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 Yield Curve of Government Bonds written by Chao He and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 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 Forecasting the Yield Curve written by Christian Scheitlin and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this thesis is to forecast the US Treasury yield curve. In order to do so, the yield curve will first be modeled by the Nelson-Siegel (1987) method with the Diebold and Li (2006) extension and then forecasted. The data used is provided by Gürkaynak, Sack, and Wright (2006). The large dataset consists of fitted yields of US Treasury bonds. The conclusion of this thesis is that there is evidence that the Diebold and Li (2006) method can be applied to the dataset used. The forecasting results show mostly the correct change in direction of the yield curve but lack accuracy. The forecasting ability is quite well considering that the model does not include any macro-economic factors which are proven to influence the yield curve largely according to the results by Diebold, Piazzesi, and Rudebusch (2005).

Download or read book Modeling Long term Government Bond Yields written by Paul Sundell and published by . This book was released on 1992 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting Interest Rates written by John B. Schwartzman and published by McGraw-Hill Companies. This book was released on 1992 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Set up your own simple, one-page charts that track and assess interest rates and the factors affecting them--on a weekly, monthly, or quarterly basis. Determine, with a high degree of accuracy, in which direction the various trends influencing interest rates are likely to push them. Supplemented by a host of charts, graphs, examples, and illustrations, Forecasting Interest Rates allows you to spot the all-important events that cause interest rates to move--whether they're front-page news or subtle incidents. It shows you how to recognize a reliable interest rate factor from a red herring--whether the source is the Department of Commerce, the Department of Labor Statistics, the Federal Reserve Board, a university research center, or a nonprofit company specializing in business economic research.

Download or read book Yield Curve Dynamics written by Ronald J. Ryan and published by Global Professional Publishi. This book was released on 1997 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: � Invaluable to financial professionals � Breakthrough that examines both theory and practical solutions Examines both the advanced theory and practice of these techniques. Topics include: single- and multi-factor models; applying yield-curve modeling to risk management; forecasting short-term interest rates; unique yield-curve volatility; and trading strategies.

Download or read book The Yield Curve and Real Activity written by Zuliu Hu and published by International Monetary Fund. This book was released on 1993-03 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial press frequently suggest that the shape of yield curve reflects information about the prospects of the economy. This paper attempts to formalize the link between the yield curve and the real economic activity. A closed-form formula for the term structure of interest rates is derived. It is shown that the term structure embodies the market’s expectation about changes in the macroeconomic fundamental--the growth in real aggregate output of the economy. The paper then documents the use of bond market data for predicting GDP growth in the G-7 industrial countries. The results suggest that a simple measure of the slope of the yield curve, namely the yield spread, serves as a good predictor of future economic growth. The out-of-sample forecasting performance of the yield spread compares favorably with that of the alternative stock price-based model and a univariate time series (ARMA) model. One practical implication is that it may be useful to add some measure of the term structure to the list of

Download or read book Essays on the Government Bond Yield Curve written by Hussain Abusaaq and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: In practice, economist do not observe the discount function, spot or forward curves so we must extract them from a few observed points along the yield curve. To do this I introduce a new method called the Global Piecewise Quartic Polynomial Interpolation to construct maximally smooth forward curves with zero pricing errors for government coupon bonds. This method can construct any spot and forward curve shape with zero pricing errors, including upward sloping, downward sloping, inverted or humped. Next, I use three methods to decompose the constructed forward and the implied spot curves into factors and loadings: (i) the DL three-factor model, (ii) principal components and (iii) Chebyshev polynomial approximations. My analysis shows that the first three loadings for the spot curve and the first, the second and the fourth loadings in the forward curve can be interpreted as level, slope and curvature, respectively. Moreover, the methods show that five, or two additional, factors are needed to model the forward curve with the same precision as can be achieved with three factors for the spot curve. Simple and multiple correlations are used to analyze the relationships between the business cycle and the five factors that are needed to model the forward curve, the three factors needed to model the spot curve and the three factors of the [4] model. The results suggest that the additional factors required to model the forward curve are indeed related to the business cycle. The third factor on the principal components on the forward is a leading indicator for the trough and the fifth factor on the principal components on the forward is a leading indicator for the peak. Finally, ARIMA models are used to estimate and forecast the spot and forward curve factors. I find that forward curve factors produce more accurate forecasts than the three [4] factors.

Download or read book Bond Pricing and Yield Curve Modeling written by Riccardo Rebonato and published by . This book was released on 2018-06-07 with total page 781 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rebonato provides an authoritative, clear, and up-to-date explanation of the cutting-edge innovations in affine modeling for government bonds, and provides readers with the precise tools to develop their own models. This book combines precise theory with up-to-date empirical evidence to build, with the minimum mathematical sophistication required for the task, a critical understanding of what drives the government bond market.

Download or read book Forecast Yield Curve of China s Government Bond with Machine Learning written by Yadong Cao and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper takes the interest rates of China's government bond as the research object, and demonstrates the feasibility of the yield curve factor model by analyzing the Bootstrap, DNS, AFNS model of yield curve. Then based on the factor construction, construct the yield curve factor. In order to make the interest rate forecast, constructed 182 features and mined the features affecting the yield curves from multiple dimensions. Then used the traditional statistical models and machine learning models to predict yield curve. Through empirical analysis, it is found that machine learning models and DNS models can construct an ideal framework for predicting yield curve. Based on the analysis and research in this paper, we propose a new framework for yield curve forecast.

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 Updating the Yield Curve to Analyst s Views written by Leonardo M. Nogueira and published by . This book was released on 2008 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fixed income analysts deal constantly with the challenge of mapping their expectations about the macroeconomic environment into movements of the yield curve. This paper assumes that an analyst is able to provide a forecast of a few benchmark yields or combinations of yields. Then it derives a forecast of the entire yield curve that is consistent with the analyst's views, and computes the expected return of a bond portfolio in that scenario. We consider examples of forecasting the government bond yield curves of the United States, the Eurozone and the United Kingdom. More generally, the proposed model allows the analyst to express views on any set of correlated random variables (such as stocks, commodities, credit spreads, etc.) and to derive forecasts that are consistent with the views. The model builds on the theory of principal component analysis (PCA), can be easily extended to other markets and has no restrictions on the number of forecast variables or the number of views. A typical application is in scenario analysis, when the analyst could split the problem of forecasting the yield curve into two parts: one in which the expected developments of the macroeconomic environment are used to forecast movements of a few benchmark yields; and another part where the model derived in this paper is used to estimate the impact of the analyst's views on the entire yield curve of one country or of several countries.

Download or read book The Slope and the Curvature of the Yield Curve in Recession Forecasting written by Periklis Gogas and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we investigate the ability of two popular models to forecast the deviation of GDP from its long-run trend, i.e. inflationary and output gaps. In doing so, we exploit the information provided by the yield curve that is documented in the literature as a good predictor of economic activity. We combine and train our forecasting model using interest rates from Treasury Bills and Government Bond rates for the period 1976Q3 to 2011Q4, in conjunction with the quarterly real seasonally adjusted GDP for the same period. Our results show that we can achieve an overall forecasting accuracy of 80% on out-of-sample data. However, our main focus in this paper is to construct a forecasting model for the recessions. Perfect accuracy in recession forecasting is achieved in more than one of the created models. The forecasting performance of our model strengthens the conviction that the yield curve can be a useful and accurate predictive tool.

Download or read book High Dimensional Yield Curves written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predicting Output Using the Entire Yield Curve written by Azamat Abdymomunov and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many studies find that yields for government bonds predict real economic activity. Most of these studies use the yield spread, defined as the difference between two yields of specific maturities, to predict output. In this paper, I propose a different approach that makes use of information contained in the entire term structure of U.S. Treasury yields to predict U.S. real GDP growth. My proposed dynamic yield curve model produces better out-of-sample forecasts of real GDP than those produced by the traditional yield spread model. The main source of this improvement is in the dynamic approach to constructing forecasts versus the direct forecasting approach used in the traditional yield spread model. Although the predictive power of the yield curve for output is concentrated in the yield spread, there is also a gain from using information in the curvature factor for the real GDP growth prediction.