Data Science Seminar
Hosted by Department of Mathematical Sciences
In financial markets, high-frequency trading (HFT) is a type of algorithmic trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools. In this talk, I will briefly talk about HFT and a Hausman test for the presence of market microstructure noise in high frequency data. This test is published by Yacine Aït-Sahalia, ( Princeton University), and Dacheng Xiu (U of Chicago) in the Journal of Econometrics (2019), which can be found by the following link.