Gurrib, Ikhlaas2021-02-032021-02-03© 20202020-10Gurrib, I. (2020). The relationship between a unified financial condition index and the most actively traded USD based foreign currency pairs. Institutions and Economies, 12(4), 93-127. https://ijie.um.edu.my/article/view/2689222321640https://ijie.um.edu.my/article/view/26892http://hdl.handle.net/20.500.12519/320This article is not available at CUD collection. The version of scholarly record of this article is published in Institutions and Economies (2020), available online at: https://ijie.um.edu.my/article/view/26892This study proposes a unified financial condition index centred around the most popular financial conditions indices used in the US and tests its relationship with the most actively traded USD based foreign currency pairs, namely the British pounds, Japanese yen, Australian dollar, Canadian dollar, Chinese yuan and the Indian rupee. Using weekly data over 1993-2018, this paper proposes a Unified Financial Condition Index (UFCI) under a principal component analysis framework. The index captures 78% of the variability inherent in St Louis Federal Reserve Financial Stress Index, the Chicago Fed National Financial Condition Index and the Adjusted National Financial Condition Index. Significant p-value of UFCI, homoscedasticity and a relatively stable root mean squared errors were observed only for EUR/USD. Mixed findings, found as lags, were increased, suggesting a weak relationship between UFCI and foreign currencies. The UFCI forecasting model is compared with the VIX (volatility index) based model, and also a random walk model. Although the UFCI model was superior only for the Canadian dollar, Chinese yuan and Indian rupee after considering heteroscedasticity in errors, results were sensitive to the number of lags and insignificant p-values. © 2020, Faculty of Economics and Administration. All rights reserved.enPermission to reuse abstract has been secured from Faculty of Economics and AdministrationExchange ratesFinancial conditionsForecastsPrincipal component analysisArticleCopyright : © 2020, Faculty of Economics and Administration. All rights reserved.