One hot summer day in 4 BC, Greek mathematician Thales had an epiphany.💡
"There's an oversupply of olives this year!"
More olives 🔜More demand for olive presses.
Yet the market price hadn't changed.
"How do I arb this🤔?" thought Thales.
👇
1/ He couldn't afford to buy every olive press in town & no bank would lend him that much.
So he devised his own leveraged strategy:
Buy the rights to future equipment use today; resell at harvest season if price goes up.
And like that the world's 1st call option was born! 🫒
Here,
"option premium" was analogous to Thales' upfront borrow fee;
"strike" to his locked-in usage rate;
"expiry" to the 1st day of autumn.
When autumn arrived demand for olive presses indeed surged just like Thales predicted.
He then exercised his call options for a profit!🧠
2/ Fast forward to 1636 AD Holland.
🌷🌷 Tulip memes have infiltrated the land!
Suddenly this exotic bulb starts going for 10x the avg man’s salary!
Johannes the plumber couldn’t afford a whole 🌷so he took out a loan... then a 2nd mortgage... then borrowed against his house!
Investors began placing purchase orders months in advance, promising planters above-market prices.
But then came a supply glut.
Investors panicked. 🙀
First they tried to renege.
“JK! We don't want your🥀s anymore!”
It didn't work, so they said, “🤔Let's change the deal terms!”
“Instead of committing 100% to buying ur bulbs come springtime, I want the choice to buy only if spot price rises higher than my lock-in!"
They settled w/ a small upfront fee of 3% for this optionality.
Overnight, the tulip futures market transformed into a tulip options market
3/ Moving on to 1720 AD London...
The House of Lords had just granted the South Sea Company monopoly access to South America's slave trade.
Shares surged 10x from £128 to £1000 in just 6 months.
“Blimey!” cried our British ape ancestors. “South Sea to the moon 🚀🍗💎!!"
When the stock got too expensive, they turned to options.
When options got too expensive, they invented options on options.🤯
OK like.. 🧠WTF!?
How do u price such a damn thing?!
Today "compound options” come in 4 flavors
- call on call
- call on put
- put on call
- put on put
The table below shows the payoff of each compound option type.
Now why would anyone buy such a #@%! beast?
Example:
$HOOD is @ $55.
$65-strike Dec 17 calls are @$13.
Say I want this call option but can't afford it. I might then buy $10-strike Sept 17 puts on such calls for <$5.
4/ Fast forward to 1791 New York 🇺🇸
Finally the birth of the US options market!
At first there was no centralized exchange. Everything was OTC; brokers would manually call up & match buyers w/ sellers.
3 major problems arose
- No standardization of pricing
- Illiquidity
- Fraud
Arbitrage was rampant.
The market needed standardization. Then,
“💡I've invented a solution!” said a big-brained man named Russell Sage. "Put-call parity!"
Put-call parity is the idea that buying 1 call & shorting 1 put creates the same risk payoff as owning 1 underlying share.
So the prices of all 3 assets are bound to reconcile according to this inter-relationship.
Officially, the equation is:
C + PV(x) = P + S
where:
C = price of the European call option
PV(x) = present value of the strike price (x)
P = price of the European put
S = spot price
Though Sage solved standardization (sorta), liquidity remained a huge headache.
Early options traders were mostly farmers and corporates looking to hedge agricultural exposure. Retail volume was still hard to access.
The market needed a centralized exchange with listed options.
5/ Some startups launch from a basement; others from a garage. CBOE launched from a smoker’s lounge!
On opening day in 1973, it could only trade a scant 16 stocks. Only calls, no puts.
Nevertheless, trading activity exploded.
By June '74, avg daily volume surged past 20,000.
6/ Then the SEC tried to intervene.
“What’s this madness?” said Gensler--JK he was still an awkward teen w/ braces back then.
Whoever his square counterpart was basically said, “we need to conduct a complete audit of all US option exchanges & write at least 42 more 69-pg docs!”
They tried to put a moratorium on all future options listings, but Wall St. resisted & the people revolted.
Finally they gave up & let CBOE add 25 more stock underliers plus puts!
[Spoiler alert: Chuck Rhoades loses every time guys.]
Some other major milestones followed!
1983:
Index options were born! First S&P 100 (OEX), then S&P 500 (SPX). Today more than 50 different index options are listed & billions of contracts have been traded!
1990:
LEAPs (long-dated options with expiries up to 3 years) were born!
7/ Today it’s real GOOD in the $HOOD!
As of Aug 2021, $15.3 billion of options contracts trade daily on US exchanges!
😲This democratization of the market was spurred by:
- Zero-commission
- WSB
- COVID pushing people to take charge of their own financial destiny.
What's next?
• • •
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Gary Gensler is out for crypto blood🩸.
Chinese Edtech ADRs are eating Wall Street.
... It's a crazy unpredictable market out there!
Through all this ruckus, here are 8 consumer fintech trends that MUST HAPPEN this decade.
👇
1/ Access to secondary markets
The delineation btw public & private is a Berlin Wall --
Getting torn down from every angle.
It’s not just SPACs & direct listings lowering the barrier to "go public."
Tiger Cap is now pouncing on every 🔥 Silicon Valley deal from seed to seriesF.
Retail investors are already demanding pre-IPO access; soon they’ll want to trade Stripe, Ramp, Openstore, etc. long before these companies are ready to go public.
How will retail gain access?
I see 3 ways.
a) Via ETFs containing private underliers
e.g. destiny.xyz
A friend of mine has zero finance background, never reads Buffett and makes 40% returns trading.
How?
He trades sneakers.
Turns out sneaker-flipping shares a lot in common with value, macro, & algo trading.
Plus there's more alpha.
🧵👇
1/ Market Overview
$2Bn was the size of the US sneaker aftermarket in 2019.
$30Bn is how big it will be in 2030.
Today 4% of all sneakers at release get purchased for immediate resale.
Why does this aftermarket opportunity exist? Why doesn't Nike/Adidas just capture the alpha?
Nike/Adidas are playing the Ferrari game: i.e. release a very limited supply to appeal to exclusivity & watch as the people bid up their kidneys.
Because of such tight finite supply, sneakerheads are the only remaining sellers after the initial drop & they get to set the market.
$HOOD/Robinhood's IPO is tomorrow.
Here's my prediction & how I'll play:
TLDR: I won't. The risk-reward just ain't right.
1/ Best prediction market to get color on retail sentiment is @FTX_Official's tokenized $HOOD/USD.
Left side shows last 1 month. Right shows last 5 days.
What happened on June 19? Why the MASSIVE plunge?
That's when $HOOD announced a price target of $38-42 per share. Before that, retail had predicted $80+! Clearly no one cares for valuation here; the marginal buyer AT THE OPEN is price-insensitive which means downhill from there.
2/ Institutions also gonna sit this one out.
Why? Well here's how IPOs normally work (credit: @matt_levine)
Hedge funds get exclusive access to buy a new stock the day before it trades openly. They buy low & flip it higher the next morning to price-insensitive retail FOMOers.
Unfortunately I read this too late. I learned the hard way that u gotta find product-PROMISE-market fit first.
The longer ur deal cycle, the costlier it gets to skip validation. Mine was 9-12 months!
Each week I write a 🧵about investing, startups, or a cool market segment. All of it is knowledge my mentors & friends have taught me over the years.
🙏💗Now I'm passing it forward.
Here's a megathread of all past & future 🧵s. I'll be updating as we go. If you <3, plz share!
👇
1/ 💸 Jim Simons’ Playbook: King of Quant 💸
90% of active managers fail to beat the market, but Medallion boasts >40% annualized returns.
For the last 10 yrs, hedge funds swarmed at "alternative data" like pigeons at bread crumbs. Why? What exactly constitutes alt data & does it actually generate investment alpha?
👇
1/ What is it?
"Alternative data" is just a fancy term for data that doesn't appear on a 10-K/Q or earnings transcript.
Things like foot traffic at a retail store or credit card orders at a restaurant. Such data helps hedge funds predict earnings better (supposedly, at least).
2/ What are some common data sources?
App usage-- # of downloads over time is used to predict MAUs/DAUs & forward adoption rate; reviews also used to gauge product quality
Supply chain & logistics-- used to predict inventory & sales bottlenecks, pricing/bargaining power, etc.