2018/06/19 by George Bissias, Bissias, George, Brian Neil Levine +3
Business, Management and Accounting · Computer Science · Decision Sciences · #Auction Theory and Applications #Blockchain Technology Applications and Security #Cryptography and Security (cs.CR) #Digital Platforms and Economics #FOS: Computer and information sciences #FinTech, Crowdfunding, Digital Finance
paper · pdf · doi:10.48550/arxiv.1806.07189
openalex publication_date 2018/06/19 · openalex created_date 2022/09/21 · openalex updated_date 2026/07/28
Abrupt changes in the miner hash rate applied to a proof-of-work (PoW)\nblockchain can adversely affect user experience and security. Because different\nPoW blockchains often share hashing algorithms, miners face a complex choice in\ndeciding how to allocate their hash power among chains. We present an economic\nmodel that leverages Modern Portfolio Theory to predict a miner's allocation\nover time using price data and inferred risk tolerance. The model matches\nactual allocations with mean absolute error within 20% for four out of the top\nfive miners active on both Bitcoin (BTC) and Bitcoin Cash (BCH) blockchains. A\nmodel of aggregate allocation across those four miners shows excellent\nagreement in magnitude with the actual aggregate as well a correlation\ncoefficient of 0.649. The accuracy of the aggregate allocation model is also\nsufficient to explain major historical changes in inter-block time (IBT) for\nBCH. Because estimates of miner risk are not time-dependent and our model is\notherwise price-driven, we are able to use it to anticipate the effect of a\nmajor price shock on hash allocation and IBT in the BCH blockchain. Using a\nMonte Carlo simulation, we show that, despite mitigation by the new difficulty\nadjustment algorithm, a price drop of 50% could increase the IBT by 50% for at\nleast a day, with a peak delay of 100%.\n