Phantom Liquidity and High-Frequency Quoting

Blocher, Jesse; Cooper, Ricky; Seddon, Jonathan J. M.; Vliet, Ben Van

doi:10.3905/jot.2016.11.3.006

Cited by 23 publications

(16 citation statements)

References 8 publications

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“…210 Under the historical-categorical approach, "the fact that the United States has a deeply rooted tradition of comparatively stringent urban gun control is an argument for treating contemporary urban gun control as, if not 'presumptively lawful,' at least meriting special deference." 211 The same can be said in reverse. Given rural America's deeply rooted lack of firearm regulation, owing to its historically robust gun culture, local tailoring of firearm restrictions should look different, and at least come from the popularly elected officials in those localities.…”

Section: Constitutional Home Rulementioning

confidence: 96%

Second Amendment Sanctuaries

Fields

2020

SSRN Journal

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Section: Constitutional Home Rulementioning

confidence: 96%

Second Amendment Sanctuaries

Fields

2020

SSRN Journal

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“…Yueshen (2014), for example, argues that following changes in asset prices, there may be a race by fast traders to be the first-in-line at the new equilibrium price leading to a temporary spike in depth before traders realize their actual position in the queue and, through subsequent cancellations, depth normalizes. Blocher et al (2016) identify clusters of extremely high and extremely low limit order cancellation activity using data on all the S&P 500 stocks for the calendar year of 2012. They find that cancel clusters largely appear to be generated by HFTs sparring with one another to get to the front of the limit order queue, rather than HFTs trapping unsuspecting investors into bad executions.…”

Section: Literature Review and Research Objectivesmentioning

confidence: 99%

Cross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidity

et al. 2019

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Wuyts as well as participants of the Group of Economic Advisors at ESMA, seminar participants at KU Leuven, participants at the 35 th Spring AFFI conference, the 4 th WiM meeting, the 2 nd ECM Workshop, and the 2 nd SAFE Market Microstructure Conference for their comments. We thank Yujuan Zhang for excellent research assistance, ESMA for providing access to the data, and the French National Research Agency (ANR) for funding through project GHOST. The views presented in this paper are those of the authors and do not necessarily reflect the views of ESMA.

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“…The global financial markets were fragmented due to rapid globalization and technological changes (Funk et al) [27]. In one of study on liquidity, Blocher et al [28] identified three key components of the financial market like 1) fund management for long term investors, 2) low-frequency trading (LFT) by the traditional brokers and 3) and high-frequency trading (HFT) by proprietary financial firms which used the Big Data and aggregated information to set the trading strategy. The capital market industry has varied data source, which included structured data like traditional banking transaction data and market data which is also called the "system of records".…”

Section: Social Media and Emerging Technologiesmentioning

confidence: 99%

A Deep Dive: Does Big Data Improve Maturity in the Developed Capital Markets?

Singh¹,

Mitra²

2019

TEL

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Over this decade, the concept of big data has been applied to industries but the capital markets have been traditionally laggard to adoption. Within the financial services' sector, Big Data has gained far more traction within retail banking and insurance due to the increasing desire of these financial institutions to profile and analyze their customers in a similar manner to early adopters of Big Data strategy such as Amazon, Baidu or Google. However, Big Data strategies have begun to make some impacts on few selected areas of the capital markets, including the social media sentiment analysis on the structured and unstructured data for trading, growth in volume, risk analytics, fraud prevention, market surveillance, predictability and forecasting of the equity prices; those are the early sign of the maturity of the capital markets. Technical and theoretical measures have evolved, but still these dimensions of the capital markets have been a mystery for the human beings till now. The Big Data in the form of structured, semi-structured and unstructured socioeconomic and demographic information from social media and blogs from consumers has started indicating impacts on the capital markets which can lead to improving the real-time systems and transaction processing, and improving operational efficiency and maturity. The intent of this paper is threefold. First, it aims to bring the clear inference from the past researches to take a holistic analysis of the work done in the emerging area of Big Data and its implications on capital markets. Second, it's to perform a deep analysis on how the influences of Big Data affect the assumptions in connection with Random Walk theory and Efficient Market Hypothesis. Third, it will provide a conclusive theoretical analysis of past research work by the scholars, which can establish the model to refine the nexus between investors' sentiments and assets' prices with advanced techniques in the Big Data. The paper has been divided into 4 broad sections. In the first section, the paper sets the introduction of connecting the dots and setting the context for the two different fields like Big Data and its influences on the capital markets. The second section

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Phantom Liquidity and High-Frequency Quoting

Cited by 23 publications

References 8 publications

Second Amendment Sanctuaries

Second Amendment Sanctuaries

Cross-Venue Liquidity Provision: High Frequency Trading and Ghost Liquidity

A Deep Dive: Does Big Data Improve Maturity in the Developed Capital Markets?

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