RQA Application for the Monitoring of Financial and Commodity markets state

TL;DR

This paper explores the use of Recurrence Quantification Analysis (RQA), a nonlinear method, to monitor financial and commodity markets in real time, aiming to detect market regularities during frequent crashes and crises.

Contribution

It applies RQA to a diverse set of financial and commodity time series for the first time in this context, demonstrating its potential for real-time market monitoring.

Findings

RQA reveals market regularities during crises

Effective for monitoring multiple asset classes

Potential for real-time financial analysis

Abstract

Nowadays, when crashes and crises are rather frequent events, an effective monitoring system for the international financial market is needed. Modern nonlinear methods, such as Recurrence Quantification Analysis (RQA), demonstrate the ability to reveal the regularities of the system behavior. Thus, they can be useful for the analysis of the market state in real time. In present paper we did an effort to apply the RQA for the purpose of economic time series monitoring. 12 stock indexes, 6 currency pairs and 4 commodities were taken for the study.