Results 1  10
of
15
Does Curvature Enhance Forecasting
 International Journal of Theoretical & Applied Finance
, 2009
"... In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential threefactor Diebold and Li (2006) model is proposed, where a fourth factor captures a second type of curvature. The new factor increases model ability to g ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential threefactor Diebold and Li (2006) model is proposed, where a fourth factor captures a second type of curvature. The new factor increases model ability to generate volatility and to capture nonlinearities in the yield curve, leading to a significant improvement of forecasting ability. The model is tested against the original Diebold and Li model and some other benchmarks. Based on a forecasting experiment with Brazilian fixed income data, it obtains significantly lower bias and root mean square errors for most examined maturities, and under three different forecasting horizons. Robustness tests based on two subsample analyses partially confirm the favorable results.
Forecasting Interest Rates
 In Handbook of Economic Forecasting
, 2012
"... This chapter discusses what the assetpricing literature concludes about the forecastability of interest rates. It outlines forecasting methodologies implied by this literature, including dynamic, noarbitrage term structure models and their macrofinance extensions. It also reviews the empirical ev ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
This chapter discusses what the assetpricing literature concludes about the forecastability of interest rates. It outlines forecasting methodologies implied by this literature, including dynamic, noarbitrage term structure models and their macrofinance extensions. It also reviews the empirical evidence concerning the predictability of future yields on Treasury bonds and future excess returns to holding these bonds. In particular, it critically evaluates theory and evidence that variables other than current bond yields are useful in forecasting.
Functional time series with applications in demography 7. Common functional principal components 19 Selected references
 Demography
, 2013
"... with applications in demography ..."
ESSAYS IN INTEREST RATES, PENSION FUNDS AND MONETARY POLICY IN EMERGING ECONOMIES
"... This dissertation focuses on the importance of pension funds investments in explaining the evolution of interest rates, and the interaction between monetary policy and the real economy. Even though there is an extensive literature on the behavior of interest rates, very few studies explain how and w ..."
Abstract
 Add to MetaCart
This dissertation focuses on the importance of pension funds investments in explaining the evolution of interest rates, and the interaction between monetary policy and the real economy. Even though there is an extensive literature on the behavior of interest rates, very few studies explain how and why a fully funded pension system contributes to the downward path of interest rates observed during the last decade. Also, there’s very dynamic literature on nonlinearities in monetary policy and the real economy, mostly as independent phenomena, but what if they can be explained simultaneously? Chapter 2 studies how a pension fund system can put downward pressure on interest rates in economies with shallow capital markets. Using data from Dominican Republic, the chapter analyzes how the term structure of the lending and deposit interest rates of domestic banks, that serve as the main destination of pension fund investments, have been affected by this inflow of financial resources and compares this effect with traditional macroeconomic factors. Both lending and deposit rates respond throughout the term structure to the investment of pension funds. The third chapter uses time series and panel data techniques to analyze the evolution of
ABSTRACT OF THE DISSERTATION A State Space Model Approach to Functional Time Series and Time Series Driven by Differential Equations
, 2012
"... This dissertation studies the modeling of time series driven by unobservable processes using state space model. New models and methodologies are proposed and applied on a variety of real life examples arising from finance and biology. More specifically, we mainly consider two types of time series: ..."
Abstract
 Add to MetaCart
This dissertation studies the modeling of time series driven by unobservable processes using state space model. New models and methodologies are proposed and applied on a variety of real life examples arising from finance and biology. More specifically, we mainly consider two types of time series: partially observed dynamic systems driven by differential equations and functional time series driven by its feature process. The first type of time series data is generated by a hidden dynamic process controlled by some underlying differential equation with a set of unknown parameters. We propose a state space approach to fit these models with observation data, which is only available at sparsely separated time points as well as with measurement error, and estimate the corresponding parameters. More specifically, we approximate the target nonlinear deterministic/stochastic differential equations by difference equations and convert the dynamic into a state space model(SSM), which is further calibrated by the likelihood calculated from the filtering scheme. The first application converts the HIV dynamic into a linear SSM and estimates all HIV viral dynamic parameters successfully without many constraints. The second application focus on the wellstudied ecological SIR
A Service of zbw LeibnizInformationszentrum Wirtschaft Leibniz Information Centre for Economics
"... StandardNutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, ..."
Abstract
 Add to MetaCart
(Show Context)
StandardNutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter OpenContentLizenzen (insbesondere CCLizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in July 2012 Abstract Many economic studies on inflation forecasting have found favorable results when inflation is modeled as a stationary process around a slowly timevarying trend. In contrast, the existing studies on interest rate forecasting either treat yields as being stationary, without any shifting endpoints, or treat yields as a random walk process. In this study we consider the problem of forecasting the term structure of interest rates with the assumption that the yield curve is driven by factors that are stationary around a timevarying trend. We compare alternative ways of modeling the timevarying trend. We find that allowing for shifting endpoints in yield curve factors can provide gains in the outofsample predictive accuracy, relative to stationary and random walk benchmarks. The results are both economically and statistically significant. JEL Classification: C32, E43, G17.
Three applications to French national electricity loadVRIJE UNIVERSITEIT
"... Statespace modelling for high frequency data ..."
Loss Functions for Forecasting Treasury Yields
, 2015
"... Many recent advances in the term structure literature have focused on model speci
cation and estimation. Forecasting the yield curve is critically important, but it has thus far not been explicitly taken into account at the estimation stage. We propose to estimate term structure models by aligning ..."
Abstract
 Add to MetaCart
Many recent advances in the term structure literature have focused on model speci
cation and estimation. Forecasting the yield curve is critically important, but it has thus far not been explicitly taken into account at the estimation stage. We propose to estimate term structure models by aligning the loss functions for insample estimation and outofsample forecast evaluation. We document the resulting di¤erences in forecasting performance using threefactor a ¢ ne term structure models with and without stochastic volatility. We con
rm that aligning loss functions provides substantial improvements in outofsample forecasting performance, especially for long forecast horizons. We document the tradeo ¤ between insample and outofsample
t. The resulting parameter estimates imply factors that di¤er from the traditional term structure factors, especially in the case of the third (curvature) factor. This suggests that the improvement in outofsample
t results from identi
cation of the third factor, which captures information otherwise hidden to conventional insample loss functions.
Stationary and Nonstationary Behaviour of the Term Structure: A
, 2012
"... We provide simple nonparametric conditions for the order of integration of the term structure of zerocoupon yields. A principle benchmark model studied is one with a limiting yield and limiting term premium, and in which the logarithmic expectations theory (ET) holds. By considering a yield curve w ..."
Abstract
 Add to MetaCart
(Show Context)
We provide simple nonparametric conditions for the order of integration of the term structure of zerocoupon yields. A principle benchmark model studied is one with a limiting yield and limiting term premium, and in which the logarithmic expectations theory (ET) holds. By considering a yield curve with a complete term structure of bond maturities, a linear vector autoregressive process is constructed that provides an arbitrarily accurate representation of the yield curve as its crosssectional dimension (n) goes to infinity. We use this to provide parsimonious conditions for the integration order of interest rates in terms of the crosssectional rate of convergence of the innovations to yields, νt(n), as n→∞. The yield curve is stationary if and only if nνt(n) converges a.s., or equivalently the innovations (‘shocks’) to the logarithm of the bond prices converge a.s. Otherwise yields are nonstationary and I(1) in the benchmark model, an integration order greater than one being ruled out by the a.s. convergence of νt(n) as n → ∞. A necessary but not sufficient condition for stationarity is that the limiting yield is constant over time. Our results therefore imply the need usually to adopt an I(1) framework when using the ET. We provide ETconsistent yield curve forecasts, new means to evaluate the ET, and insight into connections between the dynamics and the long maturity end of the term structure.