Finance As A Laboratory For Decision-Making [StockSlam Preview]

With the StockSlam Sessions rapidly approaching, I want to thank Jeff Malec at RCM Alternatives for inviting Tina, Steiner, and me to his show. You can listen to the pod or watch on Youtube. Steiner is an offline guy, so foremost this is a nice introduction to him.

  • The Game of Trading with SIG Alums Kris A, Tina L, & Steiner (Link)

    We have a little saying over here on The Derivative, “The More, The Merrier”, and on this week’s episode of The Derivative, we’re not chatting with one guest, but THREE! Class may no longer be in session, but we are taking a trip down the SIG/Susquehanna memory lane and having our own class reunion with Kris Abdelmessih, Michael Steiner, and Tina Lindstrom.

    If you’re interested in learning how big trading firms find and teach their traders, hold on to your seat because these three give you the answer key! Kris, Tina, and Michael are in session with Jeff and discussing competing with peers, finding an option’s fair value, making markets, and being in the game of trading, educating kids with board games, and of course Steiner’s new trading board game: Stock Slam! Discover how the game works and how you can join up with these three in NYC for a live session in this three-of-a-kind episode

We are doing these sessions because trading is a neat laboratory to learn about decision-making. Weighing risk-reward, thinking adversarially (this thread by @0xDoug is in my hall of fame), resisting confirmation/hindsight biases, using probability, considering counterfactuals, not “resulting”, and much more. So much of my writing focuses on these “meta” topics because trading gave me a better education than school ever did.

If we can help people practice thinking this way, it’s a like growing new brain lobe that’s adaptive for many real-life situations.

The following is adapted from a thread I wrote that demonstrates an idea in a trading context:

People understand that even though insurance has negative expectancy it can still improve a portfolio that is focused on compounded returns. It makes no sense to look at the line-item of insurance divorced from the optionality it gives you in the rest of your portfolio.

(I could pull lots of links on this idea, but let’s be brief).

This concept is fractal. Let’s zoom in on the smallest portfolio — a spread. You don’t necessarily care about the p/l of any individual leg of a spread trade but the performance of the spread overall.

Before we consider a spread, let’s just look at the single position. Suppose you buy something for $4 when it’s worth $5 but then sell it for $4.50. You made both a:

  • +$1 expected value trade
  • -$.50 EV trade.

If you knew it was worth $5 you negated half a good trade with a bad trade.

In real life, you often might like the price of a spread but it’s hard to tell which leg is the “good side”. That’s one of the reasons you trade the spread. Once you do the spread you don’t care about the individual p/ls.

Another reason you may do a spread is that you might like a trade (ie maybe vol is cheap in X) but can do it bigger if you spread it. This is one of those questions that comes up a lot on real trading desks. Do I like the outright, or do I like the trade better paired against something else (and assuming I can do the trade bigger if I spread it)? Do I like being long z units of X exposure, or do I prefer 5z units of (X-Y)? The answer depends on understanding the distribution of the outright vs the spread and the relative price of each within those distributions.

Finally, there’s the general lens of how I approach trading (which I discuss in the RCM interview). Liquid markets tell us a lot about “fair value”. If we take fair value as the consensus “outside view”, then we can examine illiquid markets for pricing discrepancies compared to that outside view. Of course, those markets have their own idiosyncracies, so you need to take an “inside view” and normalize as much as possible to the liquid reference asset. This is a standard way to identify possible opportunities. It’s a mix of art and science. The science is in the measurement but the art is in handicapping how much the differences should matter. This isn’t arbitrage. It’s informed betting. If you need certainty, you will either be too late or the strategy will have the lifespan of a mayfly.

[I actually googled “shortest lifespan” and was met with irony:

We often hear that mayflies, like the whiteflies of the Susquehanna River, have the shortest lifespan of any animal on Earth, just 24 hours for many species.

SIG is named after that river.]

Now let’s broaden the concept to investing. For that, I turn to Byrne Hobart’s paywalled post Assuming Efficient Markets to Exploit Market Inefficiencies:

If there’s an efficient market A and an inefficient one B, A is easier to trade in, but B is probably the one that’s mispriced. So that price inefficiency partly represents a measure of how hard inefficiencies are to exploit! In the case of Druckenmiller’s recession call, he actually made the paradoxical judgment that inefficient market B was priced incorrectly relative to A, but that A was the one to bet on—because the specific inefficiency at hand was that a recession was likely and it wasn’t being accurately reflected by anything.

This raises an important point, because there are two broad ways to look at relative inefficiency. One is to just stick with the relative argument: if stocks are pricing a boom and bonds are pricing a recession, bet that one of these will go away. But that’s a frustrating conclusion to draw, because it basically amounts to saying: The market is telling me something important, and I don’t care what it is. The relative-value bet works equally well regardless of which thesis is right, but it’s still outsourcing a lot of judgment to the market. And annoyingly, once the valuation gap closes, you have two problems: first, you haven’t figured out why the discrepancy existed in the first place, and if there’s an inexplicable 1-standard deviation change in some correlation, there is no law of the universe saying it can’t go to 2 or 3. (There is a weaker law saying it can go to 20, when enough levered participants are betting on it.) The other problem is that real-world theses produce additional ideas; an argument that the economy is going into a recession has second- and third-order consequences, and generates more ideas.

This kind of tradeoff, between a low-risk claim that two views are contradictory and a higher-risk claim that one of them is right, extends far beyond finance.

Through games, direct instruction, and making connections between abstract concepts and examples in the wild, Tina, Steiner and I want to see if we can help others get better. And selfishly, I want to think better, so I’m stoked to be a part of this.

*Applications are closed and invitations already went out but these sessions are an experiment to guide how we test and improve the transfer of knowledge. If you didn’t get accepted it’s because space was extremely limited compared to applicants. This is not meant to be exclusive, we are going to figure out how we can spread what we learn. As Axl once said, we just need a little patience [bandana sway].

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