The original moontower blog is https://moontowermeta.com/. The “meta” is an important word. Important enough that Facebook stole my language and turned it into their ticker. F’n Zuck. Leave some for the little people bruh.

The reason I used “meta” (besides the fact that moontower.com wasn’t available) was because a lot of things I think about are fairly meta. Knowledge is the object but how we acquire knowledge is the meta. Trading is a very meta discipline because games with counterparties require a solid “theory of mind”.

In the spirit of meta, I really enjoyed a recent post by Robot James titled:

Valuation Timing with Excel (6 min read)

It’s meta because it’s really about arming yourself with data analysis to confront a narrative or chart. It’s worth stepping through the article together to appreciate just how many meta-nuggets it contains.

First, we start with an object-level observation that you’ve likely encountered. I’ll quote freely from the post but all bold is mine:

You may have seen a lot of charts like this recently:

The conclusions people tend to draw from this chart are:

• there is an obvious and strong relationship between valuation and expected future returns (cheap = good, expensive = bad)
• valuation estimates are currently historically high; therefore, expected returns of the S&P 500 are historically low.

We should always be wary of drawing strong conclusions from stuff people share on the internet or in sell-side research.

There are a few reasons to be skeptical of the strong conclusions people tend to make on seeing this:

• the chart might just be wrong (people screw up financial data analysis all the time)
• 10 years is a really long time horizon
• all of the 10-year total returns are actually positive
• why are there so many points? How many 10-year periods has the index even existed for?!

The good news is that, with a few simple skills, we don’t have to believe what randos on the internet say.

Even if we can’t write code, we can use Microsoft Excel and free online tools to investigate these things ourselves.

James shows how simple it is to grab the data that would feed such a chart so we can manipulate it ourselves. One of the first manipulations is addressing the fact that such a chart is really derived from an extremely small sample size because each data point is highly overlapping to the others. A rolling 10-year return is comprised of 120 months so each new “sample” overlaps with the prior one by 119/120.

James starts the exploration by looking at monthly returns (instead of 10-year returns) vs CAPE.

Let’s turn back to James for interpretation.

Unsurprisingly, that looks like a big blob. (Anything with monthly returns on the y-axis will look like a big blob.)

[Kris: that bold statement is a useful bit of knowledge that comes from looking at financial data frequently]

What does James do next?

We can look at longer non-overlapping periods. Let’s keep with the 10-year forward window and look at decades.

The problem is that we now only have 15 observations! Ten years is a long time, and we simply don’t have that many unique non-overlapping ten-year periods. And we certainly don’t have many unique non-overlapping ten-year periods that are similar to the current market structure and competitive environment.

[Kris: that bold bit is an evergreen problem in finance because investing is biology not physics. Markets learn so output become inputs. What does that mean? Markets are more likely to fall AFTER everyone starts believing they can only go up. The “only goes up” is the output or observation that then becomes an input into how much risk investors take. There is always some price that peers back at history and says “not this time”.]

So James slices the data another way.

Plot the valuation metric itself…

whenever we see an effect, we should ask what other than our pet theory might be causing that effect to appear. In particular a lot has changed over that time period. The market looks nothing like what it did in 1900 today.

And, indeed, if we plot a time series of our valuation metric, it looks kinda drifty.

It’s not really reasonable, I don’t think, to assume that CAPE 20 would “mean” the same thing in 2024 as it did in 1900.

He tries another manipulation:

One cheap and dirty way we can make that metric a bit less drifty and more comparable over time is to standardize it by its values over a recent rolling window.

For example, here I’ve standardized it as a 10yr rolling score. (Not necessarily cos I think that’s the right thing to do – I just want to make a point).

Now it looks a lot more stationary. It stays in the same range. It doesn’t drift off. This is unsurprising cos we forced it to look like that.

[Kris: the bold is another lit bit of fingertip knowledge that you acquire from frequent contact with data.]

Yet, another manipulation:

Now, we can plot our next year’s returns vs this standardized z-score.

If we still see an effect when we do this, it would make us more confident in the valuation effect. If we don’t, it won’t destroy our confidence because we’ve made some pretty arbitrary and dubious scaling choices here.

Indeed, at least with this scaling choice, we don’t see the effect we are looking for.

That’s ok. That’s the nature of work like this. We’re just exploring, trying to break things. We try to look at things from as many different angles as we can and see how much of the limited evidence lines up.

[Kris: I just want to pause for beauty as my wife likes to say. James is spoon-feeding serum against chart crimes and charlatans who read “How To Lie With Statistics” as a manual].

James’ Conclusion

I think the evidence (and economic sense) supports the idea that high valuations are correlated with lower expected returns. But it’s nowhere near as clear-cut as the initial scatterplot suggests. We simply don’t have enough data, and the market is constantly changing underneath us, making it hard for us to draw strong inferences.

My conclusion

This points to an uncomfortable reality. If a data analysis was conclusive then everyone would do the thing prescribed until the data exhaust from the behavior was no longer conclusive. This is deeply reminiscent of what I call the Paradox of Provable Alpha.

Notice what James did.

He recognized that the data proves nothing but it’s simply too underpowered to accept or reject any claims. His prior barely gets updated: “I think the evidence (and economic sense) supports the idea that high valuations are correlated with lower expected returns.”

He goes to bed at night with judgment as his best guess much like a farmer’s almanac will do better at predicting the weather in a month vs some meteorological model.

Thanks again to Robot James for the heavy lifting on the original article. I was just narrating alongside it to highlight what stood out to me and how it related to other topics we discuss here.

If a tree falls in a forest, does it have a delta impact?

I didn’t feel like writing so you get the answer I’d give over a beer in Roppongi if you gave me a few minutes to collect my thoughts (and if I drank).

Dark arts. Microstructure. Options.

Enjoy…

Another story with some powerful lessons…

Let’s start with one of the best stories I got to be a part of at SIG.

Tina recounted it on Twitter, I’ll offer more color below.

Tina:

Ok, seat arb story. One day, ICE announced that they wanted to buy the NYBOT. Jeff Yass runs into me when he came into the NY office one day when this started, and asked if we should be buying these seats for edge – ICE stock in exchange for seat. I was Head of the NYBOT for SIG at the time with traders in coffee, sugar, cocoa, as well the Russell 1k,2k,3k.

I had talked to many traders beforehand and overwhelmingly, they were against the buyout. So I told Jeff, no it won’t pass and and we would lose buying these seats. Then I dug around more and realized that the vast majority of people against the buyout were leasing the seats and that owners with votes were for.

Called Jeff back and told him I changed my mind. Jeff green lights it. This became such a fun crazy time because, I would be trading during the day, watching ICE stock, watching the seat tape -seat prices on the ticker on the boards, and then when the seat offered were at a sufficient discount, I would stop trading, send my clerk to run to the membership office and bring me docs to sign. The edge from these seats became more than the edge from trading so I would literally stop trading during the day at times to do this. Of course then I had to call Jeff’s right hand man Shawn, and then the COO to free cash up.

We had to put all these seats under individual traders, since technically the traders were the members. So myself, Kris Abdelmessih, etc had many many seats in our names which was also funny. The seats were maybe $650k and I bought maybe 30-40 for SIG.

In the meantime, the CME was also bidding for the NYMEX which was in the same building btw as the NYBOT. Somehow the head of energy for SIG was out for a bit and so I was the most senior in the building. I saw Jeff during that time and he said “ I really really want to buy some NYMEX seats”.

So one day, this guy I knew who owned a clearing company is alone w me at the elevator and asked if I would buy his seat. Jeff had given me a $10m top when the seat was maybe worth $10.8m. Think the displayed market for seats was $8.5 at $9.3m or something. Guy is like, “I will sell you my seat for $8.8m. “

I call Bala [Cynwyd], get his admin, he’s in a meeting but I tell her I needed him. Jeff picks me up, approves it, tells me to call the COO to free margin up and wire the money. Was pretty exhilarating that one trade to get so much edge I must say. The best part was also that, SIG got awarded the CME specialist post on the NYSE so we were the only ones who could sell CME short, setting up for a real arbitrage.

All of this happened when I was pretty young, so you can imagine this was all super cool, the trust Jeff had in me to manage so much of his money. I am forever grateful for the opportunity.

Pretty neat.

I’ll add a bit more.

The head of energy on the NYMEX oversaw nat gas trading as well as me (I oversaw oil trading). Before we came to the NYMEX, he was also my boss on the NYSE. I remember being at the NYSE member meeting when then CEO John Thain (after the Grasso departure) started explaining what would become Reg NMS!

SIG also bought NYSE seats before it went public. By the time, the NYMEX and NYBOT were ready to demutualize they understood this particular style of special sit quite well.

Aside on the NYMEX deal

Before the NYMEX was acquired, it was member-owned. The member owned a “seat” which gave them voting rights as a matter of exchange governance plus the right to trade on the floor.

The CME offered buy the NYMEX in stock. A member would receive some amount of CME shares for each seat they owned. To value a seat you had 2 primary inputs:

1. The amount of CME shares you get x the price of the shares during some fixing window (I don’t remember the details)
2. The value of the permit which allowed you to trade on the floor

The permit could be valued by a simple DCF based on how much you could lease a seat to a trader or broker on a monthly basis. Forecasting lease rates could be tricky since the life of the trading floor was already in question.

In fact, this is why lessees were so against the deal. They owned no equity in the deal and their livelihood was at risk if the floor’s days are numbered. The seat owners had their golden ticket. In the time leading up to the sale, seats more than 10x’d in value with many seat owners buying even more. That deal spawned lot of generationally rich Sal’s from Staten Island.

The trading permit however was a small portion of the overall seat value so the DCF exercise was fairly inconsequential. The main risk was the CME’s stock price but as you saw from Tina’s story — there was a lot of edge. If CME stock had 30% vol, with the trading permit, you were basically buying the shares at a 1 standard deviation discount (and that’s if you had to hold for a year). With SIG able to short CME to it was a good trade to plow size into.

Being Nimble

You could relate this story back to my video above. There was some opacity to the market because the seat bid/offer prices were maintained by a small group of office workers employed by NYMEX. Our trading assistant would frequently go up to the membership office bearing coffee or treats to chat them up for color on who’s been poking around the order book. Know the chokepoints.

It reminds me of someone who knows their local RE duplex/multi-family market cold. Occasionally a listing comes up and they will know the exact block and layout so they immediately notice that while it says 3 bedroom, it’s really a 4 with a minor change plus it’s on a side of the street worth a 5% bump. Call the broker, offer 50k thru ask if they take the listing down immediately (and this is in the subset of cases where you didn’t get the look before it hit MLS).

Usually this type of fingertip knowledge in dark corners doesn’t scale, but the seat arb was a rare exception. A bunch of jabronis just made their grandkids rich out of the blue and didn’t want to gamble on the closing of the last 20%. Edge.

I think my favorite part of the story though was the moment. We were all in our 20s and Jeff trusted us. SIG was very entrepreneurial. I got to be a member of every exchange in NY except the NYFE in under a decade. You have enough social aptitude plus lots of training in how to think about risk…“go break into that pit”.

Trading firms, at least ones with a floor heritage, have a fairly flat org structure which is strongly on display in Tina’s story. Empowering employees and limiting bureaucracy seems to be a real edge but requires the right culture and alignment. I recently highlighted the flat structure of Valve, but like SIG they don’t answer to any outside investors.

Going from this real-life example up to the level of lesson, this is SIG’s Todd Simkin explaining the advantage in his interview with Ted Seides.

Ted: Over the 30 plus years you’ve been at SIG, you’ve seen in the hedge fund world this growth of multi-manager platforms. How do you view yourselves competitively to some of the bigger people that you see in the markets?

Todd: We have been in the fortunate position of having the most patient capital of all. One of the challenges with hedge funds is their need to frequently manage not just quarterly reports but monthly, weekly, or even daily reports. They must demonstrate adherence to their outlined strategy and deliver consistent returns.

In contrast, our investors are the principals of the firm.

They understand the risks we take, including outsized risks, and they are the ones driving these decisions. If I decide to put on a $100 million insurance risk tied to the winner of the Super Bowl, I’m not worried about explaining losses to a multitude of stakeholders. Instead, I have a single conversation with the relevant decision-maker, outlining the edge I perceive and the terms of the deal. Their involvement includes monitoring the situation, such as checking the health of the quarterback throughout the season.

This patient approach has enabled us to stay in and grow businesses during downturns while shutting down exposures when needed. Unlike others who must adhere to predefined strategies, such as maintaining a certain percentage of long-short equity exposure, we can dynamically allocate capital.

We benefit from the large capital base while retaining the flexibility and focus of having a small number of decision-makers. These decision-makers avoid imposing artificial rules that might constrain our strategies, a common issue when managing external money.

Ted: When it comes to trading, even though long-duration capital is an advantage, your focus often remains on relatively shorter time frames. What sets the traders at SIG apart that allows you to stay successful in an extremely competitive market?

Todd: I think there are a few things.

One is that we focus a lot on the decision process—the information available, how we used that information, and then what trade we made—all of that way before we discuss the results. I think a lot of other people have that upside down. They say, “How did you do? If you made money, great, keep doing what you’re doing. If you lost money, that means that you took too much risk, and that’s a bad thing.”

Whereas our traders are focused on the decision process and the expected value first, and because of that, we don’t do things that I’ve seen some of our competitors do that we would think would bleed away some of those profits.

For example, say you do all your work, there’s no selection bias, there’s no reason to think that you’ve gained new information by being able to enter a trade and you get to buy an asset for $10 that you think is worth $20. Seems great, and then somebody comes along and they say they’ll buy it back from you for $19.

Do you want to sell it?

A lot of people at that point would say, “Well, that’s great. I bought it for $10. I sell it at $19. I make $9. I put it in my pocket, and I go away pretty happy, and I sleep well tonight. Nothing bad can happen tomorrow with my position. I’m out of it, and I’ve just made my money.”

And we say, “No.” If anything, if we’re able to buy more at $19 and we still think it’s worth $20, then we would. The fact that we got to buy it for $10 is great, sort of confirmed now by the fact that someone’s willing to pay $19, but that doesn’t mean we want to sell it and lock in this profit just because you have an opportunity to close a position.

That is part of the culture of the firm. We’re not going to give something up just to feel better in our small individual portfolio, which is part of this much, much bigger firm-wide portfolio. If the whole firm had the opportunity to do that and gave up 10% of our profits every time we had a profit-making opportunity, that would be really costly. Somebody else is on the other side of that trade picking up all that extra money that we’d be giving away.

[Kris: That’s exactly the NYMEX/CME example!]

So part of the culture of the firm is one in which we are finding edges wherever we can find them but then capturing all of it by either holding to maturity or holding to expiration or closing at an appropriate rate when we have either new information or where the markets have changed.

Friends,

Within a week of the furious post-election rally I went to Twitter:

What is the most asymmetric way to bet on deflation? Is there an option on this that’s left for dead?

There’s conventional choices like bond calls but i want to hear what ya got…also not a short run expression…something long dated that gives time to see the possibility of deflation looking out the Overton window.

Also I know you think it’s impossible. I don’t care about “think” though.

I want to know where deflation is “offered at impossible“.

Deflation doesn’t have to be likely for a bet on it to be profitable. And it’s certainly nowhere near impossible — this is a rich country with wealth concentration (rich people have low MPC), declining birth rate, and an NVDA market cap says robots will have lots more high paying jobs, and an incoming government promises lower spending (although this doesn’t translate to a smaller deficit if the tax receipts fall by even more).

There were plenty of responses.

(Unsurprisingly and for good reason, the most common answer was calls on treasuries or nitroglycerine like 30 year zeros.)

After I posed the question, I thought I’d follow up with a meta-trading lesson that governed how I thought about execution as a discretionary trader. It’s more relevant for professional trading where slippage is a larger concern but I expect anyone can at least benefit from hearing about it.

Laying in the weeds

Right now the market optimism thermometer is Sahara hot.

I charted SPX earnings using data from Gurufocus:

SPX earnings are up 48% in 5 years from 9/19 to 9/24 or ~8% per year

SPX total return over that period is 110% or 16% per year so multiple expansion has been riding shotgun 1-for-1 with earnings.

And now for 2025, forward earnings expectations are expected to grow 16% after being fairly flat from late 2021 until late 2023. Forward p/e has actually dipped despite SPX at all-time highs because of the animal spirits baked into the denominator.

I’m just using this as an example of divining sentiment. You could use option surfaces, COT reports, the “is my aunt or Uber driver talking about investments” indicator to get a pulse. (See Staring At The Window for an example of thumb-in-the-air vibe detection).

Your vibe detector gives a little elbow nudge, “hey knuckle-dragger, pay attention for a sec, it would make sense that some state of the future is being heavily discounted or left for dead.”

And so you start thinking along the lines of the tweet I opened with. What’s hated? What’s offered at zero? What’s being extrapolated to where only disappointment is possible?

[The most popular post I’ve written is once again relevant: Why Investing Feels Like Astrology]

If you are in a professional seat, you have time. You’re not gonna top-tick it anyway. Relish the complacency. The FOMO. It’s the yang to the yin and why you are able to get the other side. You should toe in and hope to lose while your position is small, because every bad mark is spring-loading energy for Newton’s 3rd Law,

You don’t go lifting and hitting. You don’t aggress. You lay in the weeds. Your waiting for flow that opposes your idea.

But you also want to understand “why”.

You wonder, is there some dumb structured product flow out there whose greeks need to be recycled into listed and happen to match what I’m looking for?

Is the driver of that flow some easy-to-package message about how inflation is here to stay so convince the clients to basically sell the deflation option for free.

Classic Wall St momo herding. Package a trend as a cornerstone allocation. Commodity futures for the long run right? (Nobody talked about roll return in 2004 and it’s all anyone talked about a decade later).

Ride the narrative to sell product because the narrative “makes sense”.

While the vampires seduce the consultants and investment committees you search the conference room trash bin for glossy marketing literature. What product are they hawking now? It probably spits off a ton of greeks that are hated, contrarian, and most importantly — cheap.

So you lay in the weeds with your little axe to own that which nobody wants. You get edge on the price because it was “sold”, you didn’t have to cross the market. As a discretionary trader looking for long shots you generally don’t wanna go around overpaying for lotto tickets. Instead you wait for handsome Oxford grads with accents to convince everyone that the lotto ticket is worthless. The prepared responder vs the enthusiastic aggressor.

And the really fun thing about greeks is now someone has the other side. You don’t just want your low probability idea play out — you want someone in pain on the receiving end. It might not be your direct counterparty but it could be a part of the ecosystem that is implicitly short that option whose clamoring exacerbates the problem. When unexpected things happen, something somewhere breaks.

(I may be showing a bit too much of my commodity roots but my model for those markets is — boring, business as usual until a cowboy shows up. It’s a zero-sum game so the other big players who’ve been around for while see the cowboy pyramiding and winning. And so the funds lock arms — time to run the new guy in. Oh the margin requirements changed overnight, never saw that coming did ya cowboy.)

When the crowded side starts to realize that what was 95% true is only 90% true. They sold something at 5% that’s now worth 10%.

Then you get a little mutual reinforcement…narrative can follow price too. As they need to cover the Overton window is also moving against them. It’s invisible but visceral at the same time.

I know I want the “long where it ain’t” option. The option with volga. Because that “it’ll never get there option”, the one nobody wanted, is now the one you can’t touch and that feeds on itself.

One last thing…

Noticed this yesterday:

Better than T-bills but gotta pay state tax.

[Heard those rates have actually come down too! The crypto peeps tell me the cash/futures arb is insane right now so this is presumably a trickle down to any levered long on BTC, although I’m not sure how fat the margin requirement is on the short IBIT put would be if you were just long the synthetic future.]

Even simple SPY cash/futures arbs are fat.

I’ll re-tell some market history that I remember hearing. Hedge funds did well avoiding the dot-com crash. If you weren’t mandated to be long stocks at extreme valuation you could hide out in 5%+ treasuries. Today with P/Es where they are, the forward implied returns on stocks look pretty awful compared the risk/reward of these simple arbs.

I get the excitement. Deregulation, lower taxes, AI, all that. But I also remember the fiber bubble of the late 90s. The longs weren’t wrong — laying cable across the ocean was gonna change the world. But the competition was fierce and changing the world didn’t mean “earn a return”. shale changed the world. And we got a bunch of consumer surplus because it’s a COMMODITY. AI is amazingly useful. But what if it’s a commodity. My guess based on auction-clearing prices being set by the most optimistic bid —OpenAI, Anthropic, and a host of big companies are in a money-incineration competition. But we’re all gonna be better off for it. No reason to double down on the benefits in your portfolio where the eventuality of the benefit is least reliable.

Personal portfolio thoughts

My equity allocation is on the low end of the range I manage in it as I’ve been trimming in the 2nd half of 2024. Also poking around for asymmetric bets of the wide strangle variety. Basically replacing some length with soft upside deltas as blow-off top insurance plus some downside bullets.

One thing I find tricky is that I suspect that we are going to stay in a low correlation regime absent a large sell-off as I suspect the incoming administration will create all kinds of upside and downside headline risk for single names. But implied correlations are already low which means single-stock vols are relatively high. So this particular view is baked into market already. Means if I’m buying it’s with one hand not two.

In alignment with the trimming, my cash position is on the high end. Speaking of cash, some personal convo on real estate…

One of the reasons we are holding extra cash is we have been house-hunting more actively instead of just passively browsing. Our lease ends in August at which point it will have been 5 years. The landlords have indicated they might want their house back although we are still crossing fingers that they won’t.

Cash is a valuable option when buying a home. Especially here in the Bay Area. In fact the option is probably quantifiable. When we sold our house in 2020, the winning bid was 10% higher than the cash bid behind it and well-thru our asking price. Why?

Because the buyers were contingent on selling their home and they were getting a mortgage so they knew they had no chance if they didn’t dangle a sum that enticed us to accept the risk of their offer vs a clean cash offer.

When we bid (we have bid 3x this past year) we offer all cash and quick close times.

[This also helped us win the house in TX against 4 other bidders…which we ended up flipping a year later. See Reasoning Through a Housing Trade Out Loud]

We are never the best bid, but the cash offer is useful because it gets us a callback and into a situation where we have more info than the initial approach which is our objective. So we can probe.

Sellers don’t like closing uncertainty. They are wary of bidders drawing them into a contract with contingencies then trying to re-trade. In fact, you have no chance of buying here if you don’t waive inspection contingencies. Bring your contractor friend to check it out before you bid.

I guess this cash thing is becoming more common too. In the past year, we’ve given cash to 2 separate family members in other regions so they could win their bids. They financed after closing to pay us back.

[Random: the family we sold our TX house to financed the property with a loan against their stock portfolio. Morgan Stanley sent an appraiser!]

Anyway, back to our recent bids this year. We whiffed on all of them. And that’s fine — that’s a feature of our strategy. Mostly. Missing on the last one hurt. In hindsight, I still can’t tell what the right play was. I’ll walk you through it.

We made a cash offer about 2% higher than the asking price which seemed a touch low. We asked for a 3 day inspection period. At this point the game is hang around long enough to find out if the house is attainable at a price we are comfortable with and then sharpen our pencils if we get to the next round.

There were 7 offers. Ours was middle of the pack but attractive enough from a “they will probably close point of view” so we were one of 5 offers that received a counter.

They asked for another 3% and to waive the inspection period. That morning we brought our contractor and architect friends to see if we could do what we wanted to the house. They gave the green light.

(Having another 9 months on our lease, this was a great opportunity to scoop a smaller house put another 50% into it over the course of a year and end up what we want for an all-in price that we are comfortable with — I’ve been looking long enough to know those stars rarely align which is why this was the first house I started to feel excited about)

We accepted the counteroffer requirements.

That night Yinh and I were going out on a dinner date. I was excited that it could be a celebratory one.

I was wrong.

We were outbid by another 1.5% and they weren’t going to do more rounds. The final bid was also cash.

We understood our choices when presented with the counteroffer:

1. Accept
2. Counter with lower offer than what they ask for
3. Be aggressive and counter even higher

The winners chose option 3.

The tricky thing about the final price is it reminds me of the paradox from The Most Underappreciated Aspect of Trading:

When you look at a price, you wish you could have traded it as counterparty to the aggressing order.

Now for the anti-climax.

It’s a fake idea because had you been on the price, the price would have been different. You would have affected it. This idea is like a painting to be viewed from afar. It’s not of any practical value, um, other than the fact that it holds the deepest insight in all of trading.

Knowing the final price, gun to my head, I would pay it. But if I tried to pay that in real-time I probably wouldn’t have gotten filled and instead hit our top (at this point we are 8% through the asking price which is close to but probably still a touch short of what the highest price I could have imagined the house going for).

Pretty unsatisfying.

If I knew we could rent forever I’d just do that. I have no interest in signing up for renovations, $12k/yr home insurance bills, maintenance (or the cost of outsourcing it), and the forgone returns on the cost premium of buying vs renting.

But renting is roulette in many ways. We won to it for the past 5 years but we know we got lucky so it’s hard to get to down about the recent miss.

And yet…

I become more Georgist by the day.

A moontower.ai user asked about oil volatility and correlation in the context of WTI and Brent crude. I did the editorial equivalent of showing him a cool scar:

Let me take these in turn.

USO is relatively illiquid these days relative to the futures options. It used to be more liquid. I spent the better part of a decade relative value trading it vs the futures options including doing create/redeems (I was constantly at OCC position limits — which have a horrible one-size-fits-all application).

Long-dated USO options are very interesting instruments because they are effectively long-dated options on a rolling CL1 contract. This is very different from say a 12-month futures option that references a less volatile CL12 contract.

This difference is why you can relative value trade it, but it’s a complicated model (actually I think a good interview question for a trader or quant is to come up with a model for this conceptually). It’s nice that it offers you an option chain on CL1 while the futures options don’t.

As far as Brent or for that matter heating oil and rbob which you didn’t ask about, the correlations to WTI change periodically when the fundamental details become bottlenecks in their respective markets. Refineries can’t just easily switch their slate between product grades so you can get over/under supply idiosyncracies. There’s an active “arb option” market which is options struck on the spread between WTI and Brent.

Further complicating matters is that Brent and WTI futures and futures options for a given month do not have the same expiries so when you do relative vol trades between them you end up with these residual calendar risks (brent options expiring a week earlier than WTI!)

There was a period of time where this is all I traded so to download all there is to say on this is impossible. You can make a career out of doing nothing else. If you like bloodshot eyes and your hair to be drained of youthful pigment of course.

This past Wednesday I did an AMA with Kris Longmore’s RobotWealth community. Kris’ work and general way of being is a personal inspiration. I’m a big fan.

(His bootcamp is my #1 recommended course for retail trading because it’s grounded in both the practicality of trading but also in the conceptual — what is edge, where to find it and why it might exist)

This is all to say it was quite an honor to nerd out on his channel 🤓

​📽️Watch the replay of our conversation here.

Just a sampling of topics we discussed:

• Some differences between professional and retail trading
• How a retail trading operation can be set up to align with your life
• Good options trades and where to find them
• How important is modeling time decay?
• How important is backtesting for options strategies?

2 ideas that received some extra emphasis:

1) Traders are searching for contradiction not prediction

This is a callback to Measurement Not Prediction which explains why trading rests on “seeing the present clearly” as opposed to playing Nostradamus. The distinction might sound abstract or subtle. This section of a thread I wrote this week is a concrete example:

2) On timing vol

The topic of timing vol came up. And I shared something I suspect people might find surprising.

I had no edge in timing vol. In fact, I don’t think most professional vol traders have any edge in this. In other words, their edge doesn’t look anything like “vol in general is cheap here, let’s load up”. I almost always regret drawing lines in the sand about getting net long or short a bunch of vega. Did I tend to be leaning long vol when it was cheap and vice versa? Sure, but I was usually long or short for a considerable amount of time before it bottomed or peaked too, because markets love to stretch like they’re double-jointed ballerinas before reverting.

After getting humbled by a timing opinion gone awry, I always centered myself by going to back to basics. What does that mean?

The most basic decision in a trader’s arsenal, their reliable fastball so-to-speak is some version of:

“I’m buying this for X, because that is Y bid”

“I’m buying 1-month APPL straddles for X vol, because 3-month QQQ puts are Y bid”.

When you get away from decisions that take that grammatical form you are in the realm of “I’m buying this because the line went down”.

When you feel enough pain to accept that you did something wrong you will usually find this subtle switch in decision logic is the source. It stings the ego because re-focusing on the basics is admitting that you haven’t transcended the grind to become some market maven who just knows when something is about to turn.

(I think all traders subconsciously expect that their 10,000 or even 20,000 hours of practice will unlock that ability. These back-to-basic moments, if you are lucky enough to overcome your pride and negative p/l, to rediscover are humble reminders that markets are learning just like you are so the value of the 10,000 hours isn’t exerted on your ability to beat them, but instead on the practice of process so you have a chance of keeping up. There’s no “best”, only “next”.)

On Thursday I published a post called laying in the weeds, an expression I used regularly. Whether it was getting ready to pounce on an offer that accumulates suddenly, sniping with electronic eyes while streaming, or just keeping your mouth shut while others leak info, the lingo fits. It’s ultimately about execution — how do I get the price and size I want?

We can use that background to riff about execution which is easy but dangerous to develop lazy habits about (like laying in the weeds this is more of a professional topic because of the imperative to reduce slippage)

Here’s a common scenario in the voice option market.

Assumptions:

• An option is worth $.90
• A broker is bidding $.92 for 10,000 lots
• You and 3 additional market makers are offering at $.94. You know this because the broker, who we will assume is honest, relayed the full picture.

The case of simple 2 choice scenario tree

1. You hit the bid and get all 10,000. Expected profit = $.02 x 100 x 10,000 = $20,000
2. Nobody breaks rank, the offer is lifted with 4 market makers getting equal allocation. Expected profit = $.04 x 100 x 2,500 = $10,000

Seems like you should hit the bid. Except for that, if you do, next time all the offers are more aggressive. Tit-for-tat mutually assured destruction.

You get an interesting result if you unravel the game theory. Assuming none of the market makers are particularly axed in the option, and they all have a similar hurdle rate on how much capital they are willing to deploy for some amount of risk/reward you end up with a stable equilibrium that looks similar to what pre-communicated collusion would have resulted in.

[Aside from the dinosaur era: The way to get a lightly capitalized newcomer to your options pit to give up and go home is demoralizing attrition — trade everything for fair until they go away. I even remember days as a clerk on the specialist post where the boss would tell me to offer something so cheap on our exchange to embarrass a specialist on another exchange who ripped off the buyer at a higher price. The away specialist could lift our lower offer and lock-in a profit but they wouldn’t want to because by forcing the print they would make the customer feel bad about their fill. And if they did lock in the profit by trading with us, we were more than happy to incinerate money to make the customer think twice about routing around us in the future. I can remember the boss, crossed arms, still as Vader: “Keep offering. Filled? Reload.”]

More than 2 choices

Realistically, there are many scenarios. The option could have traded $.92 or $.93 with similar splits even if the first trader who hits the bid thinks she is getting the full bid size, but the broker being a diplomat who needs to deal with each of the market-makers daily decides to split it 4 ways anyway at the lower price. This result is common and explains why it doesn’t make sense to break price. They are unlikely to get the benefit unless they clarify with the broker that they are only going to hit the bid if they get full size (the broker weighs whether they should box the other 3 out and consequently piss them off).

How this plays out depends on your business relationship to the broker both in terms of how much you pay them and how useful you are in making fast, tight markets. When I was a local on the NYMEX I didn’t trade huge size but I was super-responsive so I could get those 25 and 50 lot berries. Those tight markets were also useful to the brokers who could use them “cuff” a related market or fish for business. At the fund, my value in the ecosystem was size, so I had leverage in setting the price of a larger order (maybe I could convince the broker to make the splits 4k, 4k, 1k, and 1k where I’m one of the larger allocations) but didn’t get the small layup orders.

We can get bogged down in scenarios forever, but the point is that this little game is being played all day. In the voice market and the electronic algo logic of sophisticated market-makers. If I divide all my profits by how many contracts I traded I end up somewhere in the penny ballpark. That’s the margin. That’s the difference between tossing coins for fair and a highly profitable business. It also means, that without a lot of reps it’s hard to tell if you have an edge.

Let’s do another example of cat-and-mouse.

An option is quoted $.21-$.23

You think it’s worth $.25

What do you do?

The correct answer is “it depends”. The first step to building a model for solving this execution problem is to identify the dependencies.

A few off the top of my head:

• If I lift, I make $.02 of edge on Y volume
• If I join the $.21 bid, what’s the probability I get hit (therefore making $.04) and how much volume would I get? Handicapping this depends on if the matching engine is time priority or pro-rata as well as if there is any priority that derives from my designation (customer, pro customer, professional, and more)
• If I bid $.22 and get hit I make $.03. But would that bid cause someone else to lift $.23s? I need some map of what other market observers think an option is worth.

Broadly, I need some priors about the distribution of what others think this option is worth based on existing bids/offers, the trades that have happened, and trades that have not happened (ie bids/offers that have been displayed but nobody cared on).

You could start with a simple equation.

P(getting hit) * volume when I get hit * edge to the bid_price= volume when I lift * edge to the ask_price

You can solve for P(getting hit) to find a breakeven for how often you’d need to get hit to compensate you for not lifting.

While this is stylized and simple it’s not an attempt to point to some abstract HFT optimization problem. It’s a reminder that reflecting on your execution techniques sharpens your thinking about trading, conditional edge, adverse selection. It’s less important for retail or if you don’t transact often, but for professionals and asset managers it is justifiably top-of-mind.

“A sale is made on EVERY call”

Remember Ben Affleck in Boiler Room:

And there is no such thing as a no-sale call. A sale is made on every call you make. Either you sell the client some stock or he sells you a reason he can’t. Either way a sale is made, the only question is who is gonna close? You or him?

Every time you trade with a broker someone gets the best of it. If you consistently get allocations for 60 contracts when you should have gotten 70 you are destroying 14% of your annual profit. Specialists and DMMs had rules about allocation quantities but there were also unwritten rules. You were expected to fight for even a single contract that you are “entitled” to and advocate forcefully for your interests constantly. The pugilism was built right into the training and culture. The stories of ruthlessness were culturally rewarded. As a junior trader, sticking it to a competitor or getting into a nose-to-nose screaming battle with a broker just to define boundaries was a way to earn stripes.

[This is not my native personality but you adopt what it takes. After all, the only point of this job is to make as much money as possible. Sure, the cost likely bore itself as chronic anxiety about work but only the most well-matched people get the luxury of getting paid and being comfortable. I don’t miss all the daily haggling but I did take it seriously since it was one of the most impactful contributions to profit for the reasons above.

One story I had brought to my attention in the past year — a PM who ran one of the large banks deriv desks reminisced about the AMEX when we were in the same pit. He’s a bit younger than me and apparently I made a big scene sticking up for him to a broker who tried to bully him in the pit. Nice to hear even though I don’t remember the exact incident. I do have a vague memory of lots of battles in that pit because it was a large crowd in a very liquid name.]

Final thoughts on this theme: if you manage a business that’s a game of inches, it’s good to periodically check-in and ask “are we clawing for those inches?”

Is everyone at the point-of-sale aware of what needs to be done or are we getting sloppy? Are we leaking info? Are we too nice? Would it pay to be squeakier? Are we paying the brokers we want to be paying? Are we paying the brokers the right amount?

Evergreen: