely still. Notice that if we just make the distribution wider, you gain more area of probability to the right side of your strike. Remember that the height of distribution at each price is influenced solely by buying/selling of options, or IV. Thus just by the market increasing the width of the entire distribution, the option can become more expensive. This ratio between the increased area for each increase in the width of the distribution is Vega.

As a bonus, you will probably notice that as a result of increased IV, the ratio between the area of the distribution per change in price, has also changed. This is vanna.

Theta

As time passes, the width of the distribution gets thinner. Why?

Imagine a $10 stock moves on average $1 a day. What chances would you give it of getting past $20 if you checked on it 250 days from now?

What about if you only gave it 1 day to do so?

See how the chances drop dramatically when there isn’t much time left for the price to move around? Thus as time passes, the distribution to the right side of your strike is moving inwards towards the ATM, reducing the area to the left of your strike over time ( and thus reducing the price of your option). This is theta.

 

As a bonus, you will probably notice that as a result of passing time, the ratio between the area of the distribution per change in price, has also changed. This is charm.

Central moments

The price of a stock is really a representation of only one thing: where will the peak of the distribution go, left or right? In fancy speak, we say it is the first central moment of the distribution, otherwise known as the mean/average of the distribution. It is just one aspect of the distribution.

When you introduce the process of delta-hedging, (see my video Gamma and Vanna Exposures) you are trying to prevent your PnL from being influenced by the shifting of the entire distribution, Ie. changes in the price of underlying.

This temporarily  “locks” your distribution in place, meaning that it can now only change in shape. Since the distribution cannot slide left or right, the only way the price of the option can change is for the shape of distribution to change.

So how can options become more expensive or cheaper now?

2nd Central Moment: Implied volatility

If implied volatility increases the distribution gets wider and the option becomes more expensive. This width of the distribution, in fancy speak, is the 2nd central moment, or the variance of the distribution. Volatility is just the square root of variance.

3rd central moment: Skew

We can get even fancier by thinking, the total variance of the distribution might not necessarily change, but that one side of the distribution will get wider but the other side gets thinner, that there will be a difference in the relative widths on either end (tail) of the distribution. This is achieved by going short vol on one side of the distribution and long vol on the other side of the distribution, delta neutral. The difference in relative areas of the tails on either side of the distribution is the 3rd central moment, or Skew.

 

4th central moment: Kurtosis

It is even possible to make a bet that mean, variance and skew don’t necessarily change, but instead bet that the width of the distribution might be thin at the middle, but wider near the ends. This is done being short vol near the middle of distribution and being long vol near the tails. The relative widths of the distribution near the middle vs the tails is the 4th central moment, which we call kurtosis.

 

By looking at the options market, we are able to gain a rich source of information and opportunities for expressing very specific views on what the market thinks the shape of the distribution is, that are independent of the entire distribution shifting left or right (Ie, price of the stock going up or down).


Appendix

Coming full circle to the original differential equation, we can now break down the meaning of this.

 

Using some basic algebra, we can re-arrange the equation (Move the right-most terms to the left side of the equation) to read like this:

This equation is simply telling you how the change in price of the option is influenced by the price of underlying, delta, theta, variance and gamma.
(For simplicity we are ignoring “r”, which represents the risk-free rate; although for those who are curious, the influence of the risk-free rate on the price of an option is known as “Rho”).

You may notice I did not highlight any vega term in the equation, to avoid getting too far into the weeds with the mathematics since Vega gets embedded inside the delta and gamma of the equation. This is because both are influenced by variance (The distribution getting wider). You can visualize this concept by changing the width of a distribution and observing how it affects delta and gamma.

Trying this out with some real numbers, lets see how this breaks down.

  • Take a call option on a stock which is currently trading at 100.
  • The strike is 110, with a 1 year expiration, interest rate at 0% and volatility of 10% annualized.
  • This stock does not pay any dividends.

An option calculator yields:

Our fundamental equation in terms of Greeks can be used to relate the value of the option to the size of the stock move. If the move size is the same as the volatility used to price the option then we’d expect the p/l to be zero. 

To see this we need to keep time units consistent. We transform annual parameters into daily ones.

  • Convert annual volatility to daily volatility by dividing it by the square root of 365
  • Annualized rates can be converted to a daily rate, simply by dividing by 365

Plug and chug:

The left and right hand sides of the equation equal each other! 

Assuming a 0% risk-free rate, if an option were priced perfectly (ie volatility is perfectly forecasted), then any gain made from movements of the price of the underlying should be offset by the theta that is going to be bled off.


More practice

What happens if one day were to pass, but the underlying did not move at all?

The purple term representing the “change in stock” will be 0 rendering the “gamma p/l” for that day to be zero.  


The option will be decay by its theta and there will be no offsetting gamma p/l. For that day, the option was “overpriced”. 

What happens if after buying the option, realized volatility were to increase from 10% annualized to 15% annualized?

We capture a gamma p/l as follows:

In this case the gamma p/l of .0082 was greater than the theta of .0036 so the owner of the option has won. The option was “underpriced” for that day because the annualized move of 15% exceeded the 10% annualized volatility the option was priced with. 

In daily terms, remember a 10% annual volatility corresponds to a 1-day change of .52% and a 15% annualized move corresponds to a 1-day change of .79%. 

The readers is welcome to discover how the p/l is a non-linear function of the difference between the realized and implied move sizes (gamma attribution is a squared term!)

Summary Tables

Conclusion

Our original equation reinforces the idea that the Black Scholes Equation is a non-arbitrage condition stating that if volatility were perfectly priced the value of the option is equal to the cost of the replicating portfolio.

Takeaways

  • Stocks only represent the first moment, a single point of the distribution but nothing about its shape or how it changes over time. 
  • Options will tell you about the entire shape of the distribution, which is why I submit that they are in a sense the true underlying distribution.

Further reading

Moontower on Gamma


If you use options to hedge or invest, check out the moontower.ai option trading analytics platform
 

The Third Eye: Rick Rubin interviews Rory Sutherland

These are my favorite bits from an outstanding (albeit 3+ hour) chat between Rick Rubin and Rory Sutherland

Spotify link to the episode


One of the things I’ve noticed about modern behavior revolves around the question: Do you want to win arguments or solve problems? We’ve mistakenly equated the two, assuming that the person with the best arguments has the best solutions. I believe we’ve both concluded that sequential logic in problem-solving doesn’t necessarily lead to the best outcomes. It’s fundamentally sub-optimal. Problem-solving is much more Darwinian and iterative. It also relies on subconscious mental processes or tacit skills that we can’t fully articulate or codify. This raises an interesting question: Is the creative process actually a process? You subtitled your book “A Way of Being,” suggesting that creativity is something you embody, not a skill that can be easily replicated.

One must acquire a sort of “third eye” to truly engage in it.

Creativity

Creative work is kind of a Galapagos Islands for understanding how you solve wicked problems. Because every day you have to go and solve a wicked problem where you can rewrite their advantages. You can rewrite the rules. You can get rid of assumptions. But fundamentally coming to a conclusion is difficult because you don’t know what success looks like before you. I mean, if you’re solving a physics problem or an engineering problem, you know when you’ve succeeded. Yes. And in this case, genuinely, you know, it’s much closer to a penicillin or a Viagra than it is, you know, you know, being able to actually spot moments of fortunate accidents or whatever. So many of the discoveries that have changed the world happened by accident. And there seems to be a blindness to this.

Newcomer advantage

On the ‘newcomer advantage’, where a fresh perspective often proves beneficial to problem-solving as it lacks the influence of preexisting assumptions:

It’s incredibly easy for experts to bring all their assumptions with them. One thing that doesn’t happen enough is that areas of scientific expertise, instead of engineering expertise, could benefit enormously. This is my main concern. This is what I spend my time fighting against, a very simple asymmetry. All creative people must present their ideas to rational people for approval. There’s someone in finance, someone in legal, someone in compliance. Well, I accept that. It never happens the other way around. Finance people with a spreadsheet never say, “I’ve arrived at this figure and my recommendation is 3.7, but before I share that with the board, I’m going to present it to some slightly wacky people to see if they have an alternative idea, or to see if they can redefine the question.” It never happens.

Artistic breakthroughs can have no sense of proportion

  1. That’s when inspiration happens, when you’re moving from one thing to another. You can cheat the odds, but you can’t force it. Anyway, John Hegarty, the great guy, told this story. He once worked with Paul McCartney on a business venture. Paul didn’t quite like John’s initial work, so he said, “I think we need to come back with this.” John said, “Well, you said next Tuesday, but can we actually have about two or three weeks because nothing good ever comes in a short time?” Paul McCartney replied, “That’s not true. I wrote ‘Yesterday’ in 15 minutes.”

    Two points to that.

    One, John Hegarty, ten minutes later, to this day, regrets not replying with, “Imagine how much better it would have been if you’d taken some time over it.”

    But the second point, which I think often causes misunderstanding, is he didn’t write it in 15 minutes, but he didn’t choose which 15 minutes. They were in the past. You could write it in 15 minutes if you have the dream the night before, of the melody, which is what happens. And so much, of course, so much of waiting to get lucky looks like laziness, actually. Or looks like a complete lack of focus.

  1. Artistic breakthroughs can have no sense of proportion

    I’ll tell the story, which I always love, which is that the decision in ‘Ring of Fire’ to use the trumpets was a kind of whimsical one, wasn’t it? So Johnny Cash was basically, you know, that moment where he just goes, “Okay, what we need here is trumpet.” I think he had an idea about the sound of like Mexican trumpets. It just painted a picture in his mind. Now, we don’t know the counterfactual. Without the trumpets, it’s not the same. It’s not the same. And so not having a sense of proportion is actually appropriate, I think, to the job in hand, where it is actually the small thing that is utterly transformative, and so not having a sense of proportion is part of the job. Sometimes the thing that makes it great is a tiny difference, not a big change. That’s also out of our control.

    Everybody, when they look for a reason for something serious, is looking for a serious reason. Yes. That the cause has to be commensurate in importance with the outcome. But actually, great things happen for stupid reasons. And stupid things happen. People trying to be important create stupid effects, whereas, people sometimes trying to be stupid can create great effects. And actually, this idea of proportionality, that the world is kind of Newtonian and that there are equal and opposite reactions and so forth, is a great model if you’re a physicist. It’s a disastrous model if you’re an economist.

    The famous case where the Beatles were turned down by the record label, which was EMI, wasn’t it? They were turned down by everyone, at first.

    They can seemingly come from nowhere:

    And so the Beatles turn up, which was interestingly on New Year’s Day, I think, where they get lost driving through London, and they go and play their demo tape to whoever it was who says, you know, small bands with guitars or on the way out and all this sort of thing. We don’t like their sound, you know, etc. And they signed I think Brian Poole and the Tremolos instead. One of the reasons for signing them was they were more of a local band, so when you recorded with them, you only had to pay for a travel card in on the tube rather than paying for return train tickets from Liverpool, which is the procurement decision of all time, if I say so.

    But was it the right decision? Because if you look at the evidence then, ‘Love Me Do’ isn’t that great a song, right? It’s like, you know, I mean, if that was all they recorded, it wouldn’t have been remembered, okay. On that demo tape, there was no evidence of greatness that anybody could reasonably be expected to notice. And indeed, you know, the Brian Poole who may sign, you had some slightly earlier success. So my question is, what was it? So it’s ‘Love Me Do,’ and then it goes to what does ‘I Want to Hold Your Hand’ as next? Or is it? I think so. I think so, okay. What happened between those two songs?

    You can ask the same question between Radiohead’s first album and their second album. Okay. If you listen to Radiohead’s first album, it has ‘Creep’ on it, which is an amazing song. But if you listen to the album you wouldn’t know this is a special group. And then they made arguably the best album of the next 10 years. So it’s hard to know what happens.

    I look at it in a spiritual way. To me, it’s like proof of the existence of God. It’s like something changes. I’m friends with Chris Rock, the comedian. And when we first became friends, he was my comedian friend who was not funny.* Sorry he was not funny. He was my comedian friend who wasn’t funny. And our relationship was about music because he loved music and had great taste in music. But he was a not funny comedian.

    And then after several years, he invited me to the Comedy Store. He said, “Oh, come see my new set.” And I went… And I went doubtfully because he’s my not funny comedian friend. And I walked in. And he was the funniest person I had ever seen. Now, for the last four or five years of our friendship, he was not that funny. I don’t know what happened. It shifted. In a moment. It was like someone upstairs pointed, it’s like, “Now you. It’s you.”

Deep insight about framing and ultimately the stories we ascribe to big concepts like “capitalism”

There’s a friend of mine who’s an economist called Nicholas Gruen, who Martin Wolf, a brilliant man from the FT, describes Gruen as the best economist you’ve never heard of. And he thinks that one of the worst things that economics foisted on the world was the idea of the trade-off. That most problems are a trade-off between one thing and an opposing thing, and the optimal thing is somehow somewhere in between these two opposing variables.

Economics encourages people to look for a trade-off, treating it as though it’s effectively inexorable, and simply look for the optimal point between these two things. He would argue that it’s basically created a massive creative deficit because people don’t look for magic, and they don’t believe it when it’s presented to them. Yes. And if all creative things are, to some extent, if not magic, by the way, you practice magic. Is that right? I did as a child. You see, this is fantastic because the understanding that actually by changing our perception of something, you can make absolutely remarkable things happen, and the usual trade-offs that are assumed need no longer apply.

By enshrining trade-offs in the mode of thinking of policymakers, and business people, and problem solvers, what you’ve actually done is create an incredibly infertile ground for creative ideas. Because you basically treat the trade-off as if it’s kind of just part of the system. I have to ask the question of this kind of obsession with efficiency. So the way I describe it in the book is that what worries me about free market capitalism is that economists and most people, management consultants, like it for entirely the wrong reason. And it’s a bit like liking Bob Dylan for his maleficent singing voice, okay? It’s very healthy opinion to like Bob Dylan, but probably his singing voice isn’t why. It’s a bad reason to hold a good opinion. And I would argue that most of the appreciation of capitalism, which is driven by the idea of its efficiency, not its inventiveness, is exactly the same problem, that we tried to optimize free market capitalism for what you might call narrow efficiency at doing preordained tasks under the natural constraints of these trade-offs, what we should have been doing is optimizing capitalism for inventiveness. So capitalism is not bad, the way that we view it is maybe not necessarily the best way. I think we’re not using it to its fullest capacity. We’re not using it to its fullest capacity. Because our appreciation of what its value is. Now, in fact, I’m not saying that consumers don’t care about efficiency entirely. If you can find a way to do something ten times cheaper, that’s a breakthrough. You know, that’s completely transformative. But given that most purchases nowadays in the developed world are from discretionary income the extent to which efficiency is prized by consumers as opposed to, for example, meaning, calls into question lower price as a strategy.

Capitalism is often viewed as an efficiency mechanism, when in reality, it’s an exploration and discovery mechanism. The Austrian School of Economists recognized this. The miraculous strength of capitalism isn’t its beautiful singing voice or fantastic lyrics. Its true strength is not efficiency. In fact, a controlled economy can be very efficient within narrowly defined parameters. The real joy of capitalism is the discovery mechanism.

Doing the wrong thing efficiently is actually worse than doing the right thing badly.

Applied “framing”: the interface

Most human behavior is strangely path-dependent. It’s significantly affected by strain and heuristics. By the way, if you sent that phone-only response out to my children’s generation, you’d get a 0% response rate because they really, really hate talking on the phone. What you do now is, for anyone under the age of 30 or 40, you provide a text response because that’s the only thing they prefer, or a WhatsApp response or something similar. The idea of talking to a human being on a phone fills them with absolute paranoia. But the fact that the short-term nature of the interface has such a massive effect is fascinating. The other benefit I had through that test was that it got me really interested in the internet because I thought when you present a choice on a screen, people will make a totally different choice than the choices they make in a shop and a totally different choice than the choices people make, for example, in a mail-order catalog. [Kris: very “medium is the message” vibes]

An interesting thing is in McDonald’s, now you order on a screen rather than face to face. Now, bear in mind, particularly men, when they order their McDonald’s from a screen not face to face, they are vastly more likely to include two burgers in a single order. This is really interesting because the screen is revealing a preference. It’s not about money or cost. It’s just that the guy might feel awkward asking for two burgers. Well, you know, do you want fries with both burgers? It could be an awkward conversation. Whereas the second you do it on a screen, apparently, the whole thing changes.

Now, if you think about it, all I can say is that the speed with which McDonald’s rolled out those screens. I’m not privy to any inside information, but the speed with which fast food outlets rolled out those screens, which was almost unprecedented, suggests that they are unbelievably lucrative in terms of changing what people order.

Now, there are other factors which are fascinating, which is that there’s another interesting psychological thing about those screens, which is that it’s more annoying waiting to place your order than waiting for your food to arrive. Because you can reframe the food coming to arrive as well, they’re preparing the food it’s adding to the quality of my meal, whereas waiting to tell people what you want is doubly frustrating. And so there is a kind of mental mind hack in that it may not reduce the end-to-end wait, but it reduces the more irritating part of the waiting, which is waiting to tell them what you want. So there are other mind hacks in that, but I find it so interesting, the extent to which the interface determines the behavior.

Decision-making

2-Way Doors

What if we need to innovate, but the only way we’ve innovated so far is by extrapolating from past successes. What we need to do is we need to actually imagine something here. We need to imagine a different reality, okay? If you can get just a proportion of people to do that sometimes where it makes sense to do so. Now I’ll give you a great thing which everybody can steal, which I only heard about recently, but within Amazon there’s a phrase which is called the two-way door where if you try it and it doesn’t work, it doesn’t really impose significant costs so you can reverse.

In Amazon, when they’re arguing something, they’ll go, why are we arguing this? It’s a two-way door. Don’t argue it. Test it. Because we can test it, we’ll very quickly find out at low expense. And if it doesn’t work or it has deleterious effects, we’ll just cancel it and revert to the status quo. They’re very conscious of the fact that you spend a load of time arguing about one-way doors, but arguing about two-way doors is stupid.

It’s exactly to your point that if you argue about it in theory, it’s a much more hotly-debated thing than if you just show it in practice. You know right away when you do it in practice. So why argue about the theory? We call it the burden of proof because proving things in advance is a massive pain in the arse, and it wastes a lot of time and it wastes a lot of effort.

Now the most interesting thing is apparently Amazon Web Services came up as an idea where someone said, we’ve got all this server capacity, why don’t we sell it to other people? And apparently, this may be anecdotal, they put together a paper that wasn’t very good. You know, it didn’t make a great business case. It was just this vague paper. And so everybody’s saying, okay, so that doesn’t work in theory. And then somebody said, yeah, but this is a two-way door, right? We’ve got the server capacity anyway. If we can sell it and make more money, it’s good. If we don’t, what have we lost, okay? And of course that’s now the most profitable bit of Amazon. The business of actually selling their server capacity to third parties. And basically selling the robustness they need as a retailer to other people who want that level of robustness. That’s what makes them the most money. Amazing.

And of course, 99% of companies will go, nah, you haven’t really made the case there, right? Without asking the question, why do we need to make that greater case? Because if it fails, it’s cost us peanuts. It’s an asymmetric bet with a manageable downside, both in terms of time and money. The upside is potentially huge. Go for those bets.

Predictive Mind Hypothesis

The predictive mind hypothesis suggests that our brain is constantly predicting, and it uses our senses only to the extent that we perceive reality differing from the prediction.

  • There are sound experiments, such as sine wave voices, where a spoken sentence is reduced to a sine wave. Initially, it sounds like modem noise, but after reading out the sentence and replaying the sine wave, it becomes impossible not to hear the sentence in the sine wave. There’s a view that these experiments, like the McGurk effect, demonstrate this.
  • In the McGurk effect, if you record someone saying “bar” repeatedly, and then record a video of the same person saying “par” or “far”, particularly “far” with the teeth, and play the video over the audio of “bar”, you hear “far”. This is because your brain effectively overwrites the audio component with the unconscious lip-reading component. There are many interesting illusions and experiments that illustrate this.

The data architecture also makes sense, as it’s similar to the algorithms used to compress photographs. These algorithms predict what the next pixel will be and only use data to describe how reality differs from the prediction. This is a much more data-intensive way of constructing a photograph than using raw files, where you have massive megabyte files because you want to be able to edit every single pixel, which can only be done in a raw file. This approach would make sense in terms of making the most efficient use of available bandwidth in the human brain. Prediction combined with Bayesian updating makes more sense as a data architecture than perceiving everything and then forging it into a whole. If this is true, it explains many oddities, like the fact that advertising changes the taste of a product.

The tension between “customer is always right” and “customers don’t know what they want”

Marketers, and creative people in general, are looking for anomalies, unique anecdotes, and outliers. They’re not really seeking the mainstream because that area is already overpopulated. Consider these two statements: “The customer is always right” and “The audience doesn’t know what they want.” Both seem true, creating a tension. They are both true in the sense that if you offend or upset a customer, you’re doing something wrong. However, this doesn’t mean you should ask your customer to design your customer service program.

Every time you upset a customer, you should learn from the experience and try not to repeat it. But don’t assume that the customer’s definition of what they want is really what they want. This is where a deeper search is needed. I don’t completely reject market research, but it must be handled very cautiously. For example, one might assume that first-class air travelers want the finest wine and magnificent food. In reality, these individuals often have access to such luxuries at home. A large part of what they want is to be left alone. The assumption that top-tier service should be very attentive may not always hold true. While customers may say they want attentive service, the trick is to maintain a distance where you can always be hailed, but not to continually approach them offering more wine or food. Even though they think they’d like that, it can actually be a nuisance. This is an interesting way to resolve the tension.

When the truth is not adaptive

If believing something untrue leads to good consequences, is it therefore rational to believe things that aren’t true? Absolutely. However, this leads to consequences such as victim culture, where it becomes complex. You may have to acknowledge that, yes, it is undoubtedly true that you are victims, but it is not beneficial to dwell on it. There’s evidence that individuals, not necessarily collective groups, who constantly blame external forces for their misfortunes, are probably right in some cases. However, the consequences of that belief state are not healthy. Therefore, it’s a good idea to move on. Similarly, there’s an opposite concept, which is believing positive things that aren’t true. If it leads you to make better decisions and therefore enjoy better consequences, go with that.

We can post rationalize. We can pre rationalize. So why make the ability to rationalize something a prerequisite for trying something? There’s no reason not to try things to find out where they lead.


Rory’s goal when he gives a talk

I have a kind of heuristic, if I do business talks, which is very simple, okay? If the AV guys are paying attention to what you’re saying, you’re doing okay. If the security guy likes it, I’m doing okay.

An area where Rory has changed his mind: the minimum wage

I’ve definitely changed my mind about behavioural science, in the sense that there is always a danger that organisations default to paying people the minimum they can afford. It isn’t actually good business, by the way, but it’s just a very easy thing with which to win an argument. Why should I pay my staff more than I need to recruit them? Actually, there are lots of reasons, but they’re hard to argue. And that’s the problem with economics. It’s a sharp science, but it’s hard to argue with. Because it’s got this artificial internal consistency that, even though it’s not actually rooted in reality, it’s an impressive kind of edifice in terms of its own internal lack of contradictions.

Moontower #217

A foolproof way to get engagement is post this thing on Twitter every couple months. Sometimes my mood is to hate on such dredging but in this case, screw it, let’s take this sucker apart and see how many things we can learn from it.

Let’s start with the obvious.

  • The expected value of choosing green is $25mm
  • Many people would choose red. Some of those people know the expected value of green is $25mm and choose red anyway.

There’s no dissonance here. The red button guarantees an entirely new life to most of the world’s population. The green button means they still might have to set an alarm for work tomorrow.

The joy of wealth has diminishing returns. I just found $40 in a pair of pants I hadn’t worn in a while (plus a covid mask). If that happened 25 years ago, it would have been a serious enough discovery that I’d hoof it to the local bank branch with a deposit slip.

Economists talk about the “utility” of wealth. They will demonstrate the concept with a sub-linear function to relate “utils” to the quantity of wealth. It’s typically a logarithmic or power function. The sub-linear part means “if your wealth doubles your happiness increases but not by 2x”. The empirical shape of the function is something academics will split hairs about.

I’m going to make one up in the spirit of Nick Maggiulli’s post Climbing the Wealth Ladder.

We will say your “utils”, the made-up satisfaction units, are equal to the cube root of wealth:

Let’s start with the simplest chart.

  • As your wealth goes up by 100x from $10k to $1mm this function says you get “only” about 5x happier.
  • As your wealth goes up by 2,500x from $10k to $25mm this function says you get “only” about 13x happier.

The function is reasonable — happiness increases at a slower rate but maintains that more wealth is always better than less (which I’d describe as a “no-arbitrage condition” — if it wasn’t you could just give money away).

But just as you want to look at long term investing returns on a log chart (compounding is an exponential function), we want to compress the chart for a more zoomed out view. Plus, there’s a non-negligible number of 🌙 readers with more than $25mm and we want to be inclusive around here, right?

Let’s transform the wealth axis to a log(wealth) axis by invoking 10x (ie $1,000 = 103)

The underlying table:

We use log charts to frame insights in a more functional way.

By using log (base-10) to transform the wealth axis, we can now see what cube root utility means:

For every order of magnitude increase in wealth, your happiness doubles.

Your wealth goes up by 10x, your happiness increases by approximately 2x.

But another fun learning moment is upon us.

When I look at that semi-log chart I’m bothered because it’s still exponential. Utility is growing by 2x.

In the case of exponential functions (like compounded returns in an investing context), a semi-log chart creates a straight line.

But a cube-root function is a power function. To get a straight line, we must use a log-log chart instead of a semi-log chart!

Let’s do that and see why such a transformation aids interpretation. First the table:

It’s handy use log (base-2) for the utility axis because utility is growing by 2x

Here’s the log-log chart:

Observations:

  • The x-axis is log base-10(wealth) and the y-axis is log base-2 (utility) and we get a straight line — that leads to an easy inference: Every order of magnitude in wealth doubles our happiness.
  • It’s obvious why many would choose a guarantee of $1mm over an expected value of $25mm — if you have $10 today your happiness doubles more than 6x (it increases more than 50x, 2 to 100) over 5 orders of magnitude. Happiness only increase about 3x (100 to 292) between $1mm and $25mm. Those $24mm are worth less than the very first $1mm.

Of course, this utility function needn’t describe any individual but is qualitatively inferred from the idea that your lifestyle looks pretty similar until you climb to a higher order magnitude of wealth. We can quibble over the actual rate but unless you are a megalomaniac it’s almost certainly sub-linear.

Next time you see the red/green button question you can appreciate how people’s answers are self-rational despite any EV-maxing wonkiness.


Addendum

This walk-through showed how to select log transformations to convert exponential charts into linear charts and maintain intuition by saying things like

  • “Y increases by a fixed rate for order of magnitude increases in X (log base-10)”
  • “Y increases by a fixed rate every time X doubles (log base-2)”

Deriving the linear transformations of semi-log and log charts:

  1. Why exponential functions are linear on semi-log chartsStart by taking log of both sides of an exponential function:

    Y = aX

    Log(Y) = X log(a)

    which looks like a line: Y = mX + b

    where:

    X log(a) corresponds to mX therefore slope or m= log(a)

  2. Power functions are linear on log-log chartsDerivation by taking log of both sides of power function:

    Y = aXb

    log(Y) = log(aXb)

    log(Y) = log(a) + log(Xb)

    log(Y) = b log(X) + log(a)

    which looks like a line: Y = mX + b

    where intercept is log(a) and slope is the exponent b


Money Angle

Now if you have trader blood you look at the question above and say “I’ll just auction this red/green option off to the highest bidder.”

So what price do you think you’d get?

Let’s reason through this.

Someone that is truly risk-neutral is ambivalent between a certain $1mm and $1mm in expectancy.

The red button is worth $25mm so our risk-neutral friend Spock would not pay more than $24mm for the chance to push the button.

Proof of $1mm in expectancy if you pay $24mm:

.50 * -$24mm + .50 * $26mm = $1mm

Unfortunately, all we did was identify an upper-bound of $24mm that one might pay for this option.

But what do you think someone would actually pay?

🤔🤔🤔

Let’s make this more relatable and see if we can scale our logic up.

Imagine the green button guarantees just $1 and the red button is a 50% chance for $50.

Would you pay $24? Probably not unless you were risk-seeking but it’s not out of the question. I mean Robinhood has millions of users who trade for the lols and the E-trade babies were back in the Super Bowl ads.

Would you pay $23 to push the red button? $22? If you are unwilling to pay $20 please just close this tab right now.

What I’m getting at with this thought experiment is to have you feel that the answer to the question depends on:

  1. your bankroll (gambling with $20 is feasible and acceptable, gambling with your net worth not so much)
  2. your risk preferences

With this in mind we can move to the next section, where we’ll generate a concrete answer to the original question.

Money Angle For Masochists

$24mm to someone worth $100b is the same as $24 is to someone with $100k.

There’s 10 people in the world who can nonchalantly take this bet as easily as someone just gambles with $20.

But like finding the upper-bound of what someone might pay, this is barely a start.

This is actually a great place to use the Kelly Criterion. In short, the Kelly Criterion is a formula that prescribes the ideal percentage of your capital to wager. The prescribed fraction is the mathematical solution to “For a given amount of edge, how much should I bet to maximize my compounded growth rate?”

I created a collection for those who want to learn more (caveats, history, and much more):

🏇🏽Kelly Criterion Resources

…but for now we want to focus on our question.

The Kelly formula for what fraction of your bankroll to bet is simply:

f* = Edge / Odds

where

f* = bankroll fraction

Edge = expected return

Odds = percent profit when you win

If my original investment is $24mm and I expect to make $1mm then:

Edge = $1mm/$24mm = 4.17%

When I win I make $26mm for a $24mm bet:

Odds = 26/24 = 108.33%

f* = edge/odds = 4.17% / 108.33% = 3.85%

Kelly prescribes betting 3.85% of your capital on this proposition.

$24mm is 3.85% of a capital base of $624mm

The number of funds, trading firms, or even individuals who could reasonably take this bet is way larger than just the 10 richest people.

And remember this bet is a game — it’s uncorrelated with markets or economic growth. Trading firms diversify across bets like this all the time. As a market maker, I’d describe the business as “pay me $10,000 up front and I’ll flip a $1mm coin with you”.

If the coin is fair it’s worth $500k and I’m basically buying it for $490k or selling it for $510k. Either way I’m getting 2% edge.

My odds are $510k/$490k = 104.08%

The prescribed bet size is 2%/104.08% = 1.9% which is only half as good as the red button for $24mm! [Market-making biz in 1 sentence: Make a dime of edge on a $5 option a few dozen times a day, make sure the edge is real, and manage the risk.]

So yea, I expect this red button opportunity to trade for about $24mm by some large firm that is used to absorbing risk for a fee.


Byrne Hobart wrote a fantastic post recently in his educational Capital Gains letter that gets into related real-world messiness:

What’s The True Bankroll?

Matt Levine referenced it as well:

The Kelly criterion tells you what percentage of your money you should put on some favorable bet. If you work in financial markets, you want to make a bunch of bets where you think the odds are in your favor, and if you can estimate the odds then Kelly gives you a guide to how much of your money you should put on each bet. Kelly gives you an answer that is a percentage of your current bankroll. But what is your bankroll?

We talked a few times last year about a dumb story from Sam Bankman-Fried’s internship at Jane Street, where he kept making the maximum bet on slightly favorable coin flips, and I was like “well that’s not very Kelly is it.” But probably I was wrong. Jane Street interns were limited to losing $100 per day, so I sort of took $100 to be the size of his bankroll and thought he was aggressive to bet it all on a 51% coin flip. But readers pointed out, no, come on, his net worth at the time was not $100; $100 was nothing to him even though it was all he could bet that day. As a percentage of his actual bankroll that was a fine bet.

Anyway here is a fun post from Byrne Hobart titled “What’s the True Bankroll?” Sometimes the true bankroll is much bigger than the obvious bankroll: Sam Bankman-Fried’s $100 daily betting allowance was much smaller than his true bankroll, and Hobart points out that if you start your first job and have $1,000 to invest, your true bankroll is more like your lifetime expected savings than it is your current $1,000. Other times the true bankroll might be smaller than the obvious bankroll: If you are a portfolio manager at a multi-manager hedge fund, and you run a $500 million portfolio, you might think that your bankroll is $500 million. But if you know that you’ll get fired for a 10% decline in your portfolio, is your actual bankroll $50 million? No, but also maybe a little bit yes.

Learn more:

  • Fortune’s Formula on The Kelly Criterion (Moontower)
  • My notes on Kelly Criterion (Moontower)
  • Understanding Risk-Neutral Probability (Moontower)
  • Bet Sizing Is Not Intuitive (Moontower)

☮️

Stay Groovy

Notes from RenTec CEO Peter Brown on the GS Podcast

Podcast: Goldman Sachs Exchanges: Great Investors

Raj Mahajan, global head Systematic Client Franchise interviews  Renaissance Technologies CEO Peter Brown on July 27, 2023

I grabbed some excerpts from the transcript for future reference.

I include my own commentary here and there.


Newsflash: Money is a big factor in what people choose to do

Raj Mahajan: Seems that you were right at the vanguard of the machine learning movement in 1993. So, why did you leave an exciting career at IBM for a small financial company in Long Island that no one had ever
heard of?

Brown: …Three things happened. First, Bob had a second daughter accepted to Stanford. But he couldn’t afford to pay for her to go to Stanford on his IBM salary. So, she had to go to the agricultural school at Cornell, which offered scholarships to New York State residents. The second thing that happened is we had a daughter born. And a third thing was that Jim then offered to double my compensation. After that offer, I came home. I took one look at our newborn daughter and realized I had no choice in the matter. So, the decision to leave computational linguistics for a small hedge fund that no one had ever heard of was made purely for financial reasons.

Examples of Emotional IQ

[Kris: The EQ vs IQ thing is a false dichotomy. I suspect they are actually positively related but when we look at outliers on either dimension there is a major Berksons Paradox effect. RenTec has the reputation of being the true “smartest guys in the room” in the IQ/STEM sense of the word. And yet, multiple times in this interview I am struck at how people-savvy they have been. Which makes perfect sense to me. In a domain where the competition constantly learns and psychology plays an enormous role this is exactly what you expect. Only the naive who believe that investing is physics as opposed to biology cling to Spock-like caricatures of effective quants. Here are several excerpts demonstrating an deep understanding of human behavior]

Selling an approach to employees

Brown: At the end of 2002, Bob and I also took over the rest of the technical side of the firm, which included the trading of currencies, bonds, options, and futures. Now, our plan was to use the equities code that we and others had developed to trade these other instruments. But we recognized they would not be so great for morale to tell, say, one of the futures researchers, “You know all that code you spent the last decade of your life developing, guess what, we’re going to throw it out.” So, we had to spend quite a bit of time getting everyone to buy into our plan. To do this we used an approach that I learned from a biography I’d recently read of Abe Lincoln, which was to get them to come up with our plan themselves. Now, that took some time, but eventually it all worked out. 

Jim Simons weighing the input to manage a risk crisis

See below: 2007 — “Quant Quake”

Jim Simons reading a situation shrewdly

Brown:  In the fall of 2008, the whole financial system was stressed. So, we were concerned with the stability of our counterparties. So, we spent a lot of time with those counterparties and examined their CDS rates and so forth. I remember at one point, two senior executives from some firm we did business with came into our New York City office to meet with us. They assured us that the funds we had in our margin account were safe with them. And I was inclined to believe them. Why not? But after the meeting, Jim said, “Peter, they wouldn’t have come to our office. They wouldn’t have requested the meeting unless they were in real trouble. It’s time to get out.” So, we did. And Jim was right because shortly thereafter, that firm just disappeared. 

Examples of automation and innovation within RenTec

Brown: When we got control of the New York office, the first thing I did was to walk around that office, find out what everyone was doing. And what I found was that many people were doing jobs that could be automated. So, we set out on a massive campaign to automate our back-office operations. We moved from checks and wires to SWIFT and ACH. We replicated counterparties margin calculations. We built a large legal database that could be accessed by computers to fill out regulatory forms. We brought in AI systems to automatically read and pay invoices. We automated the treasury department so that cash and margin needs could be managed by computers instead of humans. My point of view was that Stony Brook produces a huge list of transactions and New York City produces monthly statements, K1s, and government filings. And I just didn’t see why humans need to be involved in the process of translating trades to monthly statements. Now, 13 years later, we’re not done yet. And I’m embarrassed to admit that we still even have a few people who use Excel. But we’re getting there. In fact, I was told recently that we’ve eliminated 97 percent of the spreadsheets that had originally been used in the company.

Stories about risk management

March 2000 — Dot Com

Brown: Let me start with March of 2000 when the dotcom bubble burst. We were doing extremely well back then. And we had large positions in the internet stocks. They were traded on NASDAQ. At one point the head of risk control came to me and said he was worried about the size of our NASDAQ positions. But I told him not to worry, the computer knew what it was doing. Then we took a big loss one day. So, I worked through the night trying to understand what was going on. The next day we took another big loss. And I, again, worked through that night. So, now it’s the third day and I hadn’t slept for, I don’t know, 48 or 50 hours. And I was sitting in a meeting with Jim and a few others when the head of production knocked on the door and asked to speak with me. I walked out of the meeting, and he told me we were down again by a large amount. So, I walked back in the meeting, and I must have turned white or something because Jim took one look at me and said, “It doesn’t look good.” Now, not having slept the previous two nights, I remember thinking I’m not sure I can get through this. But I really didn’t have much choice in the matter. And so, we got back to work and eventually we did get through it. A couple days later I went into Jim’s office and told him that I’d screwed up in not appreciating the risk we were taking and said that if he wanted me to resign, I would resign. But he responded, “Peter, quite the opposite. Now that you’ve been through such a stressful losing period, you’re far more valuable to me and to the firm than you were before.” Now, that response really tells you something about Jim Simons.

2007 — “Quant Quake”

Brown: When that happened, I was on vacation, and I was on a very long flight back to Newark Airport. And the moment the plane landed, my phone went nuts with all kinds of texts and missed phone calls. So, I called into work when it was going on and I got Kim, Jim’s assistant. And she said, “Jim wants you to get back here as soon as you’re physically able.” So, I raced out. I found a taxi, leaving my family to fend for themselves at Newark Airport. And pushed the driver to drive as fast as he could from Newark to Long Island. I ran into my office, and I found Jim, Bob, Paul Broder, who was head of risk control, all holed up. And the office was full of cigarette smoke. I could barely breathe. And then there was this, I remember seeing this, 16 oz cup full of Jim’s cigarette butts. And I’m thinking, like, why do they have to do this in my office? And they were all staring through the haze at the computer screens trying to figure out what was going on. And Jim was interpreting every little wiggle and various graphs. He was really scared. And he wanted to cut back and hard. Paul also wanted to cut back. Raj, I’m sure you know, the head of risk control always wants to cut back. Because he doesn’t get paid to make money. He gets paid to make sure you don’t lose money. 

And Bob, you know, Bob’s always very calm. But he wasn’t against cutting back. But I looked at the data and saw that the model had these enormous predictions, the likes of which I had never seen before. It was clear to me what was going on. People were dumping positions that were correlated with their own positions. And they were driving prices to ridiculous levels. I felt they had to come back. I argued that we should not cut back. That this was going to be the greatest moneymaking opportunity we’d ever seen. And if anything, we should increase our positions. But it was three against one. And so, we continued cutting back. But I succeeded somewhat because we cut back at a slower pace. And then at one point, miraculously, the whole thing came roaring back. And indeed, it was an incredible money-making opportunity. Now, what we learned from that was to always make sure we have enough on reserve to just hang on. Later, when Jim was about to retire, I reminded him of this period and asked if he was concerned that I was going to be so aggressive that I was going to blow the place up. But Jim responded that the only reason I was so aggressive was because I knew he was determined to reduce risk, another example of Jim’s insight into human nature. 

What RenTec does differently

Brown: I guess there are some firms that make it their business to learn how others make money and try to learn their secrets. That’s not our style. We just hire mathematicians, physicists, computer scientists with no background in finance and no connections with Wall Street. 

A few principles we follow:

  1. ScienceThe company was founded by scientists. It’s owned by scientists. It’s run by scientists. We employ scientists. Guess what, we take a scientific approach to investing and treat the entire problem as a giant problem in mathematics.
    [Kris: In chatting with a friend who has proximity to RenTec, I learned of this a few years ago. I was intrigued by how they felt quite comfortable incubating highly promising individuals by offering a well-paying collegiate atmosphere that offered an alternative to traditional academia. It feels like just another instance of what I call risk absorption. RenTec is a highly efficient “bidder” for the risk of a scientist’s effort panning out. They can build a portfolio of talent in the form of a skunkworks knowing that they can scale important discoveries across their trading. Not unlike how a military R&D department might think of investments in scientists.
  2. CollaborationScience is best done through collaboration. If you go to a physics department, it would be absurd to imagine that the scientist in one office doesn’t speak to the scientist in the office next door about what he or she is working on. So, we strongly encourage collaboration between our scientists. For example, we encourage people to work in teams. We constantly change those teams up so that people get to know others within the firm. We pay everyone from the same pot instead of paying different groups in accordance with how much money they’ve made for us and so forth.
  3. InfrastructureWe want our scientists to be as productive as possible. And that means providing them with the best infrastructure money can buy. I remember when I was at IBM, there was this attitude that programmers were like plumbers. If you need a big project done, just get more programmers. But I knew that some programmers were, like, ten times or more productive than others. I kept pushing IBM management to recognize this fact. But it did not. I remember being in an IBM managers meeting and some guy from corporate headquarters was explaining how they created something called their headlights program. The goal of which was to identify the best programmers in the company and pay them 20 percent more than the other programmers. Now, I figured this guy from corporate was making, like, $300,000 a year. So, I raised my hand and suggested they increase the pay of their best programmers to $400,000 a year. And he was stunned. He said, “What? More than me? You’ve got to be kidding me. Well, if the guy’s Bill Gates.” I said, “No, Bill Gates was making, like, 400 million per year. Not 400,000.” Anyway, they just didn’t get it. We don’t make that mistake. We pay our programmers a ton in accordance with the value we place on the infrastructure they produce.
  4. No interferenceWe don’t impose our own judgment on how the markets behave. Now, there’s a danger that comes along with success. To avoid this, we try to remember that we know how to build large mathematical models and that’s all we know. We don’t know any economics. We don’t have any insights in the markets. We just don’t interfere with our trading systems. Yes, of course there are a few occasions where something’s going on in the world and so we’ll cut back because we think the model doesn’t appropriately appreciate the risk of what’s going on. But those occasions are pretty rare.
  5. Time

    We’ve been doing this for a very long time. For me, this is my 30th year with the firm. And Jim and others were doing it for a decade before I arrived. This is really important because the markets are complicated and there are a lot of details one has to get straight in order to trade profitably. If you don’t get those details straight, the transaction costs will just eat you alive. So, time and experience really matters. 

A word on politics

[Kris: Peter Brown is liberal and co-CEO Bob Mercer is famously conservative. I can say that coming from the trading world, the liberal perspectives are in the minority amongst the traders but less so amongst the academics.]

Raj Mahajan: Is it true that while Bob Mercer and you have different politics, you worked closely for nearly 40 years at IBM and Renaissance? 

Peter Brown: Yes. It’s true. Bob and I began working together at IBM 40 years ago. And for most of the time, we’ve had offices right next to one another. So, we’ve done a lot together. And we’re still really close. In general, I find no better way of building friendships than through the collective creative process of building something together. And I see no reason why politics should interfere with friendship. 

Man vs machine stories

1) My understanding is that you had nothing to do with finance until age 38 and, instead, began your career working on automatic speech recognition. How did that happen?

Brown: So, at one point during high school I learned about the Fast Fourier transform. And I thought this was about the coolest thing I had ever seen. Probably because I went to an all-boys’ school and had nothing better to contemplate. Anyway, for some reason I got into my head that with the Fast Fourier transform it should be possible to recognize speech. You just take the speech data, transform it into the frequency domain. Match it up against patterns for words. And presto, magic, HAL would be born. And this idea always stuck around in the back of my mind. 

Then when I went to college I majored in math and physics. But in my senior year I had to fulfill a distribution requirement. So, I took a course in linguistics. And one day in the back of that course I heard a couple students talking about some guy whose name was Steve Mosher who started a company called Dialogue Systems that was doing speech recognition. And I thought, wow, great, I remembered this idea from back in high school. After class I raced over to the physics library. That’s because this was before the internet, so you had to go to the library. And I looked this guy up. And I found a paper he’d written. And I tracked him down. Applied for a job. And he hired me. And when I was there, I just fell in love with the idea that through mathematics it might be possible to build machines that do what humans do. I just loved the idea of exposing human intelligence to be nothing more than robotic computation.

2) I recently heard that in a talk you give at Harvard Business School you mentioned that you had a role in starting up the Deep Blue project at IBM. Can you tell us about that? 

Brown: Wow. Okay. I had been at IBM for a year or two. And I was standing in the men’s room one day when the vice president of computer science, a man named Abe Peled walked up next to me. I thought to myself, now’s my chance. I turned to him and said, “Dr. Peled, do you realize that for a million dollars we could build a chess machine that would defeat the world champion? Think of the advertising value to IBM.” He turned to me, looking kind of annoyed, and said, “What’s your name?” So, I told him. And then he said, “Could you please let me finish up here?” And so, I thought, wow, I had made a big mistake. So, I apologized, and I high tailed it out of there as fast as I could hoping he’d forget my name even faster.

But a half hour later, he called me in my office and told me that if I wanted to build a chess machine, he’d put up the million dollars. I told him that I was occupied with speech recognition. I have three friends from graduate school who could build it. He said, “Okay, hire them.” So, we did. They built the machine. I named it Deep Blue. In the first match, the IBM machine was a very weak machine. Weak physically. You know, I think only one special purpose chip in it. And we lost. The final match, however, was a different story. IBM had a much, much stronger machine with hundreds of special purpose chess chips. IBM won that match and IBM’s stock jumped $2 billion afterwards. Of course, it fell back down later. 

Now, a few years ago I was asked to speak at the Harvard Business School. And when I arrived, outside the auditorium, I could see all these protesters. And I thought, oh no, why are they protesting me? What have we done? Is there something I’m not aware of? I really didn’t want to do that. But as I got closer, I could see they were all holding signs about investing in Puerto Rico. And I thought, what is this all about? I was totally confused because I didn’t think we had anything to do with Puerto Rico. Then it turned out that the speaker before me was some guy named Seth Klarman from some firm named Baupost. Evidently, that firm had some investments in Puerto Rico and the protesters were protesting him. So, I went in to see Klarman’s talk, or at least the end of Klarman’s talk, to find out what all the hullabaloo was about. 

At the end of his talk, someone asked him his thoughts on quantitative investing. I suppose it was a set up for my talk. I don’t know. And I carefully noted his answer which was, “To do what I do takes a certain amount of creativity and finesse that a computer will never have.” And all those Harvard Business School MBAs seemed to really like that response. So, when it was my time to speak, right after him, I began by pointing out that after defeating Deep Blue in the first match, Kasparov was elated and gave a press conference at which he said, “To play chess at my level takes a certain amount of creativity and finesse that a computer will never have.”I then went on to point out that two years later we crushed him. Now, I’m not sure that’s how things will evolve. But whether it’s speech recognition, machine translation, or building large language models, or chess, or making investment decisions, I continue to love the process of showing that human intelligence, intuition, creativity, and finesse are nothing more than computation.

[Kris: In defense of Klarman, like the pod shops, I don’t think RenTec is investing so much as trading. Marc Rubinstein writes:

Dmitry Balyasny, founder of Balyasny Asset Management, attributes the model to a trading view of markets as distinct from an investing view.

“[Its] origins go back to my origins as a trader and thinking about how to build out business around trading… It makes sense to have lots of different types of risk-takers, because you have less correlation, you could attack different areas, the markets, and have specialists in different areas.”

I’ve beat that drum in Trading vs Investing and with great humility in How I Misapplied My Trader Mindest To Investing

Addressing Brown’s obsession with “exposing human intelligence to be nothing more than robotic computation.”

In The Introspection of Illusions, author David McRaney parses opacity of the intelligence and preferences buried in our subconscious:

Psychologically speaking, users found it easy to access the feelings that prompted them to give those films one star or five. Explaining why they made one feel that way would require the kind of guided metacognition that the Netflix interface simply couldn’t offer. Even when you stepped away from the code and the spreadsheets and asked people in person, they might not be able to tell you. They could make a guess. They could attempt to explain, justify, and rationalize their feelings, reactions, and star ratings, but without a conversational tool, a back and forth to get past all that to something honest and perhaps previously unexplored, you ran the risk of precipitating a psychological phenomenon known as the introspection illusion which would likely result in yet another phenomenon known as confabulation. There’s an entire literature of books and papers and lectures and courses devoted to this side of psychology. To put it very simply, we are unaware of how unaware we are, which makes us unreliable narrators in the stories of ourselves. You are, however, amazing at constructing stories as if you did know the antecedents of those things when explaining yourself to yourself and/or others.

There are parts of us we can’t access, sources of our emotional states we can’t divine, and I find some strange poetry in the fact that, like us, the algorithms can’t always articulate the why of what we do and do not like. Yet, through millions of A/B tests slowly zeroing in on more and more successful correlations, the Netflix Recommendation Engine can produce a glimpse of something a bit like the sort of profound, soul-exposing knowledge earned via an intense introspection that we could never achieve. Something a few fathoms deeper than “I don’t know, it just wasn’t for me.”

Speed Round

1) Is it true that at one point you went to IBM to suggest that the statistical methods you were using in speech recognition could be applied to finance, and asked to be given an opportunity to manage some fraction of IBM’s corporate cash?

Brown: Yes. I think that was in 1993. But IBM corporate had absolutely no interest. So, instead we went to Renaissance where we did the same thing we had in mind for IBM, but instead with money Jim Simons had raised.

2) Is it true that since you first joined Renaissance you have spent nearly 2,000 nights sleeping in your office? 

Brown: Yes. My wife works in Washington DC. And my experience has been that when a husband and a wife work in two different towns, the husband commutes. Psychologically, if I’m going to be away from my family, I have to work. I sleep in my office when I’m in Long Island. 

For me, productivity-wise it’s really fantastic being able to spend nearly 80 straight hours each week with no interruptions except sleep thinking about work before spending three more normal days at home. Of course, I really miss my family. But the freedom to concentrate nonstop on work while surrounded by my colleagues is hugely valuable. And the job is so demanding, I really don’t see how I could do it otherwise.

[Adds this]  I’m just one of those types who can’t sleep. Not by choice. I just can’t sleep. So, I often am on the computer by around 2 am. And it’s true, I tend to send a lot of emails out in the middle of the night.

3) Is it true that you almost exclusively hire people with zero background and finance? 

Brown: Yes. We find it much easier to teach mathematicians about the markets than it is to teach mathematics and programming to people who know about the markets. Also, everything we do we figure out for ourselves. And I really like it that way. So, unlike some of our competitors, we try to avoid hiring people who have been at other financial firms. 

[Kris: The prop trading firms think similarly. My friend Joel talks about how Brown’s claim that it “is is easier to teach markets to mathematicians than it is to teach math to market experts, may seem dismissive to market-centric people but in reality is more of a statement about what “math” is at Renaissance.” He goes on to distinguish about levels of math but I latched on to this a more general observation:

Markets person isn’t a thing. Markets thinking is systems thinking and anyone from any discipline can learn that. From there go on Investopedia and learn how a zero coupon bond or share of stock works. start with a good, teachable mind then label the variables.

Math/STEM skills are legible markers of computational/rigorous thinking. Someone trained in the nitty gritty of assumptions, what follows, and so on. Making abstractions concrete.

If I’m generous it took a month of professional training for non-finance STEM grads at SIG to know everything finance grads would have brought to the table. But you can’t teach math and computer science in a month. 

Ultimately this is only part of the story of getting a great start in finance. There’s a Berksons Paradox once you are in the pool of high level finance employment where the math skills don’t correlate as much with talent. You get older and realize the dichotomy of being a math person vs a verbal person that you carried as an identity when you were young is bullshit. Skills in either are likely highly correlated. But maybe the right door or guidance wasn’t there to help you see that.]

4) What do you actually look for in applicants? 

Brown: Math ability. Programming ability. A love for data. A work ethic. And most importantly, the ability and desire to work will in a collegial environment.

5) How do you actually assess those qualities?

Brown: I think probably the same way other firms do. First, we get resumes. Those that look promising we give them phone interviews and we ask them for references. If those pan out, then we invite the promising applicants to give research talks. Talks like if you’re applying for a job at a university or something like that. And then we put them through a grueling day of solving problems in math, physics, statistics, computer science, and so forth at a blackboard.

6) Is it also true that your staff had to install mirrors in the corners of the office to prevent you from flying into people as you rode a unicycle around the office? 

Brown: Where did you get all these questions from? Yes, it’s true. Although, I don’t ride a unicycle anymore because at one point I crashed and the unicycle broke


If you use options to hedge or invest, check out the moontower.ai option trading analytics platform

Mark Manson Chats With Erika Kullberg

Mark Manson, author of The Subtle Art Of Not Giving A Fck*, went on the Erika Taught Me podcast.

Pound for pound some of the best self-help advice condensed into a 1-hour conversation.

My favorite excerpts including my own comments below.


On what you should be doing

“I realized I actually didn’t want to be a musician. I thought I wanted to be a musician. I thought I wanted to be on stage and people cheering and everything but I didn’t want the process that was required to achieve that. With writing it’s the opposite. I enjoy the cost. I enjoy sitting by myself in a room quietly, rewriting a paragraph over and over again. That feels very natural to me. There’s something exciting about that challenge to me in a way that there was never any excitement with the challenge of practicing scales or runs. One thing that I always tell people is that it’s easy to want the reward. It’s hard to like the struggle. When most people ask themselves, what do I want to do with my life or what am I passionate about? They think about the rewards, they don’t think about the struggle. You should be asking yourself, what is the struggle that I like? What is the struggle that I’m passionate about? What is the challenge that excites me rather than drains me?”

[Kris: thinking of “passions” as something fixed or innate is probably not constructive. You can become passionate about something that you get good at and of course, at any point in time you never know the whole menu, so passions can be discovered by trial and error or having a curious non-instrumental approach to what you spend your time on.]

‘Screw Finding Your Passion’

Even in your dream job, you’re going to be annoyed 20% of the time. There’s no such thing as a job, relationship or endeavor where you are happy all the time. Even in your dream relationship, you’re still going to be sick of the person 10% of the time. That’s just life, and there’s no escaping it completely. So, I think the goal here is not Happiness with a capital “H.”

[Kris: Denis Leary’s version —Happiness comes in small doses folks. It’s a cigarette, or a chocolate chip cookie or a five second orgasm, that’s it okay? You come, you eat the cookie, you smoke the butt, you go to sleep, you get up in the morning and go to fucking work okay? That is it, end of fucking list!

The tone of this sounds like ‘settling’ but I interpret it as not focusing on some endpoint to make you happy. Enjoy the bits along the way, but they aren’t the end all be all and stop imbuing achievement with the expectation of actualization or whatever.]

The angst advantage

[Kris: In Ambition As An Anxiety Disorder I discuss Andrew Wilkinson’s comment that Most successful people are just a walking anxiety disorder harnessed for productivity. This hints at an example of hormesis — the right amount of a “bad” thing like stress or angst can be useful while too much is destructive. Just one of those ambiguous tensions life requires we modulate.]

I don’t think being happy all the time is the most adaptable strategy in life. If you think from an evolutionary perspective, imagine two creatures: one is happy all the time, always optimistic, thinks everything is great, and everything’s going to go great. Then you have another creature who’s a little bit paranoid, a little bit freaked out every time there’s a rustle in the bush, thinking it’s a tiger. Which one’s going to survive longer? It’s the slightly paranoid one. The slightly anxious one. The one that’s constantly dissatisfied. The one that says, this food’s not enough. I need more. That’s the one that’s going to survive and procreate. So, in that sense, a moderate amount of dissatisfaction with our lives is, from an evolutionary standpoint, highly adaptable. If you look at like research on happiness and wellbeing it is an inherent part of our nature to be mildly dissatisfied most of the time.

Happiness as an indirect pursuit

People are overly focused on the feeling of happiness. They should focus more on spending their time well and doing things that are worth doing. There’s a curious thing about human emotions, which we’ve all experienced. Let’s say you’re angry and you don’t want to be angry anymore. It just makes you more angry because you get upset about your anger, or if you’re anxious and you don’t want to be anxious. You get anxious about being anxious. The peculiar thing with happiness is that if you constantly ask yourself, am I happy? How can I be happy? I want to be happy. You make yourself less happy. It’s one of the few things in life that putting more effort towards it or more focused attention towards it decreases the result. It’s one of the few things in life that by simply letting it go and not trying to control it, it happens more often. A lot of people get caught up in how they feel. Emotions are important, but you’re going to feel things all the time. You’re always going to be anxious or angry or happy or sad. Life is always going to put you in those situations. What matters is what you do. It’s how you react to the emotion. If you develop the capacity to consistently perform good actions, despite whatever emotion you’re feeling, then more often than not, you’re going to feel good about yourself.

[Kris: If I say “Don’t think of an elephant” what do you think you are going to do? You’re going to think of an elephant of course. Happiness is a byproduct. It’s an indirect pursuit. The harder you try the more elusive it is. Reminds me of Michael Crichton’s quote: If you want to be happy, forget yourself. Forget all of it—how you look, how you feel, how your career is going. Just drop the whole subject of you. People dedicated to something other than themselves are the happiest people in the world.

My friend Tom Morgan echoes the futility of focusing on happiness: Happiness often lies in the temporary suspension of our ego’s desire to explain and control everything]

Gratitude Is An Action You Can Take

Gratitude is useful because it is forcing you to take a certain perspective of just being appreciative of the things that you have. Gratitude is slightly different than happiness even if the two often coincide or happen together. Gratitude is more like an antidote to misery than it is a cause of happiness. When you feel miserable, you’re so focused on the one thing that you don’t like that you’re forgetting the 100 things that are good. The practice of gratitude forces you to take your attention off that one thing you don’t like, and realize “my life’s pretty sweet.”

[Kris: This is a key practice in our household. It keeps the angst that drives you from tipping into envy or unhealthy emotions. As hokey as it sounds, I mean it when I say any day that I get to wake up is a good day. Because is the grand scheme, it could be worse.]

The 3 pillars of well-being

  • What are we spending our time working on?
  • Who are we spending our time with?
  • How much are we taking care of our bodies?

If you can answer all three of those things satisfactorily, you’re probably a happy person most of the time. All these other questions, the philosophical ones or productivity ones, they’re window dressing. They’re not the real thing. Have a few good relationships in your life, work on a project that you care about and feels important to you, and don’t mistreat your body. That’s the 20% that drives 80% of happiness.

[Kris: A fulfilling life, like anything worth pursuing, is a simple formula. Simple, but not easy. Like losing weight. Mark just distilled it for you.]

Reconciling unconditional love with the practical need for boundaries

You set this ‘if-then’ statement within a relationship. “This thing drives me crazy, please don’t do it. If you do it, this is how I’m going to react.” It’s healthy because it sets expectations for both people. Now my wife knows what upsets me and how I’ll respond. There’s no ambiguity or uncertainty around it. A more intense example is monogamy: if you cheat on me, I’m going to leave you. That’s a clear ‘if-then’ boundary. I’m still going to love you, I’m still going to care about you, that’s unconditional. But we’ve set these boundaries, these expectations, and if you don’t live up to them, we don’t have a relationship anymore. Many people who are entangled in unhealthy relationships struggle to set boundaries because they don’t want to displease their partner or start a fight. What they don’t realize is that by setting that boundary, despite the discomfort and potential for a temporary argument, you’re preventing dozens of future fights. It’s the one fight that prevents the next 20.

[Kris: “The single biggest problem in communication is the illusion that it has taken place.” – George Bernard Shaw]

Being responsible even when you’re not at fault

You should take responsibility for everything in your life. It’s a common piece of advice, but the most frequent objection is: ‘Well, bad things happen to good people. What if I’ve been wronged or a tragedy has occurred? That’s not my fault. Why am I responsible for that?’

I differentiate between fault and responsibility. We often assume that fault and responsibility are the same thing, and legally, they usually are. However, from a personal psychological point of view, you can be responsible for many things that are not your fault. If someone leaves a newborn baby on your doorstep, it’s not your fault, but it’s absolutely your responsibility to do something. Similarly, if you get hit by a car and end up in the hospital, it’s not your fault, but it’s your responsibility to recover, take care of your health, and do everything you can to get healthy again. There are many situations in life for which we are responsible, but it’s not our fault. We had nothing to do with how it happened. I believe this concept opened many people’s eyes to separate the fault component from responsibility, helping them to accept this piece of advice more comfortably.

[Kris: This strongly aligns with my opinion that you should “put your oxygen mask on before you help your neighbor”. You have a responsibility to care for yourself so you can help others. This also means accepting help. In my own life, I’ve had a loved one refuse help thinking they have spared me a burden, but I know that by not inconveniencing me today they would become a larger burden in the future when they are less capable of helping themselves even with my aid. This experience has given me the imperative to make sure I take care of my health, my finances and my well-being. Not just so I am not someone else’s burden but so I can continue to be a source of support for others.]

The self-help advice that drives Mark crazy

The traditional “law of attraction”. Like The Secret. Manifestation. The idea is to visualize and believe something, and it will happen. It’s not entirely wrong. I addressed this topic in an extensive article on my website years ago. The concept in psychology known as confirmation bias plays a key role….It occurs consistently and the law of attraction leverages this bias in our favor. For instance, if your goal is to become rich, you’ll start noticing opportunities that were always there but went unnoticed because you hadn’t been thinking about your goal.

There’s nothing magical or cosmic about it. It’s a common, well-documented perceptual bias. When used effectively, the law of attraction trains you to use confirmation bias to your advantage. The problem is, it’s often shrouded in cosmic jargon and extends beyond simply thinking about your goal. There’s a crucial distinction between focusing on an external goal and the identity you want to inhabit. If, for example, I decide I want to be seven feet tall and play in the NBA, no amount of thinking will make it real. That’s not success; it’s delusion.

I have several issues with the law of attraction. I’ve been quite critical of it, despite recognizing the grain of sound advice within. It advises to look for the positive in anything that happens to you, which can be helpful but should not be applied indiscriminately. It’s perfectly normal and healthy to feel sadness when tragedy strikes.

[Kris: Notice how calls to be indiscriminately positive backfire by setting impossible expectations. Happiness is the gap between reality and expectations.]

What many attribute to the law of attraction is often just confirmation bias, accountability, and goal setting. When you set a goal, it provides a finish line. Without a clear goal, it’s difficult to measure your actions. For instance, if you want to make a lot of money, define the amount. Once you decide on a figure, you can break it down into monthly targets and figure out the steps needed to get there. The law of attraction isn’t responsible for this. It’s simply setting a goal, breaking it into subtasks, holding yourself accountable, and using confirmation bias. It’s easy to see why people appreciate this concept, but it’s crucial to remember that it requires action. You can’t merely wish for wealth and expect it to materialize.

[Kris: I beat this dead horse to death but this topic is really about doing the proper attribution. Mark is showing how confirmation bias can be leveraged for good. How goal setting deserves credit for progress, not magic. And notice, if “manifestation” didn’t happen to re-skin confirmation bias it wouldn’t work and therefore it would never have taken off as a self-help concept. It had to have a nugget of truth to woo followers. Every cultish movement will have a nugget of truth that is really just a hand that gets over-played]

Imposter syndrome is healthy

I have a contrarian take on impostor syndrome. I believe it’s healthy. If you made a bunch of money very quickly you should have impostor syndrome. You should be asking yourself, ‘Do I deserve this? Did I work hard enough for this?’ Because that is the opposite of taking it for granted and being arrogant. It’s not fun to feel that and I certainly went through some impostor syndrome after ‘Subtle Art’, but ultimately, it keeps you humble. It keeps you a bit hungry, thinking, ‘I should do something again to show that this wasn’t a fluke,’ and it keeps you grounded. It reminds you that you’re not necessarily better or worse than your buddies that you hung out with last year who are still making the same amount of money they did before. Impostor syndrome is actually healthy, as long as it’s not debilitating. At the end of the day, any sort of self-worth issue comes back to the same thing. Are you doing good work? Are you surrounded by good people? And are you treating yourself well? If you can say yes more often than not to all three of those questions, you’re eventually going to be in a good spot.

[Kris: Echoes Sal Khan’s take on imposter syndrome —

I think some of that impostor syndrome, I actually want to retain. I never want to forget how, like, there, there was a time not too long ago that I would pass on the organic produce. I think it lets you just appreciate the world a little bit. And we all know about hedonic adaptation and the hedonic treadmill. I don’t claim that I’m immune so I don’t want to sound like I’m some guru here. I live in Silicon Valley. We live in that same house, and a lot of our friends have now moved into houses that are multiple of the size of our house. Every now and then it’s “maybe it would be nice to have two saunas.” But I always remind myself, “well imagine their electricity bill, or like, the gardening bill or the water bill or whatever.” But, yeah, I think it’s healthy imposter syndrome.

A healthy one keeps you grounded, allows you to enjoy it a little bit. Like every now and then I get invited to meetings with people or conferences with people, where both healthy and unhealthy impostor syndrome could be at play. The healthy imposter syndrome says  “Wow, you get to meet your childhood hero, or someone that you thought you could only read books about, and you’re meeting this person, and they are interested in what you have to say, and they’re supporting Khan Academy.” That’s kind of fun. I don’t know if that’s impostor syndrome, or that’s just remembering yourself when you’re younger. And you’re like, “Wow, how is little Sal in this meeting right now? That’s kind of wild.”]

Moontower #116

Friends,

I’m a bit more than halfway through this summer’s travels. So far we have been to Tahoe, Jupiter, Disney, DFW, and Austin. We are headed to Puerto Plata this week before our last leg in the NJ/NYC area.

I didn’t publish last week and likely won’t publish next week. Other than checking Twitter a handful of times a day, I’m pretty offline this summer. I read maybe an article a day. I’m listening to none podcasts (to borrow my 5-year olds grammar). I’m not even reading a book so any intellectual side I have is being totally starved of stimulus. Total GTL life minus the gym.

The upcoming week is always a fun one. My birthday is on the 12th and Zak is on the 13th. We actually went to the hospital for his birth on the 12th but I guess he wanted his own day. July 12th has captivated me for another reason. It is the anniversary of the horrific shark attacks that inspired Jaws. In another self-centered twist, they occurred a few miles from where I grew up contributing to my and my sister’s obsession with sharks (my sister actually went as far as tagging nurse sharks in FL for a summer job in college. She subscribes to any shark news so she pointed out a video of a Great White spotting in Jupiter two weeks before we went there in June. We hid this bit of info from the rest of the family).

The shark attacks of 1916 make sense as the inspiration for Peter Benchley’s monster which he infused with vengeful intention. From Atlas Obscura:

IN JULY OF 1916, NEW Jersey became the site of a series of vicious shark attacks that would span 12 days and take the lives of four people and severely injuring one.

With previous deadly attacks in Beach Haven and Spring Lake, New Jersey, the shark made its way north and down a freshwater creek in Matawan, New Jersey on July 12, where it would attack and kill 12-year-old Lester Stillwell and 24-year-old Stanley Fisher within an hour of each other. Matawan hadn’t prepared itself for attacks like other shoreline towns in New Jersey, as they were so far inland along a freshwater creek. 

The suspected man-eater would be caught two days later in the nearby Raritan Bay. To be sure it was the killer, the over 300-pound monster was dissected, and 15 pounds of human remains were found in its stomach.

It’s has been determined that the shark was a bull shark, the only shark that can survive in both fresh and saltwater. The incident was a heavy inspiration for Peter Benchley, who would write his 1974 novel Jaws set on Martha’s Vineyard, Cape Cod in the fictional town of Amity.

While it’s unclear if it’s a permanent addition, the site of the shark attack is currently marked by a painted shark. The town of Matawan also has two separate memorials to the victims.

For the full details, check out the Wikipedia page: The Jersey Shore Attacks Of 1916

It’s a great beach read in the same way that it’s fun to read about serial killers in your tent at sleepaway camp in the woods.


The Money Angle

Before vacation, I listened to fund manager Dan McMurtrie’s interview on Howard Lindzon’s podcast. It was provocative and entertaining enough for me to jot some notes.

I recommend taking a full listen. Dan is funny. And gifted at the art of troll.

To see my notes go to Dan McMurtrie with Howard Linzon (Moontower Meta)


Last Call

We’ve been up to a lot of fun stuff in Texas. Some of it will make for good discussion when I’m ready but in the meantime, I’ll just mention a few DFW places that we have enjoyed in the past couple of weeks.
  • FC Dallas MLS games

    We went 2x. For less than $40 you get amazing seats. The overall environment is fun and positive. I have never been to an MLS game before and while I know nothing about soccer, I and everyone we went with found the fan experience to be outstanding.

  • Burger’s Lake (Fort Worth area)

    We went here 2x as well (the friends we are staying with have been hosting 2 to 4 families from our NYC/CA crews the entire time we’ve been here, so we repeat activities as the revolving door requires). It’s a lake with high diving boards, water slides, a trapeze swing, and attractions catering to younger kids. Bring your own picnic or use the camping grills to make burgers. You will need to sneak booze in. On weekends they check your cooler, but we got away with it during the week. Your welcome for the tip.

  • The Stockyards (Fort Worth area)

    Also did this 2x. Step back into the history of cattle-ranching. There’s plenty of activities for kids and rows of old saloons and restaurants for the grown-ups. And if you want something less rustic, the newish Hotel Drover is a great spot to grab a ranch water (I make this drink all the time, but didn’t realize Texans have a name for it). It also looks like a fun spot for a weekend getaway with a nice pool and access to the stockyards. Time your visit to see the daily longhorn cattle drive up the main drag.

  • Deep Ellum (Dallas)

    This is an area of Dallas that reminded me a bit of Wynwood in Miami. Cool restaurants and shops (Jack White’s baseball brand Warstic is headquartered here). Plus lots of locals flexing their muscle cars (my kids are totally obsessed with cars right now especially Challengers with kits such as Demons, Super Bees, and Hellcats. Hellcats come with 2 keys, a black and a red one. The black one is the regular one. The red ones unleash the beastly Hellcat engine. These cars are built for drag racing. If Fast and Furious movies didn’t have cringey sex scenes, I’d take the boys to see F9). If you visit and dig tequila/mezcal you need to go to the Ruins. I tweeted about it.

  • Bar hopping in Dallas

    Grab a cocktail at the Mitchell, see the decor in the Adolphus Hotel, and end at the Thompson Hotel. There you can see some prettiness and pretty people at Catbird before grabbing dinner at Monarch or sushi at Kessaku. The sushi was outstanding by any coastal city standard but pricey. Sake choices were underwhelming, but the view is a consolation prize. Finally, end the night, at a ridiculously good mezcal bar hidden in a bridal store. In a strip mall. The empanadas and cocktails are lit at this tiny spot started by two bros from Mexico City. It’s called La Viuda Negra. It was better than the movie we saw of the same name last night in IMAX.

Literary Version Of A Chart Crime

Last week, we talked about “chart crimes“. Often these are charts that poorly constructed because the authors have been fooled by correlations or invalid comparisons. These are naive but honest. Then there are charts that use sleight of hand to nudge a conclusion. This author has an axe to grind. 

This week, we will discover the literary version of chart crimes. It’s what Cedric Chin simply calls “sounding insightful”. It’s an approach honed in the internet tournament for attention. Since desire is the only barrier to publishing online we are witnessing “an arms race in writing. The best online writers are able to make something sound insightful — regardless of whether it’s true, or whether it’s useful.”

Ced continues:

This isn’t some evil conspiracy. ‘Writers optimizing to produce insight porn to grab attention’ sounds nefarious, but it’s really more like ‘writers responding to the incentives of the social internet’ — a simple side effect of the attention economy.

My own feeling is that the overlap between universally “good writing” and “optimizing for attention” is much higher than “good writing” and “being right about what you are writing about”. I’m sure there’s some mix of practice, talent, and writing ed that can make you a good writer. But I’m not sure how correlated any of that is with having accurate or well-reasoned thoughts.

A bad writer with bad takes is harmless. Nobody finds them. A bad writer with good takes needs an agent. A good writer with bad takes is hard to detect for 2 reasons:

1. Part of good writing is being effectively persuasive. A good writer has you in a spell. 
2. There are elements common to all good writing so you cannot distinguish good takes from bad takes based on style.

Ced refers to some of these common elements as “tricks”. 

Here’s 2 familiar ones:

  1. Use a story.

    I started this piece with a story. Preferably from a historical period that the reader isn’t familiar with.

     
  2. Repackage obvious truths and sprinkle them over the course of an essay

    Clichés can thus be repackaged to sound insightful. This is a useful trick because a) clichés are often truths the reader already agrees with, and b) whatever sounds insightful will keep the reader going.

     

Usefulness Separates Infotainment From Scholarship 

Ced warns that what sounds insightful isn’t always true or useful. Some excerpts:

  • [Venkat] Rao’s piece is not ok if your goal is to read for career reasons. But it’s ok if your goal is to read for entertainment. It’s ok because Rao’s goal is to attract eyeballs, not create better business leaders. And his writing is so good most people will forgive him for it.
     
  • As a writer, I admire what he’s done. But as a business person, nearly everything that [Dave] Perell says in the piece about business is subtly wrong — enough to make me treat his essay as entertainment, not education.
     
  • Writers are often seen as smarter because good writers today are trained to optimize for sounding insightful. This bleeds over into reader perception. I think that whether a writer sounds smart or a piece sounds sophisticated shouldn’t affect you if your goal is to put things you read to practice. The questions remain the same: “Is this person believable? How likely is this going to be useful? And what’s the cheapest way to find out?”
     

Clear Thoughts Do Not Equal Correct Thoughts

Ced concludes his post:

A year ago I wrote Writing Doesn’t Make You a Genius. I noticed that people tend to assume good writers are smarter than they actually are. I argued that this was mistaken — that writers sound smarter on paper because the act of writing forces them to clarify their ideas.

But now I have another reason. Writers are often seen as smarter because good writers today are trained to optimize for sounding insightful. This bleeds over into reader perception.


My Own Reconciliation My feeling is the usefulness of writing comes in 2 forms:

  • Form 1: The writing helps you make better decisions or predictions.
     
  • Form 2: The writing is useful for entertaining or provoking you. If a writer is wrong in interesting ways their work is still useful.

The most common failure is to incorrectly label a Form 2 piece as Form 1. If all you ever read is Malcolm Gladwell or self-help you might never know the difference. 


For a fuller discussion, please check out Ced’s Beware What Sounds Insightful (Link)

On Police Reform

As protests flooded the streets in the wake of George Floyd’s murder, I pulled together a stream of thoughts in my weekly letter. One of the questions I wondered aloud about was what standard police should be held to. In tweet form:

One of my readers who I chat with responded with illuminating insights on the topic. It turns out he/she had quite a background in law enforcement with a good view into local and Federal practices. As is our national habit, the discourse on police has quickly become politically polarized. Polarization is obscuring the massive degree of nuance endemic to the rich topic of law enforcement. This friend felt compelled to write down his/her thoughts and iterated on the essay over many sessions. I pushed for it to be published but the demands of this person’s current profession require anonymity. So I asked to share it on Moontower preserving anonymity. I don’t have a big platform but I’m happy to share this with those of you who do follow. Thanks to my guest and of course to you for reading.


We have a valuable opportunity to change right now but we are running the risk of not realizing powerful change due to a false equivalency in the dominant narrative.

Contents:

1. What Can You Do Today to Help Create a More Just Society

2. What is the False Equivalency and Which Key Stakeholder is Missing?

3. Worldview and Caveats

4. Race and Fatality in Police Encounters

5. A Baseline for Police Violence

6. Understanding Violent Encounters and Human Limitations

7. Societal Considerations

8. Concluding Thoughts

 

What Can You Do Today to Help

Before expanding on the false equivalency and its effect, here are some initiatives that I think will, you know, just help make society a little bit better for everyone. No need to look at it through a political ideology, just look at it and say gee, this would help a lot of people. Think of it as trying to move society closer towards John Rawls’ Justice as Fairness without making any normative judgments about the current state of affairs.

  • Immediate: Help support bail for underprivileged people. Poor people that can’t afford bail often lose their jobs while waiting for trial, even if found innocent later. I recommend the Bail Project.
  • Immediate: Support legal assistance so that disadvantaged groups are more likely to get good legal representation. Anyone who has ever seen Lionel Hutz in action knows what I mean.
  • Medium Term: Anything that helps support educational and healthcare disparities between communities. If you aren’t sure, go to CharityNavigator and sort by 4-star charities.
  • Medium Term: Take away the power police unions have to protect police officers from losing their job even after multiple complaints. This is a sticky situation because it then brings the wider circle of public unions under scrutiny. Here is a nice overview of the potential problems.
  • Policy questions to ponder: ending the criminalization of drugs. Over policing of disadvantaged areas. The militarization of the police.
  • I also feel the need to caveat this with the following: When I first wrote this, I forgot to say anything about George Floyd? Why? Because I’ve thought about this problem deeply for years, so Floyd might be the catalyst for me sharing my thoughts, but not the catalyst for me taking an interest in this narrative, that happened a long time ago. Every cop that I know thought the murder of George Floyd was just that, murder. It was heartless, bizarre, and without explanation. 

What is the False Equivalency and Which Key Stakeholder is Missing? 

We have a valuable opportunity for change and we might fail to capitalize on it. We are missing a critical opportunity to communicate about some very real issues as a society. What’s happening instead? We are screaming past one another with ideology and frameworks. Some very positive changes have occurred but what I fear is that the current narrative completely alienates and vilifies one key group that’s going to be needed in our fight for a more just society.

 On a national level, what is the false equivalency? It is the following: “a complex and long line of historical inequalities and oppression have created a system with inherent racism” is considered equivalent and just as true as the following state “the police are racist.” The first statement is substantiated, the second one really is not. Why do I think this clarification is important? Because you can disarm a lot of hostility in the discussion between the left and the right once you tweak the narrative to allow for this nuance, and maybe we can work on changes that in theory many of us support. The heart of the argument is thus bound up in these three points:

  1. Is there a complex and long line of historical inequalities, oppression, and racism that have surreptitiously and latently made the experiences of minorities in the legal and law enforcement realms to be different than mainstream populations? Yes. This is racism.
  2. Are police officers en masse a group of racists proactively attempting to discriminate against minorities solely due to their minority status? No.
  3. If you accept both points 1 and 2 it allows for constructive dialogue. Also, if you want real reform it makes a whole lot more sense to have the police as partners in that effort and not adversaries. If you vilify the police and blame them for every ugly aspect of the system, threaten their lives, and cut their funding etc. are you going to on average get better or worse qualified people applying to be police officers?

I think most people right now agree on point #1 above, so let me spend some time on point #2 and help explain parts of the law enforcement job that often go unexplained to the general public, to the detriment to all of us in this discussion.

Worldview and Caveats

I’ve already shared some of this writing with friends and was attacked for it, so let me try to be clear upfront and say: I think there are very real problems in society. The outcomes under the current state are discriminatory and there are entire segments of the population crying out saying they haven’t been heard and have been suffering from racism. We should do everything we can to help them. The pain and psychological trauma of literally living one’s entire life in this manner is are burdens that I cannot even begin to fathom.

Race and Fatality in Police Encounters

Three studies from progressive academics concluded the following:

  1. Journal of Politics, research from Shea Streeter of Stanford University2 has shown that, if you compare blacks and whites coming into contact with the police under similar circumstances, they have a virtually equal likelihood of being killed. “The reason why so many police killings of African Americans have sparked outrage is that, at least to many, the circumstances of those interactions did not appear to warrant lethal force. A jarring implication of my research is that an analogous proportion of white decedents are also killed by police under similarly dubious circumstances.”
  2. Proceedings of National Academy of Sciences – Officer characteristics and racial disparities in fatal officer-involved shootings3. “We did not find evidence for anti-Black or anti-Hispanic disparity in police use of force across all shootings, and, if anything, found anti-White disparities when controlling for race-specific crime. While racial disparity did vary by type of shooting, no one type of shooting showed significant anti-Black or -Hispanic disparity.”
  3. Ronald Fryer of Harvard University – An Empirical Analysis of Racial Differences in Police Use of Force4: On the most extreme use of force – officer involved shootings – we find no racial differences in either the raw data or when contextual factors are taken into account. We argue that the patterns in the data are consistent with a model in which police officers are utility maximizers, a fraction of which have a preference for discrimination, who incur relatively high expected costs of officer-involved shootings.
  4. Unrelated to fatal force situations, but also worth reviewing5 if you are interested in these meta-studies: 85-90% of all racial groups who called 911 for help felt they behaved properly

I think this broadly helps frame a discussion where we can dispense with the false equivalency and agree on points 1 and 2 above.

A Baseline for Police Violence

There are over 800,000 law enforcement officers in the US6. In any given year there are approximately 63 million unique interactions between a civilian and a police officer in the United States (source: US Department of Justice7). Police shootings are cataloged and scrutinized by media and the Department of Justice. The FBI has entire divisions dedicated to investigating civil rights violations of local police departments. The Washington Post has a widely publicized police database8 which broadly proclaims that “black Americans are killed by police is more than twice as high as the rate for white Americans.”

If we are looking for clearly objectionable police behavior and bias let’s filter this down and specifically look only at shootings of unarmed people and not shootings involving some kind of weapon. Filter the database for 2019 and we see 1,004 people. Filter it again for “Unarmed” and the number drops by 99% to 56 people. Of those 56 people: 25 were white, 15 were African American, 11 were Hispanic, and 5 were other.

There are pretty broad studies from Harvard and Michigan State University that conclude that at least when it comes to fatal force the police are not biased by race9. What I think is clear is that minorities are more likely to have contact with police, and more likely to be prosecuted for a crime than white people under similar circumstances. So here you have the paradox of points 1 and 2 on display: as a minority you are more likely to have a police encounter purely based off the demographics of communities and deployment of police assets (point 1 above systemic factors) but once that encounter starts you are of equal or even less likely to be killed than a white person (see footnote 4) i.e. point 2 above police officers, in general, aren’t biased in their application of fatal force.

Everyone forgets to look at police officers though – the other side of the coin. 48 police officers were killed in 2019, 40 were white, 7 were African American, and 1 was Asian. This means that if you are an unarmed African American as part of the general population in 2019 you die at the hands of police at a rate of approximately 15 per 37.1 million compared to African American police officers who died at a rate of 7 per 106,400. (800,000 police officers, of which 13.3% are African American10, compared to 12.6% of the general US population).

So even if you assume every unarmed killing (more on that later – use of force, tactics, and the fact a police officer never knows who is armed or not) is entirely without any reasonable cause you have a fatality error rate in 2019 for all citizens, regardless of color, of 56 people per 63 million unique police to citizen interactions per year. Or a rate of .00009%. I think one is one too many but when you have 800,000 people making decisions in 63 million encounters some of which are bound to involve making decisions under conditions of risk, violence, and uncertainty, I would imagine that error rate is broadly representative of the error rate in any human endeavor.

Understanding Violent Encounters and Human Limitations 

“As your heart rate goes up, your tunnel vision can get narrower and your auditory exclusion can increase.” 

— Dave GrossmanOn Combat: The Psychology and Physiology of Deadly Conflict in War and in Peace

Everyone sits back and looks at the situation and likes to think about what they might have done. Here are some realities for the people that have seen too many movies. You can start with the first 3 listed in this article: 15 Things The Police Wish The Public Knew About Law Enforcement11:

  1.   The police aren’t martial arts or even hand to hand combat experts.

    “People have been conditioned by TV to believe that a properly trained police officer of any size can take down a person of superior size and strength12, quickly, almost effortlessly, without the use of weapons, and without any injury to either party. This is not true. Few cops are expert martial artists. The defensive tactics training13 they receive is fairly perfunctory. Struggles often result in injured joints, lacerations, concussions and other injuries to both parties. There is lots of cursing and screaming involved. The cops usually win, but only because they can get enough cops on the scene to overwhelm the adversary.

    The reality of it is this: if you get physical with a police officer they are going to assume their life is in mortal danger. If at any point you can hit them hard enough to stun them, or are able to grab their weapon, their assumption is that you are going to kill them. So this is why you see multiple police officers tackle and hit people at times – they aren’t experts in hand to hand combatives, they are going to use numbers and brute force to bring the situation under control as quickly as possible.

  2.  Performance Under Stress: During a stressful event the human capacity to think and even respond with coordinated physical movements is reduced.

    What you get is brute force gross motor function moves. Let’s talk about people’s reaction under stressful situations14 for people who have never been a knockdown drag-out fight or have not been shot at:

      • During a stress event, the SNS is activated and adrenaline, chemicals, and hormones are dumped from the adrenal glands and immediately sent out to the areas of the body needed to primarily support the survival effort. At 145 heart beats per minute (BPM), most people lose complex motor skills, meaning those manual dexterity skills necessary to do several things at once or in unison.
      • At 175 BPM, the pupils dilate and flatten and visual narrowing occurs – or what is referred to as tunnel vision – and since the visual system is the primary sensory system for the brain it becomes increasingly difficult to focus and track objects and targets.
      • In the auditory system, hearing shuts down or is diminished significantly at around 115 BPMs and that is why many people say they didn’t hear anything during a life-threatening stress event.
      • The brain is ultimately affected as well. At 175 BPM, it is not uncommon for someone to have problems recalling what just occurred. This is sometimes referred to as “critical stress amnesia.” Immediately after an event, a person may only recall 30 percent of what happened with memory gradually increasing over many hours.
      • At 185-220 BPM, most people will go into a state of “hyper-vigilance.” This is also commonly known as the “deer in the headlights” or “feedback mode” where a person repeats non-effectual actions or having irrational behavior like moving from behind the protection of a building during a gunfight.
      • Lastly, at a mere 115 BPM, fine and complex physical motor skills become less available and effective. Pulling the trigger of handgun correctly, aiming on target or manipulating handcuffs or other tools becomes increasingly difficult to do. This is in direct contrast to the gross motor skills which become enhanced such as those parts of the body needed to fight or flee.

  3.  Split Second Decision Making15: Why It Can Look So Bad After The Fact
    • Go back and re-read the effects of stress on the body and the impact on motor skills and brain function. The average gunfight is over in seconds which means there is not often time for conscious thought. When people receive weapons training they are usually taught to 1. Aim center mass of a target because even when you are aren’t under stress it’s nearly impossible to hit an appendage such as an arm or leg and 2. Keep shooting until the target goes down. Why? Because sometimes getting shot actually doesn’t stop someone from coming at you. I refer to this Apple podcast: Mike Day: Navy SEAL, Shot 27 Times and Never Quit16 who was shot 27 times and still managed to take out his attacker.
    • So when you read some incendiary article that police shot someone 30 times, what they aren’t saying is that it’s not like the police had a meeting before and decided how who was going to shoot how many bullets, the entire event probably transpired in 5 seconds with no time to coordinate, and each officer drew their weapon as they were trained to do and shot repeatedly until the individual went down. Furthermore, given the effects of stress on the body, each officer was probably not even aware of what the other people around them were doing at the time.

Examples of the Types of Decisions Officers Make: I’ve spoken to people about the death statistics for police officers and the response is so what, they signed up for that job. Well, the counterpoint is that you’ve implicitly admitted then than it’s inherently dangerous and violent. Why is that an important acknowledgment? Because to understand police violence you need to understand what kinds of situations they are confronted with and how they are trained to react.

    1. Hint: it’s not easy17 and unless you’ve undergone the training18 it’s really easy to read an after the fact headline and become enraged. Footnotes 8 and 9 are really worth going to in order to get a feel for this.
    2. Two quick summary stories from my use of force training: in one class we watched bodycam videos of police shootings and voted after on if the use of force was appropriate. On one of them, the person was running, stopped, turn around really quickly and pulled a gun out. He was shot and killed. 100% of the class voted it was an appropriate shooting. They slowed the tape down and showed us the pictures after, it was a very young man and the gun was actually a cell phone.
    3. It’s not easy when it’s happening in real-time speed and your stress hormones are flooding your system – vision narrows and your brain just reacts at times without time even for conscious thought. In the virtual simulator, I was in a shoot or no-shoot decision and I shot a lady. To me, it looked like she was pointing the gun at another officer to her right. They let the video play through and it turns out she was putting the gun down, I just had a bad angle. It’s terrifying to me how hard it is to make decisions in these scenarios.
    4. Look at this scenario19 and how fast it plays out – and the officers have the benefit of daylight and helicopter telling them what the person is doing. The reality is you never know who20 has a gun – I carried a concealed weapon and was able to draw it and fire two shots into a target at close range in under 2 seconds
    5. What is the takeaway when you combine these split-second scenarios with human decision making under stress: Police officers are taught that action beats reaction – so if he/she even thinks you are reaching for something that might harm them they are going to attempt to react faster than you and shoot. If you want to see why officers often react the way they do, or attempt to react with a strong level of force to head off any resistance right up front just go on youtube and drop in something about traffic stops gone wrong. Things go from okay to getting shot at in a literal second. A lot of the posturing and domineering behavior is done in hopes to dissuade someone from even thinking about taking that road.
  1. The Damage of a Bad Media Narrative21 “Atlanta Police Officer Shoots a Black Man Dead at the Fast-Food Drive-Thru” That’s the headline, people are already protesting. The police officer has already been fired and the mayor forced the police chief to resign. You read further details: the man had passed out in his car and was blocking the drive through so police were called. He got out of his car, started wrestling with the officers, managed to take one of their tasers, and was firing it at them, and only at that point did they shoot him. None of that is in the media, instead the officer is fired and the police chief is forced to resign. Any intelligent police officer that can find work elsewhere right now is going to do so and you are going to be left with less qualified and capable candidates. This entire narrative is making the situation more volatile and more error prone rather than the opposite.

Societal Considerations

 Large datasets and false homogeneity: First point and counterpoint: Large sets of numbers hide the truth at times. If you have never worked in law enforcement it’s hard to realize that the police are not a monolithic organization. Police departments are like church parishes – each one has its own culture, leadership, training department, demographic make-up, funding sources, etc. This view enables the following conclusions 1. Don’t just look at the national level averages and say there is no problem. On the other hand 2. The fact that departments vary widely should also make people hesitant to condemn the police en masse as some collective hive mind bent on discrimination. What is clear is that you give police departments a lot of power and authority – hiring practices should come under the ultimate scrutiny.

Lack of Narrative and Effect: Well what about the other side of the story when police are entirely wrong in their actions? I think that is put on display every day, what people don’t understand is what police officers are confronted with daily and just how quickly they have to decide under pressure. When you routinely vilify the police and incite hatred towards them without understanding the demands of their job and how these kind of things can occur you are creating a real problem in the sense that no reasonably intelligent person is going to want to become a police officer and the quality of your candidate pool is going to go down drastically. This will likely make all of the above problems worse over time and not better. There is a very real human element to this that is hidden by the dominant narratives.

“All Cops Are Bad Because They Don’t Turn in The Bad Cops”: People are dismissed from law enforcement agencies all the time – it’s just not publicized. I worked for a smaller agency and over the course of four years just in my local office we dismissed 4 individuals from internal investigations, from low ranking to very high ranking. They didn’t do anything criminal, or even overtly wrong in some cases, but they were judged to have a character not appropriate to law enforcement. That being said, there is a lot of evidence piling up that police unions are a very large problem because they protect officers from complaints and the officers cannot get fired. So even if a fellow officer or citizen files multiple complaints, nothing happens22. We didn’t have a union so people could be dismissed at any point.

Concluding Thoughts

Let’s stop turning police officers into the scapegoat for all the underlying societal problems that nobody wanted to address before. You need a holistic and systemic approach. Reach out to local police departments and include them in the discussion, support politicians to change the laws they have to enforce, support charities that help ensure equal treatment in the justice system. But if you keep vilifying and blaming the police for the entire system you are only going to get less qualified and less astute police officers moving forward, and that will be to the detriment of all of us. The current narrative is largely inaccurate, it’s also damaging.

Breaking Barriers United on Defunding The Police (Link)

Jay Stalien on Being a Beat Cop in Urban America (Link)

Humanizing the Badge (Link)