Multi-player dynamic game model for Bitcoin transaction bidding prediction

【Author】 Yan, Guanghui; Wang, Shan; Li, Shikui; Lu, Binwei

【Source】NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE

【影响因子】3.136

【Abstract】With the rapid rise of cryptocurrencies, it has become an urgent problem to realize the flat use of digital currency, with making it really put into use, and giving full play to its utility in the current economic market. This paper innovatively takes the maximization of user benefit as the key point to predict transaction bidding price combining dynamic game theory. The bidding price of user transaction not only refers to historical transactions, but also considers the impact on future subsequences, and the result describes the interaction between transactions in detail. Also this paper proposes a method to express user satisfaction and establishes a user benefit model accordingly, so as to ensure the transaction is packaged successfully to the greatest extent within the acceptable range of transaction pricing. Finally this paper compares the proposed model with conventional machine learning prediction algorithms, finding that when user does not participate in the trading for the first time, the prediction effect of this proposal is better than that of machine learning over small data sets, moreover superior to machine learning methods in prediction accuracy and sensitivity, with a lower time complexity.

【Keywords】Bitcoin; Prediction algorithm; Transaction fee; Multi-player dynamic game

【发表时间】2022 APR

【收录时间】2022-06-18

【文献类型】实证性文章

【主题类别】

区块链治理-市场治理-数字货币