Beautifully Opinionated
Moontower #214
This issue:
An update on moontower.ai
Financial literacy for kids (ie Kiyosaki without the brainworms)
Insights from Fortune's Formula
How skewed returns distort mean-variance intuition
Resources for option traders and quant job seekers
Friends,
An update on moontower.ai:
We are in the midst of doing private demos with professionals for initial rounds of feedback/iteration before we start inviting the waitlist to sign up for the beta. The feedback from pros has been incredibly flattering which is cool but also just serves as more fuel to make it better — I’d rather commit harikari than underdeliver. And I do caveat that it’s an MVP that we will iterate fast on. As Emi likes to remind me: “if you are pleased with your launch product, you shipped too late.”
A reminder who moontower.ai is for:
The software is geared towards a lop-sided barbell:
Retail prosumers who use options already (small market) and
professional money managers who use options but are not “option-natives” (bigger market). Think the RIA who overlays options on behalf of their pool of clients or the fundamental/macro trader that doesn’t have access to a wizard option strategist on staff to help them make more informed choices.
What we’ve learned from these sessions:
Many of the pros have bits and pieces of these tools but haven’t seen them put together in such a coherent way. I don’t expect the hardcore option pros to sign up — they have infrastructures — but many had never seen the tools presented this way. They walked away with new ideas to copy into their own analytics. I encourage it.
Our friend @therobotjames reaction is likely to be our tagline:
"Beautifully opinionated”
The tool is a layer built on top of conventional analytics. It has a point of view and a progression. These tools are the survivors of a decades-long evolutionary tournament for what deserves real estate on my monitor.
The challenge with any visualization is balancing the desire to bring multiple dimensions into a 2d or 3d plane without raising the cognitive load commensurately. Combining the lens of a vol trader with your pre-existing trade ideas and contexts is a going to be a major unlock. You will learn not only the advantages of this lens but the pitfalls. The expected moontower candor about trade-offs, decision-making, and relative value is dyed into the presentation and supporting education.
This is not about getting-rich-quick. It’s not suitable for people who don’t know options at all. There are places that help your option journey from zero-to-one (and to be clear they can only help you — most of the effort will come from you — this is a language and a craft) but that’s not moontower at this time.
This is about helping serious investors, retail or pro, make better choices in option selection and trade expressions. And as a free byproduct, I’m certain it will make you smarter.
🌔🌒🌑Join the waitlist here: https://app.moontower.ai/access
In February, we will start admitting folks in the queue in cohorts to smooth onboarding and debugging as the user base gradually increases.
There are close to 1,100 people in line but if you refer others you can make sizeable jumps because who doesn’t like a fun game.
Financial Literacy for Kids
On Wednesday, a friend and I hosted 30 kids ranging from age 7 to 13 for Financial Literacy session I. Parents had drinks and pizza in the adjacent room. We kept it fun and highly interactive. No grown ups standing in front of a room. The feedback was overwhelming — the kids not only learned but had a blast.
You can do this for your kids’ friend groups too.
I’d describe it as “Kiyosaki without the brainworms”:
🐖Financial Literacy #1: Savings & Compounding (lesson plan)
A summary of the flow:
Start
why we need money —>
why we need savings —>
how do you get money —>
The floor and ceiling on savings (your savings don’t start until you cover your costs while savings from wages are capped by the number of hours in a day) —>
how to increase your savings rate (earn more per hour — even when your sleeping via investing or business ownership) —>
how compounding grows your savings
End
If you seriously decide to do this in your community, I’m happy to offer tips.
A few canned ones:
One tricky thing was the wide 7-13 age range. Littles run out of gas by 7:30pm and fractions are hard or inaccessible to most...but the 9+ group loved the compounding riddles. When I asked who wanted paper to do a math problem I didn't expect to get mobbed. Something I learn over and over — give kids credit. They want to be stimulated.
We had prizes for right answers and some kids were so on point we had to adlib some timed questions to cull the herd because we didn't have enough prizes.
No standing in front of the room. Get on their level. Silly is good but be quick to shut down “bottle flipping” distractions or any intra-group condescension. You are trying your best to meet every kid where they are. Also, not all kids are comfortable speaking up, it’s on you to make the environment inclusive the best to your ability as opposed to getting carried away with the energy of the dominants (much of that energy is insecure competitiveness that kids are understandably still navigating — but then again, you’ve certainly met adults wearing the same masks. They’ve just hardened into a “personality”).
We opened the discussion of compounding with this
1. You deposit $100 at 10% interest. You pocket the interest at the end of each year. Repeat for 3 years
2. You don't remove any money until 3 years elapses.
How much do you end up with in each case?For the more mathy questions we'd let them work out the questions on paper and work in groups if they wanted.
It took 75 minutes to do the whole lesson.
Money Angle
I’m about 60% through William Poundstone’s Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street.
It’s a gripping narrative full of 20th century trivia that ties together the birth of information theory, some of the greatest scientific minds of the 1900s, the rise of quantitative finance, and the role of organized crime. These topics come alive in a fresh, memorable way when discovered through the lens of its colorful characters.
It chronicles the history of the efficient market hypothesis (MIT, U Chicago, Paul Samuelson). You can organize its conclusion around this excerpt:
There is much truth in the efficient market hypothesis. The controversy has always been over just how far the claim can be pressed. Asking whether markets are efficient is like asking whether the world is round. The best way to answer depends on the expectations and sophistication of the questioner. If someone is asking whether the world is round or flat, as fifteenth-century Europeans might have asked, then "round" is a better answer. If someone knows that and is asking whether the earth is a geometrically perfect sphere, the answer is no.
A few ideas that struck me:
An industry uses academic research to protect itself from…academic research
In 1959, Harry Markowitz published his famous book on Portfolio Selection. Everyone in finance read that, or said they did. Financial advisers responded to Markowitz's model. They were growing aware of this new and threatening current in academic thought: the efficient market hypothesis. Markowitz demonstrated that all portfolios are not alike when you factor in risk.
Investopedia aside:
The efficient frontier is the set of optimal portfolios that offer the highest expected return for a defined level of risk or the lowest risk for a given level of expected return.
Poundstone continues:
Therefore, even in an efficient market, there is reason for investors to pay handsomely for financial advice. Mean-variance analysis quickly swept through the financial profession and academia alike, establishing itself as orthodoxy.
The Problem With Markowitz
1) Indecision
The Hamlet-like indecision of mean-variance analysis
When portfolios are equal on the efficient frontier, the investor’s risk appetite to decide. Unsatisfying.
2) Only useful for single period analysis
Most people do not invest this way. They buy stocks and bonds and hang on to them until they have a strong reason to sell. Market bets ride, by default. This makes a difference because there are gambles that look favorable as a one-shot, yet are ruinous when repeated over and over. Any type of extreme "overbetting" would fit that description.
(emphasis mine)
Standard mean-variance analysis does not treat the compounding of investments. It is, you might say, a theory for Kelly's dollar-a-week gambler. But as the wealth to be amassed by compounding is so fantastically greater than can be achieved otherwise, a practical theory of investment must largely be a theory of reinvestment.
A solution to both problems
Indecision
I made up this example inspired by a demonstration in the book.
Consider 2 investments that each have 10 possible discrete returns. The balanced one and the skewed one.
Simple mean-variance metrics will mislead you into thinking the skewed asset is superior. It has a
higher return
lower volatility
cheaper straddle price
higher Sharpe ratio
But the so-called “third moment” of the distribution (the skew) cannot hide from the geometric return which leaves no ambiguity about which investment is superior for a long-term hold.
Aside for masochists
The closer an asset’s return distribution looks to a bell-curve, the closer the straddle price will approximate 80% of the volatility. But when the straddle value is less than .80 of the volatility, you know there is skew or outliers lurking. If you are inspecting an asset’s returns for the first time, a quick trick is to compute the ratio of MAD to Volatility to see if it’s less than .8
A place where this is very handy is in looking at the price changes in inter-month future spreads. If you trade options on them this has important ramifications for pricing. But the lessons extrapolate.
If you need a refresher on MAD and straddles see:
Multi-period
In my contrived example, you are bound to get a “whammy” if you keep pressing.
Poundstone writes:
When you try to apply Markowitz theory to compounding, the results can be absurd. One of Ed Thorp's theoretical contributions to the Kelly criterion literature is a 1969 paper in which he demonstrated the partial incompatibility of mean-variance analysis and the policy of maximizing the geometric mean. Thorp closes his article by declaring that "the Kelly criterion should replace the Markowitz criterion as the guide to portfolio selection."
Perhaps no economist of the time would have dared such a heresy. It seems unlikely a major economic journal would have published such talk. Thorp's article appeared in the Review of the International Statistical Institute. Probably few economists saw it. In any event, few economists had heard of John Kelly. That was about to change.
Oft-forgotten history
Defense of Markowitz
Markowitz devoted a chapter of Portfolio Selection to the geometric mean criterion (possibly the most ignored chapter in the book) and cited Latane's work in the bibliography. Markowitz was virtually the only big-name economist to see much merit in the geometric mean criterion. He recognized that mean-variance analysis is a static, single-period theory. In effect, it assumes that you plan to buy some stocks now and sell them at the end of a given time frame. Markowitz theory tries to balance risk and return for that single period.
The insights derived from the Kelly Criterion have a complex history
Because of this complex lineage, the Kelly criterion has gone by a multitude of names. Not surprisingly, Henry Latané never used "Kelly criterion." He favored "geometric mean principle." He occasionally abbreviated that to the catchier "G policy" or even, simply, to "G."
Breiman used "capital growth criterion," and the innocuous-sounding "capital growth theory" is also heard. Markowitz used MEL, for "maximize expected logarithm" of wealth. In one article, Thorp called it the "Kelly[-Breiman-Bernoulli-Latané or capital growth] criterion." This is not counting the yet-more-numerous discussions of logarithmic utility.
This confusion of names has made it relatively difficult for the uninitiated to follow the idea in the economic literature. The person most shortchanged by this nomenclature is probably Daniel Bernoulli. He had 218 years' priority on Kelly. The unique and unprecedented part of Kelly's article is the connection between inside information and capital growth. This is a connection that could not have been made before Shannon rendered information measurable. Bernoulli considers a world where the cards are on the table, so to speak, and all the probabilities are public knowledge. There is no hidden information.
Money Angle For Masochists
is a pro option trader I demo’d moontower.ai for. I asked to show it to him because I find his approach and experience resonant. He writes about trade ideas and structuring. His perspective will be familiar to discretionary option traders whose theses sprout from a relative value vol lens.
He handpicked and unpaywalled these posts so I can share them here:
In our discussion, he said something in passing that I deemed profound.
Paraphrasing:
Being a retail trader vs working for a prop shop requires the individual to put extra effort into professionalizing their process. In essence, you must avoid lazy habits that insidiously emerge from a blurred line between work and personal. It’s an idea that is more pertinent in the era of WFH.
He uses writing as a way to impose a disciplined boundary. He publishes several times a week and I can totally see how the cadence can help switch one into work mode.
I gently suggested that a post about this idea would find an eager audience.
He turned it around in a matter of hours. Enjoy:
TikToker Sarah Wu posted a nice trove of trading content especially targeting job seekers. I added some of it to the QuantCodex as well.
…and if you were curious what trading interns get paid 💰💵🤯
☮️
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I'm happy to see that you are focusing on cognitive load. Way too many tools out there focus on adding one more - indicator, visualization, etc., to the point where the trader has to wade through so many things, they are, on net, not able to process any more than they could w/o the tool.