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Whether there's anything like an equilibrium in cryptoasset markets where there are no underlying fundamentals is debatable. While there's no book price, PoW coin prices might be rationally describable in terms of (average_estimated cost of energy + cost per GH/s + 'speculative value')

A proxy for energy costs, chip costs, and speculative information

Are there standard symbols for this?

Can cryptoasset market returns be predicted with quantum harmonic oscillators as well? What NN topology can learn a quantum harmonic model? https://news.ycombinator.com/item?id=19214650

"The Carbon Footprint of Bitcoin" (2019) defines a number of symbols that could be standard in [crypto]economics texts. Figure 2 shows the "profitable efficiency" (which says nothing of investor confidence and speculative information and how we maybe overvalue teh security (in 2007-2009)). Figure 5 lists upper and lower estimates for the BTC network's electricity use. https://www.cell.com/joule/fulltext/S2542-4351(19)30255-7

Here's a cautionary dialogue about correlative and causal models that may also be relevant to a cryptoasset price NN learning experiment: https://news.ycombinator.com/item?id=20163734

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