Fantazzini, Dean and Kolodin, Nikita (2020): Does the hashrate affect the bitcoin price? Forthcoming in: Journal of Risk and Financial Management (2020)
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Abstract
This paper investigates the relationship between the bitcoin price and the hashrate by disentangling the effects of the energy efficiency of the bitcoin mining equipment, bitcoin halving, and of structural breaks on the price dynamics. For this purpose, we propose a methodology based on exponential smoothing to model the dynamics of the Bitcoin network energy efficiency. We consider either directly the hashrate or the bitcoin cost-of-production model (CPM) as a proxy for the hashrate, to take any nonlinearity into account. In the first examined sub-sample (01/08/2016-04/12/2017), the hashrate and the CPMs were never significant, while a significant cointegration relationship was found in the second sub-sample (11/12/2017-24/02/2020). The empirical evidence shows that it is better to consider the hashrate directly rather than its proxy represented by the CPM when modeling its relationship with the bitcoin price. Moreover, the causality is always uni-directional going from the bitcoin price to the hashrate (or its proxies), with lags ranging from 1 week up to 6 weeks later. These findings are consistent with a large literature in energy economics, which showed that oil and gas returns affect the purchase of the drilling rigs with a delay of up to 3 months, whereas the impact of changes in the rig count on oil and gas returns is limited or not significant.
Item Type: | MPRA Paper |
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Original Title: | Does the hashrate affect the bitcoin price? |
Language: | English |
Keywords: | Bitcoin; energy e�ciency; mining; hashrate; bitcoin price |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E41 - Demand for Money E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E42 - Monetary Systems ; Standards ; Regimes ; Government and the Monetary System ; Payment Systems E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E47 - Forecasting and Simulation: Models and Applications E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E51 - Money Supply ; Credit ; Money Multipliers G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation |
Item ID: | 103812 |
Depositing User: | Prof. Dean Fantazzini |
Date Deposited: | 03 Nov 2020 10:23 |
Last Modified: | 03 Nov 2020 10:23 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/103812 |