FOREX & FUNDAMENTALS

Exchange Rates and Fundamentals

Coordinatore	EUROPEAN UNIVERSITY INSTITUTE    more  Organization address address: Via dei Roccettini 9 city: FIESOLE postcode: 50014 contact info Titolo: Mrs. Nome: Serena Cognome: Scarselli Email: send email Telefono: 390555000000 Fax: 390555000000
Nazionalità Coordinatore	Italy [IT]
Totale costo	83˙869 €
EC contributo	83˙869 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2009-IEF
Funding Scheme	MC-IEF
Anno di inizio	2010
Periodo (anno-mese-giorno)	2010-05-01   -   2011-04-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	EUROPEAN UNIVERSITY INSTITUTE  Organization address address: Via dei Roccettini 9 city: FIESOLE postcode: 50014 contact info Titolo: Mrs. Nome: Serena Cognome: Scarselli Email: send email Telefono: 390555000000 Fax: 390555000000	IT (FIESOLE)	coordinator	83˙869.70

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 Obiettivo del progetto (Objective)

'This proposal builds upon the seminal work of Engel & West (JPE, 2005) on the relationship between FX rates (FXRs) & fundamentals (FMs). They deal with the long-standing puzzle in international economics, which is the difficulty of linking floating FXRs to macroeconomic FMs. In this project, we take a new line of attack on the question of co-movement between FXRs & FMs as well as between FXRs. We work with the class of asset-pricing models of Engel & West (EW). We attempt to empirically verify their theoretical conclusion that large discount factors account for random walk behavior in FXRs. We also deal with the following: if the FX models imply RW behavior, so that their changes are unpredictable, how then can we validate the models? The study investigates different forecasting horizons & frequencies of the 6 “FX majors” & differentials of Macro-FMs relative to US. The project develops in three phases; first we explore the “nature” & direction of FXRs-FMs causality. Then a new linear/nonlinear causality-based model selection methodology is introduced & applied to forecasting. Finally, the causality-based criteria are compared to well-known methods & forecast measures. We extend the various linear multivariate models of EW towards nonlinear ones with time-varying parameters, structural breaks, regime switches & Bayesian estimation. The recent evidence on causality is based on the linear parametric Granger test, although it has low power against nonlinear alternatives. The nonparametric test by Hiemstra-Jones (1994), which is a modified version of the Baek-Brock’s (1992), is regarded a test for nonlinear dynamic causal relationship. We employ a multi-step empirical methodology as in Bekiros & Diks (2008), using multivariate VAR/VECM/GARCH filtering combined with linear & nonlinear causality tests. Improved knowledge of the direction & nature of causalities will expand the information set available to policymakers for decision-making.'