The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …

We demonstrate the application of an algorithmic trading strategy based upon the recently
developed dynamic mode decomposition on portfolios of financial data. The method is …

Managing the prediction of metrics in high‐frequency financial markets is a challenging task.
An efficient way is by monitoring the dynamics of a limit order book to identify the information …

Motivated by the literature on investment flows and optimal trading, we examine intraday
predictability in the cross‐section of stock returns. We find a striking pattern of return …

The Science of Algorithmic Trading and Portfolio Management, with its emphasis on
algorithmic trading processes and current trading models, sits apart from others of its kind …

Electronic trading of equities and other securities makes heavy use of “arrival price”
algorithms, that determine optimal trade schedules by balancing the market impact cost of …

The optimal trade execution problem is formulated in terms of a mean-variance tradeoff, as
seen at the initial time. The mean-variance problem can be embedded in a linear–quadratic …

Electronic trading of equities and other securities makes heavy use of 'arrival
price'algorithms that balance the market impact cost of rapid execution against the volatility …

We propose a general framework for intraday trading based on the control of trading
algorithms. Given a set of generic parameterized algorithms (which have to be specified by …

This paper is split in three parts: first, we use labeled trade data to exhibit how market
participants' decisions depend on liquidity imbalance; then, we develop a stochastic control …