Moontower #105

The way the term “edge” (or alpha”) is thrown around the asset management business, you’d think it grew on trees.

The most popular one in value investing is:

“Our edge is our willingness to look long-term”.

On the surface, it’s plausible. Having a different time horizon is certainly a source of edge if you can own it [HFTs carve a niche at the opposite end of the spectrum].

But I have my suspicions. They all say they are long-term. If retail only makes up 20% of the market with indexing making up more than 50%, is there enough short-sightedness going around to feed them? I don’t know. I do know that distracting clients from short-term results is self-serving even though it can be correct.

That’s the paradox. It makes sense to think long-term if you think your competition does not. But then your signal-to-noise is unusable. With weak signals, concentrated portfolios, and low turnover how do LPs know if the manager has an edge on a timeframe that’s suitable for making allocation decisions.

That is the topic of my latest post. It’s a bit longer than my typical posts and does a little Excel math. It begins:

In my indoctrination into trading the term “edge” was equated to the bookie’s “vig” or a casino’s “house edge”. This makes a sense since I started in this business as a market maker. The interview questions I faced were focused on mathematical expectation or expected value. For example, if someone offered you a game that pays you the number that comes up on a single die, what would you pay to play?

Read the rest…

Understanding Edge (Link)

The Money Angle

Real Talk On Options Trading (Link)

This is a cleaned up version of a “real talk” thread I did based on questions I get in my Twitter DMs about option trades. Novice traders/learners might find them discouraging but I think in the long-run knowing this now will help you plan your learning more efficiently.

There’s 3 large categories of using options. Each has a very different starting point. Be very aware which category your strategy targets.

  1. Options as expressions of directional axes

    If this is your strategy, then 95% of the work is upstream of your option implementation. Your fundamental work may uncover a forecasted distribution that disagrees with the option surface. Most DMs fall in this category and don’t realize it. Questions like should I sell the 5% put to buy the 10% put or whatever.

    I ask “what fundamental work have you done that suggests the surface is wrong?”

    For more depth, see Structuring Directional Option Trades (Link)

  2. Relative value volatility trading

    If you are doing this at home, may your god be with you. Correlation trading, IV vs RV, cross-sectional relative value. Do you understand funding, rates, and dividends? This is a trapdoor thru the Earth’s crust into a steaming pit of hot magma. And this just gets you to the R term in Black-Scholes which we hand-wave as a given so we can get to implied vol. Speaking of implied vol, are your IV computations even correct? Do you know how to clean vols for time and events?

    A clue to get you started:

    It’s Monday and the Friday straddle is $3.
    It’s Friday and the Thursday straddle is $3
    Both have 5 days to expiry. Your off-the-shelf model spits out the same implied vol in both cases.

    Uh oh.

    Welcome to the vol time vs wall time.

    This is the option trader’s version of accounting. It’s the foundation for measurement and cleaning data.

    The dashboard required to see what QVR’s Benn Eifert calls “disturbances in the force” requires expensive data and infrastructure.  And even then, you are trading for edges smaller than a bookie. Is your bankroll appropriately sized?  There is a good reason why most vol traders I know who go out on their own don’t do “volatility trading”. Instead they focus on more discrete bet types like special situations. SPAC trading is a recent example. You can also check out Kid Dynamite’s archive to see how an ex-institutional trader approaches markets as an independent.

  3. Using vol flows to generate directional alpha

    This is all the vanna stuff. It’s relatively new as the option market “tail wags dog” effect has amplified in the past few years. My own anecdotal experience is flows absolutely matter. Especially if options are priced too tightly ultimately providing more liquidity than the underlying. I’ve seen it in commods which is mostly the vol markets I trade. My own incorporation of it was understanding who held large chunks of OI and trying to anticipate players’ behavior on how they might manage around the greeks. Large hedging flows occur in oil and ags for example. Understanding their rhythm and triggers is important. Understanding how certain areas of the surface become “infected” is critical for survival. Although I never systematized my analysis, all discretionary vol traders always have a mental framework around “who’s holding the risk”. Accounts like @nope_its_lily@jam_croissant,  @SqueezeMetrics, and @HauVolatility are being methodical and public about how they do it.

    I link to them in the Moontower Volatility Wiki: Flow Tracking

    The major takeaway from all this is know the source of alpha you are using options to access. If you ask me about a single stock option trade, I’m just going to ask you about your fundamental research. That’s the hard part. If it’s done well, the option part is comparatively trivial.
    If you have an opinion on the vol, it better not be as naive as “well the realized vol is X or skew is Y”. You are pointing to info any donkey can easily see. Instead, you need a composite view which has seams nobody else can see.
    So #1 isn’t really about options. #2 is a game very, very few playing from home can play (@darjohn25 and a few in his sphere are people to follow). And for  #3, you know who to follow.

You can think of my view of option trading as a sub-category of the taxonomy @therobotjames outlines:

Broadly, there are 3 types of systematic trading strategy that can “work”.

In order of increasing turnover:

1. Risk premia harvesting
2. Economically-sensible, statistically-quantifiable slow-converging inefficiencies
3. Trading fast-converging supply/demand imbalances

His full thread.

Last Call

  • On Deck Investing Fellowship

    Kyla Scanlon asked me to speak at the first On Deck Investing cohort which will be taking place this summer. Registration is open until April 24th. Should be groovy. Find out more. (Link)

  • Insights From Not Boring’s Hypergrowth (Link)

    Packy McCormick’s ad-supported newsletter is 1 year old. He documented his approach to the business which has been extremely successful and innovative. It’s worth a full read because there’s a lot to digest. Some is surprising, some is confirming. He describes its “flywheel”, a term that is easy to dismiss as abused, but undoubtedly applies to writing and investing. I wrote my favorite takeaways as well some some commentary on it. You will find the original post linked as well.

From my actual life 

Yinh and I got Moderna vaccines this past week. My mom flew in for an overdue reunion. We haven’t seen each other since Dec 2019. She’s staying for the next 3 weeks and we are celebrating today with a pool party bbq. I like this year better already.

Leave a Reply