Maximally machine-learnable portfolios
P Goulet Coulombe, M Göbel - Available at SSRN 4428178, 2023 - papers.ssrn.com
When it comes to stock returns, any form of predictability can bolster risk-adjusted
profitability. We develop a collaborative machine learning algorithm that optimizes portfolio …
profitability. We develop a collaborative machine learning algorithm that optimizes portfolio …
High-dimensional canonical correlation analysis
A Bykhovskaya, V Gorin - arXiv preprint arXiv:2306.16393, 2023 - arxiv.org
This paper studies high-dimensional canonical correlation analysis (CCA) with an emphasis
on vectors which define canonical variables. The paper shows that when two dimensions of …
on vectors which define canonical variables. The paper shows that when two dimensions of …
Maximally machine-learnable portfolios
PG Coulombe, M Goebel - arXiv preprint arXiv:2306.05568, 2023 - arxiv.org
When it comes to stock returns, any form of predictability can bolster risk-adjusted
profitability. We develop a collaborative machine learning algorithm that optimizes portfolio …
profitability. We develop a collaborative machine learning algorithm that optimizes portfolio …
Dynamic Portfolio Selection under Transaction Costs and Signal Decay
This paper presents an analytical solution to the dynamic portfolio selection problem,
considering transaction costs and signals with different persistence properties. Our …
considering transaction costs and signals with different persistence properties. Our …
The Symmetric Generalized Eigenvalue Problem as a Nash Equilibrium
I Gemp, C Chen, B McWilliams - arXiv preprint arXiv:2206.04993, 2022 - arxiv.org
The symmetric generalized eigenvalue problem (SGEP) is a fundamental concept in
numerical linear algebra. It captures the solution of many classical machine learning …
numerical linear algebra. It captures the solution of many classical machine learning …
Accelerating Machine Learning Training Time for Limit Order Book Prediction
MJ Bennett - arXiv preprint arXiv:2206.09041, 2022 - arxiv.org
Financial firms are interested in simulation to discover whether a given algorithm involving
financial machine learning will operate profitably. While many versions of this type of …
financial machine learning will operate profitably. While many versions of this type of …
Commonality in Two-Dimensions: an Empirical Investigation
Z Zhou - 2022 - search.proquest.com
In this thesis, I follow Hasbrouck and Seppi (2001)'s work and use reduced-rank regression
to model the commonality in Chapter Two. The literature on the study of return commonality …
to model the commonality in Chapter Two. The literature on the study of return commonality …
[引用][C] The generalized eigenvalue problem as a nash equilibrium
I Gemp, C Chen, B McWilliams - arXiv preprint arXiv:2206.04993, 2022