67 citations · 107 across the 8 of their papers we have counts for
19 papers
Understanding stock market instability via graph auto-encoders
Dragos Gorduza, Xiaowen Dong, Stefan Zohren
Understanding stock market instability is a key question in financial management as practitioners seek to forecast breakdowns in asset co-movements which expose portfolios to rapid…
Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units
Zihao Zhang, Stefan Zohren
We design multi-horizon forecasting models for limit order book (LOB) data by using deep learning techniques. Unlike standard structures where a single prediction is made, we adopt…
Deep Learning for Market by Order Data
Zihao Zhang, Bryan Lim, Stefan Zohren
Market by order (MBO) data - a detailed feed of individual trade instructions for a given stock on an exchange - is arguably one of the most granular sources of microstructure info…
Building Cross-Sectional Systematic Strategies By Learning to Rank
Daniel Poh, Bryan Lim, Stefan Zohren +1
The success of a cross-sectional systematic strategy depends critically on accurately ranking assets prior to portfolio construction. Contemporary techniques perform this ranking s…
Sentiment Correlation in Financial News Networks and Associated Market Movements
Xingchen Wan, Jie Yang, Slavi Marinov +3
In an increasingly connected global market, news sentiment towards one company may not only indicate its own market performance, but can also be associated with a broader movement…
Investment sizing with deep learning prediction uncertainties for high-frequency Eurodollar futures trading
Trent Spears, Stefan Zohren, Stephen Roberts
In this work we show that prediction uncertainty estimates gleaned from deep learning models can be useful inputs for influencing the relative allocation of risk capital across tra…