Cryptocurrency Value Formation: An Empirical Analysis Leading to a Cost of Production Model for Valuing Bitcoin

By Adam S. Hayes. Mediterranean Conference on Information Systems, 2017

385 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/2ba63113a5675ebb6bb58d5f261c6117f95cb379

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Citations in the corpus

Are cryptocurrencies connected to forex? A quantile cross-spectral approach (2019, background): “Hayes (2017) empirically confirmed that the marginal cost of mining one Bitcoin is very close to the Bitcoin price.”
Bitcoin price and its marginal cost of production: support for a fundamental value (2018, background): “…that the average rate of electricity worldwide accounting for both residential and commercial rates is approximately USD $0.135 per kWh.5 Following Hayes (2016), the (marginal) cost of production per day, Eday per unit of mining power can be expressed as follows: Eday¼ ρ=1000ð Þ $=kWh WperGH=s…”
Spillovers between Bitcoin and other assets during bear and bull markets (2018, methodology): “We also included crude oil and energy prices in the analysis, given the empirical evidence that Bitcoin mining consumes considerable oil and energy1 (Hayes 2016).”
Cryptocurrencies as a financial asset: A systematic analysis (2019, methodology): “…Data Source Selected Controls N 67 Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing Bitcoin Hayes 2017 Price Production Cost Regression Model Crosssection coinmarketcap Market Structure 66 68 Informed trading in the Bitcoin market Fenga et…”
Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin? (2019, background): “…determined by a unique set of non-financial and non-economic variables that include social sentiment (Kristoufek, 2015; Bouoiyour and Selmi, 2015; Polasik et al., 2015), energy prices (Hayes, 2017), user anonymity (Ober et al., 2013), computer programming enthusiasts (Yelowitz and Wilson, 2015).”
Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting (2019, background): “These include the Global Financial Stress Index (Bouri et al., 2018b), global and Chinese economic policy uncertainty (Demir et al., 2018), and crude oil (Hayes, 2017).”
Price manipulation in the Bitcoin ecosystem (2018, background): “Additionally, Hayes constructs a model for determining the value of a bitcoin-like cryptocurrency by calculating its cost of production [10].”
Return, volatility and shock spillovers of Bitcoin with energy and technology companies (2018, background): “Pricing for new projects is so favourable for renewables that worldwide in 2017 more solar was installed than any other fossil fuel energy source (https://www.unenvironment.org/news-and-stories/press-release/bankingsunshine-world-added-far-more-solar-fossil-fuel-power). et al., 2017; Hayes, 2017).”
Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions (2016, result): “A similar finding has been shown by Hayes (2016).”
Sustainability of bitcoin and blockchains (2017, background): “The bitcoin mining hardware has seen four generations [19 ,20,17], see Table 1.”