Emeritus ProfessorTony Constantinides, FREng
Honorary Emeritus Professor of Comm & Signal Processing
Department of Electrical and Electronic Engineering - Faculty of Engineering
- Honorary Emeritus Professor of Comm & Signal ProcessingDepartment of Electrical and Electronic Engineering - Faculty of Engineering
- 020 7594 6231 (Work)
- 618, Electrical Engineering, South Kensington Campus, United Kingdom
RESEARCH
Financial Signal Processing
Currently, Professor Constantinides leads the Financial Signal Processing Laboratory and his latest research is focused on the following topics:
Short Term Prediction and Long Term Forecasting of financial time series using unique advanced Digital Signal Processing and Machine Learning algorithms, including also advanced stochastic techniques through tailored Kalman Filters, Particle Filters and others.
Moving Horizon Portfolio Optimization based on Adaptive Constrained Optimization Algorithms. Targets can include typically Mean-Variance, including Asymmetric Variance, Risk Minimization, Optimal Hedging.
Unique Very Low Latency Financial Data Smoothing and Modelling
New algorithms from unique areas of Surrogate Time Series Models, Endomorphic Models, Instantaneous Frequencies/Amplitudes/Data Bandwidths, Financial Data Dominant Component Models and Prediction.
Currently, Professor Constantinides leads the Financial Signal Processing Laboratory and his latest research is focused on the following topics:
Short Term Prediction and Long Term Forecasting of financial time series using unique advanced Digital Signal Processing and Machine Learning algorithms, including also advanced stochastic techniques through tailored Kalman Filters, Particle Filters and others.
Moving Horizon Portfolio Optimization based on Adaptive Constrained Optimization Algorithms. Targets can include typically Mean-Variance, including Asymmetric Variance, Risk Minimization, Optimal Hedging.
Unique Very Low Latency Financial Data Smoothing and Modelling
New algorithms from unique areas of Surrogate Time Series Models, Endomorphic Models, Instantaneous Frequencies/Amplitudes/Data Bandwidths, Financial Data Dominant Component Models and Prediction.