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seminars:datasci:191112

Data Science Seminar
Hosted by Department of Mathematical Sciences

  • Date: Tuesday, November 12, 2019
  • Time: 12:00pm – 1:00pm
  • Room: WH-100E
  • Speaker: Kexuan Li (Binghamton University)
  • Title: A Hausman test for the presence of market microstructure noise in high frequency data

Abstract

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.

seminars/datasci/191112.txt · Last modified: 2019/11/08 12:41 by qyu