Bitcoin is a peer-to-peer electronic payment system that has rapidly grown in popularity in recent years. Usually, the complete history of Bitcoin blockchain data must be queried to acquire variables with economic meaning. This task has recently become increasingly difficult, as there are over 1.6 billion historical transactions on the Bitcoin blockchain. It is thus important to query Bitcoin transaction data in a way that is more efficient and provides economic insights. We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in the social sciences. Specifically, we query and process the Bitcoin transaction input and output data within each daily cohort. This enables us to create datasets and visualizations for some key Bitcoin transaction indicators, including the daily lifespan distributions of spent transaction output (STXO) and the daily age distributions of the cumulative unspent transaction output (UTXO). We provide a computationally feasible approach for characterizing Bitcoin transactions that paves the way for future economic studies of Bitcoin.
翻译:Bitcoin是一个近年来受到欢迎的对等电子支付系统。 通常, Bitcoin 块链数据的完整历史必须查询,才能获得具有经济意义的变量。 这项任务最近变得越来越困难, 因为Bitcoin 块链上的历史交易量超过16亿。 因此,有必要以更有效的方式查询Bitcoin 交易数据,并提供经济见解。 我们运用社会科学中为人口数据开发的方法,对Bitcoin 块链数据进行群落分析,解释Bitcoin 块数据。 具体地说, 我们查询和处理Bitcoin 交易输入和输出数据, 以便每个日组都能够为一些关键 Bitcoin 交易指标创建数据集和可视化数据, 包括用过的交易产出(STXO) 的日使用寿命分布和累计未用交易产出(UTXO) 的每日年龄分布。 我们为Bitcoin 交易的特点提供了一种计算上可行的方法, 为Bitcoin 的未来经济研究铺平了道路。