Article
Computer Science, Artificial Intelligence
Haizhou Guo, Dian Zhang, Siyuan Liu, Lei Wang, Ye Ding
Summary: This study focuses on the importance of cryptocurrency price forecasting and the challenges faced by traditional approaches. A new price forecasting model WT-CATCN is proposed, leveraging Wavelet Transform and Casual Multi-Head Attention Temporal Convolutional Network to forecast Bitcoin prices. Experimental results show that the model improves price forecasting performance by 25%.
DECISION SUPPORT SYSTEMS
(2021)
Article
Business, Finance
Hossein Jahanshahloo, Shaen Corbet, Les Oxley
Summary: This research finds that Bitcoin trading activity is influenced by the trading sessions of NYSE, which have strengthened over time but diminished during weekends. These findings have significant implications for traders, especially in terms of centralized exchange liquidity and transaction confirmation speed.
FINANCE RESEARCH LETTERS
(2022)
Article
Economics
Benjamin M. Blau, Todd G. Griffith, Ryan J. Whitby
Summary: The study shows that changes in Bitcoin price lead to changes in forward inflation rate, suggesting Bitcoin can be used as a hedge against inflation. Bitcoin price changes tend to precede changes in expected inflation.
Article
Business
Debidutta Pattnaik, M. Kabir Hassan, Arun Dsouza, Aviral Tiwari, Shridev Devji
Summary: Due to its transparency, portability, divisibility, and resistance to inflation, the cryptocurrency market has gained immense support from global investors and traders. This has led most central banks to plan the launch of their own cryptocurrencies. This study provides a comprehensive overview of the academic trends and thematic dimensions of cryptocurrency research.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Article
Business, Finance
Anantha Divakaruni, Peter Zimmerman
Summary: The Lightning Network allows for Bitcoin payments to be made off the blockchain, resulting in reduced congestion and increased efficiency. Our study reveals that this improvement cannot be accounted for by other factors and the impact of centralization on efficiency remains inconclusive. These findings have implications for the future of cryptocurrencies as a payment method and their environmental impact.
FINANCE RESEARCH LETTERS
(2023)
Article
Computer Science, Information Systems
Massimo Bartoletti, Stefano Lande, Andrea Loddo, Livio Pompianu, Sergio Serusi
Summary: The cryptocurrency market has exceeded initial expectations since the inception of Bitcoin in 2009, with thousands of tokenised assets available and daily trades surpassing billions of USD. However, the pseudonymity features of cryptocurrencies have attracted cybercriminals, leading to a wide range of scams. Research in this field is hindered by the lack of comprehensive data sources and a standard taxonomy for scams.
Article
Computer Science, Information Systems
Gyeongho Kim, Dong-Hyun Shin, Jae Gyeong Choi, Sunghoon Lim
Summary: This paper proposes a novel framework for predicting the price of Bitcoin. The framework utilizes change point detection technique to segment time-series data and on-chain data as input variables. It also employs a self-attention-based multiple long short-term memory model for prediction. Experimental results demonstrate the effectiveness of the framework in BTC price prediction.
Article
Business, Finance
Sahin Telli, Xufeng Zhao
Summary: This study investigates the clustering phenomenon in Bitcoin wallet balances by examining the Bitcoin rich list. Significant clustering is found in both the integer and fractional parts of the balances, particularly at 00. Using probit models, the study reveals that wallet age, number of transactions, and balance significantly impact clustering, with balance being the most influential factor. The findings suggest that economic and behavioral factors may contribute to the observed preference clustering among Bitcoin wallet holders. This study offers valuable insights into the behavior of Bitcoin users and lays the foundation for further research in this area.
FINANCE RESEARCH LETTERS
(2023)
Article
Computer Science, Theory & Methods
Maruf Monem, Md Tamjid Hossain, Md. Golam Rabiul Alam, Md. Shirajum Munir, Md. Mahbubur Rahman, Salman A. AlQahtani, Samah Almutlaq, Mohammad Mehedi Hassan
Summary: Bitcoin, the largest cryptocurrency, faces challenges in broader adaption due to long verification times and high transaction fees. To tackle these issues, researchers propose a learning framework that uses machine learning to predict the ideal block size in each block generation cycle. This model significantly improves the block size, transaction fees, and transaction approval rate of Bitcoin, addressing the long wait time and broader adaption problem.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Green & Sustainable Science & Technology
Swathi Punathumkandi, Venkatesan Meenakshi Sundaram, Prabhavathy Panneer
Summary: Bitcoin is a digital currency based on blockchain technology, with the potential to replace fiat money. Most industrial applications rely on permissioned blockchain, however, it has some issues in terms of interoperability among different platforms. This paper suggests a sustainable system to solve the interoperability issue of permissioned blockchain by designing a new infrastructure, which has been successfully tested in ethereum and hyperledger frameworks.
Article
Computer Science, Hardware & Architecture
Yannan Li, Guomin Yang, Willy Susilo, Yong Yu, Man Ho Au, Dongxi Liu
Summary: Monero offers high anonymity for users and transactions, but lacks user accountability, which is crucial to combat criminal activities in cryptocurrency transactions. This paper introduces Traceable Monero, a new cryptocurrency that aims to strike a balance between user anonymity and accountability. By overlaying Monero with tracing mechanisms, Traceable Monero ensures security without significantly impacting transaction efficiency.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Business
Christoph F. Breidbach, Silviana Tana
Summary: The study explores the roles of individuals in shaping cryptocurrency markets, identifying four distinct roles and six micro-level market actions. It fills the knowledge gap on non-firm actors shaping markets and offers managerial guidelines for practitioners benefiting from cryptocurrencies.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Computer Science, Information Systems
Nishant Jagannath, Tudor Barbulescu, Karam M. Sallam, Ibrahim Elgendi, Asuquo A. Okon, Braden Mcgrath, Abbas Jamalipour, Kumudu Munasinghe
Summary: This paper introduces on-chain metrics derived from data on the Bitcoin network to predict the price of Bitcoin using a deep learning model and a self-adaptive technique. Compared to traditional LSTM model, this approach offers higher accuracy and lower error rates.
Article
Computer Science, Theory & Methods
Shengmin Xu, Jianting Ning, Jinhua Ma, Xinyi Huang, Robert H. Deng
Summary: Blockchain, as an immutable and append-only distributed ledger, faces challenges when dealing with illegal content and data modification requirements. Researchers propose a new notion called K-time modifiable and epoch-based redactable blockchain with a monetary penalty to control rewriting and penalize malicious behaviors.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Economics
Crina Anina Bejan, Dominic Bucerzan, Mihaela Daciana Craciun
Summary: This study investigates the relationship between Bitcoin price evolution and energy consumption tendency and finds a strong correlation between them.
Article
Computer Science, Information Systems
Jongwuk Lee, Hyeonseung Im, Gae-won You
INFORMATION SCIENCES
(2016)
Article
Computer Science, Artificial Intelligence
Dongwon Kim, Hyeonseung Im, Sungwoo Park
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2012)
Article
Computer Science, Information Systems
Gae-won You, Mu-Woong Lee, Hyeonseung Im, Seung-won Hwang
INFORMATION SYSTEMS
(2013)
Article
Chemistry, Analytical
Sebin Park, Myeong-Seon Gil, Hyeonseung Im, Yang-Sae Moon
Article
Computer Science, Theory & Methods
Hyeonseung Im, Pierre Geneves, Nils Gesbert, Nabil Layaida
THEORETICAL COMPUTER SCIENCE
(2020)
Article
Mathematics
Hyeonseung Im
Summary: This paper discusses the method of embedding classical logic into intuitionistic logic using double negation translation, as well as continuation passing style transformation implemented through the Curry-Howard isomorphism in programming languages. By selectively translating nontrivial expressions into CPS functions using a type and effect system, a logical account of CBV selective CPS transformation is provided. The selective DNT derived from the corresponding type and effect system can translate classical proofs into equivalent intuitionistic proofs, presenting a smaller scale compared to traditional DNTs.
Article
Chemistry, Analytical
Seong Uk Kim, Jihyun Roh, Hyeonseung Im, Jongmin Kim
Summary: Three-dimensional mesh post-processing is crucial due to hardware limitations and imperfect capture environments. In this study, we propose a novel approach utilizing a deep learning framework to complete and denoise 3D mesh data. Experimental results demonstrate improved reconstruction quality and higher accuracy compared to previous neural network systems.
Article
Computer Science, Information Systems
Suhwan Ji, Dohyung Kim, Hyeonseung Im
Summary: This paper discusses the evolution of blockchain technology, DApps, and vulnerabilities in smart contracts. A software tool is proposed to evaluate and select the most effective countermeasures for vulnerabilities, revealing trade-offs in detecting vulnerabilities.
Article
Computer Science, Information Systems
Gihun Joo, Yeongjin Song, Hyeonseung Im, Junbeom Park
Proceedings Paper
Computer Science, Information Systems
Giuseppe Castagna, Hyeonseung Im, Kim Nguyen, Veronique Benzaken
PROGRAMMING LANGUAGES AND SYSTEMS
(2015)
Article
Computer Science, Software Engineering
Giuseppe Castagna, Kim Nguyen, Zhiwu Xu, Hyeonseung Im, Serguei Lenglet, Luca Padovani
ACM SIGPLAN NOTICES
(2014)
Proceedings Paper
Computer Science, Information Systems
Hyeonseung Im, Keiko Nakata, Sungwoo Park
AUTOMATA, LANGUAGES, AND PROGRAMMING, PT II
(2013)