From Prediction to Profit: A Comprehensive Review of Cryptocurrency Trading Strategies and Price Forecasting Techniques

被引:2
作者
Otabek, Sattarov [1 ]
Choi, Jaeyoung [1 ]
机构
[1] Gachon Univ, Sch Comp, Seongnam 13120, South Korea
来源
IEEE ACCESS | 2024年 / 12卷
基金
新加坡国家研究基金会;
关键词
Cryptocurrency; Reviews; Predictive models; Biological system modeling; Accuracy; Prediction algorithms; Adaptation models; Machine learning; Cryptocurrency trading; price prediction; trading strategies; machine learning; NEURAL-NETWORKS; TECHNICAL ANALYSIS; BITCOIN; MODEL; VOLATILITY;
D O I
10.1109/ACCESS.2024.3417449
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The rapid evolution of cryptocurrency markets and the increasing complexity of trading strategies necessitate a comprehensive understanding of price-prediction models and their direct impact on trading efficacy. While extensive research has been conducted separately on price prediction methods and trading strategies, there remains a significant gap in studies explicitly correlating precise price forecasts with successful trading outcomes. This review paper addresses this gap by critically examining the role of accurate cryptocurrency price predictions in enhancing trading strategies. We conducted a systematic review of sufficient scholarly articles and web resources, focusing on the methodologies and effectiveness of various predictive models and their integration into cryptocurrency trading strategies. Our selection criteria ensured the inclusion of papers that demonstrate methodological rigor, relevance, and recent contributions to the field, spanning from economic theories and statistical models to advanced machine learning techniques. The findings reveal that precise price predictions significantly contribute to the development of adaptive and risk-managed trading strategies, which are crucial in the highly volatile cryptocurrency market. The review also identifies current challenges and proposes directions for future research, emphasizing the need for interdisciplinary approaches and ethical considerations in predictive modeling. This synthesis aims to bridge the existing research gap and guide future studies, thereby fostering more sophisticated and profitable trading strategies in the cryptocurrency domain.
引用
收藏
页码:87039 / 87064
页数:26
相关论文
共 159 条
  • [1] Acerbi C., 2002, Econ. Notes, V31, P379, DOI [10.1111/1468-0300.00091, DOI 10.1111/1468-0300.00091]
  • [2] ACM Digital Library, About us
  • [3] Agarwal Aastha, 2021, 2021 IEEE Mysore Sub Section International Conference (MysuruCon), P538, DOI 10.1109/MysuruCon52639.2021.9641735
  • [4] Using algorithmic trading to analyze short term profitability of Bitcoin
    Ahmad, Iftikhar
    Ahmad, Muhammad Ovais
    Alqarni, Mohammed A.
    Almazroi, Abdulwahab Ali
    Khalil, Muhammad Imran Khan
    [J]. PEERJ COMPUTER SCIENCE, 2021, 7 : 1 - 19
  • [5] Prediction of cryptocurrency returns using machine learning
    Akyildirim, Erdinc
    Goncu, Ahmet
    Sensoy, Ahmet
    [J]. ANNALS OF OPERATIONS RESEARCH, 2021, 297 (1-2) : 3 - 36
  • [6] Empirical Evaluation of Machine Learning Performance in Forecasting Cryptocurrencies
    Al Hawi, Lauren
    Sharqawi, Sally
    Abu Al-Haija, Qasem
    Qusef, Abdallah
    [J]. JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY, 2023, 14 (04) : 639 - 647
  • [7] Alamery F. M. S., 2023, J. Comput. Electr. Electron. Eng. Sci., V1, P29
  • [8] Aldridge I, 2013, WILEY TRADING SER, P1
  • [9] Anticipating Cryptocurrency Prices Using Machine Learning
    Alessandretti, Laura
    ElBahrawy, Abeer
    Aiello, Luca Maria
    Baronchelli, Andrea
    [J]. COMPLEXITY, 2018,
  • [10] Alipour P., 2023, European Journal of Business and Management Research, V8, P211, DOI [10.24018/ejbmr.2023.8.2.1865, DOI 10.24018/EJBMR.2023.8.2.1865]