I strongly recommend posting in the Metagame 2025 Discord, or potentially trying to recruit people in person at Metagame (https://metagame.games) at Lighthaven this September if you haven't filled the role by then. It's literally just a bunch of game design nerds collaborating on building out a giant game together with online and in person elements, a bunch of whom also have lots of AGI risk knowledge.

Also possibly you guys want to run the TTX at Metagame, or beta test the online version there?

I'm running a quant trading bootcamp at Lighthaven (in Berkeley) Nov 6-10. This is my first time trying the extended weekend model; it starts Wednesday night so if you're local you only have to take off Thursday and Friday. You can register here, or check out the LessWrong event here.

The course covers the fundamentals of quant trading (markets, order books, auctions, risk and sizing, adverse selection, arbitrage, how quant trading firms make money). In terms of vibes, it's a cross between the Jane Street trading internship, Manifest, and summer-camp-style colorwar. 

Also, if you check "LessWrong" for "How did you hear about this bootcamp?" you get a $150 discount.

Puzzle Hunt Credits

• Organizers:
  • Ricki Heicklen
  • Rosie Campbell
  • Phil Parker
• Puzzle Creators:
  • Drake Thomas
  • Eric Neyman
  • Adam Scherlis 
  • Jacob Cohen
  • Guy Srinivasan 
  • Samira Nedungadi
  • Seraphina Nix
• Writers:
  • Sammy Cottrell
  • Avital Morris
  • Ronny Fernandez
  • Rafe Kennedy
  • Ruby Bloom 
• Engineers:
  • Julian Aveling
  • Sophie Superconductors
  • Art Zeis
  • Robert Mushkatblat
  • Peter Schmidt Neilson
• Playtesters:
  • Brian Smiley
  • Eloise Rosen
  • Lawrence Kesteloot
  • Judy Heicklen
  • (& many others)
• General Helpers:
  • Tess Hegarty
  • Simon Baars
  • Ms. Aveling
  • Paul Crowley
  • Sparr
  • Ross Rheingans-Yoo
  • Sydney Von Arx

(Any omissions accidental and will be fixed upon review)

InDesign! Or anything on page layout / publishing / how to make a pretty and well formatted book

Probably worth including that the winner's curse will also tend to be a feature when the object to be bought is a one time, one customer type setting.

I don't think the winner's curse is limited to this; e.g., I think if the top five bidders win in an auction for vacation tickets (not knowing the value of the vacation package in advance), the effect still exists. It also doesn't need to be a one time thing, or a unique good. 
 

Or would you agree that under your view, the market clearing price of a Walrasian auctioneer the price is also too high in some way? After all, it's pretty clear from the simple S & D graph that most of the buyers could have, in theory at least and likely in reality if they could directly communicate, bough whatever they bough at a price lower than the market clearing price; S slopes upwards and includes the producers required rate of return.

I don't think the clearing price in such an auction is skewed high (if it were, you could profit in expectation by consistently selling, and this should correct the effect). I do think adverse selection concerns should enter your calculation even when submitting orders to two sided auctions like this one (e.g. any US stock market opening/closing auction), because your orders are still getting filled by the market as a whole, but I agree the dynamic does not have the directional bias of the auction I describe here.

In response to various comments, I've edited this post to change the title, clarify my fundamental thesis and some terminology choices, and provide explanations for each example. I apologize if this makes some of the existing comments confusing; for posterity, the original version is here.

The high level changes:

1. I changed the title from "Conditional on Getting to Trade, Your Trade Wasn’t All That Great" to "Toward a Broader Conception of Adverse Selection," since I think the former was distracting from the substance of the piece and led to people believing I think trades cannot be positive sum. Thanks in particular to @Thomas Kwa for the gentle advice to change it.
2. I added in an introductory section defining adverse selection, motivating the piece, clarifying some misconceptions, and providing a roadmap for the next posts in the sequence.
3. I reordered the examples and added section headers. The divisions aren't perfect, there's overlap between them, but hopefully this adds some clarity. 
   1. Because of the reordering, some of the comments referring to examples by number might not make sense. The original numbering was:
      1. 1: The Subway Seat
      2. 2: The Juggling Contest
      3. 3: The Bedroom Allocation 
      4. 4: The Thanksgiving Leftovers
      5. 5: The Wheelbarrow Auction
      6. 6: The Wheelbarrow Auction pt 2
      7. 7: The Laffy Taffys
      8. 8: The Field
      9. 9: The Parking Spot
      10. 10: MoviePass
      11. 11: Widgets Inc.
           
4. I explained each section with 1-2 sentences, and added explanations for ~all of the examples. 
5. I added the example "Alice’s Restaurant vs Bob’s Burgers," adapted from a comment I wrote.
6. I included various strategies for combating adverse selection in specific scenarios. I feel conflicted about this, since I'm worried the strategies will distract from the examples and also be redundant with a lot of the content in the second post, but I think this was the right call to help motivate why paying attention to these effects can be useful.
7. I changed a couple of the names
8. I added a few footnotes

I refuse to remove the Karl/Groucho Marx joke.

It seems like the more the EMH is true in a situation/amount of optimisation pressure applied the more you should expect to be disappointed with a trade.

Yes, this is exactly right—post #2 in the sequence is about what environmental factors increase or decrease the prevalence of adverse selection, and ways to improve trading (and everyday decision making) in light of it. Stay tuned :)

... I would also not be doing it nearly as badly as OP postulates I would. (Because I would be, say, a market-maker like Jane Street, which makes a lot of money off doing that sort of thing.)

I'm not sure I follow. Is the argument here that Jane Street is good enough at market-making that they are not vulnerable to adverse selection? i.e. that the dynamic in example #11 (Widgets stock) wouldn't apply to them?

The fact that you have to reach for exotic scenarios ... [such as] auctions by naive non-auction goers who don't even know to account for winner's curse or getting stuff for free should make you rethink what you are claiming about "most trades you make aren't all that great".

The thing I'm describing here is winner's curse—my point is that the winning bidder (in example #5) overpays relative to the true value, while the median bidder (in example #6) neither profits nor loses. (A bidder whose model is mistaken such that they substantially underbid also profits $0). That is, there's an asymmetry between your PnL when your model is correct (#6) and when your model is incorrect (#5). 

Some auction goers know about winner's curse; they likely make more conservative bids to protect against this. Some auction goers don't. The person winning the auction is more likely to not be thinking hard about winner's curse, or to have a sufficiently wrong pricing model to counteract the size of their adjustment in light of it.

The point is: conditional on winning the auction, you outbid every other person. You are at the extreme end of bids. The price you bid ($180) is a combination of your model of the wheelbarrow's price ($200, with some uncertainty) and the amount of edge you ask for on account of winner's curse concerns (10%, or $20). If you are the winner, it means everybody else either models the price as lower, or asks for greater edge, or (most likely) some blend of the two. If it's just because they're asking for more edge, your bid may still be profitable. But it's likely some combination of the two, and their price models all (or almost all) being lower than yours should cause you to update that the true value of the wheelbarrow is lower than you'd previously estimated.

I don't claim here that all trades you get to do are bad. I claim that they're worse than they might naively seem without accounting for adverse selection, i.e. for the fact that your opportunity to get something depends on nobody else wanting it (as in the case of the subway seat or the parking spot) or somebody else actively wanting the other side of the trade (as in the case of the zero-sum bedroom selection or the juggling contest).

I'm surprised that these are exotic scenarios to you. I regularly take the subway. I might not be understanding the relevance of subways as an example of "government failure," but I'll rephrase the example without needing to invoke a government resource:

1. The Restaurant Seat: You’re in a food court at dinnertime. Almost all of the restaurants are full to the brim, and don't have any tables available, but you notice one that is entirely empty. You’ll be able to get a table! You enter the restaurant, order your food, and take a bite. The food is mediocre.

Bad restaurants are more likely to have open tables than good restaurants. Alice's Restaurant and Bob's Burgers might look identical to you from the outside, but if all the tables at Alice's Restaurant are full and the tables at Bob's Burgers are open, that's evidence that Alice's Restaurant is better quality—and you'd rather eat there. Unfortunately for you, all the tables there are full, so you can't. The trades you get to do (eating at Bob's) are worse than the ones you don't (eating at Alice's).

That doesn't mean that eating at Bob's is worse than going hungry. It might still be worth buying food there instead of not at all. But, if a week ago you had had the opportunity to make a reservation at either one (before Alice's filled up), you would have been better off flipping a coin and reserving one at random than waiting to slot into whichever is available.

Does this help clarify the confusion? If so, I'll edit in this example, so as to not have the government goods degrading element distract from the core idea.