Download or read book Modelling and Forecasting the Yield Curve Under Model Uncertainty written by Paola Donati and published by . This book was released on 2008 with total page 44 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 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 Modelling and forecasing the yield curve under model uncertainty written by Paola Donati and published by . This book was released on 2008 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Predicting the Term Structure of Interest Rates written by Michiel De Pooter and published by . This book was released on 2010 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We assess the relevance of parameter uncertainty, model uncertainty, and macroeconomic information for forecasting the term structure of interest rates. We study parameter uncertainty by comparing Bayesian inference with frequentist estimation techniques, and model uncertainty by combining forecasts from individual models. We incorporate macroeconomic information in yield curve models by extracting common factors from a large panel of macro series. Our results show that accounting for parameter uncertainty does not improve the forecast performance of individual models. The predictive accuracy of single models varies over time considerably and we demonstrate that mitigating model uncertainty by combining forecasts leads to substantial gains in predictability. Combining forecasts using a weighting method that is based on relative historical performance results in highly accurate forecasts. The gains in terms of forecast performance are substantial, especially for longer maturities, and are consistent over time. In addition, we find that adding macroeconomic factors generally is beneficial for improving out-of-sample forecasts.
Download or read book Forecasting Financial Time Series Using Model Averaging written by Francesco Ravazzolo and published by Rozenberg Publishers. This book was released on 2007 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Believing in a single model may be dangerous, and addressing model uncertainty by averaging different models in making forecasts may be very beneficial. In this thesis we focus on forecasting financial time series using model averaging schemes as a way to produce optimal forecasts. We derive and discuss in simulation exercises and empirical applications model averaging techniques that can reproduce stylized facts of financial time series, such as low predictability and time-varying patterns. We emphasize that model averaging is not a "magic" methodology which solves a priori problems of poorly forecasting. Averaging techniques have an essential requirement: individual models have to fit data. In the first section we provide a general outline of the thesis and its contributions to previ ous research. In Chapter 2 we focus on the use of time varying model weight combinations. In Chapter 3, we extend the analysis in the previous chapter to a new Bayesian averaging scheme that models structural instability carefully. In Chapter 4 we focus on forecasting the term structure of U.S. interest rates. In Chapter 5 we attempt to shed more light on forecasting performance of stochastic day-ahead price models. We examine six stochastic price models to forecast day-ahead prices of the two most active power exchanges in the world: the Nordic Power Exchange and the Amsterdam Power Exchange. Three of these forecasting models include weather forecasts. To sum up, the research finds an increase of forecasting power of financial time series when parameter uncertainty, model uncertainty and optimal decision making are included.
Download or read book Building and Using Dynamic Interest Rate Models written by Ken O. Kortanek and published by John Wiley & Sons. This book was released on 2001-11-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a new approach to interest rate and modeling term structure by using models based on optimization of dynamical systems, rather than the traditional stochastic differential equation models. The authors use dynamic models to estimate the term structure of interest rates and show the reader how to build their own numerical simulations. It includes software that will enable readers to simulate the various models covered in the book.
Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.
Download or read book Modelling the Yield Curve written by Mr.Mark P. Taylor and published by International Monetary Fund. This book was released on 1991-12-01 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: We test and estimate a variety of alternative models of the yield curve, using weekly, high-quality U.K. data. We extend the Campbell-Shiller technique to the overlapping data case and apply it to reject the pure expectations hypothesis under rational expectations. We also find that risk measures, in the form of conditional interest rate volatility, are unable to explain the term premium. A simple, market segmentation approach is, however, moderately successful in explaining the term premium.
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 Developments in Macro Finance Yield Curve Modelling written by Jagjit S. Chadha and published by Cambridge University Press. This book was released on 2014-02-06 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Changes in the shape of the yield curve have traditionally been one of the key macroeconomic indicators of a likely change in economic outlook. However, the recent financial crises have created a challenge to the management of monetary policy, demanding a revision in the way that policymakers model expected changes in the economy. This volume brings together central bank economists and leading academic monetary economists to propose new methods for modelling the behaviour of interest rates. Topics covered include: the analysis and extraction of expectations of future monetary policy and inflation; the analysis of the short-term dynamics of money market interest rates; the reliability of existing models in periods of extreme market volatility and how to adjust them accordingly; and the role of government debt and deficits in affecting sovereign bond yields and spreads. This book will interest financial researchers and practitioners as well as academic and central bank economists.
Download or read book Yield Curve Modeling written by Y. Stander and published by Springer. This book was released on 2005-06-23 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will give the reader insight into how to model yield curves in our incomplete and imperfect financial markets. An extensive list of yield curve models are shown and discussed. Using actual market instruments, these models are then applied and the different yield curves are compared. It is assumed that the reader has a basic understanding of the financial instruments available in the market. Various issues that have to be taken into account in practice are discussed, like daycount conventions, business-day rules, the credit quality of the instrument and liquidity to name but a few. It is also shown how yield curves can be used to estimate credit spreads and country risk premiums. Creating a yield curve model has some implications in risk management. Specifically - the model, operational, liquidity and basis risks are discussed.
Download or read book Comparing Models for Forecasting the Yield Curve written by Marco S. Matsumura and published by . This book was released on 2006 with total page 40 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 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 Simple Monetary Policy Rules Under Model Uncertainty written by Ann-Charlotte Eliasson and published by International Monetary Fund. This book was released on 1999-05-01 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using stochastic simulations and stability analysis, the paper compares how different monetary rules perform in a moderately nonlinear model with a time-varying nonaccelerating-inflation-rate-of-unemployment (NAIRU). Rules that perform well in linear models but implicitly embody backward-looking measures of real interest rates (such as conventional Taylor rules) or substantial interest rate smoothing perform very poorly in models with moderate nonlinearities, particularly when policymakers tend to make serially correlated errors in estimating the NAIRU. This challenges the practice of evaluating rules within linear models, in which the consequences of responding myopically to significant overheating are extremely unrealistic.
Download or read book Perturbation Methods in Credit Derivatives written by Colin Turfus and published by John Wiley & Sons. This book was released on 2021-03-15 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stress-test financial models and price credit instruments with confidence and efficiency using the perturbation approach taught in this expert volume Perturbation Methods in Credit Derivatives: Strategies for Efficient Risk Management offers an incisive examination of a new approach to pricing credit-contingent financial instruments. Author and experienced financial engineer Dr. Colin Turfus has created an approach that allows model validators to perform rapid benchmarking of risk and pricing models while making the most efficient use possible of computing resources. The book provides innumerable benefits to a wide range of quantitative financial experts attempting to comply with increasingly burdensome regulatory stress-testing requirements, including: Replacing time-consuming Monte Carlo simulations with faster, simpler pricing algorithms for front-office quants Allowing CVA quants to quantify the impact of counterparty risk, including wrong-way correlation risk, more efficiently Developing more efficient algorithms for generating stress scenarios for market risk quants Obtaining more intuitive analytic pricing formulae which offer a clearer intuition of the important relationships among market parameters, modelling assumptions and trade/portfolio characteristics for traders The methods comprehensively taught in Perturbation Methods in Credit Derivatives also apply to CVA/DVA calculations and contingent credit default swap pricing.
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.
