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Book Modelling and Forecasting Short Term Interest Rate Volatility

Download or read book Modelling and Forecasting Short Term Interest Rate Volatility written by Ai Jun Hou and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rates. The Monte Carlo study shows that the semiparametric approach produces more accurate volatility estimates than models that accommodate asymmetry, level effect and serial dependence in the conditional variance. Moreover, the semiparametric approach yields robust volatility estimates even if the short rate drift function and the underlying innovation distribution are misspecified. Empirical investigation with the U.S. three-month Treasury bill rates suggests that the semiparametric procedure produces superior in-sample and out-of-sample forecast of short rate changes volatility compared with the widely used single-factor diffusion models. This forecast improvement has implications for pricing interest rate derivatives.

Book Estimating Parameters of Short Term Real Interest Rate Models

Download or read book Estimating Parameters of Short Term Real Interest Rate Models written by Mr.Vadim Khramov and published by International Monetary Fund. This book was released on 2013-10-17 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper sheds light on a narrow but crucial question in finance: What should be the parameters of a model of the short-term real interest rate? Although models for the nominal interest rate are well studied and estimated, dynamics of the real interest rate are rarely explored. Simple ad hoc processes for the short-term real interest rate are usually assumed as building blocks for more sophisticated models. In this paper, parameters of the real interest rate model are estimated in the broad class of single-factor interest rate diffusion processes on U.S. monthly data. It is shown that the elasticity of interest rate volatility—the relationship between the volatility of changes in the interest rate and its level—plays a crucial role in explaining real interest rate dynamics. The empirical estimates of the elasticity of the real interest rate volatility are found to be about 0.5, much lower than that of the nominal interest rate. These estimates show that the square root process, as in the Cox-Ingersoll-Ross model, provides a good characterization of the short-term real interest rate process.

Book Modelling and forecasting stock return volatility and the term structure of interest rates

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.

Book Another Look at Models of the Short Term Interest Rate

Download or read book Another Look at Models of the Short Term Interest Rate written by Robin J. Brenner and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The short-term rate of interest is fundamental to much of theoretical and empirical finance. Yet no consensus has emerged on the dynamics of its volatility. We show that models which parameterize volatility only as a function of interest rate levels tend to over-emphasize the sensitivity of volatility to levels and fail to model adequately the serial correlation in conditional variances. On the other hand, serial correlation-based models like GARCH models fail to capture adequately the relationship between interest rate levels and volatility. We introduce and test a new class of models for the dynamics of short- term interest rate volatility which allows volatility to depend on both interest rate levels and information shocks. Two important conclusions emerge. First, the sensitivity of interest rate volatility to interest rate levels has been overstated in the literature. While this relationship is important, adequately modeling volatility as a function of unexpected information shocks is also important. Second, we conclude that the volatility processes in many existing theoretical models of interest rates are misspecified, and suggest new paths toward improving the theory.

Book Forecasting Spot Interest Rate Volatility

Download or read book Forecasting Spot Interest Rate Volatility written by Miguel A. Ferreira and published by . This book was released on 2004 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper compares the in-sample and out-of-sample forecasting performance of models of the spot interest rate volatility using French and Germany short-term interest rates, 1981-1997. For a one-week horizon, the volatility forecasts evaluation shows that the model with the best fit does not have the highest forecasting power. The out-of-sample evidence supports that models with only news effect have similar forecasting power and effciency to models with mixed level and news effect, which have the best fit. Also, sample variance forecasts calculated using exponentially declining weights present forecasting power and effciency similar to the best volatility models.

Book An Elementary Introduction to Stochastic Interest Rate Modeling

Download or read book An Elementary Introduction to Stochastic Interest Rate Modeling written by Nicolas Privault and published by World Scientific. This book was released on 2012 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest rate modeling and the pricing of related derivatives remain subjects of increasing importance in financial mathematics and risk management. This book provides an accessible introduction to these topics by a step-by-step presentation of concepts with a focus on explicit calculations. Each chapter is accompanied with exercises and their complete solutions, making the book suitable for advanced undergraduate and graduate level students. This second edition retains the main features of the first edition while incorporating a complete revision of the text as well as additional exercises with their solutions, and a new introductory chapter on credit risk. The stochastic interest rate models considered range from standard short rate to forward rate models, with a treatment of the pricing of related derivatives such as caps and swaptions under forward measures. Some more advanced topics including the BGM model and an approach to its calibration are also covered.

Book Forecasting Short Term Interest Rates Using Arma  Arma Garch and Arma Egarch Models

Download or read book Forecasting Short Term Interest Rates Using Arma Arma Garch and Arma Egarch Models written by S. Radha and published by . This book was released on 2006 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting interest rates is of great concern for financial researchers, economists and players in the fixed income markets. The purpose of this study is to develop an appropriate model for forecasting the short-term interest rates i.e., commercial paper rate, implicit yield on 91 day treasury bill, overnight MIBOR rate and call money rate. The short-term interest rates are forecasted using univariate models, Random Walk, ARIMA, ARMA-GARCH and ARMA-EGARCH and the appropriate model for forecasting is determined considering six-year period from 1999. The results show that interest rates time series have volatility clustering effect and hence GARCH based models are more appropriate to forecast than the other models. It is found that for commercial paper rate ARIMA-EGARCH model is most appropriate model, while for implicit yield 91 day Treasury bill, overnight MIBOR rate and call money rate, ARIMA-GARCH model is the most appropriate model for forecasting.

Book Yield Curve Modeling and Forecasting

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.

Book Modelling the Yield Curve

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.

Book Interest Rate Risk Models

Download or read book Interest Rate Risk Models written by Anthony G. Cornyn and published by Global Professional Publishi. This book was released on 1997 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: � Practical guide for asset-liability managers faced with the decision as to whether to build or buy a financial model � Topics include modeling cash flows, net investment income versus net portfolio value, projections of interest rates, and volatility A guide for asset-liability managers and other investment professionals who are faced with the decision of whether to build or buy a financial model to measure, monitor, and help manage their institution's risk exposure. It reviews the evolution of interest rate risk models and evaluates the state-of-the-art models in use. Includes Modeling cash flows; modeling the term structure; OAS technology; net interest income versus net portfolio value; build versus buy analysis; practical methods for deriving input assumptions; prepayment rates; deposit decay rates; projections of interest rate and volatility.

Book The Volatility of Short term Interest Rates

Download or read book The Volatility of Short term Interest Rates written by Clark Leavitt and published by . This book was released on 1987 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Predicting Short term Interest Rates

Download or read book Predicting Short term Interest Rates written by Chew Lian Chua and published by . This book was released on 2011 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper examines the forecasting qualities of Bayesian Model Averaging (BMA) over a set of single factor models of short-term interest rates. Using weekly and high frequency data for the one-month Eurodollar rate, BMA produces predictive likelihoods that are considerably better than the majority of the short-rate models, but marginally worse off than the best model in each dataset. We observe preference for models incorporating volatility clustering for weekly data and simpler short rate models for high frequency data. This is contrary to the popular belief that a diffusion process with volatility clustering best characterizes the short rate.

Book Interest Rate  Term Structure  and Valuation Modeling

Download or read book Interest Rate Term Structure and Valuation Modeling written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2002-11-29 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This ultimate guide contains an excellent blend of theory and practice This comprehensive guide covers various aspects of model building for fixed income securities and derivatives. Filled with expert advice, valuable insights, and advanced modeling techniques, Interest Rate, Term Structure, and Valuation Modeling is a book that all institutional investors, portfolio managers, and risk professionals should have. John Wiley & Sons, Inc. is proud to be the publisher of the esteemed Frank J. Fabozzi Series. Comprising nearly 100 titles-which include numerous bestsellers—The Frank J. Fabozzi Series is a key resource for finance professionals and academics, strategists and students, and investors. The series is overseen by its eponymous editor, whose expert instruction and presentation of new ideas have been at the forefront of financial publishing for over twenty years. His successful career has provided him with the knowledge, insight, and advice that has led to this comprehensive series. Frank J. Fabozzi, PhD, CFA, CPA, is Editor of the Journal of Portfolio Management, which is read by thousands of institutional investors, as well as editor or author of over 100 books on finance for the professional and academic markets. Currently, Dr. Fabozzi is an adjunct Professor of Finance at Yale University's School of Management and on the board of directors of the Guardian Life family of funds and the Black Rock complex of funds.

Book Interest Rate Risk Modeling

Download or read book Interest Rate Risk Modeling written by Sanjay K. Nawalkha and published by John Wiley & Sons. This book was released on 2005-05-09 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive guide to fixed income valuation and risk analysis The Trilogy in Fixed Income Valuation and Risk Analysis comprehensively covers the most definitive work on interest rate risk, term structure analysis, and credit risk. The first book on interest rate risk modeling examines virtually every well-known IRR model used for pricing and risk analysis of various fixed income securities and their derivatives. The companion CD-ROM contain numerous formulas and programming tools that allow readers to better model risk and value fixed income securities. This comprehensive resource provides readers with the hands-on information and software needed to succeed in this financial arena.

Book Forecasting Volatility in the Financial Markets

Download or read book Forecasting Volatility in the Financial Markets written by John L. Knight and published by Butterworth-Heinemann. This book was released on 2002 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modeling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.

Book A Practical Guide to Forecasting Financial Market Volatility

Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.

Book A General Stochastic Volatility Model for the Pricing and Forecasting of Interest Rate Derivatives

Download or read book A General Stochastic Volatility Model for the Pricing and Forecasting of Interest Rate Derivatives written by Anders B. Trolle and published by . This book was released on 2006 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop a tractable and flexible stochastic volatility multi-factor model of the term structure of interest rates. It features correlations between innovations to forward rates and volatilities, quasi-analytical prices of zero-coupon bond options and dynamics of the forward rate curve, under both the actual and risk-neutral measure, in terms of a finite-dimensional affine state vector. The model has a very good fit to an extensive panel data set of interest rates, swaptions and caps. In particular, the model matches the implied cap skews and the dynamics of implied volatilities. The model also performs well in forecasting interest rates and derivatives.