Analysing and Interpreting the Yield Curve (Wiley Finance) by Moorad Choudhry

Author:Moorad Choudhry [Choudhry, Moorad]
Language: eng
Format: azw3
ISBN: 9781119141051
Publisher: Wiley
Published: 2019-04-14T16:00:00+00:00

This is just the beginning, and there are a range of issues which must be considered by users when selecting an interest rate model. For example, in practice it has been observed that models incorporating mean reversion work more accurately than those that do not feature this. Another factor is the computer processing power available to the user, and it is often the case that single‐factor models are preferred precisely because processing is more straightforward.

IMPORTANCE OF PRACTICALITY

It is important to remain focused on the practical requirements of interest rate modelling. Market participants are more concerned with the ease with which a model can be implemented, and its accuracy with regard to pricing. In practice, different models are more suited to different applications, so the range of products traded by a market practitioner also influences which model is chosen. For instance, the extended Vasicek model can be fitted very accurately to the initial term structure, and its implementation is relatively straightforward, being based on a lattice structure. It is also able to accurately price most products, however, like all one‐factor models, it is not a valid model to use when pricing instruments that are sensitive to two or more risk factors, for example, quanto options. The extended CIR model is also quite tractable, although it has a more restricted set of term structures compared to the extended Vasicek model, as a result of the limitations imposed by the term on the volatility parameter. Both types of models are unable to capture the dynamics of the whole yield curve, for which HJM models must be used.

A drawback of these models is that although they fit the initial term structure, due to their structure they may not continue to calculate prices as the term structure evolves. In practice, the models must be re‐calibrated frequently to ensure that they continue to describe term structure volatilities that reflect the market.

In selecting the model, a practitioner selects the market variables that are incorporated in the model. These can be directly observed such as zero‐coupon rates or forward rates, or swap rates, or they can be indeterminate such as the mean of the short rate. The practitioner then decides the dynamics of these market or state variables, so for example, the short rate may be assumed to be mean‐reverting. Finally, the model must be calibrated to market prices, so the model parameter values must be input that produce market prices as accurately as possible. There are a number of ways that parameters can be estimated, the most common techniques of calibrating to time series data such as interest rate data are general method of moments and the maximum likelihood method. For information on these estimation methods, refer to the bibliography.

Models exhibit different levels of sensitivity to changes in market prices and rates. The extent of a model's sensitivity also influences the frequency with which the model must be re‐calibrated. For example, the Black–Derman–Toy model is very sensitive to changes in market prices, because it is a log‐

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.