Skip to content
All library documents

VMAT: Volatility and Model Adaptation for Multivariate Pair Trading

Article arXiv papers · Author: Chenyanzi Yu et al.

Summary

The paper introduces Volatility & Model Adaption Trade-off (VMAT), a strategy for multivariate pair trading. It addresses a gap the authors identify in prior work: research often refines trading rules, while portfolio management across multiple time series and the choice of portfolio weights receive less attention. VMAT is presented as a way to account for this portfolio-level problem through a trade-off involving volatility and model adaptation.

The document reports experimental comparisons in which VMAT performs better in profit terms than baseline methods. However, the excerpt does not describe the strategy’s mechanics, the assets or period studied, the baselines, or risk-adjusted results. Its performance claim is therefore difficult to evaluate from the available description, and should not be treated as evidence of general profitability.

Key ideas

  • VMAT is proposed as a portfolio approach for multivariate pair trading.
  • The method focuses on a trade-off between volatility and model adaptation.
  • The paper highlights portfolio weighting as an underexplored issue in pair-trading research.
  • Experiments are said to show higher profit performance than baseline methods, but details are absent.

Tags

Full text
# Multivariate Pair Trading by Volatility & Model Adaption Trade-off


# Multivariate Pair Trading by Volatility & Model Adaption Trade-off









Pair trading is one of the most discussed topics among financial researches. Despite a growing base of work, portfolio management for multivariate time series is rarely discussed. On the other hand, most researches focus on refining strategy rules instead of finding the optimal portfolio weight. In this paper, we brought up a simple yet profitable strategy called Volatility & Model Adaption Trade-off (VMAT) to leverage the issues. Experiment studies show its superior profit performance over baselines.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.