| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP13278 |
| DP13278 Long Run Growth of Financial Data Technology | |
| Laura Veldkamp; maryam farboodi | |
| 发表日期 | 2018-10-23 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | “Big data” financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others’ information, rather than produce information themselves. We allow agents to choose how much to learn about future asset values or about others’ demands, and explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies. However, in the long run, as data processing technology becomes more and more advanced, both types of data continue to be processed. What keeps the data economy in balance is two competing forces: Data resolves investment risk, but future data creates risk. The efficiency results that follow from these competing forces upend common wisdom. They offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient. |
| 主题 | Financial Economics ; Macroeconomics and Growth |
| 关键词 | Fintech Big data Financial analysis Liquidity Information acquisition Growth |
| URL | https://cepr.org/publications/dp13278 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/542088 |
| 推荐引用方式 GB/T 7714 | Laura Veldkamp,maryam farboodi. DP13278 Long Run Growth of Financial Data Technology. 2018. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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