NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

The Forecasting Ability of Correlations Implied in Foreign Exchange Options

Jose M. Campa, P. H. Kevin Chang

NBER Working Paper No. 5974
Issued in March 1997
NBER Program(s):   AP   IFM

This paper evaluates the forecasting accuracy of correlation derived from implied volatilities in dollar-mark, dollar-yen, and mark-yen options from January 1989 to May 1995. As a forecast of realized correlation between the dollar-mark and dollar-yen, implied correlation is compared against three alternative forecasts based on time series data: historical correlation, RiskMetrics' exponentially weighted moving average correlation, and correlation estimated using a bivariate GARCH (1,1) model. At the one-month and three-month forecast horizons, we find that implied correlation outperforms, often significantly, these alternative forecasts. In combinations, implied correlation always incrementally improves the performance of other forecasts, but not the converse; in certain cases historically based forecasts contribute no incremental information to implied forecasts. The superiority of the implied correlation forecast holds even when forecast errors are weighted by realized variances, reflecting correlation's contribution to the dollar variance of a multicurrency portfolio.

download in pdf format
   (1350 K)

email paper

This paper is available as PDF (1350 K) or via email.

Machine-readable bibliographic record - MARC, RIS, BibTeX

Document Object Identifier (DOI): 10.3386/w5974

Published:

Users who downloaded this paper also downloaded these:
Campa, Chang, and Reider w6179 Implied Exchange Rate Distributions: Evidence from OTC Option Markets
Engle and Sheppard w8554 Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH
Gorton and Souleles Special Purpose Vehicles and Securitization
 
Publications
Activities
Meetings
NBER Videos
Data
People
About

Support
National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138; 617-868-3900; email: info@nber.org

Contact Us