The Impact of High-Frequency Trading on Market Volatility

2016 ◽  
Vol 11 (2) ◽  
pp. 55-63 ◽  
Author(s):  
Gianluca Virgilio

This book illustrates and assesses the dramatic recent transformations in capital markets worldwide and the impact of those transformations. ‘Market making’ by humans in centralized markets has been replaced by supercomputers and algorithmic high frequency trading operating in often highly fragmented markets. How do recent market changes impact on core public policy objectives such as investor protection, reduction of systemic risk, fairness, efficiency, and transparency in markets? The operation and health of capital markets affect all of us and have profound implications for equality and justice in society. This unique set of chapters by leading scholars, industry insiders, and regulators sheds light on these and related questions and discusses ways to strengthen market governance for the benefit of society at large.


2020 ◽  
Vol 29 (4) ◽  
pp. 7-18
Author(s):  
Nathanael Berger ◽  
Mark DeSantis ◽  
David Porter

CFA Magazine ◽  
2011 ◽  
Vol 22 (2) ◽  
pp. 10-11 ◽  
Author(s):  
Frank Zhang ◽  
Stuart Baden Powell

Author(s):  
Andrei A. Kirilenko ◽  
Albert S. Kyle ◽  
Mehrdad Samadi ◽  
Tugkan Tuzun

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
GuangWei Shi ◽  
Yun Chen

Since China’s first stock index futures, China Securities Index 300 (CSI300) stock index futures were published in 2010, and China’s stock index futures market is now in a period of rapid development and play a key role in price discovery. During 2014 to 2015, China’s stock index futures market fluctuated abnormally, and the overuse of high-frequency trading (HFT) strategies in the stock index futures market was blamed as the main reason of the abnormal volatility. To lower down market fluctuation, the regulatory institute then announced a series of trade restriction policy to prevent the overuse of HFT behaviour. However, until now, the impact of such trade restriction policy for HFT remains uncertain. To tackle this issue, based on minute-level HFT data from the CSI 300 index futures market, this paper aims to investigate the relationship between HFT and the exogenous liquidity risk and how HFT affects China’s stock index futures market on its liquidity using the liquidity-adjusted value at risk (LVaR) model. The findings indicate that HFT improves the return of the liquidity provider and reduces the exogenous liquidity risk significantly.


2020 ◽  
Vol 27 (4) ◽  
pp. 51-76
Author(s):  
Panha Heng ◽  
Scott J. Niblock ◽  
Jennifer L. Harrison ◽  
Hansi Hu

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