Notes from PlanB podcast
These are the high-level notes that I took from the PlanB podcast with Stephan Livera. FASCINATING podcast and a must-listen event. PlanB Stephan Livera — please let me know if I missed something or mis-stated something
— — — — — notes below — — — — —
Opening Comments
Professional finance background He watched BTC go from $100 to $1000 but waited until 2015 to make first investment 2019 — feels like 2015 — very positive environment
Influencers? Nick Szabo, Adam Back, Satoshi
“it’s all about digital money” — better money = better trade = better allocation — bitcoin will bring the next renaissance
Favorite Satoshi Quote — “As a thought experiment, imagine there was a base metal as scarce as gold but with the following properties: — boring grey in colour — not a good conductor of electricity — not particularly strong, but not ductile or easily malleable either — not useful for any practical or ornamental purpose and one special, magical property: — can be transported over a communications channel If it somehow acquired any value at all for whatever reason, then anyone wanting to transfer wealth over a long distance could buy some, transmit it, and have the recipient sell it.” Satoshi
Writers? John Nash — nobel prize winner — game theory — money is like a technology. Hayek — nationalization of money. Milton Friedman — predicted rise of something like bitcoin in 1999. Saifedon’s book — stock to flow ratios.
Stock to Flow — Digging into the Details
Digital scarcity to unforgeable costliness to stock-to-flow Scarce — hard to mine (proof of work, hash rate) — decentralization The key → Saifedean made scarcity quantifiable using stock to flow ratio
Definitions and Examples:
Stock is the current stockpile of something Flow is the yearly production
Stock/Flow = stock to flow ratio Flow/Stock = inflation rate or money supply rate
eg. Gold — stock = 185k tons & yearly flow of 3k tons = 62 S2F eg. Silver — stock = 71k tons & yearly flow of 25k tons = 3 S2F
Paladium, platinum have S2F of basically zero Generally rare to have S2F above 1 for anything
Value is derived from utility when S2F <1 Monetary assets have S2F >1
Bitcoin current stock of 17.5M — flow of about .7M per year = 25 S2F S2F of bitcoin and silver were very close as well as their value
The halvings become very important — every 4 yrs These double the S2F at every halving so:
In 2020, S2F will go to 50 In 2024, S2F to 100 In 2028, S2F to 200 and so on, doubling S2F every halving
When he first plotted S2F, he saw nothing with linear scale But using log scale he saw this perfect straight line Used color overlay to indicate ‘months to next halving’
3 distinct areas in his S2F chart: 1) before first halving 2) after the first halving 3) after second halving (current period)
What is the theoretical pricing based on S2F model?
At last all time high (nov/dec 2017) , $3,700 model price (so at $19k it was overbought) (on podcast, planB said $37,000 but I think he meant $3700) Current pricing based on model is $6000 price Next halving 2020 is $50000 price All time high could be 3–10x higher than that Halving 2024 model price is around $400,000 each
Model price is simple — but actual market with fear/greed changes (over and undershoots) Overshoots historically 3–10x Undershoots historically 50% maximum So current bottom is modeled at $3000
Overshoots on next bull run (model of $55k value) could overshoot to $100k+ and then could undershoot to $25000 (50% pull back)
Knowledge is not given equally — Austrian school of economics
You can clearly see that the halving was not priced in the last 2 times so best guess is that the price isn’t factored in now (yet), assuming un-equal knowledge (eg — many folks don’t know about the halving yet)
Black and Scholes Model from 1973 — arbitrage price differences but people had to learn it, digest it and believe it so both folks traded for 10 yrs on their publicly available model until others learned/believed it
Can we predict with just 2 samples?
— go to the model — if you just used the first 4 years of data, you would have exactly the same results — but yes, additional halving data would increase confidence in the model — back testing is useful — only 10 years of data available
A random walk down wall street discusses curve overfitting? do we see a pattern that actually isn’t a pattern?
PlanB has an AI background and so yes you have to be careful With linear regression, the overfitting isn’t too much of a risk There might be other issues though Eg — price data before 2010 is questionable Eg— 10000 BTC for $41 of pizza Price before 2010 is found by data archeology So Rsquared would be down from 95 to 92 if you removed those 2 data price points
Institutional money is coming to bitcoin but we have a long way to go
People in the US must not understand 0 interest on savings account or even have to pay, then you might be looking for plan b
Some of the bitcoin investment might come from gold and silver
Active vs Passive Debate?
Hard to outperform the market — unless you have info or models that others don’t have Stick to passive You can do TA on bitcoin and try to trade on tops and bottoms but he prefers passive (buy/hold)
Bitcoin Allocations?
Depends on the specific case Difficult to answer Don’t invest more than you are willing to lose Small probability that it’ll go to zero (although very small) DOYR — lots of scammers so be careful — shitcoins If you are still interested and are a millionaire, get 1 to 10 BTC For institutions, it’s a different game — research the best performing asset
Bitcoin is the biggest asymmetrical bet of our lifetime
Take some profits — nothing wrong with that — you gotta live Survive the next bear market If something goes 10 to 100x, take some profit If bitcoin overshoots to $100k or $200k, he’ll take some profits You could put in 1% to 10% of your money but bc it’s asymmetrical, your return could be quite high
Suppose QE doesn’t go well
You should have a plan b Arbitrage is possible that can earn you a risk free return — it might be out there That’s the next step in bitcoin’s growth Financial arbitrage between fiat world borrowing against negative interest rates He’s trying to discover that arbitrage opportunity
The Big Short — movie is a must see
Great example that some people saw it coming and had a plan to take advantage of it
All his scripts are on GitHub
