Date of Award
Spring 2020
Degree Name
Bachelor of Science (BS)
Advisor(s)
N.K. Chidambaran
Abstract
For more than a decade, algorithmic trading (AT) has been growing rapidly around the world. Regulations regarding algorithmic trading were close behind the spread of AT. Algorithmic trading regulation is different in every country based on specific trading behaviors. This paper aims to test whether legal origin, a historical factor that defines the underlying social constructs of a country’s laws, including AT regulation in financial markets. There has been abundant research about legal origin and algorithmic trading. However, no research has explored the possible relationship between legal origin and algorithmic trading implicitly or explicitly, which allows room for the contribution of this research. By thoroughly analyzing literature and market liquidity data I will address the possible relationship between legal origin and the existing AT regulations in all countries this data is available. This research expects to find that civil law countries have stricter algorithmic trading regulations.
Recommended Citation
Yao, Wenchao, "A Study of Legal Origin and Algorithmic Trading" (2020). Gabelli School of Business Honors Thesis Collection. 66.
https://research.library.fordham.edu/gabelli_thesis/66
