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題名 加密貨幣設計之代理人基計算模型
Agent-Based Computational Modeling of Cryptocurrency Design
作者 吳立思
Ude, Felix
貢獻者 陳樹衡
Chen, Shu-Heng
吳立思
Ude, Felix
關鍵詞 加密貨幣
比特幣
代理人基計算模型
Cryptocurrency
Bitcoin
Agent-Based Computation
日期 2019
上傳時間 7-Aug-2019 17:20:11 (UTC+8)
摘要 Cryptocurrencies, such as Bitcoin, witnessed a surge in popularity during recent years. With the rise of attention, the discussion about a better design of these cryptocurrencies also increased, to solve issues like security problems and network congestion. Many suggested solutions require a total redesign of the cryptocurrency. This thesis looks into ways to redesign the cryptocurrency Bitcoin in a more subtle way, by only optimizing its current parameters.
For that reason an agent-based computation model is used to simulate the Bitcoin market and its transaction system. Its parameters are optimized and compared to the real Bitcoin parameters. The results suggest a trade-off between security and economic efficiency, and that the real parameter values of Bitcoin are sub-optimal.
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(2016).
Electricity consumption - country comparision.
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studying a cryptocurrency market. Journal of Economic Interaction and Coordina-
tion, 12(2), 345–365. doi: 10.1007/s11403-015-0168-2
Cocco, L., & Marchesi, M. (2016). Modeling and simulation of the economics of
mining in the Bitcoin market. PLoS ONE, 11(10), 1–42. doi: 10.1371/journal.pone
.0164603
Cocco, L., Tonelli, R., & Marchesi, M. (2019). An agent based model to analyze
the bitcoin mining activity and a comparison with the gold mining industry. Future
Internet, 11(1), 8.
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doi: 10.2139/ssrn.3143724
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tive genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation,
6(2), 182–197.
Decker, C., & Wattenhofer, R. (2013). Information propagation in the Bitcoin network.
13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 -
Proceedings. doi: 10.1109/P2P.2013.6688704
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from https://digiconomist.net/bitcoin-energy-consumption
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Retrieved 2019-03-19, from https://www.bbc.com/news/
business-47553048
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bitcoin transaction fees. Journal of Financial Economics.
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(1993).
Allocative efficiency of markets with zero-
intelligence traders: Market as a partial substitute for individual rationality. Journal
of political economy, 101(1), 119–137.
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’Cryptography and computer’ security at MIT.
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(2019).
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arXiv:1902.03899.
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nal of Cryptology, 3(2), 99–111. Retrieved from https://www.anf.es/pdf/
Haber{ }Stornetta.pdf
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描述 碩士
國立政治大學
應用經濟與社會發展英語碩士學位學程(IMES)
106266012
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0106266012
資料類型 thesis
dc.contributor.advisor 陳樹衡zh_TW
dc.contributor.advisor Chen, Shu-Hengen_US
dc.contributor.author (Authors) 吳立思zh_TW
dc.contributor.author (Authors) Ude, Felixen_US
dc.creator (作者) 吳立思zh_TW
dc.creator (作者) Ude, Felixen_US
dc.date (日期) 2019en_US
dc.date.accessioned 7-Aug-2019 17:20:11 (UTC+8)-
dc.date.available 7-Aug-2019 17:20:11 (UTC+8)-
dc.date.issued (上傳時間) 7-Aug-2019 17:20:11 (UTC+8)-
dc.identifier (Other Identifiers) G0106266012en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/125104-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 應用經濟與社會發展英語碩士學位學程(IMES)zh_TW
dc.description (描述) 106266012zh_TW
dc.description.abstract (摘要) Cryptocurrencies, such as Bitcoin, witnessed a surge in popularity during recent years. With the rise of attention, the discussion about a better design of these cryptocurrencies also increased, to solve issues like security problems and network congestion. Many suggested solutions require a total redesign of the cryptocurrency. This thesis looks into ways to redesign the cryptocurrency Bitcoin in a more subtle way, by only optimizing its current parameters.
For that reason an agent-based computation model is used to simulate the Bitcoin market and its transaction system. Its parameters are optimized and compared to the real Bitcoin parameters. The results suggest a trade-off between security and economic efficiency, and that the real parameter values of Bitcoin are sub-optimal.		en_US
dc.description.tableofcontents List of Figures II
List of Tables III

1 Introduction 1
1.1 Research Motivation ........................... 1
1.2 Contribution ................................ 2
1.3 Organization ................................ 2

2 Literature Review 4
2.1 Cryptocurrencies ............................. 4
2.1.1 Blockchain ............................ 4
2.1.2 Signature of Transactions ..................... 5
2.1.3 Bitcoin Mining .......................... 6
2.1.4 Development of Bitcoin ..................... 9
2.2 Economic Literature ........................... 10
2.2.1 Economic Analysis of Bitcoin .................. 10
2.2.2 Agent-Based Computational Economics in Blockchains . . . . 14
2.3 Summary ................................. 15

3 Methodology 17
3.1 Model Overview ............................. 17
3.2 Types of Agents .............................. 18
3.2.1 Chartist .............................. 18
3.2.2 User ................................ 19
3.2.3 Miner ............................... 19
3.3 The Model ................................. 22
3.3.1 The Bitcoin Market ........................ 22
3.3.2 The Transaction System ..................... 26
3.4 Initialization ................................ 28
3.4.1 Number of Agents and their Type Distribution .........
3.4.2 Agent’s Wealth .......................... 29
3.5 Calibration ................................ 31
3.5.1 Realistic Parameters ....................... 31
3.5.2 Optimization for Economic Efficiency .............. 32
3.5.3 Optimization for Economic Efficiency and Hashing Power . . . 34
3.6 Summary ................................. 35

4 Findings 36
4.1 Real Parameters .............................. 36
4.1.1 Price Development ........................ 36
4.1.2 Hashing Power Development ................... 37
4.1.3 Transaction Fee Development .................. 39
4.1.4 Wealth Development ....................... 40
4.2 Optimized Wealth ............................. 42
4.3 Optimized Wealth and Hashing Power .................. 43
4.3.1 Parameters ............................ 44
4.3.2 Outcomes ............................. 48
4.4 Summary ................................. 5 1

5 Conclusion 52
5.1 Review of Findings ............................ 52
5.2 Application of Findings .......................... 52
5.3 Limitations ................................ 53
5.4 Future Work ................................ 54

Bibliography 55

A Table of Variables 62		zh_TW
dc.format.extent 3273957 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0106266012en_US
dc.subject (關鍵詞) 加密貨幣zh_TW
dc.subject (關鍵詞) 比特幣zh_TW
dc.subject (關鍵詞) 代理人基計算模型zh_TW
dc.subject (關鍵詞) Cryptocurrencyen_US
dc.subject (關鍵詞) Bitcoinen_US
dc.subject (關鍵詞) Agent-Based Computationen_US
dc.title (題名) 加密貨幣設計之代理人基計算模型zh_TW
dc.title (題名) Agent-Based Computational Modeling of Cryptocurrency Designen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Altman, E., Reiffers, F. A., Menasché, D. S., Matar, M., Dhamal, S., & Touati, C.
(2018). Mining competition in a multi-cryptocurrency ecosystem at the network
edge: a congestion game approach. 1st Symposium on Cryptocurrency Analysis
(SOCCA 2018).
Arifovic, J. (2002). Exchange rate volatility in the artificial foreign exchange market.
In Evolutionary computation in economics and finance (pp. 123–134). Springer.
Athey, S., Parashkevov, I., Sarukkai, V., & Xia, J. (2016). Bitcoin Pricing, Adoption,
and Usage: Theory and Evidence. Stanford University Graduate School of Business
Research Paper, 16(42), 70. Retrieved from https://papers.ssrn.com/
sol3/papers.cfm?abstract{ }id=2826674
Back, A. (2002). Hashcash - A Denial of Service Counter-Measure. Technical Re-
port(August), 1–10.
Bitcoin Wiki. (2019a). Block chain. Retrieved from https://en.bitcoin.it/
wiki/Block chain
Bitcoin Wiki. (2019b). Controlled supply. Retrieved from https://en.bitcoin
.it/wiki/Controlled supply
Bitcoinfees.info.
(2019).
Bitcoin transaction fees.
Retrieved 2019.05.25, from
https://bitcoinfees.info/
BitInfoCharts.
(2019a).
Bitcoin avg. transaction fee historical chart.
Retrieved
2019.06.04, from https://bitinfocharts.com/comparison/bitcoin
-transactionfees.html
BitInfoCharts.
(2019b).
Bitcoin median transaction value historical chart.
Re-
trieved 2019.04.23, from https://bitinfocharts.com/comparison/
mediantransactionvalue-btc-sma90.html
Blank, J., & Deb, K.
(n.d.).
pymoo - Multi-objective Optimization in Python.
https://pymoo.org.
55Blockchain.com. (2019a). Bitcoin difficulty. Retrieved 2019.05.26, from https://
www.blockchain.com/charts/difficulty?timespan=3years
Blockchain.com. (2019b). Blockchain size. Retrieved 2019.05.25, from https://
www.blockchain.com/charts/blocks-size
Blockchain.com. (2019c). Hash rate. Retrieved 2019.05.26, from https://www
.blockchain.com/charts/hash-rate?timespan=3years
Blockchain.com.
(2019d).
Hashrate distribution.
Retrieved 2019.05.26, from
https://www.blockchain.com/pools
Blockchain.com.
(2019e).
Hash rate; the estimated number of tera hashes per
second (trillions of hashes per second) the bitcoin network is performing. Re-
trieved 2019.04.13, from https://www.blockchain.com/charts/hash
-rate?timespan=all
Blockchain.com. (2019f). Market price (usd). Retrieved 2019.05.29, from https://
www.blockchain.com/charts/market-price?timespan=all
Blockchain.com. (2019g). Mempool size. Retrieved 2019.05.29, from https://
www.blockchain.com/de/charts/mempool-size?timespan=all#
Blockchain.com.
from
(2019h).
Miner’s revenue.
Retrieved 2019.05.25,
https://www.blockchain.com/charts/miners-revenue
?timespan=2years
Budish, E. (2018). The economic limits of bitcoin and the blockchain (Tech. Rep.).
National Bureau of Economic Research.
Buterin, V. (2016). On inflation, transaction fees and cryptocurrency monetary policy.
Ethereum Blog. Retrieved 2016-07-26, from https://blog.ethereum.org/
2016/07/27/inflation-transaction-fees-cryptocurrency
-monetary-policy/
Buybitcoinworldwide.
(2019).
How many bitcoins are there?
Retrieved
2019.04.25, from https://www.buybitcoinworldwide.com/how-many
-bitcoins-are-there/#
56Calle, P.
(2017).
NSGA-II explained.
Analytics lab of University of Okla-
Retrieved 2017-10-24, from http://oklahomaanalytics.com/
homa.
data-science-techniques/nsga-ii-explained/
Carlsten, M., Kalodner, H., Weinberg, S. M., & Narayanan, A. (2016). On the insta-
bility of bitcoin without the block reward. Proceedings of the 2016 ACM SIGSAC
Conference on Computer and Communications Security, 154–167.
Catalini, C., & Gans, J. S. (2016). Some simple economics of the blockchain (Tech.
Rep.). National Bureau of Economic Research.
CEIC. (2019). China electricity price. Retrieved 2019.04.13, from https://www
.ceicdata.com/en/china/electricity-price
Chen, S.-H., & Chie, B.-T. (2008). Lottery markets design, micro-structure, and macro-
behavior: An ace approach. Journal of Economic Behavior & Organization, 67(2),
463–480.
Chiu, J., & Koeppl, T. V. (2017). The economics of cryptocurrencies–bitcoin and
beyond. Available at SSRN 3048124.
CIA.
(2016).
Electricity consumption - country comparision.
Retrieved
2019.05.26, from https://www.cia.gov/library/publications/the
-world-factbook/rankorder/2233rank.html
Cocco, L., Concas, G., & Marchesi, M. (2017). Using an artificial financial market for
studying a cryptocurrency market. Journal of Economic Interaction and Coordina-
tion, 12(2), 345–365. doi: 10.1007/s11403-015-0168-2
Cocco, L., & Marchesi, M. (2016). Modeling and simulation of the economics of
mining in the Bitcoin market. PLoS ONE, 11(10), 1–42. doi: 10.1371/journal.pone
.0164603
Cocco, L., Tonelli, R., & Marchesi, M. (2019). An agent based model to analyze
the bitcoin mining activity and a comparison with the gold mining industry. Future
Internet, 11(1), 8.
57Cong, L. W., He, Z., & Li, J. (2018). Decentralized Mining in Centralized Pools. Ssrn.
doi: 10.2139/ssrn.3143724
Croman, K., Decker, C., Eyal, I., Gencer, A. E., Juels, A., Kosba, A., . . . others (2016).
On scaling decentralized blockchains. International Conference on Financial Cryp-
tography and Data Security, 106–125.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjec-
tive genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation,
6(2), 182–197.
Decker, C., & Wattenhofer, R. (2013). Information propagation in the Bitcoin network.
13th IEEE International Conference on Peer-to-Peer Computing, IEEE P2P 2013 -
Proceedings. doi: 10.1109/P2P.2013.6688704
Digiconomist.net. (2019). Bitcoin energy consumption index. Retrieved 2019.05.26,
from https://digiconomist.net/bitcoin-energy-consumption
Di Salvo, M. (2019). Why are venezuelans seeking refuge in crypto-currencies?
BBC News.
Retrieved 2019-03-19, from https://www.bbc.com/news/
business-47553048
Easley, D., O’Hara, M., & Basu, S. (2019). From mining to markets: The evolution of
bitcoin transaction fees. Journal of Financial Economics.
Gode, D. K., & Sunder, S.
(1993).
Allocative efficiency of markets with zero-
intelligence traders: Market as a partial substitute for individual rationality. Journal
of political economy, 101(1), 119–137.
Goldwasser, S., & Bellare, M. (1996). Lecture notes on cryptography. Summer course
’Cryptography and computer’ security at MIT.
Goren, G., & Spiegelman, A.
(2019).
Mind the mining.
arXiv preprint
arXiv:1902.03899.
Haber, S., & Stornetta, W. S. (1991). How to Time-Stamp a Digital Document. Jour-
nal of Cryptology, 3(2), 99–111. Retrieved from https://www.anf.es/pdf/
Haber{ }Stornetta.pdf
58Hoofnagle, C. J., Urban, J. M., & Li, S. (2012). Mobile payments: Consumer benefits
& new privacy concerns. Available at SSRN 2045580.
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