78 citations · 161 across the 7 of their papers we have counts for
10 papers
What Makes An Asset Useful?
Yves-Laurent Kom Samo, Dieter Hendricks
Given a new candidate asset represented as a time series of returns, how should a quantitative investment manager be thinking about assessing its usefulness? This is a key qualitat…
Inferring agent objectives at different scales of a complex adaptive system
Dieter Hendricks, Adam Cobb, Richard Everett +2
We introduce a framework to study the effective objectives at different time scales of financial market microstructure. The financial market can be regarded as a complex adaptive s…
Optimal client recommendation for market makers in illiquid financial products
Dieter Hendricks, Stephen J. Roberts
The process of liquidity provision in financial markets can result in prolonged exposure to illiquid instruments for market makers. In this case, where a proprietary position is no…
The statistical significance of multivariate Hawkes processes fitted to limit order book data
Roger Martins, Dieter Hendricks
Hawkes processes have seen a number of applications in finance, due to their ability to capture event clustering behaviour typically observed in financial systems. Given a calibrat…
Using real-time cluster configurations of streaming asynchronous features as online state descriptors in financial markets
Dieter Hendricks
We present a scheme for online, unsupervised state discovery and detection from streaming, multi-featured, asynchronous data in high-frequency financial markets. Online feature cor…
Deviations in expected price impact for small transaction volumes under fee restructuring
Michael Harvey, Dieter Hendricks, Tim Gebbie +1
We report on the occurrence of an anomaly in the price impacts of small transaction volumes following a change in the fee structure of an electronic market. We first review evidenc…
Statistical Inference, Learning and Models in Big Data
Beate Franke, Jean-François Plante, Ribana Roscher +11
The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context. Statistical ideas are an essenti…
Detecting intraday financial market states using temporal clustering
Dieter Hendricks, Tim Gebbie, Diane Wilcox
We propose the application of a high-speed maximum likelihood clustering algorithm to detect temporal financial market states, using correlation matrices estimated from intraday ma…
A reinforcement learning extension to the Almgren-Chriss model for optimal trade execution
Dieter Hendricks, Diane Wilcox
Reinforcement learning is explored as a candidate machine learning technique to enhance existing analytical solutions for optimal trade execution with elements from the market micr…
High-speed detection of emergent market clustering via an unsupervised parallel genetic algorithm
Dieter Hendricks, Diane Wilcox, Tim Gebbie
We implement a master-slave parallel genetic algorithm (PGA) with a bespoke log-likelihood fitness function to identify emergent clusters within price evolutions. We use graphics p…