Linear Trading Position with Sparse Spectrum

Fuente: arXiv
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Auteurs principaux: Lai, Zhao-Rong, Yang, Haisheng
Format: Preprint
Publié: 2025
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author Lai, Zhao-Rong
Yang, Haisheng
author_facet Lai, Zhao-Rong
Yang, Haisheng
contents The principal portfolio approach is an emerging method in signal-based trading. However, these principal portfolios may not be diversified to explore the key features of the prediction matrix or robust to different situations. To address this problem, we propose a novel linear trading position with sparse spectrum that can explore a larger spectral region of the prediction matrix. We also develop a Krasnosel'ski\u ı-Mann fixed-point algorithm to optimize this trading position, which possesses the descent property and achieves a linear convergence rate in the objective value. This is a new theoretical result for this type of algorithms. Extensive experiments show that the proposed method achieves good and robust performance in various situations.
format Preprint
id arxiv_https___arxiv_org_abs_2508_18596
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Linear Trading Position with Sparse Spectrum
Lai, Zhao-Rong
Yang, Haisheng
Machine Learning
The principal portfolio approach is an emerging method in signal-based trading. However, these principal portfolios may not be diversified to explore the key features of the prediction matrix or robust to different situations. To address this problem, we propose a novel linear trading position with sparse spectrum that can explore a larger spectral region of the prediction matrix. We also develop a Krasnosel'ski\u ı-Mann fixed-point algorithm to optimize this trading position, which possesses the descent property and achieves a linear convergence rate in the objective value. This is a new theoretical result for this type of algorithms. Extensive experiments show that the proposed method achieves good and robust performance in various situations.
title Linear Trading Position with Sparse Spectrum
topic Machine Learning
url https://arxiv.org/abs/2508.18596