🕙 24/7 Options🕙

Restricting trading between 9:30-4pm M-F is pure stupidity. It's market discrimination.

24/7 is the future

And our fastest way to get there is via crypto derivatives: on-chain markets for tokenized US equities and options.

🧵on OPTIONS MARKET-MAKING ON-CHAIN monkey graph credits: u/CalamariAce on WSB
Note: this thread is a collection of all the operational challenges and structural considerations required to bring a fully functional system of tokenized options on-chain.

Expect more questions than answers.
Because such a fully functional system doesn't yet exist.
PART 1: How "normal" options MM works

As traders we take a lot for granted. Options markets somehow "just work" in TradFi.

But how does price discovery actually work?
How do local updates propagate to rest of the options chain?
What happens to longs when shorts get liquidated?
Let's start with the MM's biggest problem: price discovery

e.g. TSLA Dec $1400 calls are initially quoted $35-38. A large whale buys. Quote moves to $36-39.

How much should the $1450-strike contracts move up by?
What about Jan $1400 calls?
Does the whole vol surface reshape?
Mechanically, prices move when market makers adjust their quote. Every adjustment is the result of either:
- a mean reversion hypothesis
or
- a momentum hypothesis.

Biggest inputs affecting which view the MM takes:
- real-time order flow
- breaking news (earnings, merger, etc.)
Absent breaking news (no reason to justify price shift) MMs tend to:
- Treat anomalous hits+lifts as flukes
or
- Take the other side of anomalous trades

After events (high volatility), MMs tend to:
- Widen quotes
- Stop quoting
or
- Quote asymmetrically, i.e. move the (mid)price
Next up: Margining

Each clearing firm has its own margin requirements & different ways of handling each of these key questions.
- How should collateral be denominated?
- What is the forced liquidation threshold?
- Who eats losses when the market blows past liquidation threshold?
Robinhood requires all short options positions to be collateralized by underlying stock. This forces shorts to instead sell covered calls (a different risk payout).
But if margin is posted in dollars, how much is enough?

And what happens to shorts when longs decide to exercise?
Apparently every options writer holds a hidden "call risk" that NOBODY talks about!

Namely, when TraderA decides to exercise a long call option, the OCC then calls up a random writer (TraderB) and forces them to unwind their short position equivalent to what TraderA exercised.
PART 2: Market-making for tokenized equity options (btw 9:30-4pm EST)

Good news: During market hours, price discovery on tokenized securities is a trivial problem.

No Black-Scholes.
No spline interpolation of vol surfaces.
Just need a robust fast oracle like SOL's @PythNetwork
What is @PythNetwork & why is it a groundbreaking step forward for tokenized options on chain?

Pyth bridges TradFi data into @solana every 400ms (vs 15s on ETH), i.e. on-chain MMs can simply call an API & get near-simultaneous quote updates across the entire options chain.
In other words, on-chain MMs would not need to do double-duty price discovery on a new isolated system, and arbitrageurs would not need to constantly arb between the two systems to lock in price consistency.

On-chain prices would simply "mirror" traditional exchanges' bid-asks.
Lots of problems can arise, however, if a slow oracle were in use:
- rapid price divergence between tradfi & defi market quotes
- tradfi front-running opportunities
- outdated margin thresholds based on a previous iteration's stale quote, leading to rampant on-chain liquidations
While price discovery is trivial, liquidity is not.
In fact illiquidity is the #1 problem tokenized equity platforms face today.

Takers don't want to trade b/c spreads are too wide; spreads are wide b/c makers don't want to make given low taker demand.

How to solve this 🐤🔄🥚?
To bootstrap liquidity, one method is to incentivize LPs/makers first.

Highly liquid derivatives markets exhibit these qualities:
- Constant uptime
- 2-sided liquidity provision
- Depth
- Tight spreads
- Ability to support LP delta neutral hedging strategies
. @dydxprotocol's LP Rewards program is a great model of successful liquidity boosting.

Below is the equation they use to assess how many reward tokens to give each LP.
- Constant uptime is rewarded by summing up binary counts of an LP's availability at each minute.
- 2 sided liquidity is emphasized by considering the MIN of liquidity provided btw bid- & ask-side
- depth & spread tightness is rewarded via min/max reward eligibility thresholds
Let's say we solve the liquidity problem.
"Odd-lots"/fractional options will be the next biggest hurdle.

Explanation: In TradFi, options trade in minimum lot sizes of 100x (representing 100 shares). In DeFi, the tokenized options would trade in arbitrarily small order amounts.
LPs running delta neutral strategies wouldn't be able to provide liquidity for a fractional "odd-lot" order on-chain (e.g. sell 25.3-lots of tokTSLA 1400) and subsequently hedge with the exactly matching inverse position on a TradFi exchange (e.g. buy 25.3 lots of $TSLA 1400).
PART 3: Market-making for tokenized equity options when markets close (aka the Wild West!)

Key Issues:
- Price discovery returns as a problem (no TradFi data source for the oracle to bridge)
- What happens at the next market open? Prices may diverge significantly overnight.
Solutions to the price discovery problem will vary depending on:
a) if there's a sole tokenized options exchange
vs
b) multiple low-liquidity exchanges

And in case (b):
i) if MMs can see depth on all other exchanges
vs
ii) if MMs can only see NBBOs on non-LPed exchanged
The "what happens at market open" problem is equally tricky.
- TradFi markets can jump at the open because of DMMs & auction market structure
- On-chain LPs don't know which way they'll jump & might not want to take the "snapping back" risk, thus decide to sit out during the MO
- Unfortunately if every LP decided to sit out, on-chain tokenized exchange(s) would have zero liquidity during each market open. What incentives make sense to prevent this?

- Should exchanges require extra collateral on overnight trades in case of a steep jump at next open?
End/

If you've ever wanted to trade US equities or options outside of market hours, OR if you want to get involved to make this a reality for every trader in every time zone of the world, then I want to talk to you!

My DMs are waiting for you with open arms!

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More from @FabiusMercurius

30 Oct
Yield Farming is a Misnomer

There. I said it.

Earning yield/ "LP"ing is marketed as "passive income" as if risk-free, but in fact that's a traitorously inaccurate sales pitch for what it ACTUALLY is:

Covered options writing.

An exposé on the real risks & returns👇.

🧵/
1/ People think it's like holding treasuries. It's not.

Returns on yield farming depend on:
- absolute returns of the underlying (aka beta)
- impermanent loss (aka relative volatility)
- fees & rewards (theta premium)
- capital concentration - @Uniswap V3 (strike selection)
Returns on treasuries (and safe/IG bonds) depend on:
- interest rates
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For high yield bonds, add:
- counter-party/default risk
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Clearly "yield" in TradFi and "yield" in DeFi look NOTHING alike.

LP yield is more like betting on options premium. Why?
Read 11 tweets
24 Oct
Designing an Exchange
(Order books, AMMs, RFQs)

Exchanges are the market's DNA. Details of their inner workings determine all downstream trading dynamics.

A 🧵 on the different exchange microstructures and their mechanisms for order matching & market-making.
👇
1/ There are 4 main ways for an exchange to provide liquidity:

1. via CLOBs, aka central limit order books
2. via bonding curve AMMs, aka automated market maker
3. via RFQs, aka requests for quote
4. via auctions

Each design has its strengths and tradeoffs.
Each design reflects a relative prioritization between:

- price discovery
- liquidity
- slippage
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- responsiveness to volatility
- capital efficiency for market makers
- manipulability
- composability
- defensibility
Read 25 tweets
17 Oct
Crypto Market Map 101
(aka a hierarchical DeFi-TradFi mapping)

If ur a:
- crypto newbie
- confused by who's who & what they all do
- dying for someone to draw parallels btw defi & tradfi infra
- crypto entrepreneur looking for opps

I made this map for u:
docs.google.com/spreadsheets/d…
DeFi vs Traditional Finance Infrastructural Comparison

from @mccannatron

i highly suggest you read Chris's whole blog post:
medium.com/racecapital/de…
Eth to Solana Mapping

also from @mccannatron
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2 Oct
🇺🇸🏦 America's Shadow Banks

With all this Debt Ceiling talk, here's another throwback:

What are shadow banks?
How did they spur the 2008 financial crisis?

"But shadow banks aren't a thing anymore, right?"
Wrong.

Today they underwrite more debt than regular banks.

Thread👇
1/ If it looks like a duck & quacks like a duck...

Is it a 🦆?

If a company moves money around and lends to other companies even (especially) when real banks refuse, then is it a bank?

In 2007, economist Paul McCulley named these things "shadow banks."

The name stuck around.
2/ What do they do?

4 things.

- Transfer credit risk: from loan originator to 3rd party
- Lever up: borrow $ to invest & make more $
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- Transform maturity: use short-term deposits to fund long term loans
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21 Sep
Post-Evergrande: China's Waterfall of Pain

China itself is one big Evergrande.
One big debt crisis.

For years massively over-levered shadow banks masqueraded as propcos, got drunk on credit, flirted w/ default & called for bailout like a late-night uber.

Contagion has begun
👇 https://twitter.com/rosetechnology_/status/14328496098613534
1/ How Evergrande is Actually a (Shadow) Bank

On the surface Evergrande is a propco. It has insatiable demand for capital cuz it needs to buy land. That's what propcos do.

But then Evergrande started stuffing its commercial paper into WMPs & selling it off to its own employees.
Let's be more explicit.

In June 2019, Evergrande plowed 13.2B¥ into Shengjing Bank, acquiring 36% stake in a literal lender.
Shengjing was on the brink of default. Tier 1 capital adequacy ratio was 8.52%, barely above regulatory req.

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18 Sep
🇨🇳Evergrande's Backstory🇨🇳

🌎 The world demands answers.

From Fortune 500 to 1.95 Trillion in debt: How did China's #2 real estate giant get to this point?

How much cash does it *actually* have?
Will there be a bailout?
Who's gonna get f*cked?

Here goes. Story time.
👇
1/ First, how bad is the current situation?

There's not much info on Evergrande's finances on the Western web (aka Google) so I had to dig through the Chinese web (aka Baidu).

This poster shows China's top 3 most indebted real estate co's in 2020:

#1 is Evergrande (@ 1.95T ¥!) #2 is Country Garden #3 is Vanke
2/ According to the company's 2020 annual report, 674B ¥ (35%) is interest-bearing debt, which means it incurs new interest liability of 180+M ¥ every day!

Comparatively, it only has 158B in cash to repay all its short term debt + interest which means...

Major defaults to come.
Read 15 tweets

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