71 research outputs found
Estimating the Price of Default Risk
No full textthis article are those of the author and do not indicate concurrence by other members of the research staff, by the Board of Governors, or by the Federal Reserve Banks. Address correspondence to Greg Duffee, Mail Stop 91, Federal Reserve Board, Washington, DC 20551, or email: [email protected]
Idiosyncratic Variation of Treasury Bill Yields.
No full textThe author documents a dramatic increase in the importance of two types of variation in Treasury bill yields beginning in the early 1980s. The first is idiosyncratic variation in individual short-maturity (less than three months) bill yields. The second is a common component in Treasury bill yields that is not shared by yields on other instruments, such as short-maturity privately issued instruments or longer-maturity Treasury notes and bonds. Some evidence suggests the first type reflects increased market segmentation. These results have important implications for the calibration and testing of no-arbitrage term structure models and interpreting tests of the expectations hypothesis. Copyright 1996 by American Finance Association.
Term structure estimation without using latent factors
No full textA combination of observed and unobserved (latent) factors capture term structure dynamics. Information about these dynamics is extracted from observed factors using restrictions implied by no-arbitrage, without specifying or estimating any of the parameters associated with latent factors. Estimation is equivalent to fitting the moment conditions of a set of regressions, where no-arbitrage imposes cross-equation restrictions on the coefficients. The methodology is applied to the dynamics of inflation and yields. Outside of the disinflationary period of 1979 through 1983, short-term rates move one-for-one with expected inflation, while bond risk premia are insensitive to inflation. r 2005 Elsevier B.V. All rights reserved. JEL classification: C51; E43; E4
Information in (and not in) the term structure
No full textStandard approaches to building and estimating dynamic term structure models rely on the assumption that yields can serve as the factors. However, the assumption is neither theoretically necessary nor empirically supported. This paper documents that almost half of the variation in bond risk premia cannot be detected using the cross section of yields. Fluctuations in this hidden component have strong forecast power for both future short-term interest rates and excess bond returns. They are also negatively correlated with aggregate economic activity, but macroeconomic variables explain only a small fraction of variation in the hidden factor
Evidence on Simulation Inference for Near Unit-Root Processes with Implications for Term Structure Estimation
No full textThe high persistence of interest rates has important implications for the preferred method used to estimate term structure models. We study the finite-sample properties of two standard dynamic simulation methods—efficient method of moments (EMM) and indirect inference—when they are applied to an first order autoregressive (AR[1]) process with Gaussian innovations. When simulated data are as persistent as interest rates, the finite-sample properties of EMM differ both from their asymptotic properties and from the finite-sample properties of indirect inference and maximum likelihood. EMM produces larger confidence bounds than indirect inference and maximum likelihood, yet is much less likely to contain the true parameter value. This is primarily because the population variance of the data plays a much larger role in the EMM conditions than in the moment conditions for either indirect inference or maximum likelihood. These results suggest that, under Gaussian assumptions, indirect inference (if practical) is preferable to EMM when working with persistent data such as interest rates. EMM's emphasis on the population variance strongly enforces stationarity on the underlying process, so this same reasoning suggests that EMM may be preferable in settings where stability and stationarity are important and difficult to impose. Copyright The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected], Oxford University Press.
Time Variation in the Covariance between Stock Returns and Consumption Growth
No full textThe conditional covariance between aggregate stock returns and aggregate consumption growth varies substantially over time. When stock market wealth is high relative to consumption, both the conditional covariance and correlation are high. This pattern is consistent with the "composition effect," where agents' consumption growth is more closely tied to stock returns when stock wealth is a larger share of total wealth. This variation can be used to test asset-pricing models in which the price of consumption risk varies. After accounting for variations in this price, the relation between expected excess stock returns and the conditional covariance is negative. Copyright 2005 by The American Finance Association.
Asymmetric cross-sectional dispersion in stock returns: evidence and implications
No full textThis paper documents that daily stock returns of both firms and industries are more dispersed when the overall stock market rises than when it falls. This positive relation is conceptually distinct from - and appears unrelated to - asymmetric return correlations. I argue that the source of the relation is positive skewness in sector-specific return shocks. I use this asymmetric behavior to explain a previously-observed puzzle: aggregate trading volume tends to be higher on days when the stock market rises than when it falls. The idea proposed here is that trading is more active on days when the market rises because on those days there is more non-market news on which to trade. I find that empirically, the bulk of the relation between volume and the signed market return is explained by variations in non-market volatility.Stock market ; Econometric models
Term premia and interest rate forecasts in affine models
No full textI find that the standard class of affine models produces poor forecasts of future changes in Treasury yields. Better forecasts are generated by assuming that yields follow random walks. The failure of these models is driven by one of their key features: the compensation that investors receive for facing risk is a multiple of the variance of the risk. This means that risk compensation cannot vary independently of interest rate volatility. I also describe and empirically estimate a class of models that is broader than the standard affine class. These 'essentially affine' models retain the tractability of the usual models, but allow the compensation for interest rate risk to vary independently of interest rate volatility. This additional flexibility proves useful in forming accurate forecasts of future yields.Government securities ; Econometric models ; Forecasting
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