Dan McMurtrie with Howard Lindzon

Link: https://howardlindzon.com/dan-mcmurtrie-founder-of-tyro-partners-llc-joins-me-on-panic-with-friends-to-discuss-information-overload-and-behavioral-investing-ep-151/

About Dan: Dan McMurtrie is a 28-year-old founder, portfolio manager, and Twitter phenom more commonly known to his nearly 60,000 followers as @SuperMugatu. He’s an insanely funny, original and inspiring person who knows a lot about social media, maintaining an audience and the behavioral side of investing. Dan’s New York-based hedge fund, Tyro Partners LLC, focuses on trends and supply chains driving technology, healthcare, industrial, and consumer markets.


An insight common to making money and making people laugh

Something everybody knows it to be true but no one’s speaking up about it being true

On people struggling to make sense of the world

It’s a paradigm shift to a networked world…going from one-to-many media to many-to-many media, and having cycle times for communications go down to sub-second, meaning the number of cycles, the number of communications is going to infinity really fast. That’s leading to all these weird neurological effects because your brain is not used to having hundreds or thousands of opinions scattered at it. Your brain is used to thinking that an opinion from somebody means something, which is super wrong. And so I think this knee-jerk reaction to dismiss things that well-trained investors in the past three years have developed is actually the biggest weakness you can have, because everything now is like this kind of meta game of “it looks absurd but it’s actually not. Actually you shouting that it’s absurd, is what’s going to give it the audience that makes it real!”

The output of our quickly networked world is disrupting seasoned investors’ heuristics

It’s scaring the shit out of people. They’re looking at this and they’ve been around the block a few times, and their experience is betraying them because they’re seeing things that are so behaviourally horrifying to them that they don’t realize that they’re then becoming just instinctive and knee jerk, And they’re not running basic numbers [and asking themselves] “Is this a material amount of money?”.

[consider the lazy argument against Dogecoin that it has unlimited supply]

Is it actually unlimited supply? I’m like, “Yes, but is it unlimited supply forever. No. There’s a more nuanced point  that it’s not unlimited supply at any individual point in time, there’s a rate limiter on time with those points, which is why this pump thing is working. 

An example of how brains get hacked in this networked world, orchestrated by the guy that oversaw such hacking at Facebook

There’s a technique that I think Chamath does that I call “the 90% rule”. What you do is you say something that’s technically accurate, but like maybe 10% off of how a professional would say it, or maybe it’s 10% not correct, but it’s in the spirit of correct. For example, Chamath said something on Twitter — that he was up 120 basis points this year, and the market’s up 30 basis points, so he said he’s outperforming by like 300% or 400% or something. [Everyone jumped on Chamath for this], but do you actually think that Chamath doesn’t understand basic math. Do you think the guy who led monetization of mobile advertising for Facebook doesn’t understand the way things are reported. The guy who’s leading several SPACs, who’s talking to bankers every day, who has a sophisticated family office. You could dislike the guy for a million things, but basic numeracy is not one of them. And yet the knee jerk reaction [by people on Twitter] is that he’s wrong. I think the reality is, and here’s the brutal thing about Twitter, most people on Twitter are strivers. The people that are working really hard, they’re trying to make it, and candidly for most people it’s not working out. Especially the finance guys. The guys who went to finance, they’re not getting the money. It’s not working out. They’ve got the CFA, they’ve got the MBA, they worked at Goldman, they went to Wharton and they’re still not making a fraction what they thought they were. They’re not moving up. It’s not working out because of top-down industry dynamics which you’ve talked about ad nauseum, but that makes them really bitter. They’re really bitter because they feel like they’re getting screwed. And so when they see this guy, who’s making billions of dollars, making a beginner mistake, that would have gotten them fired, the amount of unrighteousness or injustice feels so massive. It overrides all logic and reasoning.

Nobody is immune from the brain-hacking that the networked world is doing, but the first step to understanding it is being aware of it.

My big thesis right now is technology is being used to program people, not the other way around. In the frickin documentary on Netflix [referring to “Social Dilemma”] is half of the stuff and [Chamath] is doing it. It’s crazy how effective this stuff is. A great example of this was when I tweeted a stupid joke that “no one actually knows what’s in chalk, they just teach you to accept the premise when you’re so young, and they just go with it.” And you have people, like real people with PhDs responding like I’m a fucking idiot. Everybody knows what chalk is. Don’t you see this as tweeted from my iPhone?! I tweeted this from a supercomputer in my pocket. Even if I didn’t know what chalk is, I could obviously put faith in it. [This is obvious if you think about this] for more than a split second but you have people who have multiple PhDs from places like MIT, who are completely hacked. Their brains are being hacked. And they look like fools, and they think they think that they’re smart because they’re speaking. Not to validate what they’re saying. They’re speaking to validate themselves, and that’s the weakness that all people have. This is the dark arts that you have to study now.

Change is occurring at an accelerating rate

There’s a concept called the Overton window, which, not to be like a dropper of concepts but Overton Window refers to what like types of political policies are acceptable to talk about in public. [A few years ago universal basic income was considered a quack idea], last year Donald Trump initiates universal basic income. Admittedly because of a virus so I’m not saying it was a wrong move, but you need to understand how insane that shift is society that that went from unthinkable to expecting it, and actually the people almost revolted. I mean I was in Richmond, Virginia when the protests were happening there. We were watching the breakdown of society happened, because there was some uncertainty around it that changed in a year.

You can’t put your head in the sand about the role of social media. The genie is out of the bottle. Dan sees evidence that some managers do not understand that reality.

The thing about Twitter within hedge funds or institutional endowments that nobody really wants to admit is, even if the CIO isn’t on Twitter, (and if he isn’t, it’s only because he’s too old) all of their analysts are! So, like there’s this huge issue right now of mass group gaslighting of mimetics and ideas spreading like viruses and if you’re a CIO right now, you probably don’t actually know what your firm’s sourcing mechanism is (unless you’re pushing all your ideas down). The number of times I meet with the senior guy who runs a fund, and he starts rattling off ideas I’m like “Yo, you know your analysts ripped all of that from Twitter right. And they’re like ‘What are you talking about?’ and I’m like, Look, there are these cliques of people on Twitter, I’m not even I’m not saying they’re bad ideas, but they aren’t original ideas. I’m just telling you. I’m not going to doxx your boy, I’m not going to get anybody in trouble, but I’m just telling you that you don’t know how your own investment process works. You don’t realize you’ve already been fully infiltrated by social media.”

Instead of fighting this new reality, adapt to it.

[You’ve been infilitrated by social media] but you actually kind of want that because if you are the only guy who’s not participating in these things [you are missing important context]. For example in January, and the end of December [during the stock squeezes]. I’m not particularly smart, especially relative to other hedge fund guys, but I was seeing where the liquidity was in the market and I was seeing the type of stuff happening on StockTwits and Reddit and all these other places I mean there was just gonna be just some crazy stuff happening. I went to my clients and said “Look, I’m not gonna play this game. I’m gonna take exposure way down. Yes, I believe I should be short half these companies, but I’m short the stock not the company. I’m not messing with this.” I had several people say I lack conviction, long-term investing blah, blah. Then the next three months it was just a hedge fund after hedge fund blow up. This is not going away, it’s not going back because it’s not 2000. This is not instant messaging. Last year was the first year that most waking hours for humans were online, and everybody was on one to five websites. Nobody really understands how significant that is. Everybody’s now networked, all the time 24/7.

The bar for what is considered table stakes is rising. Psychology and the repercussions of being highly networked should receive more of your attention to gain an edge.

People don’t realize how fast these big changes happen and so when I just look at some people who think we’re gonna, we’re gonna be good investors because we do more conservative discounted cash flow analysis than the other guys I’m like, “You’re like a dude with a horse and a saber walking into WWII. You’re about to have a really bad time. Like I can’t even explain to you the ways in which you’re going to get beaten down, and you’re not psychologically prepared to deal with any of this stuff because it’s gonna seem random. It’s just gonna be chaos. There’s gonna be bombs dropping and machine guns and you’re not gonna know what either of those things are. It’s just a really weird time to be an investor and I think you have to move the psychology stuff up in how you’re relating to the world into a really forefront position. Or these systems are just going to eat you.

How Dan’s fund is adapting

We’ve continued to zoom in on this behavioral stuff. Everything else is table stakes. Of course, you need to know how to value something, you need financial analysis, you need to be able to read transcripts, and do value research. But that became commoditized sometime between 1995 and 2010. Look at the number of people who have CFAs or how many people went through banking here or internationally. Companies like thedeal.com. You can go online, hire somebody anywhere in the world in like 10 minutes with a contract and a 1099.

Right now, I think the markets become a pure metagame of the game. Where does it go from there? The thing is humans are still very human, and actually, the rise of passive means the humans are a smaller percentage of the market. When they move at once they have a bigger price impact, because it’s just everybody running out the fire door of a theater. It’s as old as the hills. It’s all the same stuff again but remixed and much faster. It’s still music but it’s going from jazz to dubstep, way more aggressive, way faster, with all these different games being played. So we spent a lot of time trying to understand the fundamentals and what’s going on in these businesses and what’s going on in the supply chain, but also what is the psychological game going on in the market.

You must find a lineup where you’ve got great fundamentals, good business improvement, a really long-term runway, and you have some really distracting psychological thing that’s distorting the price. Or more importantly, maybe in this era, mandate arbitrage. As more and more capital is just driven by somebody’s investment policy statement, or an endowment investment policy statement or the S&P index rebalances. Those legal mandates are really powerful and just getting bigger. So we want to see a clustering of understanding why the opportunity exists. Because of legal mandate, because of agency costs and behavioral things like [where investors] can’t go to LPs and own it because they are going to get upset. If we see that plus it’s a good business [that becomes a potential opportunity].

This bit reminds me of the style of trading I’m more accustomed to where we don’t predict so much as try to “see the present clearly”. I’m more accustomed to measuring what is happening now than predicting tomorrow. (An example from my world would be owning optically expensive volatility because it’s carrying well)

We don’t try to predict. We try to observe. We might have a starter position on but when we see thesis confirmation, we’re going to add. What we do not really like to do, is make a big bet because we think x is going to happen. I don’t think it’s necessary because I don’t think the market adjusts to new information as well.

Dan loves Warren Buffet but scoffs at his cargo-cult imitators

I’m a huge Warren Buffett fanboy. My favorite people in investing are Warren and Charlie and then my least favorite people in investing, generally speaking, are people who tell you that they’re fans of Warren and Berkshire.

A great filter is to ask them “what’s your favorite Berkshire business?” If they say See’s Candy, you know that they know nothing. Nothing about Warren Buffett or Berkshire Hathaway. The reason is Warren Buffett is probably one of the greatest marketers to ever live. He’s built this brand. He’s built this brand that’s hyper-consistent. That allows him to not answer any critical questions, because he doesn’t actually have to defend objectively right or wrong. He just has to defend consistency with his brand.

There are several value investors that really market themselves as like Warren Buffett or Charlie Munger brands. Baby Buffetts. They all have kind of good records of not losing huge amounts of money but none of their records would stand on their own in a vacuum. They live off this same narrative. Recently I’ve had some interesting interactions with a couple these people. You ask them “How do you think about your business?” They’re very candid. “Look, I am looking for somebody, where that’s what they want. They want to feel that they’re investing in a long-term, conservative thing. They’re not going to lose their money. They will compound well and they get to feel like they’re part of the church of Buffett.”

At the end of the day, what are they selling is a psychological safety blanket. They’re not selling an investment product at all…they will only take inbound clients because they don’t want to go out and convert anybody. Look at how these [investors] behave. If you’ve ever studied cults, you see the exact same behavior. I don’t necessarily think it’s malevolent or bad, but I think that in the modern era, with everything that Warren Buffett did now being sped up 100,000 times, and on Twitter everyday with people doing these explainer threads and Substacks. These are all the same psychological manipulation techniques. It doesn’t mean they’re malevolent. If you really understand how Warren built his public persona, why he built it the way he did, and how he changed his business at every scale level of capital [out of necessity] you’d understand that the idea that Warren Buffett The Empire Builder, bears any resemblance to Warren Buffett The Ruler is naivete.

Why 2020 made Dan optimistic

Looking forward, I think the takeaway from last year, has to be a profound optimism for humanity. We just took a global pandemic on the jaw. As pissed off as everybody is we’re calling it the Five Aces Problem. It’s like you being dealt a poker hand with four aces and people are like “It would be good if we had a fifth ace”. There’s no fifth ace in the deck! You can tap something on your phone and have a pizza in 20 minutes! You can have a date in 5 minutes. You can have anything you want delivered to your house within 2 days. Like woe is you that you couldn’t get the specific dumbbells you wanted that week. During quarantine, we were living a better life than people in the 1960s were able to live. People in the 25th income percentile now live better than Rockefeller did. We’re going up a curve that is getting exponential so people are not understanding how insanely awesome the performance last year was of humanity. And sure we have some supply chain chokeholds leftover from last year. Yes, there are obvious knock-on effects. We’ve got some issues around the government explicitly putting all risk onto the dollar and making some big bets on modern monetary policy. Those are generally concerning things, but they are super obvious. I just don’t see how you can’t be optimistic about our ability to solve these problems.

I think one of the things people struggle with, I just wrote about this, is as the world gets better, as you go from being a caveman to being an office worker, your job is moving further and further away from the kind of base Maslow needs. You’re not hunting a saber-toothed tiger, you’re typing in data entry or doing social media posts. That’s why every generation looks at the next generation and thinks they’re soft as hell. You know “they had to walk both ways to school uphill in the snow.”

It always happens like that. That’s what progress is.

Darrin Johnson On Flirting With Models

Independently Shorting Volatility with Darrin Johnson (Podcast)
Corey Hoffstein’s Flirting With Models

Darrin Johnson is an options trader and the first independent trader Corey’s had on the pod. Considering Corey’s show focuses on institutional and cutting edge investment professionals, it says a lot that he had Darrin on the show. I’m not surprised, I’ve been following Darrin on Twitter for years and impressed by his understanding of options trading. I have always believed that option trading is an apprentice activity. I cannot imagine how difficult it would be to learn the game with the guidance of masters. Darrin has managed to cobble together that guidance from a variety of sources including Euan Sinclair’s books, Twitter, hiring grad students to walk him through the academic math, running countless simulations, and detailed reconstructions of financial products.

Here are some of my favorite aspects and insights from the interview (with my commentary):

  • Darrin’s entrepreneurial path before he even found his way to trading is worthy of an interview of its own.
  • The importance of building sims instead of backtesting as a way to get more samples. For those of us who trade for firms, we benefit from the collective osmosis of many traders discussing trades and situations in detail. All those morning huddles and afternoon meetings help us build a mental library of counterfactuals. Darrin did the next best thing…build simulations, knowing that a backtest is a single version of what could happen. This is crucial to get a fingertip feel for how positions behave.
  • The idea of pricing out financial products to the penny. Darrin called it “back-office” kinda stuff that retail traders don’t do. Corey said he does this too. This is exactly what you do at a mm/arb shop. As a clerk I remember building giant spreadsheets to price fair value for ETFs. This is not optional work. You will use those skills to attack new products and understand the frictions to arbitrage.
  • At around the 40:00 minute mark Darrin explains why he concentrates his selling on at-the-money or meaty options not the wings. He makes the correct insight: when you sell tails, you need to capture the entire premium. The hit ratio of selling tails is high but when you lose you lose many multiples of the premium. If you fail to collect the full premium, it will not make up for the losing trades. The difficulty of selling tails is even trickier yet. Darrin explains how betting against longshots leaves you uncertain if you have an edge in the first place. In my words: good luck differentiating between a 50-1 shot vs a 100-1 shot. That’s the difference of 1 probability point but it’s massive in payoff space. I discuss further in Tails Explained.
  • Here’s a more subtle insight from the interview. Darrin tries to find the structure that has the best payoff to his vol forecasts or thesis. Notice the subtext. If there’s a “best” there must be a “worst”. This is the basis of relative value trading — buy the best payoff and sell the worst payoff contingent on the vol forecast coming true. For example, if you thought skew was cheap in the oil complex compared to macro backdrop, you could buy the cheapest puts across the oil and products suite. You could buy some ratio of oil puts and selling RBOB or HO puts depending on how how you think the macro stress plays out. Now you might want to be outright long the vol forecast coming true so you might not want to turn this into a basis trade (the advantage of a basis style trade is you can likely do it bigger). Or you could choose to buy oil puts and say sell puts on an equity index where the stress has been priced in. Because you’d be taking an even larger basis risk than staying within the oil complex, you would size the trade smaller than the oil basis trade, but perhaps larger than an outright long oil vol position. The point is there is a lot of creativity on trade expression that balances edge and basis risk.

Since the interview was so good, it got passed around quite a bit on Twitter. In one of the ensuing discussions, I offered my down-to-the-studs view of what options trading really is:

There’s nothing magical about options trading. Paraphrasing Darrin, the intellectuals who are drawn to it prolly need a more blue collar view. Step back and think about what the market needs. What risks doesn’t it want to hold? Obsess over the who and why, not moments [of a distribution]… For years the “job to be done” in vol was be willing to pay theta The marketplace was bidding for that role and vol folks that filled it did well. The market “bids” for different roles all the time in vol-land and the job of a vol trader is to fill it. Simple not easy.

@TheSpeculator0, who trades for a firm, astutely observes: It’s not easy to catch the regime change that switches up the roles.

My response:

That’s why risk management is key. The nature of market-making, even if you don’t explicitly have that title, is you lose on the regime change. So you adjust and hope the next regime lasts long enough to pay you for the [money-losing] transitions.

If you want a fuller discussion for the raison d’etre of vol trading, you probably won’t do better than Corey’s podcast with QVR’s Benn Eifert who describes the job as “bringing balance to the force”. I took full notes for you…Flirting With Models: Benn Eifert (Link)

Notes from Marc Andreessen on Education

Link: https://a16z.com/2020/09/10/education-myths-monopoly-oligopoly-cartel-costs-past-present-change/


The education system is based on model that pre-dated the printing press. It has had little innovation in light of the technological advancements. Yes there are experiments like Lambda School and its ISA alignments. There are MOOCs which offer micro degrees. But in 2020, distance learning as necessitated by Covid, has accelerated the questions we have about a system whose costs were already outpacing inflation. We are left to wonder who our current system is serving and if it is time to examine more efficient possibilities.

Recently Google dropped the requirement that new hires need college degrees and it’s expected other large employers will follow suit. It begs the question, what were degrees good for?

The CEO of Figma, Dylan Field, interviews Marc Andreessen to hear what the cost/benefit of our college system is and how recent developments will test theories about what college is good for and what alternatives may serve those requirements better or more cheaply.


Purpose of college

Overt purpose: A bundle of actual education/skills acquisition, social/dating service, network building, “attached to a hedge fund” (in the form of an endowment)

Cynical purpose: Outsourced personality and IQ testing (via SAT) as these screens have become either socially undesirable or illegal for employers to perform.

The personality dimension being tested for is known as conscientiousness 1 which has 2 components.

  1. Industriousness: Basically self-starting energy
  2. Orderliness: Attention to detail, time management, organization

The “sheepskin effect”

Somebody who goes to college for seven out of eight semesters does not receive seven eighths of the income of somebody who goes for eight out of eight semesters, they receive half the income of somebody who goes for eight out of eight. So the diploma signals your conscientiousness by evidence of you clearing the 4 year hurdle.

A diploma tells employers you are a smart kid who can get their work done, signaling conscientiousness, rather than being about knowledge acquired.

Testing the purpose of college

  • Covid-19 will tease out how much people are willing to pay for an online education which will hint as to how much of the value proposition derives from the degree, from the social, and from the actual learning (this acting as a constant). International enrollment which is unsubsidized would be an especially useful clue as you would expect the loss of social network effects would impact those students the most.
  • The test of college as an outsourced intelligence test will naturally occur as leading universities shed standardized testing requirements

Understanding the source of the student debt crisis

We need a conversation about value given vs value received of college from an economic lens because it is subsidized by Federal and state government. If the ROI is not there the victims are tax payers and the students who cannot discharge the debt via bankruptcy.

How did we arrive at a mountain of debt that cannot be serviced?

The system is a hostage of a govt sponsored cartel.

  • K-12 education is compulsory and state-run. Captive audience.
  • Hallmark of monopoly: real dollars spent on education have 3x in 40 years and outcomes are unchanged
  • Funding is monopolized
    • Accreditation: Loans are subsidized by the government and are only available to accredited institutions that are certified by the govt. Accreditation or admittance to the cartel is nearly impossible.
    • University research funding comes from the government. Can’t remember the last research university to come into existence
    • Operating a university is taxed as a non-profit
    • Endowments are taxed as non-profit

    Meanwhile between sports programs and endowments these institutions have more in common with for-profit businesses.

The spiraling costs are exactly what you might expect from a monopoly and to be contrasted with perfectly competitive businesses such as manufacturing that have led to goods disinflation.

Basically what the government does to education is just like what they do in health care, it’s just like what they do in housing. A two part strategy for managing these markets. They restrict supply. And then, and then restricting supply causes prices to rise, because there’s more kids that want to go to school than can get in. And then on the other side rising prices create political pressure which they resolve by subsidizing demand.

(This was part of his anti-govt rant. I haven’t fact checked any of this. He also points out that spiraling costs without an improvement in service is also the hallmark of 2 other heavily govt influenced areas: housing and healthcare. The story of the ultra-liberal Cal professor who called for subsidized housing while he votes against development to maintain “historical charm” came to mind.)

The value proposition of university for people in “show your work” fields is changing.

One of the most basic revelations the internet has surfaced is the different nature of professions.

Internet has made the largest difference in “show your work” professions: occupations where it is valid and easy to demonstrate your value online. For example, coding, design, music, art, game dev, animation. Open source projects and writing, democratized, pure examples of “show your work” fields.

From an employer’s point of view conscientiousness is a proxy for being a good employee. But this can be circumvented by just showing your work online. This erases the value of a degree that derives from employer demand.

GitHub has like an internal ranking and rating system for software code, and for programmers. So you can actually build an actual professional reputation as a software developer on GitHub without ever actually being face to face with another human being. People all over the world today who were basically taken advantage of this to be able to basically build these incredible track records as a software developer and make themselves more employable. Employers like my venture firm. We recommend that our employers spend as much time on GitHub looking for good programmers as they do on LinkedIn, or going to college fairs.

YouTube, blogs, Figma for design all play a similar role as GitHub does for software developers. He tells the story of South Park as an early example of a viral video that was able to spread organically through a distributed technology. The show born from Matt Parker and Trey Stone’s irreverent holiday card which made its rounds as a downloadable Quicktime vid!

“If you can go to college, go to college”

  • Even jobs that probably shouldn’t require degrees require them.

I think it’s actually quite dangerous to give somebody, somebody as an individual the advice, don’t go to college, like in the current system that we have that’s basically saying don’t prove that you’re smart don’t prove that you’re industrious, and conscientious and then basically be prepared to settle for fundamentally lower income for the rest of your life.

  • Understand the proposition

Gates and Zuckerberg notwithstanding, if you go to college finish college. Get the piece of paper.

  • The 2×2 matrix of what to study and where to study.

The spread of outcomes for technical degrees is not that wide. If you have a technical degree your choice of school matters less. This is exactly the opposite of what you find with liberal arts degrees. Since the output of a liberal arts degree are more subjective or uneven the school issuing the diploma carries more weight. 

Possible explanation: in absence of concrete skills, the network from a top school is valuable.

Tips for those in college or considering college

Execute on the opportunity — take the hardest course load you can. Get the skills (obviously get good grades but focus more on getting the skills).

If you are at a sub-tier college taking liberal arts, de-risk by acquiring marketable technical skills.

For those considering alt paths

At this point Marc, still recommends college and acquiring technical skills but if you choose an alt path be aware of the trade-offs. For example, if you choose to do open source work recognize it’s better to make major contributions to one project (as opposed to minor contributions to multiple projects) because that really demonstrates what employers are looking for. Put yourself in the mind those who will be evaluating you years down the road.

Consistent work demonstrates conscientiousness and the nature of the work is an embedded intelligence test.

What should a software developer do? Unquestionably the answer is create an open source project or go become a member of an existing open source project and make successful high quality sustained contributions to that project over time. At this point I think that’s clearly a better credential than getting a computer science degree. I’d hire people like that myself and the great thing now is you can do that from all over the world.

So what matters to Andreesen when they hire or fund someone?

The good news:

They do not care about a degree or GPA or test scores and in fact question if too much conscientiousness means you are too much of a rule-follower.

The tough news:

They measure you by what you have actually done. Building companies requires being able to do things so that is the capacity they are looking for. List of things a founder will need to be able to do:

  • Building an actual product that somebody will actually pay for.
  • Figuring out a way to actually sell it to them
  • Actually collect the money
  • Actually service the customer so they actually have a good experience
  • Actually tell their story so that anybody will even know that they exist
  • Run a finance function so that they don’t lose all the money
  • Run a legal function so they don’t get sued all the time
  • Actually get others to work with them.

There are many talented people so the way to stand out is to actually demonstrate the ability to build or create.

Steve Martin best career advice ever: Be so good they can’t ignore you.

Developments to watch

  • New credentials2 to replace bachelor’s degrees (ie Google certification program, coding tests, and math puzzles)

  • Still early innings of “show your work” online as way to qualify yourself



Kathleen Mercury on Board Gaming With Education Podcast

Link: https://www.boardgamingwitheducation.com/games-in-schools-and-libraries/

About Kathleen: Educator with a special focus on teaching gifted students game design (Link)

Transcription: Otter.AI

I incorporated Kathleen’s presentation to these notes for the sake of consolidation.


Overview

Kathleen believes:

“Happiness comes from being able to choose the life you want to live.”

To empower students there are 2 anchor ideas:


Be Producers Not Consumers

…what I want more than anything for my students is for them to be creators, not consumers…The only thing I care about is what ideas they have, and giving them the tools where they feel empowered to take on big complex challenges where they have no idea of what the final product will be, but that they can build in and learn the skills and confidence that they can hopefully get themselves there. That’s what I care about because if I can get them to accept that and do that, then they can pretty much take on whatever challenges come their way for the rest of their lives.

Bias Towards Action

For those familiar with the Silicon Valley ethos of “Move fast and break things” this will be familiar. Despite, her midwest roots and home Kathleen’s thinking has been heavily influenced by the Stanford D-School.

…probably the biggest thing that’s helped me is the Stanford design school’s method of prototype development. I went to a design-thinking boot camp, and the design mindsets that were presented as far as when you’re wanting to design something for someone else, and how you should think about it. Here’s how you should approach it. And it was so different from what I was doing, but it was just one of those things where it’s like, oh my god this is 100%, what I should be doing and it completely pivoted everything that I was doing. For example “bias towards action”. Instead of just thinking about something just start doing it. Rapid iteration making prototypes fast and cheap so you can get them on the table so that you can fail quickly see what works, see what doesn’t work quickly and so you can make more versions of something even faster.

It’s designed to keep them moving quickly so that nothing becomes precious and nothing becomes so sacred that they won’t get rid of it. And I think for me as a teacher, that’s really helped me and also helped me as a game designer in terms of trying something getting it out there, seeing what happens getting feedback on it and making improvements to it as well.

Lessons From Teaching


On using games in learning

  • I think for a lot of gaming experiences in the classroom, having everybody involved at the same time, really, really matters for success.” (Party games are a good tool for this)
  • A good teacher can make a lot of things fun. Sparks a love of learning.
  • Bridging the abstract to concrete
  • Critical Thinking
  • Information more sticky/accessible. Increases connections.
  • Boosts engagement & connections (made me think of how a local teacher used Pokemon cards to bring the boys and girls in 1st grade together)

On kids having different abilities

  • Everyone deserves to learn at their level every single day that’s just one of those tenets that I just hold. If you’re doing something where their disabilities or inabilities become apparent to others. I think you have to be really careful about how you handle that. As far as you know what you’re willing to do to, you know, protect them to take care of them because if they’re stressed out and embarrassed.

  • Approach to gifted kids:

    1. If you don’t give gifted kids problems to solve, they will create their own.
    2. They need to learn how to struggle and work through it.
  • Heterogeneous groupings can protect kids by partnering up.

  • But homogenous groupings have advantages too.

For my gifted kids, a lot of times when that happens, they’re always like the ones that are like spread out amongst the other groups, and then they put all the spread out all the middle kids and then they spread out all this sort of low kids and pardon me for speaking in broad brushstrokes but I am. And so a lot of times they never get chances to work with each other. And one thing that research shows is that when you let kids have similar abilities work with each other. Everyone gains, because the kids on the middle step it up, and the kids on the lower end also step it up, even if it’s like one notch higher, you know, that’s okay for them, you know they’re using their abilities and what they know and trying to push themselves up to be more competitive as well

  • Why the emphasis on points in winning is redundant.

Points are used to ultimately communicate your position in the game to other people. And if we’re playing a game that is just to be, you know, a review or something like that I don’t care about the points at all. And so, what I will often do is even if they get points, or if one team starts to get a blow out. I will, you know, do something like say “this is a 20 point question”, and then somehow I manage to make it so that kids on the other team get those points, or I start awarding ridiculous points my cool you just got a puppy. So drop puppy up there on the scoreboard.  

Why teach game design?

  • Develop analytical, practical, and creative thinking skills

  • Autonomy and collaboration
  • Teaching game design is teaching to orient towards an internal scorecard not an external one

That quantitative checkmark feeds into a lot of the programming that we’ve already done with kids as far as you know letter grades and standardized tests and success is 100% and success is, you know, an A plus is, you know, and I think for a lot of my students especially having to sort of break that mentality. A lot of what I do in teaching game design is here is this problem that cannot be solved, or notions like that. Here is this problem that you will have to you have to define the problem. You have to figure out how you’re going to solve this problem, you’re going to design your tests with these resources in terms of you know how close are you to solving this problem and you’re gonna do this again and again and again, you’re going to make a prototype you’re going to put it in front of other people, they’re going to play it, you’re going to get their feedback, and then you’re going to take those ideas, and that, you know, good, bad, the ugly. Incorporate that into your next design so that when that hits the table hopefully it’s better. Thinking of it as an unfinished unending hopefully upwardly ascending sort of cascade. See that process as a real process reflective of what life will be, I think is really important, because for a lot of my kids, you know they’ve learned what successes is and it’s an A+. I’m trying to show them that if you want to do anything cool, there will never be A+. You will never be finished. You will always just have to try to do your best to put out your best possible effort, listen to other people, and hopefully make that idea better and so that’s why I teach game design.

The reason why I teach game design is a teaches them this process of thinking design, thinking hands-on, trying to create solutions and learning how to see successes incremental progress, not as I finished I’m done.

We do talk about how it can be finished and not perfect and that’s really important for a lot of them. That you can have something that is unfinished. And you can see it as successful because you did try to make it better, even if you don’t think it’s better. And that’s really really hard for them to accept because it goes against everything they’ve always done

  • An antidote to results-based thinking

I honestly try to minimize any type of objective points in any kind of game situation as much as possible, because no one should ever be blamed for losing for their team, and I honestly don’t want anybody to be, you know, the fourth batter to just hit the Grand Slam home run and they get all the credit, not the people who also got on first, second and third.

  • Be thoughtful about when points matter

It does make sense to have kids have scoring that matters, but I think you have to really ask yourself, is this that time.

  • Not having grades at all doesn’t really work

And if I had my choice I wouldn’t do grades at all, but this is the world we live in and I have to actually try tried one year to not give out grades and our gifted class. There’s some unintended consequences there but there you go. We tried it once. As much as we wanted it to work it didn’t really work.

Projects Kathleen and Dustin Are Pushing Forward

  • Game Database To Aid Teachers looking to use games to augment material

    I think that something you touched on and I’ve been kind of thrown around in my head is creating some sort of database where teachers are teaching a unit on something and they can go on there and see what kind of games they can use in their class to either tackle review or tackle preview and concepts of the whatever material they’re learning. It would be really good for teachers to find like a resource where they can just go to, and save time and kind of have this lesson plan that they can use.

  •  Formalizing standards

Look at the curriculum that I have and formalize it a little bit in terms of standards that it’s meeting. That’s something that people ask me about that I haven’t really ever have had to do. And I think it’s something that I’m interested in one because it will make it even easier for people to use these resources in their classroom but it also. I’m really like thinking about the idea of what are the things that people could do to get their kids to think like game designers to use design thinking, using games, what would be appropriate, you know the early elementary level, the later elementary level, the middle school level, the high school level. So that if somebody wants to do something with game design in the classroom, they’ve got a better chance of success. That they’re not over-shooting or under-shooting what their kids are able to do but also in terms of tying this, you know, more specifically to actual curriculum. Then it can be easier for their administrators to use.

Flirting with Models: Wayne Himelsein

Link: https://blog.thinknewfound.com/podcast/s2e7-wayne-himelsein/

About Wayne: CIO of Logica Capital

Transcription: Otter.ai


Overview

Every trade is implicitly long or short volatility or optionality

  • There is variability in every asset and its distribution dictates whether you are long or short.
  • Every trade is either a bet on convergence or divergence. Convergence trades are short volatility

Quant vs Discretionary

“There’s good and bad in all of it. So the best you can do for yourself by going with what you know because you’ll be able to ask better questions and be more comfortable with what’s happening day-to-day.”

  • Myth of quants building a black box then “going to the beach”

“The market is always changing. In fact, it’s funny even the idea of factors and categories, if you think of something like value and growth. These two big facets of the market, even those are evolving. [Consider] that you buy a value stock, and it turns around and starts moving in your favor. Well, now it’s a growth stock. So literally, the categories are changing on us. So if you bought a value book, and you leave it for six months, you’re now a growth book, if you were right on your picks.”

  • Using quant to “mechanize” what works vs mining for patterns

“Finance algorithms that developed from logic and experience that simply seek to mechanize what is already well understood, have a chance at success. Those that begin in data analysis, categorization, quantification, or statistical or numerical gymnastics do not.”

Opportunities in volatility trading

Traders have different “assumptions across the volatility surface, the strikes up and down and across the calendar upwards and outwards, There are different prices for every option. Because of all this modeling and people having demand for different options at different calendars in different strikes, there’s going to be cheaper and more expensive….Take advantage of the weirdness and pricing and model variants across the option surface.”

An inverse relationship between signal strength and opportunity size

  • As your signal strength declines you need to diversify more. “To have more probabilities repeated more often, [so] more positions”
  • Hoffstein: “Information ratio is equal to your information coefficient times square to breadth. If you have to lower your information coefficient, but your breadth goes way up, you can actually end up with higher information ratio”

Re-phrasing a bit: expectancy scales with number of trials but volatility scales with square root of number of trials. If your bankroll is large and your business diversified, it follows that your focus should be on hunting for high expectancy games, not minimizing risk.

Evaluating a strategy

  1. Use daily returns to get more data points. Monthly returns mask too much.
  2. Are you achieving your premise?

    “So you’ve said yourself, I know where I want to neutralize, and I know where I want to get my alpha. And if that’s where you get your alpha, you have to know that number one, you have alpha there. So if you look at your growth tilt and measure that against Fama growth factor, do you beat it? If not, you’ve got no edge.”

    • Map the strategy.
      • Compare the exposures to time series of different exposures to see how it behaves. This requires using mathematical tools that do not rely on linearity (ie regressions).
        • “I don’t ever listen to what [the manager] tells me. I just run it versus we have in here about 180 different exposures that we have time series for factors or exposures [to find out] “what is inside this thing?”
      • How intentional are the exposures?
        • Managers will tell you that they’re doing something but don’t even know what they’re exposed to. “Did you know you have a 30% exposure to momentum? Oh, no, I didn’t. I’m actually a value investor.” (Me: sounds similar to performance attribution frameworks behind “hedge fund replication” strategies)

Risk

Beta is a poor quantity to use to balance your portfolio

  • Beta equals correlation times vol ratio
    • It’s easy to compute which makes it popular
    • …but since its inputs are non-stationary, non-linear and themselves volatile it’s garbage in/garbage out.
    • Important to understand if a beta-hedge portfolio will bleed longer or shorter as correlation increases. (Me: This is why gross exposures are important to constrain)
  • How to balance a portfolio without relying on beta?
    • Geometric approaches that account for non-linearity
      • Clustering distance approaches
      • Stochastic dominance

Market neutrality is a “funny” concept

  • What does it mean to even be neutral?
    • “What do you want to be neutral to? Are you directionally neutral? Are you factor neutral? You can [initiate] a directionally neutral portfolio that has equal long shorts, with a complete growth, tilt, or a value tilt or some other factor tilt like a volatility tilt.

Overcrowding

“If we find a good pair trade, rest assured, many others have found it. And there’s just gobs of computing power, and PhDs and all the rest doing the same thing. And so we’re all going after the same edge. When things start to go wrong, the differences between the different groups is that they manage the risk differently. And one of the best means of managing risk in these markets [is to manage leverage]. The overcrowding risk is that everybody’s in this trade, and it’s a good trade. That’s why everybody’s in it. So you’ve done the right thing. But as some of these bigger shops start to unwind, it becomes everything going the wrong way. Others are needing to exit because they have LPs to answer to or they have risk that they’re managing to, so as long as you’re in it, you’re exposed to that. And it’s difficult to manage because at the get-go, you made the right bet.”

Walking away or sticking with a “broken” strategy?

Difficult question since the pricing may be more favorable as anomaly gets stretched but unclear whether the relationship will revert and on what timeline. There’s career risk is sticking with it vs the weight of the historical evidence for the opportunity.

“The more your measure won’t determine whether something’s out of favor, the more time you might give it to try to fix it”

“Comes down to a personal decision. How much time am I willing to spend tweaking and contorting to try to figure out whether I can fix it. And we all have our limits. It comes down to a business question as well. It’s not just tweaking and contorting and trying to fix it. But how much time can you spend defending it? How sticky is your capital? Even if it does come back still be in business?”

An easy example was the trade that shorted both the triple long and triple short ETFs on the same reference asset. The trade was over once the cost to borrow the shares exceeded the edge in the trade. This was easy to measure and therefore abandon when it became too crowded.

Hedging non-linearity or skew

  • “The only way to get rid of the left tail is to balance it with the right tail. And to have that obviously, you have to have the right offset temporarily. You need the time association to match that when this thing goes down, the other thing goes up. So you need to understand the time relationship between the two.”
    • Stop-losses are “synthetic left tail mitigator”. They are not fully reliable because of:
      1. Gaps
      2. Discipline
    • Tradeoffs between hit rate and cost of the hedge. Need to define what type of exposure you are ok with to target the right option hedge. Just like insurance has cost levers like premiums, coverage amounts, durations, and deductibles options portfolios can be custom tailored.
    • Flight to quality assets like gold, USD, treasuries in a permanent portfolio
    • Managers who engineer defensive market-neutral portfolios

Final words on hedging

  • Depending on the nature of the crisis hedges behave differently. Since we cannot predict the nature nor timing of a crisis it’s best to be diversified across hedges.
    • “Back to the larger insurance analogy, you have your medical and you have your dental and you have your vision. And so I don’t know where I’m going to get hurt. But either way it’s covered.”
  • Tolerating the cost
    • “Optionality being potentially the heaviest cost again, to me, it’s not expensive when you get what you want. But since it is more often a bleed than a payoff, perhaps people should have more treasures and gold and a little bit less optionality. But definitely all concurrently.”

Thought experiment

You can only own 1 asset and never trade it again, what do you pick?

SP500. The only reason people underperform the market is they want to control volatility and liquidity needs. But if we remove these concerns the best thing is to just own the market in perpetuity.

Flirting with Models: Benn Eifert

Link: https://blog.thinknewfound.com/podcast/s2e2-benn-eifert/

About Benn: Founder of QVR Advisors specializing in option-based strategies


Selected notes from his conversation with Corey Hoffstein, co-founder of quant management firm Newfound Research

Can you maybe explain the difference between what you would consider to be more of an option strategy versus what actual volatility investing is?

  • A common option strategy is call overwriting or put writing. They are both long equity exposures. That exposure is going to be the biggest risk factor. I would contrast that with volatility strategy which tries to isolate features of the distribution of returns, but not the direction of returns.

You mentioned that you guys focus somewhat heavily on relative value strategies in the volatility space. Can you explain what constitutes a relative value strategy? What’s a trade that you might put on?

  • Create value buying cheap exposures and selling expensive exposures at the same time, trying to hedge out the main directional market risks that would dominate a traditional asset allocation.
  • Identifying trades is really an important part of the process as they move around all the time over different cycle frequencies. Imagine, for example, long volatility in large-cap energy companies versus short volatility of smaller energy companies. That might be an opportunity at a point in time driven by a series of large transactions in the equity market. A large fund may have done a bunch of overwriting in their large-cap energy names, which suddenly made them very cheap. You really have to monitor, see the prices move and understand why there are dislocations and other relative value opportunities that might cycle over time.
  • Pension fund overwriting or cash-secured put selling are types of opportunities that might last for several years while those strategies are popular. You can imagine them becoming too popular over some number of years, then the pendulum swinging the other way. I wouldn’t say that there’s risk premia that you would expect in the space to just exist in perpetuity in a relative value sense.
  • There’s a large need to provide liquidity for end-users of options and distribute risk from where options are being heavily supplying to where they’re heavily demanded. These markets really developed on the back of end-user demand and their need to transfer risk. The key thing in relative value investing and in volatility, is that the marginal price setter for the probabilities and the market prices that prevail is not a volatility investor who is thinking about nuances in implied volatility. For a specialist volatility investor, many of the best opportunities really arise from either explicitly or implicitly providing liquidity to meet the needs of end-users, and to warehouse basis risk between what they’re buying and what they’re selling.

Analogs and Differences from traditional investing?

  • Selling vol and overwriting are expressions of carry styles
  • Rather than using traditional factor language to describe volatility trading he prefers a “Star Wars” analogy: Derivative users do things in big herds. And they typically have very large size relative to the absolute return community. Those flows are very sticky and implemented in similar ways with similar benchmarks, for example selling one-month index options. This creates congestion in one segment of the overall options market creating a ‘disturbance in the force’ — this creates really steep term structures, market makers get stuffed with short term options, they don’t have the risk limits to hold. And the relative value community’s job is really to distribute that risk much more broadly, throughout the ecosystem. A nice risk-reward profile is the payment to provide the liquidity to that market. Concentrated flows need someone on the other side to warehouse and distribute that basis risk.

How do you think about identifying trades in this space? How do you think about managing trades? How do you think about exiting trades? How does the book come together? It seems like a very overwhelming landscape to try to get your arms around.

  • Our investment process as a collection of bottoms-up strategy sleeves. So an individual strategy sleeve would really be a theme that’s driven by some particular type of dislocation or some particular type of underlying flow that end-users are generating. In a cross-sectional portfolio, opportunities are more fleeting, as opposed to being structural flows that are very consistent over long periods of time. It involves building out quite a lot of infrastructure, to identify those opportunities quickly.
  • In the example of a fund running a big overwrite sale on their long, large-cap, equity names portfolio, that would feed through quickly into the prices of options within that universe, and you’d see a significant reduction in those prices, relative to the prices of the small-cap energy names. You’d see it probably wasn’t driven by underlying realized volatility dynamics, it wasn’t that the spread compressed(because the names in the short baskets started becoming very volatile, and their prices started rising). You’d have various other ways of quantitatively triangulating that which would trigger an investigation into a type of the trade to add to the portfolio.
  • Where the dislocations are potentially more persistent, it might be more a question of measuring those dislocations. How do you track the ebb and flow over time? Is it a particularly attractive opportunity set? Do you want to have maximum risk on? Is it a less attractive opportunity set? Do you only want to have 30, or 40% of risk on? The identification of those type of opportunities is a starting point in the design of the strategies.
  • Again much is driven by what end-users of derivatives are doing in really big size and affecting markets. It’s not hard to see if you are an active market participant. You spend a lot of time talking to market makers and talking to the end-users of derivatives so you see it very quickly.

How do you think about the trade off between systematic versus discretionary and volatility investing?

  • I think in terms of a spectrum between, on the one hand, fully discretionary, and gut feel based investing all the way to the other end of the spectrum of fully automated back to front, systematic trading. Most volatility managers lie somewhere in between on that spectrum. It’s really hard to get that last mile to full automation. Since options are non-linear, you need to manage the very small risk of automation failures which also makes full automation elusive.

Are there any examples that come to mind where either an opportunity was systematically identified and you had a discretionary override? How about the opposite, where you thought there was an opportunity and the systems were not flagging it?

  • Back in the early days of Abenomics, in Japan, when the Nikkei was incredibly depressed, there was an interesting dynamic showing up in skew on Japanese equity indices. So skew is the relative price and an implied volatility sense of upside, call options versus downside put options. And in Japan, it actually started to go positive, which is very unusual. In other words, upside call options, were trading at a higher implied volatility than downside put options. A lot of folks in the volatility community got really excited about how silly it was, that an upside call option would trade at a higher implied probability than a downside put option, and really aggressively sold upside call options. But the key thing to remember back then was the Japanese equity market had just been incredibly depressed for a long time. There was a tremendous macro narrative building around big structural reforms and a great unconventional monetary policy. What followed was a very volatile rally! It was really a sucker’s trap to look at skew based on the historical data set because you were selling an upside crash scenario.
  • Another example was the model not appreciating how cheap the options on VIX were when the sizing in XIV became extreme and creating a very negatively convex profile in VIX due to the size of the rebalance. If you have a fund that requires a mechanical response that has to buy volatility when vol is up, it creates a problem if the size in the market became too large. It was just a market microstructure time bomb waiting to happen. The timing of that type of event happening was uncertain. But the sizes of those positions made it almost inevitable.

When you see a very steep VIX futures curve, in your opinion, is that an expression of the markets viewpoint? Or do you think that’s just an expression of a market imbalance?

  • Typically, it’s more related to risk premium than it is some kind of unbiased forecast of future volatility. If you look academic research or practitioner research there are some fundamentals to that term structure and some expectation element but often quite a lot of element of risk premium.

If you were doing due diligence, on a volatility strategy, describe red flags (besides leverage and are they selling tail insurance) and other concerns.

  • I would want to drill into sophisticated, top-down risk systems that stress all of the main risk factors in the portfolio to very extreme levels, and see that the risks were acceptable. There is no portfolio that makes money under all circumstances which is fine. But if there’s a major risk factor in the portfolio, you should be able to take it to a very extreme unprecedented level and see that the portfolio is not going to be getting liquidated at that level.
  • It should be contained in a level that’s acceptable to the end investor.
  • I’d want to understand the assumptions they’re making in those stress tests.
  • I would really want to see the actual positions and hear them explain what other parts of the market and what other market participants are doing to understand what the squeeze risk looks like.
  • I would want to see that they had at least contemplated thoughtfully and analytically how the strategy should be expected to perform going forward. And really a thought about how the market changed in the past 20 or 30 years versus right now. Markets in general change over time but volatility and options markets have changed dramatically.

Notes from EconTalk: Anja Shortland

Link: http://www.econtalk.org/anja-shortland-on-kidnap/

About Anja: Researcher and author of  Kidnap: Inside the Ransom Business


Economist Russ Roberts interviews Anja Shortland

Kidnapping for ransom as a business

The hint that kidnapping was in fact a business: 97% are resolved peacefully

How can the chance of a peaceful resolution be so high if all these things must go right:

  • Both sides must negotiate a price from a wide range
  • How to payment, typically unmarked cash, to the kidnapper?
  • Trust that the kidnapper will acknowledge payment
  • The kidnapper to trust they will not be arrested during the hand-off
  • The kidnapper must expect that the hostage will not be a witness

“The only reason for this kind of trade to go smoothly is what economists call the shadow of the future. So, people behave well this time ’round because it will help them in their business in future interactions.”

“This will only work if the kidnapper understands that he’s better off keeping the promises than breaking the promises. And that works because there must be a mechanism for information about good and bad behavior to be transmitted to future victims. So, if you have a kidnapping gang working in a city, then local gossip will probably ensure that people know whether or not they can trust the kidnappers. However, how does that work for transnational hostages? How does it work for the tourist that gets picked up in a bar late at night? How does that work for the aid-worker? How does that work for the expatriate?

Enter kidnap insurance

“There’s a very limited number of insurers, syndicates, underwrite kidnap-for-ransom, and they exchange information about trustworthy kidnappers and rogue kidnappers.”

  • Insurance actually ‘orders the market’, creating moral hazard in the process.
  • Corps buy ‘kidnap for ransom’ insurance with conditions:
    • Insured cannot know about it
    • Corporation provides security
  • In some areas, kidnapping occurs because corp didn’t know who to pay protection money to
  • Lloyd’s of London brokers a market of insurance companies willing to ensure special risks (like a basketball player’s knee)
    • The market settles into a civil equilibrium
    • Small supply. Crisis responders (often ex-special forces) retained by the insurer will have specific experience with a class of kidnapper
    • Insurers share info and more coordinated than the heterogenous kidnappers which keep prices down. However, when gov’t come in splashing the pot it changes the dynamics of the game as it raises the expectations of kidnappers b/c of public pressures and gov’t large resources and because unlike insurers they are in a one-off game (France hopes the next victim is Swiss)
  • Each kidnap market has local conventions
    • Example: Pirates want money dropped in canisters next to the ship so that kidnappers can stay high enough to avoid capture himself
    • Businesses that provide secure common ground for handoffs(almost like escrow!)
    • Trustworthy middlemen — again ‘shadow of the future’; reputations and long-running exchanges (reminds me of my open-outcry trading past. In the pits, your “word was your bond”)
    • While any one transaction can go wrong on average the market hovers around a going price.
    • If kidnappers make mistakes, then they are out of business.
      • “Sometimes you have very emotional kidnappers. Sometimes you have stupid kidnappers. But stupid kidnappers will reveal information. And ultimately it is in the insurer’s interest to eliminate stupid kidnappers–well, eliminate kidnappers where possible. But if you have stupid kidnappers who make mistakes, you can remove them from the market by dropping some hints to the police.”

On the game theory of negotiation

  • Manage kidnapper’s expectation of ransom size (hide the fact that the captive is insured)
  • “Squeezing the towel” process as the concessions offered to the kidnappers turn in to a slow drip
    • Eventually, the concessions are below the kidnappers’ cost to hold the victim. For example, the longer a hostage in custody the more expensive (via bribes) to keep it secret
  • Can’t reward kidnapper’s bad behavior or threats (“parenting lesson”)
  • Negotiators help the kidnappers see things through a more rational perspective. And, they educate them. And say, ‘Yes, we don’t want you to hurt Uncle Ted.’ And, ‘You’re not going to get anything out of hurting Uncle Ted.’ And they just help the kidnappers see how that strategy is not going to be helpful.

Notes from Alpha Exchange: Harley Bassman

Link: https://www.youtube.com/watch?v=X8wioRF0434&t=26s

About Harley: There is but one “Convexity Maven” in the world, a moniker that belongs uniquely to Harley Bassman. A 35-year career in financial markets has left Harley steeped in all things relating to the price of and characteristics of optionality.


Dean Curnutt of Macro Risk Advisors interviews “Convexity Maven” Harley Bassman

  • Is there too much short convexity out there?
    • Not in listed option markets where there’s a clearinghouse and vol is explicit traded and monitored
    • Risk is in the implicit convexity similar to portfolio insurance
  • Bassman on volatility surfaces
    • Term structure reflect flows; SPX has option sellers near term and insurance company buying in the longer term
    • Skew in bond markets has flipped since GFC. Pre-GFC puts were richer than calls as large asset managers hedged their bond exposures buying puts. Since GFC, the market recognizes that low interest rates are more coincident with financial stress which has re-priced the upside higher.
    • Forwards will typically price in line with long term options
    • Structured note issuance has vol-suppressing influence on surfaces
      • Europe has more structured note issuance b/c older more income-demanding demographic (looks more like covered calls)
      • Auto-callables in Asia suppresses downside vol (until roughly 10-15% knockout levels)
  • Bassman on a low interest rate worldWith central banks setting policy rates negative, the market is setting pricing across the curve very low.
    • Germany is -.20% out to 10 years yet have nominal positive growth and breakeven inflation is priced at 90 bps, so an extremely negative real interest rate out 10 years.

    Demographic motivated argument for secular stagnation

    • Negative short term rates are not unprecedented and typically accompany short-term market stress. Insurance premium to secure assets
    • Longer term negative rates are a symptom of market expectations for slower growth due to demographic headwinds.
      • In US boomers are getting older. Japan is further ahead and Europe behind Japan.
      • Declining labor force participation is biggest concern since growth = total hours worked x productivity
      • Labor force participation and yields are correlated over long periods
      • The trend of each decade is bluntly explained by demographics but it’s slow moving and difficult to trade
      • Immigration necessary to balance the ratio of workers to retirees. Immigration very important.
    • Trump is a symptom of low wage growth
      • Bassman believes QE1 was necessary to save economic system but later rounds of stimulus should have been fiscal not monetary. Monetary has caused asset inflation without wage growth. Inflation therefore was uneven and regressive leading to Trump and dissatisfied public
    • MMT
      • It’s coming. 2029 boomers will be fully retired and Republicans will not want to cut spending so there will be no check on Democrats
      • Japan a good example that MMT can work in the short term if you borrow in your own currency. The issue is that MMT will not be restrained even if inflation starts to emerge so is likely bad idea in grand scheme
      • The fallout can take decades but it’s not sustainable to print money at a faster rate than the economy grows

    Trade idea

    • Since bond vol term structure is flat, buy long dated (10 year) vol to hedge against longer term seismic shift while levering coupons on CEFs, MLPs, REITs and/or sell puts in 1 to 3 years bond options since demographics will limit rate upside to 3-4%. Can lever the near dated trades while owning the vol protection. This is a version of long time spread since near-dated levering or outright option selling is all short vol.
    • Outright tail protection too expensive and path dependent to be relied upon