This resource stands on the shoulders of research by many others who
are curious about Bitcoin and the Satoshi Nakamoto persona. Here you’ll
find a listing of resources that this researcher has studied since first
becoming interested in the topic in 2017.
Research papers
Gur Huberman, Jacob D Leshno, Ciamac Moallemi, Monopoly without a
Monopolist: An Economic Analysis of the Bitcoin Payment System, The
Review of Economic Studies, Volume 88, Issue 6, November 2021, Pages
3011–3040, https://doi.org/10.1093/restud/rdab014
Several studies have been published across a range of academic
journals exploring the economics and finance aspects of Bitcoin and
related cryptocurrencies.
Communications of the ACM
Ittay Eyal and Emin Gün Sirer. 2018. Majority is not enough: bitcoin
mining is vulnerable. Commun. ACM 61, 7 (July 2018), 95–102. https://doi.org/10.1145/3212998
Marcin Andrychowicz, Stefan Dziembowski, Daniel Malinowski, and
Łukasz Mazurek. 2016. Secure multiparty computations on Bitcoin. Commun.
ACM 59, 4 (April 2016), 76–84. https://doi.org/10.1145/2896386
Edoardo Rainone, Real-Time Identification and High-Frequency
Analysis of Deposits Outflows, Journal of Financial Econometrics, Volume
22, Issue 4, Fall 2024, Pages 868–907, https://doi.org/10.1093/jjfinec/nbad012
Peter Reinhard Hansen, Chan Kim, Wade Kimbrough, Periodicity in
Cryptocurrency Volatility and Liquidity, Journal of Financial
Econometrics, Volume 22, Issue 1, Winter 2024, Pages 224–251, https://doi.org/10.1093/jjfinec/nbac034
Leon Li, Carl R Chen, When Safe-Haven Asset Is Less than a
Safe-Haven Play, Journal of Financial Econometrics, Volume 22, Issue 4,
Fall 2024, Pages 808–838, https://doi.org/10.1093/jjfinec/nbad009
Dillon Huddleston, Fred Liu, Lars Stentoft, Intraday Market
Predictability: A Machine Learning Approach, Journal of Financial
Econometrics, Volume 21, Issue 2, Spring 2023, Pages 485–527, https://doi.org/10.1093/jjfinec/nbab007
Nikolaus Hautsch, Ostap Okhrin, Alexander Ristig, Maximum-Likelihood
Estimation Using the Zig-Zag Algorithm, Journal of Financial
Econometrics, Volume 21, Issue 4, Fall 2023, Pages 1346–1375, https://doi.org/10.1093/jjfinec/nbac006
Sam Astill, David I Harvey, Stephen J Leybourne, A M Robert Taylor,
Yang Zu, CUSUM-Based Monitoring for Explosive Episodes in Financial Data
in the Presence of Time-Varying Volatility, Journal of Financial
Econometrics, Volume 21, Issue 1, Winter 2023, Pages 187–227, https://doi.org/10.1093/jjfinec/nbab009
Olivier Scaillet, Adrien Treccani, Christopher Trevisan,
High-Frequency Jump Analysis of the Bitcoin Market, Journal of Financial
Econometrics, Volume 18, Issue 2, Spring 2020, Pages 209–232, https://doi.org/10.1093/jjfinec/nby013
Ai Jun Hou, Weining Wang, Cathy Y H Chen, Wolfgang Karl Härdle,
Pricing Cryptocurrency Options, Journal of Financial Econometrics,
Volume 18, Issue 2, Spring 2020, Pages 250–279, https://doi.org/10.1093/jjfinec/nbaa006
Wolfgang Karl Härdle, Campbell R Harvey, Raphael C G Reule,
Understanding Cryptocurrencies, Journal of Financial Econometrics,
Volume 18, Issue 2, Spring 2020, Pages 181–208, https://doi.org/10.1093/jjfinec/nbz033
Christian M Hafner, Testing for Bubbles in Cryptocurrencies with
Time-Varying Volatility, Journal of Financial Econometrics, Volume 18,
Issue 2, Spring 2020, Pages 233–249, https://doi.org/10.1093/jjfinec/nby023
Simon Trimborn, Mingyang Li, Wolfgang Karl Härdle, Investing with
Cryptocurrencies—a Liquidity Constrained Investment Approach, Journal of
Financial Econometrics, Volume 18, Issue 2, Spring 2020, Pages 280–306,
https://doi.org/10.1093/jjfinec/nbz016
Andrea Bucci, Realized Volatility Forecasting with Neural Networks,
Journal of Financial Econometrics, Volume 18, Issue 3, Summer 2020,
Pages 502–531, https://doi.org/10.1093/jjfinec/nbaa008
IEEE
M. Saad, A. Anwar, S. Ravi and D. Mohaisen, “Revisiting Nakamoto
Consensus in Asynchronous Networks: A Comprehensive Analysis of Bitcoin
Safety and Chain Quality,” in IEEE/ACM Transactions on Networking,
vol. 32, no. 1, pp. 844-858, Feb. 2024, https://ieeexplore.ieee.org/document/10225481
X. Luo, P. Zhang, M. Zhang, H. Li and Q. Cheng, “A Novel Covert
Communication Method Based on Bitcoin Transaction,” in IEEE Transactions
on Industrial Informatics, vol. 18, no. 4, pp. 2830-2839, April 2022, https://ieeexplore.ieee.org/document/9497763
E. Zaghloul, T. Li, M. W. Mutka and J. Ren, “Bitcoin and Blockchain:
Security and Privacy,” in IEEE Internet of Things Journal, vol. 7, no.
10, pp. 10288-10313, Oct. 2020, https://ieeexplore.ieee.org/document/9122595
A. Manimuthu, R. Sreedharan V., R. G. and D. Marwaha, “A Literature
Review on Bitcoin: Transformation of Crypto Currency Into a Global
Phenomenon,” in IEEE Engineering Management Review, vol. 47, no. 1,
pp. 28-35, Firstquarter,march 2019, https://ieeexplore.ieee.org/document/8651284
S. Zollner, K. -K. R. Choo and N. -A. Le-Khac, “An Automated Live
Forensic and Postmortem Analysis Tool for Bitcoin on Windows Systems,”
in IEEE Access, vol. 7, pp. 158250-158263, 2019, https://ieeexplore.ieee.org/document/8878085
M. Conti, E. Sandeep Kumar, C. Lal and S. Ruj, “A Survey on Security
and Privacy Issues of Bitcoin,” in IEEE Communications Surveys &
Tutorials, vol. 20, no. 4, pp. 3416-3452, Fourthquarter 2018, https://ieeexplore.ieee.org/document/8369416
M. C. Kus Khalilov and A. Levi, “A Survey on Anonymity and Privacy
in Bitcoin-Like Digital Cash Systems,” in IEEE Communications Surveys
& Tutorials, vol. 20, no. 3, pp. 2543-2585, thirdquarter 2018, https://ieeexplore.ieee.org/document/8325269
M. Rahouti, K. Xiong and N. Ghani, “Bitcoin Concepts, Threats, and
Machine-Learning Security Solutions,” in IEEE Access, vol. 6,
pp. 67189-67205, 2018, https://ieeexplore.ieee.org/document/8528406
J. Bohr and M. Bashir, “Who Uses Bitcoin? An exploration of the
Bitcoin community,” 2014 Twelfth Annual International Conference on
Privacy, Security and Trust, Toronto, ON, Canada, 2014, pp. 94-101, https://ieeexplore.ieee.org/document/6890928
Articles by
institutes, journalists, and researchers
The Satoshi Nakamoto
Institute makes some information and resources freely available,
including communications, code archives, quotes, and a sizeable library
of relevant papers.
SatoshiBlocks
created to help Bitcoiners visualize public information about mining in
the early times of Bitcoin.
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│ ⚠ THIS CONTENT MAKES NO CLAIMS ABOUT THE IDENTITY OF SATOSHI NAKAMOTO │
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