IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1805.04698.html
   My bibliography  Save this paper

Bitcoin Risk Modeling with Blockchain Graphs

Author

Listed:
  • Cuneyt Akcora
  • Matthew Dixon
  • Yulia Gel
  • Murat Kantarcioglu

Abstract

A key challenge for Bitcoin cryptocurrency holders, such as startups using ICOs to raise funding, is managing their FX risk. Specifically, a misinformed decision to convert Bitcoin to fiat currency could, by itself, cost USD millions. In contrast to financial exchanges, Blockchain based crypto-currencies expose the entire transaction history to the public. By processing all transactions, we model the network with a high fidelity graph so that it is possible to characterize how the flow of information in the network evolves over time. We demonstrate how this data representation permits a new form of microstructure modeling - with the emphasis on the topological network structures to study the role of users, entities and their interactions in formation and dynamics of crypto-currency investment risk. In particular, we identify certain sub-graphs ('chainlets') that exhibit predictive influence on Bitcoin price and volatility, and characterize the types of chainlets that signify extreme losses.

Suggested Citation

  • Cuneyt Akcora & Matthew Dixon & Yulia Gel & Murat Kantarcioglu, 2018. "Bitcoin Risk Modeling with Blockchain Graphs," Papers 1805.04698, arXiv.org.
    • Handle: RePEc:arx:papers:1805.04698
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1805.04698
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dyhrberg, Anne Haubo, 2016. "Bitcoin, gold and the dollar – A GARCH volatility analysis," Finance Research Letters, Elsevier, vol. 16(C), pages 85-92.
    2. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    3. Yhlas Sovbetov, 2018. "Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 1-27.
    4. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    5. Peter Gomber & Jascha-Alexander Koch & Michael Siering, 2017. "Digital Finance and FinTech: current research and future research directions," Journal of Business Economics, Springer, vol. 87(5), pages 537-580, July.
    6. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kurbucz, Marcell Tamás, 2019. "Predicting the price of Bitcoin by the most frequent edges of its transaction network," Economics Letters, Elsevier, vol. 184(C).
    2. Samuel W. Akingbade & Marian Gidea & Matteo Manzi & Vahid Nateghi, 2023. "Why Topological Data Analysis Detects Financial Bubbles?," Papers 2304.06877, arXiv.org.
    3. Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
    4. Matthew F. Dixon & Cuneyt Gurcan Akcora & Yulia R. Gel & Murat Kantarcioglu, 2019. "Blockchain analytics for intraday financial risk modeling," Digital Finance, Springer, vol. 1(1), pages 67-89, November.
    5. Xiao Fan Liu & Xin-Jian Jiang & Si-Hao Liu & Chi Kong Tse, 2020. "Knowledge Discovery in Cryptocurrency Transactions: A Survey," Papers 2010.01031, arXiv.org.
    6. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    7. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    8. Yufang Wang & Haiyan Wang, 2020. "Using Networks and Partial Differential Equations to Predict Bitcoin Price," Papers 2001.03099, arXiv.org.
    9. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    10. Apergis, Nicholas & Koutmos, Dimitrios & Payne, James E., 2021. "Convergence in cryptocurrency prices? the role of market microstructure," Finance Research Letters, Elsevier, vol. 40(C).
    11. Thomas E. Koker & Dimitrios Koutmos, 2020. "Cryptocurrency Trading Using Machine Learning," JRFM, MDPI, vol. 13(8), pages 1-7, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Akcora, Cuneyt Gurcan & Dixon, Matthew F. & Gel, Yulia R. & Kantarcioglu, Murat, 2018. "Bitcoin risk modeling with blockchain graphs," Economics Letters, Elsevier, vol. 173(C), pages 138-142.
    2. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    3. Julián A. Parra & Carlos Arango - Joaquín Bernal & José E. Gómez - Javier Gómez & Carlos León - Clara Machado & Daniel Osorio - Daniel Rojas & Nicolás Suárez - Eduardo Yanquen, 2019. "Criptoactivos: análisis y revisión de literatura," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, issue 92, pages 1-37, November.
    4. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
    5. Matthew F. Dixon & Cuneyt Gurcan Akcora & Yulia R. Gel & Murat Kantarcioglu, 2019. "Blockchain analytics for intraday financial risk modeling," Digital Finance, Springer, vol. 1(1), pages 67-89, November.
    6. Vidal-Tomás, David & Ibañez, Ana, 2018. "Semi-strong efficiency of Bitcoin," Finance Research Letters, Elsevier, vol. 27(C), pages 259-265.
    7. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    8. Aniruddha Dutta & Saket Kumar & Meheli Basu, 2020. "A Gated Recurrent Unit Approach to Bitcoin Price Prediction," JRFM, MDPI, vol. 13(2), pages 1-16, February.
    9. Kajtazi, Anton & Moro, Andrea, 2019. "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 143-157.
    10. Sercan Demiralay & Selçuk Bayracı, 2021. "Should stock investors include cryptocurrencies in their portfolios after all? Evidence from a conditional diversification benefits measure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6188-6204, October.
    11. Abdelkader Derbali & Lamia Jamel & Monia Ben Ltaifa & Ahmed K. Elnagar, 2020. "Return, Volatility and Shock Spillovers of Bitcoin with Energy Commodities," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 10(3), pages 157-170.
    12. Panayiotis Theodossiou & Polina Ellina & Christos S. Savva, 2022. "Stochastic properties and pricing of bitcoin using a GJR-GARCH model with conditional skewness and kurtosis components," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 695-716, August.
    13. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
    14. Pedro Bação & António Portugal Duarte & Helder Sebastião & Srdjan Redzepagic, 2018. "Information Transmission Between Cryptocurrencies: Does Bitcoin Rule the Cryptocurrency World?," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(2), pages 97-117, June.
    15. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    16. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    17. Apopo, Natalay & Phiri, Andrew, 2019. "On the (in)efficiency of cryptocurrencies: Have they taken daily or weekly random walks?," MPRA Paper 94712, University Library of Munich, Germany.
    18. Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
    19. Duc Huynh, Toan Luu & Burggraf, Tobias & Wang, Mei, 2020. "Gold, platinum, and expected Bitcoin returns," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    20. Frankovic, Jozo & Liu, Bin & Suardi, Sandy, 2022. "On spillover effects between cryptocurrency-linked stocks and the cryptocurrency market: Evidence from Australia," Global Finance Journal, Elsevier, vol. 54(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1805.04698. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.