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Creators/Authors contains: "Kantarcioglu, M."

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  1. ; ; ; ( , NeurIPS)
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  2. ; ; ; ; ( , NeurIPS)
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  3. ; ; ; ; ; ; ( , 61st IEEE Conference on Decision and Control)
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  4. ; ; ( , Wiley interdisciplinary reviews)
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  5. ; ; ; ( , KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining)
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  6. ; ; ; ; ( , ECML PKDD)
  7. ; ; ; ( , Network and Distributed Systems Security (NDSS) Symposium 2020)
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  8. ; ; ; ( , Proceedings of the 2020 International Joint Conference on Artificial Intelligence (IJCAI))
  9. ; ; ; ; ; ( , Proceedings of the 2020 SIAM International Conference on Data Mining (SDM))
  10. ; ; ; ( , Phung D., Tseng V., Webb G., Ho B., Ganji M., Rashidi L. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2018. Lecture Notes in Computer Science, vol 10939. Springer, Cham)
    Over the last couple of years, Bitcoin cryptocurrency and the Blockchain technology that forms the basis of Bitcoin have witnessed a flood of attention. In contrast to fiat currencies used worldwide, the Bitcoin distributed ledger is publicly available by design. This facilitates observing all financial interactions on the network, and analyzing how the network evolves in time. We introduce a novel concept of chainlets, or Bitcoin subgraphs, which allows us to evaluate the local topological structure of the Bitcoin graph over time. Furthermore, we assess the role of chainlets on Bitcoin price formation and dynamics. We investigate the predictive Granger causality of chainlets and identify certain types of chainlets that exhibit the highest predictive influence on Bitcoin price and investment risk. 
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