Journal of Finance and Economics
ISSN (Print): 2328-7284 ISSN (Online): 2328-7276 Website: http://www.sciepub.com/journal/jfe Editor-in-chief: Suman Banerjee
Open Access
Journal Browser
Go
Journal of Finance and Economics. 2019, 7(1), 42-47
DOI: 10.12691/jfe-7-1-5
Open AccessArticle

Determinants of Bitcoin Expected Returns

Frederick Adjei1,

1Economics and Finance Department, Southeast Missouri State University, One University Plaza, Cape Girardeau

Pub. Date: January 22, 2019

Cite this paper:
Frederick Adjei. Determinants of Bitcoin Expected Returns. Journal of Finance and Economics. 2019; 7(1):42-47. doi: 10.12691/jfe-7-1-5

Abstract

In this study, we investigate the relationship between Bitcoin mining technology variables and Bitcoin returns, using a GARCH-M model. Additionally, we examine the predictive power of the mining technology variables on future Bitcoin returns. We find that mining difficulty and block size are inversely related to Bitcoin returns. Additionally, our findings signifying that the higher the block size the lower the Bitcoin price and consequently the lower the expected return. Second, our findings show that mining difficulty and block size are robust predictors of future Bitcoin returns.

Keywords:
Bitcoin expected returns

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Satoshi Nakamoto. (2008). BitCoin: A Peer-to-Peer Electronic Cash System - Bitcoin.org, the bitcoin white paper.
 
[2]  Grinberg, Reuben. “Bitcoin: An Innovative Alternative Digital Currency.”Hastings Science & Technology Law Journal 4 (2011): 160-210.
 
[3]  Buchholz, Martis , Jess Delaney, Joseph Warren and Jeff Parker. “Bits and Bets Information, Price Volatility, and Demand for BitCoin”. Working paper.
 
[4]  Kristoufek, Ladislav “BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era.” Scientific Reports 3 (2013): 1-7.
 
[5]  Bouoiyour, Jamal andRefk Selmi What Does BitCoin Look Like? Annals of Economics and Finance, 16 (2015), issue 2: 449-492.
 
[6]  Balcilar, Mehmet, Elie Bouri, Rangan Gupta, and David Roubaud.” Can volume predict BitCoin returns and volatility?” A quantiles-based approach; Economic Modelling 64 (2017): 74-81.
 
[7]  Ciaian, Pavel , Miroslava Rajcaniova, and d’Artis Kancs. “The Economics of BitCoin Price Formation.” Information Systems and e-Business Management, 14 (2016), Issue 4: 883-919.
 
[8]  Lee, T.B. "These four charts suggest that BitCoin will stabilize in the future." Washington Post (2014), http://www.washingtonpost.com/blogs/the-switch/wp/2014/02/03/thesefour-charts-suggest-that-bitcoin-will-stabilize-in-the-future/
 
[9]  Nyberg, Henri. “Risk–return tradeoff in U.S. stock returns over the business cycle.” Journal of Financial and Quantitative Analysis 47 (2012): 137-158.
 
[10]  Fama, Eugene F, and Kenneth R. French. “Business conditions and expected returns on stocks and bonds.” Journal Financial Economics 25 (1989): 23-49.
 
[11]  Richardson, Matthew, and James H. Stock. “Drawing inferences from statistics based on multiyear asset returns.” Journal of Financial Economics 25 (1989): 323-348.
 
[12]  Hansen, Lars Peter. "Large Sample Properties of Generalized Method of Moments Estimators,” Econometrica 50.4 (1982): 1029-1054.
 
[13]  Cochrane, John H. “The dog that did not bark: A defense of return predictability.” Review of Financial Studies 21.4 (2008): 1533-1575.