BIGDATA: IA: Collaborative Research: Understanding the Financial Market Ecosystem

BIGDATA：IA：协作研究：了解金融市场生态系统

• 批准号: 1838183
• 负责人: Mao Ye
• 金额: $ 42.23万
• 依托单位: National Bureau of Economic Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838183&HistoricalAwards=false
• 关键词: BIGDATA; IA; Collaborative; Research; Understanding

This is an interdisciplinary project involving computer science and economics. The big data problem to be addressed concerns how to analyze and understand financial trading, and its effects on the stock market. The project introduces new behavioral models of financial trading and applies big data techniques to implement them. The project will foster research on the financial ecosystem of machine-machine and machine-human interactions by bringing financial economists and data scientists together in a series of workshops.The PIs will work with the National Center for Supercomputing and develop a new and more accurate taxonomy of trading frequencies by categorizing high frequency traders (HFT), buy-side algorithmic traders (BAT) and human traders using two proprietary high frequency datasets. The workshops will foster research on the implications of the new financial ecosystem for the overall financial system and the economy in general, as well as creating new metrics and data for the discipline of finance in economics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这是一个涉及计算机科学和经济学的跨学科项目。要解决的大数据问题涉及如何分析和理解金融交易及其对股市的影响。该项目引入了新的金融交易行为模型，并应用大数据技术来实现这些模型。 该项目将通过将金融经济学家和数据科学家聚集在一系列研讨会上，促进对机器-机器和机器-人类交互的金融生态系统的研究。PI将与国家超级计算中心合作，通过对高频交易者（HFT）进行分类，买方算法交易者（BAT）和人类交易者使用两个专有的高频数据集。该研讨会将促进研究新的金融生态系统对整个金融体系和经济的影响，并为经济学中的金融学科创造新的指标和数据。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Who provides liquidity, and when?

谁提供流动性、何时提供？

• DOI: 10.3386/w25972
• 发表时间: 2021
• 期刊: Journal of financial economics
• 影响因子: 8.9
• 作者: Li, Sida;Wang, Xin;Ye, Mao
• 通讯作者: Ye, Mao

Big Data in Finance

• DOI: 10.1201/b18050-22
• 发表时间: 2015
• 作者: Taruna Seth;V. Chaudhary

The Effect of Tick Size on Managerial Learning from Stock Prices

• DOI: 10.1016/j.jacceco.2022.101515
• 发表时间: 2022-05
• 期刊: Journal of Accounting and Economics
• 影响因子: 5.9
• 作者: Mao Ye;Miles Zheng;Wei Zhu