Corey Hofstein introduces the podcast and its focus on the human factor behind quantitative strategy.

Introduction to Flirting with Models Podcast

Introduction of Chris Abdul-Messiah, co-founder of MoonTower AI, and his background in market making and relative value trading.

Guest Introduction: Chris Abdul-Messiah

Discussion on the accelerated learning environment of the trading floor, the dynamics of competition and cooperation, and the unique opportunities for learning from market makers.

The Accelerated Learning Environment of the Trading Floor

Comparison of market making and relative value trading, the shift in perspective on what constitutes a good trade, and the challenges of transitioning to a warehousing mindset.

Transition from Market Making to Relative Value Trading

Exploration of optimizing P&L on a daily basis, the impact of unstructured data on value assessment, and the use of sparse data to identify trading opportunities.

Optimizing P&L and Data Influence in Discretionary Trading

Exploring the reasons for lower volatility in USO relative to futures options

Understanding USO Volatility

Analyzing the impact of embedded put options and the volatility of the USO portfolio

Risk Management and Portfolio Volatility

Comparing the volatility of USO portfolio with real futures and its impact on daily basis

Comparing Portfolio Volatility

Understanding the impact of deferred commodity futures and changes in portfolio composition on volatility

Exponential Volatility and Portfolio Composition

Exploring the risk management strategies of fund managers and their impact on portfolio volatility

Portfolio Volatility and Risk Management

Understanding the relationship between volatility and future contracts in breakout situations

Impact of Volatility on Future Contracts

Analyzing the impact of changing the composition of the portfolio to hold less volatile futures

Changing Portfolio Composition

Exploring the implications of bid side liquidity in the voice market and its impact on USO volatility

Understanding Bid Side Liquidity

Discussing the influence of large language models on discretionary and systematic trading

Technology and Discretionary Trading

Analyzing the challenges in data capture, particularly in broker interactions and counterfactual scenarios

Challenges in Data Capture

Exploring the influence of firm lineages on trading approaches and the distinction between flippers and warehousers

Trading Firms and Lineages

Discussing the evolution of trading concepts and the launch of Moontower.ai

Evolution of Trading Concepts

Introducing Moontower.ai as a software to help users make better auction trades and its progression

Introduction to Moontower.ai

Identifying the problem Moontower.ai solves for options traders and its target audience

The Problem Moontower.ai Solves

Exploring the use of a volatility lens to express stock opinions more efficiently

The Role of Volatility in Stock Trading

Analyzing the term structure and IV versus RV.

Analyzing XLK Volatility

Evaluating put options, at-the-money options, and skew.

Choosing Option Strategies

Analyzing the cheapness of out-of-the-money calls.

Identifying Cheap Call Options

Selecting the best option expression based on directional axis.

Expressing the Bet

Exploring the concept of put-call parity and its application.

Understanding Put-Call Parity

Recommendations for board games and their educational value.

Using Games for Learning

Enjoying the comedy of Nate Bargatze with family.

Passion for Nate Bargatze

- Corey Hofstein introduces his podcast, Flirting with Models, and his guest, Chris Abdelmessiah, co-founder of MoonTower AI
- Chris discusses his career trajectory, starting as a market maker and eventually moving into relative value trading and founding MoonTower AI
- They talk about the accelerated learning experience on the trading floor and the shift to electronic trading
- Chris emphasizes the cooperative and competitive dynamic on the trading floor, which he believes is lost in the electronic trading environment

- The speaker discusses the unique learning opportunities of trading on the floor, where traders can observe and learn from others in real time.
- They also talk about the differences between market making and running a relative value book, highlighting the shift from quick arbitrage trades to more long-term value-based trades.
- The speaker suggests that traders can reclaim the learning rate in the electronic era by being more outward and proactive in seeking out learning opportunities, such as through social media platforms like Twitter.

- The speaker discusses a trade they made selling out of the money puts and watching a colleague do a similar trade in Xerox for 10 times the profit
- They talk about the importance of knowing how the transaction game is played and understanding market maker thinking
- They discuss the impact of a mentor's question about optimizing daily P&L and the importance of not ignoring unstructured data in discretionary trading
- They provide an example of trading oil options and USO during a volatile market, highlighting the importance of understanding market dynamics and not just relying on structured data.

- The speaker discusses the reasons why the implied volatility of USO is lower than that of futures options
- They mention the limited liability structure of the ETF as a reason for the lower volatility
- They also discuss the impact of rolling to the next month on the volatility
- The conversation then shifts to the influence of large language models on discretionary trading, with the speaker acknowledging the trend towards closer alignment of discretionary and systematic trading
- The discussion ends with the influence of firm lineage on trading strategies, with examples of firms being "flippers" or "warehousers"

- The piece discusses the evolution of trading strategies and the shift from "flipping" to "warehousing" in the market.
- It also touches on the importance of lineage in hiring traders, especially in banks.
- The speaker then introduces the Moontower.ai project, a software designed to help users make better auction trades, and explains its origins and purpose.

- The piece discusses the use of options to express investing ideas, particularly in the context of vol trading.
- It emphasizes the importance of understanding the nuances of options trading and the potential challenges for at-home vol traders.
- The focus is on using a vol trader lens to choose the best options for expressing investment opinions, and the benefits of options in forcing discipline in decision-making.
- The piece also highlights the software's ability to compress the decision space by focusing on four main dimensions: straddles, vertical spreads, strangles, and time spreads.
- It provides an example of how a volatility lens can be helpful in expressing a cautious investment opinion in a high market.

- The speaker discusses using options to express a stock opinion
- They analyze the term structure and the relationship between implied volatility and realized volatility
- They consider buying long-dated options on XLK due to low volatility
- They also consider buying cheap out-of-the-money calls and selling the stock as an alternative strategy
- The speaker also shares their favorite board games and recommends poker and engine builder games for learning trading concepts

- Corey Hofstein introduces his podcast, Flirting with Models, and his guest, Chris Abdelmessiah, co-founder of MoonTower AI
- Chris discusses his career trajectory, starting as a market maker and eventually moving into relative value trading and founding MoonTower AI
- They talk about the accelerated learning experience on the trading floor and the shift to electronic trading
- Chris emphasizes the cooperative and competitive dynamic on the trading floor, which he believes is lost in the electronic trading environment
- The speaker discusses the unique learning opportunities of trading on the floor, where traders can observe and learn from others in real time.
- They also talk about the differences between market making and running a relative value book, highlighting the shift from quick arbitrage trades to more long-term value-based trades.
- The speaker suggests that traders can reclaim the learning rate in the electronic era by being more outward and proactive in seeking out learning opportunities, such as through social media platforms like Twitter.
- The speaker discusses a trade they made selling out of the money puts and watching a colleague do a similar trade in Xerox for 10 times the profit
- They talk about the importance of knowing how the transaction game is played and understanding market maker thinking
- They discuss the impact of a mentor's question about optimizing daily P&L and the importance of not ignoring unstructured data in discretionary trading
- They provide an example of trading oil options and USO during a volatile market, highlighting the importance of understanding market dynamics and not just relying on structured data.
- The speaker discusses the reasons why the implied volatility of USO is lower than that of futures options
- They mention the limited liability structure of the ETF as a reason for the lower volatility
- They also discuss the impact of rolling to the next month on the volatility
- The conversation then shifts to the influence of large language models on discretionary trading, with the speaker acknowledging the trend towards closer alignment of discretionary and systematic trading
- The discussion ends with the influence of firm lineage on trading strategies, with examples of firms being "flippers" or "warehousers"
- The piece discusses the evolution of trading strategies and the shift from "flipping" to "warehousing" in the market.
- It also touches on the importance of lineage in hiring traders, especially in banks.
- The speaker then introduces the Moontower.ai project, a software designed to help users make better auction trades, and explains its origins and purpose.
- The piece discusses the use of options to express investing ideas, particularly in the context of vol trading.
- It emphasizes the importance of understanding the nuances of options trading and the potential challenges for at-home vol traders.
- The focus is on using a vol trader lens to choose the best options for expressing investment opinions, and the benefits of options in forcing discipline in decision-making.
- The piece also highlights the software's ability to compress the decision space by focusing on four main dimensions: straddles, vertical spreads, strangles, and time spreads.
- It provides an example of how a volatility lens can be helpful in expressing a cautious investment opinion in a high market.
- The speaker discusses using options to express a stock opinion
- They analyze the term structure and the relationship between implied volatility and realized volatility
- They consider buying long-dated options on XLK due to low volatility
- They also consider buying cheap out-of-the-money calls and selling the stock as an alternative strategy
- The speaker also shares their favorite board games and recommends poker and engine builder games for learning trading concepts"""

- The speaker discusses the feeling of compounding and option Greeks in certain games
- He mentions a game called Fantastic Factories that he enjoys playing with his kids
- He is passionate about clean comedian Nate Bargatze and enjoys watching his stand-up with his kids
- The speaker is also passionate about his work with Moon Tower AI and improving his writing skills
- He feels that his new perspective on the market has allowed him to explore new ideas in his writing and trading

The speaker discusses compounding and option Greeks in games, enjoys playing Fantastic Factories and watching Nate Bargatze's stand-up with his kids, is passionate about his work with Moon Tower AI, and feels his new perspective on the market has improved his writing and trading ideas.

My guest in this episode is Kris Abdelmessih, co-founder of moontower.ai.

Kris began his career at SIG, where he worked as a market maker in several different option pits, before moving to Parallax where he ran a relative value commodities volatility book.  For the last five years, Kris has been writing on his blog Party at the Moontower, which is one of my favorite reads for all things probability, payoff space, trading, optionality, and seeing the world through a volatility lens.

Kris is a passionate educator, so it should come as no surprise that learning is a key thread throughout this entire episode.  Kris discusses how learning is accelerated in the pits and how we can think about replicating it in electronic space.  Kris discusses what he had to unlearn and relearn in his move from market making to relative value trading.  He also shares his thoughts about how firm lineage influences how you learn to trade markets.

Finally, we discuss Kris’s newest venture, moontower.ai, which seeks to provide a “volatility lens” to opinionated traders to help them better express their bets in option space.

There is a lot of experience to unpack in this one.  

I hope you enjoy my conversation with Kris Abdelmessih.

I'm Corey Hofstein and this is Flirting with Models, the podcast that pulls back the curtain to discover the human factor behind the quantitative strategy.

Corey Hofstein is the co-founder and chief investment officer of Newfound Research.

Due to industry regulations, he will not discuss any of Newfound Research's funds on this podcast.

All opinions expressed by podcast participants are solely their own opinion and do not reflect the opinion of Newfound Research.

This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions.

Clients of Newfound Research may maintain positions and securities discussed in this podcast.

For more information, visit thinknewfound.com.

My guest in this episode is Chris Abdul-Messiah, co-founder of MoonTower AI.

Chris began His career at SIG, where he worked as a market maker in several different option pits, before moving to Parallax, where he ran a relative value commodities volatility book.

For the last 5 years, Chris has been writing on his blog Party at the Moon Tower, which is 1 of My favorite reads for all things probability, payoff space, trading, optionality, and seeing the world through a volatility lens.

So it should come as no surprise that learning is a key thread throughout this entire episode.

Chris discusses how learning is accelerated in the option pits and how we can think about replicating that in electronic space.

He discusses what he had to unlearn and relearn in his move from market making to relative value trading, and Chris shares his thoughts about how firm lineage influences how you learn to trade markets.

Finally, we discuss Chris's newest venture, MoonTower AI, which seeks to provide a volatility lens to opinionated traders to help them better express their bets in option space.

There is a lot of experience to unpack in this 1.

I hope you enjoy my conversation with Chris Abdelmessiah.

Moon Tower Meta himself, long time fan of the blog and the newsletter.

I think it might be my most recommended newsletter.

I was looking earlier as to how many times I've recommended articles you've written.

You are constantly churning out great think pieces on probability and investing, particularly in the option space.

So very excited to have you here with me today.

I'm such a fan of you, the way you carry yourself, your honesty, the way you balance being lighthearted, but serious.

And your writing was massively inspirational to my own writing.

And the way you think about trading and investing is just rare and very kindred.

You're the smarter version of everything I want to be.

It's funny, I almost feel like today is like, Hey, we're taking a break from our regular episodes with all these geniuses to have to bring out a monkey on a unicycle, but I'm just so stoked to be here.

Well, I feel like I'm gonna have to edit most of that out, but I appreciate the kind words.

And I think at the end of this episode, nobody will be thinking of you as a monkey on a unicycle.

And certainly nobody who's read your writing would think of you that way.

But for those who haven't read your writing, for those who maybe aren't as active on FinTwit, don't know who you are, can you start us off with the background?

Cause you have had a bit of a trajectory to your career.

You've stayed within the vol space but had a couple different cuts of how you've thought about vol.

So maybe we can start at the beginning of your time on the floor and take us forward to where you are today.

I was kind of a traditional entry into the business.

I had an idea that I wanted to go into finance and trading specifically, but I was walking around a career fair and there was a booth with a guy that had some dice and a deck of cards And there was nobody at the booth because everybody in their ill-fitting suits was all surrounding the bankers.

Everybody wanted to be, I don't know, Frank Quattrone or whatever.

And this guy just kind of looked at me wandering around like a lost fawn and said, Hey, do you like games?

And there was nobody else at the booth and nobody knew who SIG was.

So I went over there, did a little interview, didn't do so great.

And then I asked them, I said, I don't feel like I did very good in this interview, but I liked these questions that you asked me and I like this stuff.

What can I do to get better at this and he recommended a book to me called getting the best of it by David Sklansky and of course, I went and got it and read it and I to my surprise got a call back for a second interview?

And all the questions were straight out of the beginning of that book.

So I guess he liked me because he wanted me to get through.

So I end up At SIG, got into their trainer program.

I spent 6 to 9 months clerking for various pits, clerking in a Spiders ETF.

ETFs were in relatively new product at the time.

The king of ETFs, Reggie Brown was my boss.

So I was clerking in spiders and then I did index options, equity options, all that other clerking, all that went through their training program, lived in Ballackinwood, Pennsylvania for 3 months, mock trading theory, all this stuff.

Honestly, a lot of the stuff that I write about was super inspired by what we learned, all those basics.

And then after that, was a market maker on the Amex floor in equity options for a couple of years.

And then I was a specialist in ETFs for almost a year.

And then after that, I was asked to go start the oil options trading business on the NYMEX for SIG.

And if I remember correctly, I had failed twice before.

So it was the proposition was like, Hey, go over there, see if we can figure it out.

So it's a great setup for, I was like high upside, low downside situation.

So I went over there, took us about 6 months to figure it out.

This time we ended up being very successful and there's a lot component to it.

We were going there right at the transition of the markets going from, you know, When I stepped into the pit, we was, as we say, trading on fingers, flashing our hedges to the futures pit.

Markets were not very electronic at the time.

There was a thing called, I think it was called Access or something.

There was electronic markets at night, but it was open outcry, hand signals and all that.

But we were coming from a world where we were used to trading electronically.

So basically we were early adopters of using technology over there and built that business that went well traded.

And then after 3 years of doing that, I left and I went over to trading.

So it was basically like put up some of my own money and then for almost 4 years built my own little market making operation.

And I'll talk more about that later, but that we did spend 4 years learning to trade a lot of different commodity products, futures options.

And then I went to, after that Parallax, which is a big hedge fund in San Francisco.

Their traditional business is relative value equity vol trading, also has a bit of a SIG lineage and they asked me if I'd move out to California and build a commodity options trading business for them.

So I went out there, I spent almost a decade with Parallax and then in 2021 decided to leave the Daily Grind and since then I started writing about 5 years ago.

So I was at Parallax when I had started writing online and then by 2021 decided that I didn't want to sit in front of a screen all day anymore.

So I left, now I write, I teach, and my newest project is an options trading software that we launched a couple months

I think it's clear to anyone who has read your writing that you think a lot about thinking and you think a lot about learning.

And 1 of the things you mentioned to me in our pre-call is that you thought the trading floor provided an environment where your learning rate can really be accelerated.

Your learning rate about the market, your learning rate about trading, and something that potentially has been lost as we move into a more pure electronic world.

I'm curious why you think that that learning rate was so accelerated in the floor and what exactly is getting lost as we all go electronic?

This is a fun topic for me because I was very fond of the floor because it was very well suited to how I learn which is the key thing on the floor that feels very different than today is the who.

Because when you are on the floor, you are mixed in there with all these competing firms as well as all the people from your own firm.

And there's a sort of frenemy dynamic where you show up to work every day and you can see what your competitors are doing, but they're competitors right now, but tomorrow they might be employees or You might be asking them for a job.

So it is a very cooperative but combative ecosystem at the same time.

It's very unique in that way Imagine everybody's sitting upstairs today on their screens trading.

Imagine if you just all got in a room and were trading, what that dynamic could feel like.

So on the floor, your learning rate would be very high because you had this amazing and unique opportunity to try to reverse engineer what people were doing.

So for example, a broker might come to the pit, let's say an option's worth $5, and a broker comes into the pit and says, hey, I'll sell 100 of these at 495.

And then everybody in the pit's gonna go buy them, buy them, buy them.

But what happens if that broker comes into the pit and says I'll sell these at 5 dollars in 1 market maker Lifts it and then that market maker says I'll buy more there So what you have is this new piece of information.

Why is this 1 market maker want to buy these options?

But the thing is you've seen this market maker, you know what firm he works for.

Most of the people in the pit, maybe they don't have a headset, but This guy has a headset on.

So in other words, he's seeing something that you're not.

So what will happen is maybe 3 minutes later, all of a sudden you see that there's all these bids.

So what happened is that market maker had an upstairs trader that saw something trade away that knows that falls higher, but not everybody else got to see that.

So what you're doing is you're weighting the credibility of the actors, like subconsciously as they make decisions.

And from there, that is guiding your own decision process So there's other examples of this like you might see you watching how people lean markets So you might think that options worth 5 dollars, but a big market maker who's fast is the first person to yell out that order gets quoted and that market maker is $495.

That market maker is heavily betting that that order is a seller.

So by watching smart market makers or market makers that work for firms that you know see a lot, you can figure out, oh, they must have a good feeling for who this other side is.

They're tracking what's going on and you learn to do that as well.

So another example is you're walking by a pit that seems to do no volume.

There doesn't seem to be a whole lot of options volume in that pit.

It's a tumbleweed, but there's a very smart trader standing in that pit.

So you're like, there must be money over there.

So why would that firm put a strong trader in that pit if it really was a wasteland?

So you can kind of figure out what tables you want to play at just from walking around the floor and paying attention.

And also just the way information flows when you're down there.

Something could be ripping much higher and is it a short squeeze, is it not?

Well, you can talk to brokers, you can talk to other traders.

And again, you're weighting everybody's input by how credible you think they are.

And that credibility score, that informal credibility score you have is built up over watching repeated interactions with these people all the time.

So super unique environment for learning very quickly.

As someone who is super passionate about learning and teaching, how do you think that learning rate can be reclaimed in an electronic era?

The first of all, I want to back up for a second and just say that I'm saying that something is lost, but that's because of my own skill set where I'm a flesh-and-blood humanoid.

I want to hear how they bid and how they offer.

And so for me, something feels like it's lost.

When I think about it, electronic markets offer people ways to disguise their order.

What's happening is you are getting a lot of information from lots of very, very small transactions and it's big data.

So it's almost like the skill set is converged with sort of like big tech doing ad targeting.

It was not the world I grew up in in trading.

So I think that there are people that can have a very high learning rate if they are attuned to those methods today.

But as far as reclaiming the learning rate, I think you can do that by cultivating like Twitter is amazing.

You can go online and if you have good taste and develop taste into who's a real G versus who's a LARPR, you can figure out who you can learn from.

And even though you're not on the floor and you have all these opportunities for serendipitous meetings with other people because they just happen to be right next to you, you have to put more effort into it and I think traders can reclaim some of that learning rate by putting themselves out there more.

I think it's a good idea to sort of like live outwardly as a trader more so than the typical trader believes.

There's a bit of a lone wolf introversion that does attract people to trading.

And I was like that too, to some degree and over time have sort of like opened up more and I found that traders as they've gotten older have told me the same thing that by opening up more it helped them to adapt and learn quicker.

So I think that that's the way you reclaim it is just sort of being a little bit more outward.

And it's as always this game of like, you got to give to get, but obviously nobody wants to give information that's super valuable to what they're doing.

So there's a bit of a game there and you got to play that game.

But I think that's the way you reclaim that learning rate.

After SIG, you moved to Parallax, as you mentioned, where you went from being a market maker to running this relative value book in the commodity space.

Can you talk a little bit about the similarities and the differences between market making and running a relative value book?

What skills translate, what don't, and maybe what was sort of the steepest part of the uptake curve for you?

So the first thing is your definition of what's a good trade evolves.

So I remember in training distinctly, 1 of the teachers at SIG had very succinctly defined a good trade as if you buy something and it's bid there after you bought it, that's a good trade.

And what's native to that statement is that you have a free roll.

If I don't like it, I can scratch it by turning around and selling to the person next to me.

So you have to know where you are in the pecking order.

You have to be fast and you also have to be aware of, am I in a situation where I'm going to know that this trade is going to go south before other people do.

See all Flirting with Models transcripts on Youtube

Kris Abdelmessih - Life Through a Volatility Lens (S7E10)