Foreign Exchange Market Performance: Evidence from Bivariate Time Series Approach

TL;DR

This paper introduces a bivariate time series approach using Escoufier's RV coefficient to analyze currency similarities in the foreign exchange market, offering a new perspective on market structure analysis.

Contribution

It applies the RV coefficient to bivariate time series for currency similarity measurement, enhancing the analysis of forex market topology.

Findings

Demonstrates the effectiveness of RV coefficient in forex analysis

Provides insights into currency network structure

Highlights advantages over univariate approaches

Abstract

There are many studies dealing with the analysis of similarity among currencies in foreign exchange market by using network analysis approach. In those studies, each currency is represented by a univariate time series of exchange rate return. This is the standard practice to analyze the underlying information in the foreign exchange market. In this paper, Escoufier's RV coefficient is applied to measure the similarity among currencies where each of them is represented by bivariate time series. Based on that coefficient, we analyze the topological structure of the currencies. An example of FOREX analysis will be presented and discussed to illustrate the advantages of RV coefficient.