Direct Estimation of the Risk Neutral Factor Dynamics of Affine Term Structure Models
Author | : Dennis Bams |
Publisher | : |
Total Pages | : 54 |
Release | : 1998 |
Genre | : Affine algebraic groups |
ISBN | : |
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Author | : Dennis Bams |
Publisher | : |
Total Pages | : 54 |
Release | : 1998 |
Genre | : Affine algebraic groups |
ISBN | : |
Author | : Sanjay K. Nawalkha |
Publisher | : John Wiley & Sons |
Total Pages | : 722 |
Release | : 2007-05-23 |
Genre | : Business & Economics |
ISBN | : 0470140062 |
Praise for Dynamic Term Structure Modeling "This book offers the most comprehensive coverage of term-structure models I have seen so far, encompassing equilibrium and no-arbitrage models in a new framework, along with the major solution techniques using trees, PDE methods, Fourier methods, and approximations. It is an essential reference for academics and practitioners alike." --Sanjiv Ranjan Das Professor of Finance, Santa Clara University, California, coeditor, Journal of Derivatives "Bravo! This is an exhaustive analysis of the yield curve dynamics. It is clear, pedagogically impressive, well presented, and to the point." --Nassim Nicholas Taleb author, Dynamic Hedging and The Black Swan "Nawalkha, Beliaeva, and Soto have put together a comprehensive, up-to-date textbook on modern dynamic term structure modeling. It is both accessible and rigorous and should be of tremendous interest to anyone who wants to learn about state-of-the-art fixed income modeling. It provides many numerical examples that will be valuable to readers interested in the practical implementations of these models." --Pierre Collin-Dufresne Associate Professor of Finance, UC Berkeley "The book provides a comprehensive description of the continuous time interest rate models. It serves an important part of the trilogy, useful for financial engineers to grasp the theoretical underpinnings and the practical implementation." --Thomas S. Y. Ho, PHD President, Thomas Ho Company, Ltd, coauthor, The Oxford Guide to Financial Modeling
Author | : Qiang Dai |
Publisher | : |
Total Pages | : 51 |
Release | : 1997 |
Genre | : Geometry, Affine |
ISBN | : |
This paper characterizes, interprets, and tests the over-identifying restrictions imposed in affine models of the term" structure. Letting r(t) = ë Y(t), where Y is an unobserved vector affine process, our analysis proceeds in three steps. First, we show that affine models can be categorized according to the different over-identifying restrictions they impose on (i) ë, and (ii) the parameters of the diffusion matrices. Second, this formulation is shown to be equivalent to a model in which there is a terraced drift structure with one of the state variables being the stochastic long-run mean of r. This equivalence allows direct comparisons of the substantive restrictions on the dynamics of interest rates imposed in CIR-style models and models in which the state variables are the stochastic long-run mean and volatility of r. Third, we compute simulated method of moments estimates of a three-factor affine term structure model, and test the over-identifying restrictions on the joint distribution of long- and short-term interest rates implied by extant affine models of r. We find allowing for correlated factors is key to simultaneously describing the short and long ends of the yield curve. This finding is interpreted in terms of the properties of the risk factors underlying term structure movements
Author | : Stan Maes |
Publisher | : |
Total Pages | : 54 |
Release | : 2006 |
Genre | : |
ISBN | : |
This paper provides an introduction to the mathematical models that describe the shape of the term structure of interest rates across time. In essence, all these so-called term structure models are driven by the assumption that arbitrage opportunities are absent. The intuitive concept of absence of arbitrage can be linked directly to the existence of a pricing kernel and a risk neutral probability measure. The latter concepts are at the heart of the finance literature and play a unifying role in it. Moreover, by assuming that the state of the economy is well-described by factors that follow diffusion dynamics, factor-dependent expressions for prices and yields can be derived. Typically and for reasons of tractability, additional model assumptions are imposed on the factor dynamics, giving rise to the so-called affine class of term structure models. We discuss the fundamental trade-off between empirical flexibility and theoretical rigor that applies to all models within the affine class of term structure models. Recently, the class of quadratic term structure models has been proposed and seems to outperform the affine class in terms of matching the economic moments of the yield curve. However, given the lack of uniform data samples and the widely differing estimation methods, much robustness work remains to be done.
Author | : Michael W. Brandt |
Publisher | : |
Total Pages | : 36 |
Release | : 2006 |
Genre | : |
ISBN | : |
We show how to estimate affine term structure models from a panel of noisy bond yields using simulated maximum likelihood based on importance sampling. We approximate the likelihood function of the state-space representation of the model by correcting the likelihood function of a Gaussian first-order approximation for the non-normalities introduced by the affine factor dynamics. Depending on the accuracy of the correction, which is computed through simulations, the quality of the estimator ranges from quasi-maximum likelihood (no correction) to exact maximum likelihood as the simulation size grows.
Author | : Kris Jacobs |
Publisher | : |
Total Pages | : 53 |
Release | : 2007 |
Genre | : |
ISBN | : |
Several papers have questioned the ability of multifactor affine models to extract interest rate volatility from the cross-section of bond prices. These studies find that the conditional volatility implied by these models is very poorly or even negatively correlated with model-free volatility. We provide an in-depth investigation of the conditional volatility of monthly Treasury yields implied by three-factor affine models. We investigate different specifications of the price of risk and different specifications of volatility. For long maturities, the correlation between model-implied and EGARCH volatility estimates is approximately 82% for yield differences and 92% for yield levels. For short-maturity yields, the correlation varies between 58% and 71% for yield differences and between 62% and 76% for yield levels. The differences at short maturities are largely accounted for by the number of factors affecting volatility. A model-free measure of the level factor is highly correlated with EGARCH volatility as well as model-implied volatilities, which explains most of our findings. We conclude that multifactor affine models are much better at extracting time-series volatility from the cross-section of yields than argued in the literature. However, existing models have difficulty capturing volatility dynamics at the short end of the maturity spectrum, perhaps indicating some form of segmentation between long-maturity and short-maturity bonds. These results are robust to the choice of sample period, interpolation method and estimation method.
Author | : Yacine Ait-Sahalia |
Publisher | : Elsevier |
Total Pages | : 809 |
Release | : 2009-10-19 |
Genre | : Business & Economics |
ISBN | : 0080929842 |
This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. - Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity - Contributors include Nobel Laureate Robert Engle and leading econometricians - Offers a clarity of method and explanation unavailable in other financial econometrics collections
Author | : George J. Jiang |
Publisher | : |
Total Pages | : 13 |
Release | : 2012 |
Genre | : |
ISBN | : |
In this paper, we propose a unifying class of affine-quadratic term structure models (AQTSMs) in the general jump-diffusion framework. Extending existing term structure models, the AQTSMs incorporate random jumps of stochastic intensity in the short rate process. Using information from the Treasury futures market, we propose a GMM approach for the estimation of the risk-neutral process. A distinguishing feature of the approach is that the time series estimates of stochastic volatility and jump intensity are obtained, together with model parameter estimates. Our empirical results suggest that stochastic jump intensity significantly improves the model fit to the term structure dynamics. We identify a stochastic jump intensity process that is negatively correlated with interest rate changes. Overall, negative jumps tend to have a larger size than positive ones. Our empirical results also suggest that, at monthly frequency, while stochastic volatility has certain predictive power of inflation, jumps are neither triggered by nor predictive of changes in macroeconomic variables. At daily frequency, however, we document interesting patterns for jumps associated with informational shocks in the financial market.
Author | : David Jamieson Bolder |
Publisher | : |
Total Pages | : 89 |
Release | : 2008 |
Genre | : |
ISBN | : |
Modelling term-structure dynamics is an important component in measuring and managing the exposure of portfolios to adverse movements in interest rates. Model selection from the enormous term-structure literature is far from obvious and, to make matters worse, a number of recent papers have called into question the ability of some of the more popular models to adequately describe interest rate dynamics. The author, in attempting to find a relatively simple term-structure model that does a reasonable job of describing interest rate dynamics for risk-management purposes, examines two sets of models. The first set involves variations of the Gaussian affine term-structure model by modestly building on the recent work of Dai and Singleton (2000) and Duffee (2002). The second set includes and extends Diebold and Li (2003). After working through the mathematical derivation and estimation of these models, the author compares and contrasts their performance on a number of in- and out-of-sample forecasting metrics, their ability to capture deviations from the expectations hypothesis, and their predictions in a simple portfolio-optimization setting. He finds that the extended Nelson-Siegel model and an associated generalization, what he terms the exponential-spline model, provide the most appealing modelling alternatives when considering the various model criteria.