Abstract

https://ssrn.com/abstract=2700350
 


 



Noisy Information and Expectation Formation in the Foreign Exchange Market


Alex Luiz Ferreira


University of São Paulo

Michael Moore


University of Warwick - Warwick Business School

Satrajit Mukherjee


Ghent University - Department of Financial Economics

December 15, 2015


Abstract:     
Market microstructure and the imperfect common knowledge literature in macroeconomics both analyze the effect of dispersed information on prices. This paper draws on both sources to understand exchange rate forecasting errors. A theoretical model is developed showing that forecasting errors depend on both forecast revisions as in the Woodford noisy information model and order flow as in the Evans-Lyons simultaneous trade model. This is applied to Brazilian data using a unique data set of daily consensus exchange rate forecasts managed by the Banco Central do Brasil along with order flow derived from the FX futures market. The results strongly support the theory.

Number of Pages in PDF File: 34

Keywords: Noisy Information, Microstructure, Order Flow, Exchange Rates

JEL Classification: F31, F37, G14, D82


Open PDF in Browser Download This Paper

Date posted: December 9, 2015 ; Last revised: December 21, 2016

Suggested Citation

Ferreira, Alex Luiz and Moore, Michael and Mukherjee, Satrajit, Noisy Information and Expectation Formation in the Foreign Exchange Market (December 15, 2015). Available at SSRN: https://ssrn.com/abstract=2700350 or http://dx.doi.org/10.2139/ssrn.2700350

Contact Information

Alex Luiz Ferreira
University of São Paulo ( email )
Av. Bandeirantes 3900 - Monte Alegre
Ribeião Preto, 14040-900
Brazil
Michael John Moore (Contact Author)
University of Warwick - Warwick Business School ( email )
Coventry CV4 7AL
United Kingdom
Satrajit Mukherjee
Ghent University - Department of Financial Economics ( email )
Sint-Pietersplein 5
Ghent, East Flanders B9000
Belgium
Feedback to SSRN


Paper statistics
Abstract Views: 509
Downloads: 90
Download Rank: 225,024