3 citations · 6 across the 4 of their papers we have counts for
4 papers
Efficient structure learning with automatic sparsity selection for causal graph processes
Théophile Griveau-Billion, Ben Calderhead
We propose a novel algorithm for efficiently computing a sparse directed adjacency matrix from a group of time series following a causal graph process. Our solution is scalable for…
Efficient computation of mean reverting portfolios using cyclical coordinate descent
Théophile Griveau-Billion, Ben Calderhead
The econometric challenge of finding sparse mean reverting portfolios based on a subset of a large number of assets is well known. Many current state-of-the-art approaches fall int…
A Dynamic Bayesian Model for Interpretable Decompositions of Market Behaviour
Théophile Griveau-Billion, Ben Calderhead
We propose a heterogeneous simultaneous graphical dynamic linear model (H-SGDLM), which extends the standard SGDLM framework to incorporate a heterogeneous autoregressive realised…
A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios
Théophile Griveau-Billion, Jean-Charles Richard, Thierry Roncalli
In this paper we propose a cyclical coordinate descent (CCD) algorithm for solving high dimensional risk parity problems. We show that this algorithm converges and is very fast eve…