Forecasting realized exchange rate volatility by decomposition

Abstract We compare forecasts of the realized volatility of the exchange rate returns of the Euro against the U.S. Dollar and the Japanese Yen obtained both directly and through decomposition. Decomposing the realized volatility into its continuous sample path and jump components, and modeling and forecasting them separately instead of directly forecasting the realized volatility, is shown to lead to improved out-of-sample forecasts. Moreover, the gains in forecast accuracy are fairly robust with respect to the details of the decomposition, but the jump component should probably not be defined too tightly.

[1]  Fulvio Corsi,et al.  A Simple Long Memory Model of Realized Volatility , 2004 .

[2]  George Tauchen,et al.  Cross-Stock Comparisons of the Relative Contribution of Jumps to Total Price Variance , 2012 .

[3]  P. Hansen A Test for Superior Predictive Ability , 2005 .

[4]  Francis X. Diebold,et al.  Modeling and Forecasting Realized Volatility , 2001 .

[5]  F. Diebold,et al.  Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility , 2005, The Review of Economics and Statistics.

[6]  James D. Hamilton Specification testing in Markov-switching time-series models , 1996 .

[7]  P. Hansen,et al.  Consistent Ranking of Volatility Models , 2006 .

[8]  James D. Hamilton A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .

[9]  Jon Danielsson,et al.  Real trading patterns and prices in spot foreign exchange markets , 2002 .

[10]  N. Shephard,et al.  Power and bipower variation with stochastic volatility and jumps , 2003 .

[11]  Anthony S. Tay,et al.  Evaluating Density Forecasts with Applications to Financial Risk Management , 1998 .

[12]  Markku Lanne,et al.  A Mixture Multiplicative Error Model for Realized Volatility , 2006 .

[13]  Franz C. Palm,et al.  The message in weekly exchange rates in the European Monetary System: mean reversion , 1993 .

[14]  M. Dacorogna,et al.  Volatilities of different time resolutions — Analyzing the dynamics of market components , 1997 .

[15]  Daniel B. Nelson,et al.  Inequality Constraints in the Univariate GARCH Model , 1992 .

[16]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.