The best of two worlds: Forecasting high frequency volatility for cryptocurrencies and traditional currencies with Support Vector Regression

Y Peng, PHM Albuquerque, JMC de Sá… - Expert Systems with …, 2018 - Elsevier
This paper provides an evaluation of the predictive performance of the volatility of three
cryptocurrencies and three currencies with recognized stores of value using daily and hourly …

[HTML][HTML] Deep learning in the stock market—a systematic survey of practice, backtesting, and applications

K Olorunnimbe, H Viktor - Artificial Intelligence Review, 2023 - Springer
The widespread usage of machine learning in different mainstream contexts has made deep
learning the technique of choice in various domains, including finance. This systematic …

High‐frequency trading: Definition, implications, and controversies

KZ Zaharudin, MR Young… - Journal of Economic …, 2022 - Wiley Online Library
High‐frequency trading (HFT) is an important component of stock market activity on major
exchanges. In the United States, HFT contributed approximately 52% of total equity trading …

What's not there: Odd lots and market data

M O'hara, C Yao, M Ye - The Journal of Finance, 2014 - Wiley Online Library
We investigate odd‐lot trades in equity markets. Odd lots are increasingly used in
algorithmic and high‐frequency trading, but are not reported to the consolidated tape or in …

Back-running: Seeking and hiding fundamental information in order flows

L Yang, H Zhu - The Review of Financial Studies, 2020 - academic.oup.com
We model the strategic interaction between fundamental investors and “back-runners,”
whose only information is about the past order flow of fundamental investors. Back-runners …

[HTML][HTML] Abrupt rise of new machine ecology beyond human response time

N Johnson, G Zhao, E Hunsader, H Qi, N Johnson… - Scientific reports, 2013 - nature.com
Society's techno-social systems are becoming ever faster and more computer-orientated.
However, far from simply generating faster versions of existing behaviour, we show that this …

Microstructure in the machine age

D Easley, M López de Prado, M O'Hara… - The Review of …, 2021 - academic.oup.com
Understanding modern market microstructure phenomena requires large amounts of data
and advanced mathematical tools. We demonstrate how machine learning can be applied to …

How algorithmic trading undermines efficiency in capital markets

Y Yadav - Vand. L. Rev., 2015 - HeinOnline
In 2012, traders in the United States submitted over two billion offers to buy and sell
securities on major national exchanges, resulting in around seventy-four million completed …

[BOOK][B] A political economy of contemporary capitalism and its crisis: Demystifying finance

D Sotiropoulos, J Milios, S Lapatsioras - 2013 - api.taylorfrancis.com
The recent financial meltdown and the resulting global recession have rekindled debates
regarding the nature of contemporary capitalism. This book analyses the ongoing …

Discerning information from trade data

D Easley, ML De Prado, M O'Hara - Journal of Financial Economics, 2016 - Elsevier
How best to discern trading intentions from market data? We examine the accuracy of three
methods for classifying trade data: bulk volume classification (BVC), tick rule and …