Toy Model for Large Non-Symmetric Random Matrices

TL;DR

This paper introduces a toy model for large non-symmetric random matrices to analyze correlations in high-dimensional data, offering an alternative to classical cointegration methods in economics.

Contribution

It develops a novel toy model for non-symmetric matrices and demonstrates its application to macroeconomic data analysis, providing a new approach to correlation detection.

Findings

Effective extraction of meaningful correlations in large datasets

Application to Polish macroeconomic data shows practical utility

Offers an alternative to classical cointegration methods

Abstract

Non-symmetric rectangular correlation matrices occur in many problems in economics. We test the method of extracting statistically meaningful correlations between input and output variables of large dimensionality and build a toy model for artificially included correlations in large random time series.The results are then applied to analysis of polish macroeconomic data and can be used as an alternative to classical cointegration approach.