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Stefano Mazzotta

3 June 2004
WORKING PAPER SERIES - No. 366
Details
Abstract
Financial decision makers often consider the information in currency option valuations when making assessments about future exchange rates. The purpose of this paper is to systematically assess the quality of option based volatility, interval and density forecasts. We use a unique dataset consisting of over 10 years of daily data on over-the-counter currency option prices. We find that the OTC implied volatilities explain a much larger share of the variation in realized volatility than previously found using market-traded options. Finally, we find that wide-range interval and density forecasts are often misspecified whereas narrow-range interval forecasts are well specified.
JEL Code
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
28 February 2005
WORKING PAPER SERIES - No. 447
Details
Abstract
We compare option-implied correlation forecasts from a dataset consisting of over 10 years of daily data on over-the-counter (OTC) currency option prices to a set of return-based correlation measures and assess the relative quality of the correlation forecasts. We find that while the predictive power of implied correlation is not always superior to that of returns based correlations measures, it tends to provide the most consistent results across currencies. Predictions that use both implied and returns-based correlations generate the highest adjusted R2s, explaining up to 42 per cent of the realised correlations. We then apply the correlation forecasts to two policyrelevant topics, to produce scenario analyses for the euro effective exchange rate index, and to analyse the impact on cross-currency co-movement of interventions on the JPY/USD exchange rate.
JEL Code
F31 : International Economics→International Finance→Foreign Exchange
F37 : International Economics→International Finance→International Finance Forecasting and Simulation: Models and Applications
G15 : Financial Economics→General Financial Markets→International Financial Markets