Valuation of Data Assets Based on the Multi-Period Excess Earnings Method—A Case Study of BYD

大数据时代的蓬勃发展为传统行业注入了新动能，数据融入社会的各行各业，其作用更是不容忽视，数据资产是企业发展过程中的关键生产要素和战略资产，对数据资产进行合理评估能够促进企业资源的管理与有效利用。本文以新能源汽车企业比亚迪为例，基于多期超额收益模型，结合1年期及5年及以上银行贷款利率设定资产收益率，并采用行业平均加权平均资本成本作为折现率，以比亚迪2019~2023年营业收入为基础历史数据，分析预测其未来自由现金流量以及各项资产的贡献收益，对其数据资产进行价值评估，为企业数据资产管理与战略决策提供参考。The rapid development of the era of big data has injected new momentum into traditional industries, with data permeating various sectors of society, its role being increasingly significant. Data assets are key production factors and strategic assets in the development process of enterprises. Conducting reasonable evaluation of data assets can enhance the management and effective utilization of corporate resources. This paper takes BYD, a prominent electric vehicle manufacturer, as a case study. Based on a multi-period excess return model, we establish asset return rates in line with both one-year and five-year bank loan interest rates, employing the industry average weighted average cost of capital as the discount rate. Using the historical data of BYD’s revenue from 2019 to 2023, we analyze and forecast its future free cash flows and the contribution of various assets to returns, providing a valuation of its data assets. This research aims to offer references for corporate data asset management and strategic decision-making.