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Two factors along the yield curve
Gong, Frank F.; Remolona, Eli M. (1996)
We estimate two-factor equilibrium models on different parts of the yield curve. In this exploration of the term structure of interest rates, we use two-factor affine yield models as our diagnostic tool. The exercise provides insights on how to reconcile the time-series dynamics of interest rates with the cross-sectional shapes of the term structure and on how movements in the yield curve are related to macroeconomic fundamentals. The evidence favors models in which one factor reverts over time to a time-varying mean. One such model seems adequate to explain three-month to two-year bond ...
Research Paper , Paper 9613

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A three-factor econometric model of the U.S. term structure
Remolona, Eli M.; Gong, Frank F. (1997)
We estimate and test a model of the U.S. term structure that fits both the time series of interest rates and the cross-sectional shapes of the yield and volatility curves. In the model, three unobserved factors drive a stochastic discount process that prices assets so as to rule out arbitrage opportunities. The resulting bond yields are conveniently affine in the factors. We use monthly zero-coupon yield data from January 1986 to March 1996 and estimate the model by applying a Kalman filter that takes into account the model's no-arbitrage restrictions and using only three maturities at a ...
Research Paper , Paper 9619

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Modeling volatility dynamics
Lopez, Jose A.; Diebold, Francis X. (1995)
Many economic and financial time series have been found to exhibit dynamics in variance; that is, the second moment of the time series innovations varies over time. Many possible model specifications are available to capture this phenomena, but to date, the class of models most widely used are autoregressive conditional heteroskedasticity (ARCH) models. ARCH models provide parsimonious approximations to volatility dynamics and have found wide use in macroeconomics and finance. The family of ARCH models is the subject of this paper. In section II, we sketch the rudiments of a rather general ...
Research Paper , Paper 9522

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Evaluating the predictive accuracy of volatility models
Lopez, Jose A. (1995)
The volatility forecast evaluations most meaningful to forecast users are those conducted under economically relevant loss functions. Although several such loss functions are proposed in the literature, their implied economic costs are of interest only to specific types of volatility forecast users. A forecast evaluation framework that incorporates a more general class of economic loss functions is proposed. A user's loss function specifies the three key elements of the evaluation framework: the economic events to be forecast, the criterion with which to evaluate these forecasts, and the ...
Research Paper , Paper 9524

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Conditional mean-variance efficiency of the U.S. stock market
Froot, Kenneth A.; Engel, Charles; Frankel, Jeffrey A.; Rodrigues, Anthony P. (1989)
Research Paper , Paper 8901

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How stable is the predictive power of the yield curve? evidence from Germany and the United States
Estrella, Arturo; Rodrigues, Anthony P.; Schich, Sebastian (2000)
Empirical research over the last decade has uncovered predictive relationships between the slope of the yield curve and subsequent real activity and inflation. Some of these relationships are highly significant, but their theoretical motivations suggest that they may not be stable over time. We use recent econometric techniques for break testing to examine whether the empirical relationships are in fact stable. We consider continuous models, which predict either economic growth or inflation, and binary models, which predict either recessions or inflationary pressure. In each case, we draw on ...
Staff Reports , Paper 113

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Inflation dynamics in a small open-economy model under inflation targeting: some evidence from Chile
Del Negro, Marco; Schorfheide, Frank (2008)
This paper estimates a small open-economy dynamic stochastic general equilibrium (DSGE) model, specified along the lines of Gal and Monacelli (2005) and Lubik and Schorfheide (2007), using Chilean data for the full inflation-targeting period of 1999 to 2007. We study the specification of the policy rule followed by the Central Bank of Chile, the dynamic response of inflation to domestic and external shocks, and the change in these dynamics under different policy parameters. We use the DSGE-VAR methodology from our earlier work (2007) to assess the robustness of the conclusion to the presence ...
Staff Reports , Paper 329

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Forecasting economic and financial variables with global VARs
Pesaran, M. Hashem; Schuermann, Til; Smith, L. Vanessa (2008)
This paper considers the problem of forecasting real and financial macroeconomic variables across a large number of countries in the global economy. To this end, a global vector autoregressive (GVAR) model previously estimated over the 1979:Q1-2003:Q4 period by Dees, de Mauro, Pesaran, and Smith (2007) is used to generate out-of-sample one-quarter- and four-quarters-ahead forecasts of real output, inflation, real equity prices, exchange rates, and interest rates over the period 2004:Q1-2005:Q4. Forecasts are obtained for 134 variables from twenty-six regions made up of thirty-three countries ...
Staff Reports , Paper 317

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Generalized canonical regression
Estrella, Arturo (2007)
This paper introduces a generalized approach to canonical regression, in which a set of jointly dependent variables enters the left-hand side of the equation as a linear combination, formally like the linear combination of regressors in the right-hand side of the equation. Natural applications occur when the dependent variable is the sum of components that may optimally receive unequal weights or in time series models in which the appropriate timing of the dependent variable is not known a priori. The paper derives a quasi-maximum likelihood estimator as well as its asymptotic distribution ...
Staff Reports , Paper 288

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Extracting business cycle fluctuations: what do time series filters really do?
Estrella, Arturo (2007)
Various methods are available to extract the "business cycle component" of a given time series variable. These methods may be derived as solutions to frequency extraction or signal extraction problems and differ in both their handling of trends and noise and their assumptions about the ideal time-series properties of a business cycle component. The filters are frequently illustrated by application to white noise, but applications to other processes may have very different and possibly unintended effects. This paper examines several frequently used filters as they apply to a range of dynamic ...
Staff Reports , Paper 289

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