This paper develops a new neural network architecture for modeling spatial distributions (ie
distributions on R d) which is more computationally efficient than a traditional fully …

The purpose of the paper is to understand the role of strategic flexibility in mediating
between leadership and strategy execution among private enterprises in Bangladesh which …

Algorithmic trading strategies for execution often focus on the individual agent who is
liquidating/acquiring shares. When generalized to multiple agents, the resulting stochastic …

In this chapter, we overview the uses of machine learning for high frequency trading and
market microstructure data and problems. Machine learning is a vibrant subfield of computer …

We analyze the optimal execution problem of a portfolio manager trading multiple assets. In
addition to the liquidity and risk of each individual asset, we consider cross asset …

I study the presence of order anticipation strategies by examining predictable patterns in
large order trades. I construct three simple signals based on child‐order execution patterns …

We consider a Nash equilibrium between two high-frequency traders (HFTs) in a simple
market impact model with transient price impact and additional quadratic transaction costs …

We consider n risk‐averse agents who compete for liquidity in an Almgren–Chriss market
impact model. Mathematically, this situation can be described by a Nash equilibrium for a …

We consider a market impact game for n risk-averse agents that are competing in a market
model with linear transient price impact and additional transaction costs. For both finite and …

We study the high-frequency limits of strategies and costs in a Nash equilibrium for two
agents that are competing to minimize liquidation costs in a discrete-time market impact …