Download or read book Yield Curve Modeling and Forecasting written by Francis X. Diebold and published by Princeton University Press. This book was released on 2013-01-15 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures, Yield Curve Modeling and Forecasting contains essential tools with enhanced utility for academics, central banks, governments, and industry.
Download or read book Forecasting the Term Structure of Government Bond Yields written by Francis X. Diebold and published by . This book was released on 2003 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 no-arbitrage approach, which focuses on accurately fitting the cross section of interest rates at any given time but neglects time-series dynamics, nor the equilibrium approach, which focuses on time-series 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 Nelson-Siegel exponential components framework to model the entire yield curve, period-by-period, as a three dimensional parameter evolving dynamically. We show that the three time-varying 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 term-structure forecasts at both short and long horizons encouraging results. In particular, our forecasts appear much more accurate at long horizons than various standard benchmark forecasts.
Download or read book Forecasting the Term Structure of Interest Rates with Potentially Misspecified Models written by Yunjong Eo and published by . This book was released on 2018 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: We compare the out-of-sample predictive accuracy of a mixture of bond yield models with that of the individual models. The individual models considered here are the dynamic Nelson--Siegel model, arbitrage-free Nelson--Siegel model, and random-walk model. Out-of-sample forecasts for U.S. bond yields show that none of the individual models dominates the others across all maturities and forecast horizons, although the random-walk model performs well in most cases. We then assess the predictive accuracy for two subsamples: before and during a period of zero interest rates. In the first subperiod, overall the mixture of the three models outperforms the individual models, whereas the random-walk model seems to forecast better than all combinations for the period of zero interest rates. We show that these mixed results on the forecasting ability of the mixture models across the subsamples can be attributed to the zero interest-rate policy.
Download or read book The Forecasting Accuracy of Models of the Term Structure of Interest Rates written by Alan David Kraus and published by . This book was released on 1969 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Term Structure Forecasting Using Macro Factors and Forecast Combination written by Michiel De Pooter and published by . This book was released on 2010 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modelling and forecasting stock return volatility and the term structure of interest rates written by Michiel de Pooter and published by Rozenberg Publishers. This book was released on 2007 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of a collection of studies on two areas in quantitative finance: asset return volatility and the term structure of interest rates. The first part of this dissertation offers contributions to the literature on how to test for sudden changes in unconditional volatility, on modelling realized volatility and on the choice of optimal sampling frequencies for intraday returns. The emphasis in the second part of this dissertation is on the term structure of interest rates.
Download or read book Forecasting the U S Term Structure of Interest Rates Using a Macroeconomic Smooth Dynamic Factor Model written by Siem Jan Koopman and published by . This book was released on 2014 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: We extend the class of dynamic factor yield curve models for the inclusion of macro-economic factors. We benefit from recent developments in the dynamic factor literature for extracting the common factors from a large panel of macroeconomic series and for estimating the parameters in the model. We include these factors into a dynamic factor model for the yield curve, in which we model the salient structure of the yield curve by imposing smoothness restrictions on the yield factor loadings via cubic spline functions. We carry out a likelihood-based analysis in which we jointly consider a factor model for the yield curve, a factor model for the macroeconomic series, and their dynamic interactions with the latent dynamic factors. We illustrate the methodology by forecasting the U.S. term structure of interest rates. For this empirical study we use a monthly time series panel of unsmoothed Fama-Bliss zero yields for treasuries of different maturities between 1970 and 2009, which we combine with a macro panel of 110 series over the same sample period. We show that the relation between the macroeconomic factors and yield curve data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Finally, we perform an extensive out-of-sample forecasting study. Our main conclusion is that macroeconomic variables can lead to more accurate yield curve forecasts.
Download or read book Forecasting the U S Term Structure of Interest Rates Using a Macroeconomic Smooth Dynamic Factor Model written by Siem Jan Koopman and published by . This book was released on 2011 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting the U S Term Structure of Interest Rates Using Nonparametric Functional Data Analysis written by João Caldeira and published by . This book was released on 2016 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we consider a novel procedure for forecasting the US yield curve by using the methodology of nonparametric kernel estimation of functional data (NP-FDA). Within this approach, each element of the sample is a monthly yield curve, evaluated at points corresponding to maturities. In this framework we attempt to capture the dynamics present in the sample of curves to forecast future values for the yield at a given maturity without imposing any parametric structure. In order to evaluated forecast performance of the proposed estimator, we consider four forecast horizons and the results are compared with widely known parametric models. Our estimates with NP-FDA present predictive performance superior to its competitors in many situations considered, especially at longer time horizons for long-term maturities. The methodol- ogy applied in this paper may be important for policy makers, fixed income portfolio managers, financial institutions and academics as it may prove useful in the construction of long-term scenarios for the yield curve.
Download or read book Forecasting the Term Structure of Government Bond Yields Using Credit Spreads and Structural Breaks written by Azamat Abdymomunov and published by . This book was released on 2015 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we investigate whether credit spread curve information helps forecast the government bond yield curve and whether the joint dynamics of the government bond yields and credit spreads have structural changes. For this purpose, we use a joint dynamic Nelson-Siegel (DNS) model of the term structures of U.S. Treasury interest rates and credit spreads. We find that this joint model produces substantially more accurate out-of-sample Treasury yields forecasts compared with a standard DNS yield curve only model. We also find that the predictive gain from incorporating the credit spread curve information substantially increases if the joint model accounts for structural changes in the dynamics of yield and credit spread curves. In addition, our model incorporates a zero lower bound restriction ensuring that our predictions are economically plausible.
Download or read book Handbook of Economic Forecasting written by Graham Elliott and published by Elsevier. This book was released on 2013-08-23 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics
Download or read book Dynamic Modeling Approach to Forecast the Term Structure of Government Bond Yields written by Min Fu and published by . This book was released on 2013 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since arbitrage-free is a desirable theoretical feature in a healthy financial market, many efforts have been made to construct arbitrage-free models for yield curves. However, little attention is paid to review if such restriction will improve yield forecast. We evaluate the importance of arbitrage-free restriction on dynamic Nelson-Siegel term structure when forecasting yield curves. We find that it doesn't help. We also compare these two Nelson-Siegel dynamic models with a benchmark dynamic model and show that Nelson-Siegel structure improve forecasts for long-maturity yields.
Download or read book The Information Content of the Term Structure of Interest Rates written by Frank Browne and published by [Paris, France] : OECD, Department of Economics and Statistics. This book was released on 1989 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting the Term Structure of Interest Rates written by David Fischer and published by . This book was released on 2018 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Future Economic Growth written by Maria Khait and published by . This book was released on 2012 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: The broad literature documents the empirical regularity that slope of the term structure of interest rates is a reliable predictor of future real economic activity. Steeper slopes presage increasing growth, and downward sloping term structures presage declining growth or even recession. Some instances of slope's misleading signals were recorded in 2006 (the term structure was flat, indicating decline in economic activity when high growth continued) and 2008 (the term structure was very steep, predicting economic growth when recession continued and took a deep dive). Moreover, Breeden (2012a) showed that the term structure of interest rates has had less predictive power over the past fifty years than has been found in earlier researches over shorter periods of time. The key idea underlying this paper was to test whether the term structure of volatility and the term structure of inflation combined with the term spread could improve predictions of future economic growth compared to interest rate based forecasts with only one variable. This study finds that while the term structure spread and volatility appear to be statistically significant variables there is little evidence of improved performance compare to interest rate based forecasts with only one variable.
Download or read book A Multi country Comparison of Term Structure Forecasts at Long Horizons written by Philippe Jorion and published by . This book was released on 1991 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper extends previous work on the information in the term structure at longer maturities to other countries besides the United states, using a newly constructed data set for 1 to 5 year interest rates from Britain, West Germany and Switzerland. Even with wide differences in inflation processes across these countries, there is we find strong evidence that the term structure does have significant forecasting ability for future changes in inflation, particularly so at long maturities. On the other hand, the ability of the term structure to forecast future changes in 1-year interest rates is somewhat weaker; only at the very longest horizon (5 years) is there significant forecasting ability for interest rate changes.
Download or read book Forecasting the Term Structure of Government Bond Yields in Unstable Environments written by Joseph Byrne and published by . This book was released on 2019 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we model and predict the term structure of US interest rates in a data-rich and unstable environment. The dynamic Nelson-Siegel factor model is extended to allow the model dimension and the parameters to change over time, in order to account for both model uncertainty and sudden structural changes, in one setting. The proposed specification performs better than several alternatives, since it incorporates additional macro-finance information during hard times, while it allows for more parsimonious models to be relevant during normal periods. A dynamic variance decomposition measure constructed from our model shows that parameter uncertainty and model uncertainty regarding different choices of predictors explain a large proportion of the predictive variance of bond yields.
