1/ Musings about variance in trading, in sports, and in life.

A thread.
2/ Why does poker get played for big $ but chess (mostly) doesn’t?

Because of variance.

In chess, if you’re rated 1800 ELO and you’re playing someone rated 2000, you pretty much know exactly your P(win) and P(tie). (It’s 15% and 19%, go check).
3/ There’s no sense in betting for two reasons:

- A wide spread of ability directly creates wide spread in outcome. A 2400 will NEVER lose to an 1800.
- All these probs are pretty much known. $ gets traded when people disagree about probs. No such thing exists in chess.
4/ In poker, the variance is huge. Even if there’s a large spread in ability, the bad player still wins enough, on timescales that matter (days, weeks).

That’s what gambling is.
5/ Lots of people misunderstand what gambling is about.

Why aren’t there any coin-flipping tournaments for a million dollars? It’s plenty of variance right?
6/ Because everyone knows P(heads) is 50%. That makes it boring.

When everyone agrees on probs, no one wants to gamble for real $.

People who know and understand the probs of slot machines don’t play them. People who don’t know or try to forget these probs do play slots.
7/ This is precisely what you see in trading.

Trading is the expression of disagreement about probabilities.
8/ I decided to write this thread after seeing @LouStagner claim (correctly I’m quite sure) that match play doesn’t identify the best player that week nearly as well as stroke play.
9/ Yes that’s true.

But match play is more fun (as a rare event) because it has more outcomes and variance.

And in sports, high variance and disagreements about probabilities are very strongly connected (unlike with a coin flip).
10/ The thing that spectator sports are always optimizing for is having the right amount of variance.
11/ Too little var is boring. The same person/team winning every single time makes people turn away.
12/ Too much var is confusing.

If every baseball team had a .500 record, that would SUCK!

If the winningest player on the PGATour only won twice a year, that would be awful. People like *some* amount of predictability.
13/ When Tiger Woods was dominating, a big part of the reason he drew people to the game is because his dominance pushed golf towards the optimal amount of variance.

Golf is a VERY high variance game. And his dominance (winning ~ half the time) was perfect for the casual fan.
14/ Why isn’t tennis scoring just one long game to 200 points or something? Because the better player will win basically 100% of the time.

Once the score gets to 120-90, the game just becomes an exercise in score management. Zzzz.

Games and sets are a way to increase var.
15/ Remember Daytona 500 the video game?

When you were behind in a race, the game gave your car superpowers. So that you could catch up and make the race more exciting.
16/ Back to poker. The forms of poker that persist over time are the ones that find the optimal amount of variance to make the game.
17/ If good players win all the time, the game dies. Fish lose money too fast.

If it’s too random, the game dies too. Pros don’t have an incentive to sit there and make the game during slow times.

It’s a balance. Optimal variance rules the world.

18/ Following up on the tennis thing, I modeled the game assuming every point is the same (i.e. serving doesn't matter) and independent.
19/ The x-axis is P(win point) and the curves are win probabilities for game, set, match and hypothetical 101pt and 201pt single-game matches.

Basically if you're 55% to win a point, then you're 95% to win a best-of-5 match.
20/ The best-of-5 curve is pretty similar to that 201pt hypothetical match.

But as @wait4thegoodlif and I were discussing yesterday, the multi-set match creates more inflection points, i.e. a subset of points which have a large effect on the match.

And hence more excitement.
21/ Just like match play does in golf. There is a higher variance in how much a random point or shot matters to the outcome, and that manufactures excitement.

Baseball's awesome at this. Most pitches don't matter, but bases loaded 3-2 counts are super exciting.

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More from @AgustinLebron3

10 Mar
1/ Quick mini-thread on a useful way to think about risk based on a recent discussion I had.

"If I have an opinion about lithium price, should I trade $LIT?"
2/ Almost definitely not. $LIT is a very weird monster. Many ETFs that target second-tier commodities are equally weird. Why?

Because $LIT includes both producers and consumers.
3/ High Li prices are good for producers, bad for consumers. So what's the effect on $LIT?

It depends on the balance of producers and consumers.
Read 10 tweets
22 Feb
1/ Taking a break from options to talk about a general trading concept.

Intended audience: people who are getting into trading, people have read a bunch of “experts” and came away even more confused, etc.

A thread…
2/ I thought about putting this in the book, but in the end I decided it’s too technical for a general audience. The one sentence claim I make here is:

“Trading is the wrong term for what trading is. Trading is more accurately called positioning.”
3/ What do I mean by this?

Retail traders seem to obsess about “entries” and “exits”. But in my career as a trader, I *never thought about entries and exits. At least, not explicitly.
Read 34 tweets
8 Feb
1/ Welcome to Options 201! You might remember me from such threads as Options 101:

Or What’s The Deal With Having Edge?

2/ I wasn’t sure if I should keep going. We’re getting closer to “how to make money in options,” and I think public sources of such claims are always and invariably scams.

But I’ve decided this is still more “useful information to know” than trading edge, so it should be ok.
3/ Let’s start by talking about time. Time is surprisingly hard to think about. But why do we care?

Well, as we said in Options 101, we want to convert our options prices into vols because of #reasons. And to do so, you need to know t_exp.
Read 62 tweets
30 Jan
More ruminations on what trading can teach us about non-trading things. A thread...
Recently reading @SinclairEuan's excellent "Positional Option Trading", and he reminded me of something I hadn't thought about for a while:

Great trades start with a known risk premium and then add idiosyncratic inefficiencies on top to get more alpha.
The risk premium is a long-term thing. The vol premium or the carry trade aren't going anywhere.

But you can't really build a business on them alone. Too many people know about it, so returns are at best "ok" (i.e. low Sharpe) but with terrible tail behavior under stress.
Read 14 tweets
4 Jan
1/ Options 101 (a thread):

When you teach options, they put you in jail if you don't start with this:

A call/put is the right (but not the obligation) to buy/sell a security for a given price at (or by) a certain time. Boring! Let's do an example:
2/ If I own the Mar 700 call in $TSLA then that means anytime before ~5pm on Mar 19 2021, I can exercise my right to buy TSLA shares.

I hand over $700/share and I get some TSLA stock. First let's note a few things:
3/ US equity multipliers are typically 100 (barring corporate actions). So when you buy 1 options contract (call or put), you're actually buying the right to 100 shares.

Remind me to tell you the story of when I messed up the DAX multiplier. I was *sure* was going to get fired.
Read 56 tweets
23 Dec 20
Many different-seeming activities have a very similar characteristic when you compare skilled people to world-class people:

Almost all of the difference can be explained by the quality of left tail performance.

1. In golf, @LouStagner and @scottfawcett have shown that scratch player vs professional "good shots" are fairly similar (within a few %), but the bad shots are sometimes 2x worse for scratch players vs pros.

And scratch players are really good at golf.
2. In chess, a big part of your ELO is how often and big your blunders are. The difference between an IM and world-class GM isn't that @GMHikaru finds brilliancies much more often, it's that his worst plays are still really good.

Arguably this is how @MagnusCarlsen wins so much.
Read 6 tweets

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