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166
Yield Spreads and Interest Rate Movements: A Bird’s Eye View,” Review of Economic Studies, LVIII
, 1991
"... This paper was prepared for presentation at the UK Conference on the ..."
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Cited by 276 (11 self)
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This paper was prepared for presentation at the UK Conference on the
Term Premia and Interest Rate Forecasts in Affine Models
, 2001
"... I find that the standard class of a#ne 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 faci ..."
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Cited by 247 (8 self)
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I find that the standard class of a#ne 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 a#ne class. These "essentially a#ne" 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. Address correspondence to the University of California, Haas School of Business, 545 Student Services Building #1900, Berkeley, CA 94720. Phone: 5106421435. Email address: du#ee@haas.b...
Predictive regressions
 Journal of Financial Economics
, 1999
"... When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nitesample properties, derived here, can depart substantially from the standard regression setting. Bayesian ..."
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Cited by 247 (9 self)
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When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's "nitesample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under speci"cations that di!er with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is speci"ed as "xed or stochastic. The posteriors di!er across such speci"cations, and asset allocations in the presence of estimation risk exhibit sensitivity to those
Forecasting the term structure of government bond yields
 Journal of Econometrics
, 2006
"... Despite powerful advances in yield curve modeling in the last twenty years, comparatively little attention has been paid to the key practical problem of forecasting the yield curve. In this paper we do so. We use neither the noarbitrage approach, which focuses on accurately fitting the cross sectio ..."
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Cited by 133 (12 self)
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Despite powerful advances in yield curve modeling in the last twenty years, comparatively little attention has been paid to the key practical problem of forecasting the yield curve. In this paper we do so. We use neither the noarbitrage approach, which focuses on accurately fitting the cross section of interest rates at any given time but neglects timeseries dynamics, nor the equilibrium approach, which focuses on timeseries dynamics (primarily those of the instantaneous rate) but pays comparatively little attention to fitting the entire cross section at any given time and has been shown to forecast poorly. Instead, we use variations on the NelsonSiegel exponential components framework to model the entire yield curve, periodbyperiod, as a threedimensional parameter evolving dynamically. We show that the three timevarying parameters may be interpreted as factors corresponding to level, slope and curvature, and that they may be estimated with high efficiency. We propose and estimate autoregressive models for the factors, and we show that our models are consistent with a variety of stylized facts regarding the yield curve. We use our models to produce termstructure forecasts at both short and long horizons, with encouraging results. In particular, our forecasts appear much more accurate at long horizons than various standard benchmark forecasts. Finally, we discuss a number of extensions, including generalized duration measures, applications to active bond portfolio management, and arbitragefree specifications. Acknowledgments: The National Science Foundation and the Wharton Financial Institutions Center provided research support. For helpful comments we are grateful to Dave Backus, Rob Bliss, Michael Brandt, Todd Clark, Qiang Dai, Ron Gallant, Mike Gibbons, Da...
A Nonparametric Model of Term Structure Dynamics and the Market Price of Interest Rate Risk
, 1997
"... This article presents a technique for nonparametrically estimating continuoustime di#usion processes which are observed at discrete intervals. We illustrate the methodology by using daily three and six month Treasury Bill data, from January 1965 to July 1995, to estimate the drift and di#usion of t ..."
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Cited by 124 (5 self)
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This article presents a technique for nonparametrically estimating continuoustime di#usion processes which are observed at discrete intervals. We illustrate the methodology by using daily three and six month Treasury Bill data, from January 1965 to July 1995, to estimate the drift and di#usion of the short rate, and the market price of interest rate risk. While the estimated di#usion is similar to that estimated by Chan, Karolyi, Longsta# and Sanders (1992), there is evidence of substantial nonlinearity in the drift. This is close to zero for low and medium interest rates, but mean reversion increases sharply at higher interest rates.
Asset pricing at the millennium
 Journal of Finance
"... This paper surveys the field of asset pricing. The emphasis is on the interplay between theory and empirical work and on the tradeoff between risk and return. Modern research seeks to understand the behavior of the stochastic discount factor ~SDF! that prices all assets in the economy. The behavior ..."
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Cited by 123 (3 self)
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This paper surveys the field of asset pricing. The emphasis is on the interplay between theory and empirical work and on the tradeoff between risk and return. Modern research seeks to understand the behavior of the stochastic discount factor ~SDF! that prices all assets in the economy. The behavior of the term structure of real interest rates restricts the conditional mean of the SDF, whereas patterns of risk premia restrict its conditional volatility and factor structure. Stylized facts about interest rates, aggregate stock prices, and crosssectional patterns in stock returns have stimulated new research on optimal portfolio choice, intertemporal equilibrium models, and behavioral finance. This paper surveys the field of asset pricing. The emphasis is on the interplay between theory and empirical work. Theorists develop models with testable predictions; empirical researchers document “puzzles”—stylized facts that fail to fit established theories—and this stimulates the development of new theories. Such a process is part of the normal development of any science. Asset pricing, like the rest of economics, faces the special challenge that data are generated naturally rather than experimentally, and so researchers cannot control the quantity of data or the random shocks that affect the data. A particularly interesting characteristic of the asset pricing field is that these random shocks are also the subject matter of the theory. As Campbell, Lo, and MacKinlay ~1997, Chap. 1, p. 3! put it: What distinguishes financial economics is the central role that uncertainty plays in both financial theory and its empirical implementation. The starting point for every financial model is the uncertainty facing investors, and the substance of every financial model involves the impact of uncertainty on the behavior of investors and, ultimately, on mar* Department of Economics, Harvard University, Cambridge, Massachusetts
Interest Rate Policy and the Inflation Scare Problem: 19791992,” Federal Reserve Bank of Richmond Economic Quarterly 79
, 1993
"... monetary policy since the late 1970s is unique in the postKorean War era in that rising inflation has been reversed and U.S. stabilized at a lower rate for almost a decade. The current inflation rate of 3 to 4 percent per year, representing a reduction of 6 percent or so from its 1981 peak, is the ..."
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Cited by 86 (3 self)
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monetary policy since the late 1970s is unique in the postKorean War era in that rising inflation has been reversed and U.S. stabilized at a lower rate for almost a decade. The current inflation rate of 3 to 4 percent per year, representing a reduction of 6 percent or so from its 1981 peak, is the result of a disinflationary effort that has been long and difficult. This article analyzes the disinflation by reviewing the interaction between Federal Reserve policy actions and economic variables such as the longterm bond rate, real GDP growth, and inflation. The period breaks naturally into a number of phases, with the broad contour of events as follows. A period of rising inflation was followed by disinflation which, strictly speaking, was largely completed in 1983 when inflation stabilized at around 4 percent per year. But there were two more “inflation scares ” later in the decade when rising longterm rates reflected expectations that the Fed might once more allow inflation to rise. Confidence in the Fed was still relatively low in 1983, but the
Expectation puzzles, timevarying risk premia, and affine models of the term structure
 Journal of Financial Economics
, 2002
"... Though linear projections of returns on the slope of the yield curve have contradicted the implications of the traditional “expectations theory, ” we show that these findings are not puzzling relative to a large class of richer dynamic term structure models. Specifically, we are able to match all of ..."
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Cited by 79 (15 self)
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Though linear projections of returns on the slope of the yield curve have contradicted the implications of the traditional “expectations theory, ” we show that these findings are not puzzling relative to a large class of richer dynamic term structure models. Specifically, we are able to match all of the key empirical findings reported by Fama and Bliss and Campbell and Shiller, among others, within large subclasses of affine and quadraticGaussian term structure models. Additionally, we show that certain “riskpremium adjusted ” projections of changes in yields on the slope of the yield curve recover the coefficients of unity predicted by the models. Key to this matching are parameterizations of the market prices of risk that let the risk factors affect the market prices of risk directly, and not only through the factor volatilities. The risk premiums have a simple form consistent with Fama’s findings on the predictability of forward rates, and are also shown to be consistent with interest rate, feedback rules used by a monetary authority in setting monetary policy.
Term Structure of Interest Rates with Regime Shifts
 Journal of Finance
, 2002
"... We develop a term structure model where the short interest rate and the market price of risks are subject to discrete regime shifts. Empirical evidence from efficient method of moments estimation provides considerable support for the regime shifts model. Standard models, which include affine specifi ..."
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Cited by 76 (1 self)
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We develop a term structure model where the short interest rate and the market price of risks are subject to discrete regime shifts. Empirical evidence from efficient method of moments estimation provides considerable support for the regime shifts model. Standard models, which include affine specifications with up to three factors, are sharply rejected in the data. Our diagnostics show that only the regime shifts model can account for the welldocumented violations of the expectations hypothesis, the observed conditional volatility, and the conditional correlation across yields. We find that regimes are intimately related to business cycles. MANY PAPERS DOCUMENT THAT THE UNIVARIATE short interest rate process can be reasonably well modeled in the time series as a regime switching process ~see Hamilton ~1988!, Garcia and Perron ~1996!!. In addition to this statistical evidence, there are economic reasons as well to believe that regime shifts are important to understanding the behavior of the entire yield curve. For example, business cycle expansion and contraction “regimes ” potentially
Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in MacroFinance. Unpublished working paper
, 2010
"... This paper incorporates a timevarying severity of disasters into the hypothesis proposed by Rietz (1988) and Barro (2006) that risk premia result from the possibility of rare large disasters. During a disaster an asset’s fundamental value falls by a timevarying amount. This in turn generates time ..."
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Cited by 73 (5 self)
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This paper incorporates a timevarying severity of disasters into the hypothesis proposed by Rietz (1988) and Barro (2006) that risk premia result from the possibility of rare large disasters. During a disaster an asset’s fundamental value falls by a timevarying amount. This in turn generates timevarying risk premia and thus volatile asset prices and return predictability. Using the recent technique of linearitygenerating processes, the model is tractable and all prices are exactly solved in closed form. In this paper’s framework, the following empirical regularities can be understood quantitatively: (i) equity premium puzzle; (ii) riskfree rate puzzle; (iii) excess volatility puzzle; (iv) predictability of aggregate stock market returns with pricedividend ratios; (v) often greater explanatory power of characteristics than covariances for asset returns; (vi) upward sloping nominal yield curve; (vii) predictability of future bond excess returns and long term rates via the slope of the yield curve; (viii) corporate bond spread puzzle; (ix) high price of deep outofthemoney puts; and (x) high put prices being followed by high stock returns. The calibration passes a variance bound test, as normaltimes market volatility is consistent with the wide dispersion of disaster outcomes in the historical record. The model also extends to EpsteinZinWeil preferences and to a setting with many factors.