Estimating Profitability of Alternative Cryptocurrencies (Short Paper)

Danny Yuxing Huang, Kirill Igorevich Levchenko, Alex C. Snoeren

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Digital currencies have flourished in recent years, buoyed by the tremendous success of Bitcoin. These blockchain-based currencies, called altcoins, are associated with a few thousand to millions of dollars of market capitalization. Altcoins have attracted enthusiasts who enter the market by mining or buying them, but the risks and rewards could potentially be significant, especially when the market is volatile. In this work, we estimate the potential profitability of mining and speculating 18 altcoins using real-world blockchain and trade data. Using opportunity cost as a metric, we estimate the mining cost for an altcoin with respect to a more popular but stable coin. For every dollar invested in mining or buying a coin, we compute the potential returns under various conditions, such as time of market entry and hold positions. While some coins offer the potential for spectacular returns, many follow a simple bubble-and-crash scenario, which highlights the extreme risks—and potential gains—in altcoin markets.

Original languageEnglish (US)
Title of host publicationFinancial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers
EditorsSarah Meiklejohn, Kazue Sako
PublisherSpringer-Verlag
Pages409-419
Number of pages11
ISBN (Print)9783662583869
DOIs
StatePublished - Jan 1 2018
Event22nd International Conference on Financial Cryptography and Data Security, 2018 - Nieuwpoort, Belgium
Duration: Feb 26 2018Mar 2 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10957 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Financial Cryptography and Data Security, 2018
CountryBelgium
CityNieuwpoort
Period2/26/183/2/18

Fingerprint

Profitability
Mining
Alternatives
Currency
Volatiles
Costs
Crash
Reward
Estimate
Bubble
Extremes
Market
Electronic money
Metric
Scenarios

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Huang, D. Y., Levchenko, K. I., & Snoeren, A. C. (2018). Estimating Profitability of Alternative Cryptocurrencies (Short Paper). In S. Meiklejohn, & K. Sako (Eds.), Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers (pp. 409-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10957 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-662-58387-6_22

Estimating Profitability of Alternative Cryptocurrencies (Short Paper). / Huang, Danny Yuxing; Levchenko, Kirill Igorevich; Snoeren, Alex C.

Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers. ed. / Sarah Meiklejohn; Kazue Sako. Springer-Verlag, 2018. p. 409-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10957 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Huang, DY, Levchenko, KI & Snoeren, AC 2018, Estimating Profitability of Alternative Cryptocurrencies (Short Paper). in S Meiklejohn & K Sako (eds), Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10957 LNCS, Springer-Verlag, pp. 409-419, 22nd International Conference on Financial Cryptography and Data Security, 2018, Nieuwpoort, Belgium, 2/26/18. https://doi.org/10.1007/978-3-662-58387-6_22
Huang DY, Levchenko KI, Snoeren AC. Estimating Profitability of Alternative Cryptocurrencies (Short Paper). In Meiklejohn S, Sako K, editors, Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers. Springer-Verlag. 2018. p. 409-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-662-58387-6_22
Huang, Danny Yuxing ; Levchenko, Kirill Igorevich ; Snoeren, Alex C. / Estimating Profitability of Alternative Cryptocurrencies (Short Paper). Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers. editor / Sarah Meiklejohn ; Kazue Sako. Springer-Verlag, 2018. pp. 409-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{501ec9cf62db42a181489d12d9c6fa38,
title = "Estimating Profitability of Alternative Cryptocurrencies (Short Paper)",
abstract = "Digital currencies have flourished in recent years, buoyed by the tremendous success of Bitcoin. These blockchain-based currencies, called altcoins, are associated with a few thousand to millions of dollars of market capitalization. Altcoins have attracted enthusiasts who enter the market by mining or buying them, but the risks and rewards could potentially be significant, especially when the market is volatile. In this work, we estimate the potential profitability of mining and speculating 18 altcoins using real-world blockchain and trade data. Using opportunity cost as a metric, we estimate the mining cost for an altcoin with respect to a more popular but stable coin. For every dollar invested in mining or buying a coin, we compute the potential returns under various conditions, such as time of market entry and hold positions. While some coins offer the potential for spectacular returns, many follow a simple bubble-and-crash scenario, which highlights the extreme risks—and potential gains—in altcoin markets.",
author = "Huang, {Danny Yuxing} and Levchenko, {Kirill Igorevich} and Snoeren, {Alex C.}",
year = "2018",
month = "1",
day = "1",
doi = "10.1007/978-3-662-58387-6_22",
language = "English (US)",
isbn = "9783662583869",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "409--419",
editor = "Sarah Meiklejohn and Kazue Sako",
booktitle = "Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers",

}

TY - GEN

T1 - Estimating Profitability of Alternative Cryptocurrencies (Short Paper)

AU - Huang, Danny Yuxing

AU - Levchenko, Kirill Igorevich

AU - Snoeren, Alex C.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Digital currencies have flourished in recent years, buoyed by the tremendous success of Bitcoin. These blockchain-based currencies, called altcoins, are associated with a few thousand to millions of dollars of market capitalization. Altcoins have attracted enthusiasts who enter the market by mining or buying them, but the risks and rewards could potentially be significant, especially when the market is volatile. In this work, we estimate the potential profitability of mining and speculating 18 altcoins using real-world blockchain and trade data. Using opportunity cost as a metric, we estimate the mining cost for an altcoin with respect to a more popular but stable coin. For every dollar invested in mining or buying a coin, we compute the potential returns under various conditions, such as time of market entry and hold positions. While some coins offer the potential for spectacular returns, many follow a simple bubble-and-crash scenario, which highlights the extreme risks—and potential gains—in altcoin markets.

AB - Digital currencies have flourished in recent years, buoyed by the tremendous success of Bitcoin. These blockchain-based currencies, called altcoins, are associated with a few thousand to millions of dollars of market capitalization. Altcoins have attracted enthusiasts who enter the market by mining or buying them, but the risks and rewards could potentially be significant, especially when the market is volatile. In this work, we estimate the potential profitability of mining and speculating 18 altcoins using real-world blockchain and trade data. Using opportunity cost as a metric, we estimate the mining cost for an altcoin with respect to a more popular but stable coin. For every dollar invested in mining or buying a coin, we compute the potential returns under various conditions, such as time of market entry and hold positions. While some coins offer the potential for spectacular returns, many follow a simple bubble-and-crash scenario, which highlights the extreme risks—and potential gains—in altcoin markets.

UR - http://www.scopus.com/inward/record.url?scp=85072865689&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85072865689&partnerID=8YFLogxK

U2 - 10.1007/978-3-662-58387-6_22

DO - 10.1007/978-3-662-58387-6_22

M3 - Conference contribution

AN - SCOPUS:85072865689

SN - 9783662583869

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 409

EP - 419

BT - Financial Cryptography and Data Security - 22nd International Conference, FC 2018, Revised Selected Papers

A2 - Meiklejohn, Sarah

A2 - Sako, Kazue

PB - Springer-Verlag

ER -