Team Krugman vs Team Satoshi and the hunt for the epsilon

What happens when money turns into religion. An unrolled tweetstorm of more bite than technicality. More tweets and storms at @ecoinomia.

Let me just write another footnote on Team Krugman, Team Satoshi, the hunt for the epsilon, and why having these two camps of zealots dominate the discussion is so detrimental to the cryptosphere.

“Epsilon”, as I posted before, is a very small but nonzero probability of something very big and very profitable happening. In other words, it’s like a lottery ticket, except we don’t know the big payoff, the payday, or even if it’s going to happen at all.

Team Krugman and Team Satoshi are currently trying to dominate the discussion by pushing through their view that “epsilon = zero” (Team Krugman) vs “epsilon = one” (Team Satoshi) and roping in all kinds of technical or historical arguments.

But the simple reality is that this epsilon is with absolute certainty not one, it is near-certainly not zero, and in fact absolutely nobody knows what the true value of epsilon is. So pretending otherwise is not only bullshit but also reckless toxic (typically male) posturing.

Whether Bitcoin or any cryptocurrency will “change the world” (and reward the hodlers) or “go bust” (and expose the fraudsters) still depends on so many socio-econo-techno-polito-unpredicto factors that it is pointless to actually model its trajectory with any accuracy.

But we can have a look at the evidence roped in by both sides to see how absolutely terrible and driven by posturing rather than truthfinding it is.
Exhibit #1: the adoption trajectory. Right now both sides are busy posting historical trajectories to bolster their cases.

Curves, curves, curves. Source: me.

But at any state of ascendancy, whether this will turn into a simple successful adoption curve, whether it will crash down to earth, or whether it will simmer down to something in between is completely unsettled. If it weren’t econ would be easy.

Even during downturns, there is no way to predict whether they will persist or are only ephemeral. But it’s always the ones most fearful of the dark who are whistling the loudest. Those charts about concatenated boom-bust cycles look nice but tell us nothing about the future.

The only things they tell us: 1. boom-bust-cycles are bad regardless of future development, 2. everybody is still wildly guessing at what the epsilon is, 3. too many people still believe asset hodlership matters more than (true economic) transaction velocity.

The discussion about “fundamental technology” is even worse. The shared playbook works on the lines of defending the adequacy of ones own supported technology regime while picking up any piece of scrap anecdotal evidence to show how the other model must be!! fundamentally flawed.

Exhibit #2: Team Satoshi’s QE argument. Sorry, but Paul Krugman won that debate hands down against the runaway inflation types. Steering an economy is hard. I know Janet Yellen, Janet Yellen was a professor of mine. You folks are no Janet Yellens.

Exhibit #3: Team Krugman’s botched natural Ponzi argument. Even Bob Shiller used natural Ponzis as a metaphor for corrections of curves that would end up rising again. Bubbles show nothing other that high uncertainty leads to expectation and delivery being out of sync.

To wrap this up, in situations of high uncertainty, the demand for signals of certainty and for confirmation of ones biases is strong. But anyone who publicly professes to know with certainty where things are going does not have your best interest in mind.

Footnote to the footnote: the secret history of epsilon.

Another footnote to the footnote: Since we’re in stochastic dominoes territory now, the market epsilon for the Finney lottery has shifted from 0.2% to 0.07%. The conclusion that we are heading for 0% is tempting, but keep in mind each participant has their own individual epsilon.

Btw, as is typical for lotteries, this should be considered a serious overestimation probably by an order of magnitude. Markets, even sophisticated ones, learn to price high-risk, high-reward investments as a series of bloody nose cycles. Viz. spectrum auctions.

The original tweetstorm appeared on @ecoinomia. The text has been slightly edited and it might still evolve into a real essay. Oliver Beige is an industrial engineer turned economist (PhD Berkeley, MBA Illinois, MSIE Karlsruhe) who is focusing on how technologies like machine learning or blockchain might change the value creation between markets and enterprises.

I write about how technology shapes the world we live in.