Bitcoin expert has compared coronavirus trends with the possible Bitcoin price movement and claimed that the stochastic modeling and other tools work perfectly in this case.
Balaji Srinivasan, who used to work at Coinbase and now writes for Nakamoto.com, claims that Bitcoin price can hit $100,000 after striking twice the important psychological level of $10,000.
The Nakamoto.com analyst claims that Bitcoin’s rally is pretty predictable if you look at the stats under a certain angle. Whether this is the correct comparison or not, but Balaji thinks that Bitcoin will reach $100,000 following the coronavirus dynamics:
In 2009, it was unlikely that BTC would cross $100k. But conditional on BTC having *already crossed* $10k, it was more likely to cross $100k.
On Dec 1, 2019 it was unlikely the virus would cross 100k cases. But having *accelerated* past 10k, it was more likely to cross 100k. pic.twitter.com/XzFvxKZbEC
— Balaji (@balajis) February 13, 2020
He compares the statistics of coronavirus spreading across the planet with the possible price action. People read news about Bitcoin, jump in, buy it, then tell a friend about it, they jump in, buy it, and so on. Bitcoin’s properties are pretty interesting, not some usual boring financial stuff, so people usually involve quickly.
He offers plenty of links to back his assumptions, including the link to Wikipedia pages of Excursion probabilities and Geometric Brownian Motions.
Some links:
1) BTC prices: https://t.co/QwqIFY7kIF
2) JHU dashboard: https://t.co/k2ZtXkevaQ
3) Geometric Brownian Motions: https://t.co/rFIQUUqtzP
4) SEIR[S]: https://t.co/QiTqFciubJ
5) Level crossings: https://t.co/Di8fTc7o0H
6) Excursion probabilities: https://t.co/M8sdhRE3V7— Balaji (@balajis) February 13, 2020
Geometric Motion and SEIRS Models Help in Bitcoin Price Prediction?
Bitcoin and coronavirus are somewhat different ‘asset types’. But the math laws can work even in such an unusual case, if you know what you are doing. Nikhil Krishnan asks Balaji over Twitter how can he compare such different things:
“Generally… why are you trying to compare these things? This feels like a very forced and contrived connection”
Srinivasan responds that he use stochastic modeling to look for a second into the possible future:
“Despite very different underlying dynamics, the general concept of “conditional on this improbable event having already happened, we need to update our probability of the future” is applicable.
Of course, the dynamics of prices & cases are different, but both are often modeled as stochastic processes: prices as GBMs, epidemics as SEIR[S]. At the beginning the parameters of these stochastic processes are unknown. But as data comes in, parameter estimates update.”
According to commentators, such a prediction looks more like an exercise in math than something real.
It's a good example of survivorship bias.
A baby boy at birth has a 1% chance of living to 100.
But once he makes it to 99, he has a 65% chance of living to 100.
— rcrsv (@rcrsv) February 14, 2020
Balaji wrote that the underlying dynamics are different, but the general idea is still applicable.
Bankers used to impress girls with their banking system terms knowledge until 2009. It wasn’t so effective, but now they explicitly declare that ‘blockchain’ is not something they fear, citing Andreas Antonopoulos and making price predictions that sound sweet in the maximalist’s ears.
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