Download or read book Yield Curve Modeling and Forecasting Using Semiparametric Factor Dynamics written by Wolfgang Karl Härdle and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Yield Curve Modeling and Forecasting Using Semiparametric Factor Dynamics written by Wolfgang K. Härdle and published by . This book was released on 2017 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: Standard fixed symmetric kernel type density estimators are known to encounter problems for positive random variables with a large probability mass close to zero. We show that in such settings, alternatives of asymmetric gamma kernel estimators are superior but also differ in asymptotic and finite sample performance conditional on the shape of the density near zero and the exact form of the chosen kernel. We therefore suggest a refined version of the gamma kernel with an additional tuning parameter according to the shape of the density close to the boundary. We also provide a data-driven method for the appropriate choice of the modified gamma kernel estimator. In an extensive simulation study we compare the performance of this refined estimator to standard gamma kernel estimates and standard boundary corrected and adjusted fixed kernels. We find that the finite sample performance of the proposed new estimator is superior in all settings. Two empirical applications based on high-frequency stock trading volumes and realized volatility forecasts demonstrate the usefulness of the proposed methodology in practice.
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 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 225 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 Term Structure Modeling Forecasting and Implications for Monetary Policy written by Chamadanai Marknual and published by . This book was released on 2015 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis examines the macro-finance-fiscal term structure model to incorporate fiscal instability variables and the term spread to understand the impact of the sovereign debt crisis on the evolution of the yield curve. My findings reveal financial instability increases the term spread associated with the expectation of higher sovereign default risk and consequently signals economic agents to reduce their spending, and thus worsens economic activity. Secondly, I also investigate whether the dynamic factor model with nonparametric factor loadings is more accurate relative to other term structure models by employing the dynamic semi-parametric factor model (DSFM). The empirical results indicate that a better in-sample fit is provided by the dynamic semiparametric factor model. However, the overall forecasting results are not encouraging. The dynamic semiparametric factor model provides accurate results in forecasting a persistent trend while the dynamic Nelson-Siegel model is more suitable to fit more volatile series. Thirdly,I use a Sheen-Trueck-Wang business conditions index for term structure modeling and forecasting. I find the cross-sectional yield provides guidance to anchor the yield in the next period. The prediction performance of the model is enhancedby using the index since it includes information on frequently released or more recent available data. The index is significantly related to the slope factor, which suggests the forward-looking information from the index inuences the adjustmentthe in the yield slope. Lastly, I examine the effectiveness of the US quantitative easing (QE) policy with a Bayesian structural vector auto regressive (B-SVAR)model with sign restrictions. I find the transmission mechanism of the Federal Reserve asset purchase effectively expands output and avert deflation through a compression in the yield spread.
Download or read book Modelling the Yield Curve Based on a Partial Conjecture of Future Yields written by Ramtien Kalantar Nayestanaki and published by Grin Publishing. This book was released on 2017-02-27 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2016 in the subject Business economics - Operations Research, grade: 8, University of Groningen, language: English, abstract: The reader is introduced to term structure modelling using the Dynamic Nelson-Siegel model. Assuming an independent and correlated specification for its factors, we estimate the factor dynamics by maximum likelihood. Additionally, estimation of the factors is done by Kalman filtering. We derive a closed-form distribution for future factors, forecast them and present the insample and out-of-sample forecasts. As a useful addition, we discuss the main finding of the thesis, namely a stochastic model for the predicted yield curve, when a future yield with certain maturity is given.
Download or read book A Practitioner s Guide to Discrete Time Yield Curve Modelling written by Ken Nyholm and published by Cambridge University Press. This book was released on 2021-01-07 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Element is intended for students and practitioners as a gentle and intuitive introduction to the field of discrete-time yield curve modelling. I strive to be as comprehensive as possible, while still adhering to the overall premise of putting a strong focus on practical applications. In addition to a thorough description of the Nelson-Siegel family of model, the Element contains a section on the intuitive relationship between P and Q measures, one on how the structure of a Nelson-Siegel model can be retained in the arbitrage-free framework, and a dedicated section that provides a detailed explanation for the Joslin, Singleton, and Zhu (2011) model.
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 Predicting the Yield Curve Using Forecast Combinations written by João Caldeira and published by . This book was released on 2013 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: We examine the statistical accuracy and economic value of modelling and forecasting the term structure of interest rates using forecast combinations. We adopt five alternative methods to combine point forecasts from several univariate and multivariate autoregressive specifications, as well as from factor models for the yield curve such as the dynamic versions of the Nelson-Siegel and Svensson specifications. Moreover, we conduct a detailed performance evaluation based not only on statistical measures of forecast accuracy, but also an economic criteria like Sharpe ratios of optimal mean-variance fixed income portfolios constructed based upon forecasts from individual models and their alternative combinations. Our empirical application based on a large panel of Brazilian interest rate future contracts with different maturities shows that combined forecasts consistently outperform individual models in several instances, specially when economic criteria are taken into account.
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 Yield Factor Volatility Models written by Christophe Perignon and published by . This book was released on 2013 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model's fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.
Download or read book Forecasting of Macro Aggregates Using Yield Curve Information written by Juan Sebastián Rassa Robayo and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper obtains the forecasts of Colombian macroeconomic variables and the yield curve by jointly modeling their dynamics. For this purpose, I use unrestricted Bayesian Vector Auto Regressive (VAR) models and the no-arbitrage state-space representation developed by Ang and Piazzesi [2003]. Both the Bayesian VAR and the no-arbitrage representations are used to estimate closed economy, small open economy ancl macro-latent factor models. The parameters of the models are estimated with Bayesian techniques for different horizons using the predictive likelihood function. Monthly data between 2006-2012 of the inflation, the overnight-interbank interest rate, an economic activity indicator, the 10-year treasury rate and the 5-year CDS was used The main finding is that the out-of-sample forecasts of the interbank overnight interest rate and the inflation consistently improve when the yield curve is incorporated. Moreover, the models thnt irnpose the no-arbitrage restriction consistently out-perform the unrestrict.ed VARs. On the Other hant, the model wit,h the best. performance in terms of both the RMSE and the standard deviation of the forecasts incorporates closed-economy variables and the short-term yield. Adding longer-term yields and small open economy variables does not appear to improve further the forecasts.
Download or read book Macro Factors and the Yield Curve written by Peyron Law and published by . This book was released on 2005 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling and Forecasting the Yield Curve Under Model Uncertainty written by Francesco Donati and published by . This book was released on 2009 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a methodology that permits to investigate and forecast the behavior of a variable and its determinants in real time, both in the time and in the frequency domain, starting from a model designed in the time domain, which makes the presentation and evaluation of the results straightforward. This paper applies the methodology to the yield curve. We extract all the shocks affecting the forward rates and the yields and we divide them into three disjoint classes: 1) long-run shocks giving rise to possibly permanent effects, 2) medium-run forces and 3) short-run forces giving rise to transitory effects. These forces drive the low-, medium- and high-frequency component, respectively, composing the time series of the variables used in the model. We explicitly model and estimate such cause-and-effect relationships. The analysis of the shocks and the frequency components provides a timely and comprehensive overview of the nature of the movements in the yields. Furthermore, using the forecast of the frequency components to forecast the yields enhances forecast accuracy, also at long prediction horizons. To perform the frequency decompositions, to identify the forces governing the evolution of the model variables, and to perform the out-of-sample forecasts we use a dynamic filter whose embedded feedback control corrects for model uncertainty.
Download or read book Forecasting the Yield Curve in a Data rich Environment Using the Factor augmented Nelson Siegel Model written by and published by . This book was released on 2010 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Gaussian Estimation and Forecasting of the UK Yield Curve with Multi Factor Continuous Time Models written by Diana Tunaru and published by . This book was released on 2016 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we estimate the term structure of daily UK interest rates using more flexible continuous time models. The multivariate CKLS framework is employed for dynamic estimation and forecasting of four classical models over the eventful period of 2000-2013. The extensions are applied in two stages to four and five factor formulations, allowing us to assess the potential benefit of gradually increasing the model-flexibility. The Gaussian estimation methods for dynamic continuous time models yield insightful comparative results concerning the two different segments of the yield curve, short-term and long-term, respectively. In terms of in-sample performance the multi-factor general CKLS model is superior to all the other restricted models. When compared to benchmark discrete time models, the out-of-sample performance of the extended continuous time models seem to be consistently superior with regards only to the short-term segment of the yield curve.
Download or read book Yield curve Based Probit Models for Forecasting U S Recessions written by Heikki Kauppi and published by . This book was released on 2008 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
