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Term Structure Models with Unspanned Factors and Unspanned Stochastic Volatility

Term Structure Models with Unspanned Factors and Unspanned Stochastic Volatility
Author: Alex Backwell
Publisher:
Total Pages: 134
Release: 2018
Genre:
ISBN:

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Certain models of the term structure of interest rates exhibit unspanned stochastic volatility (USV). A model has this property if it involves a source of stochastic variation -- called an unspanned factor -- that does not affect the model's interest rates directly, but does affect the extent to which future interests are liable to change (that is, interest-rate volatility). This thesis is concerned with these models, from a variety of perspectives.Firstly, the theoretical foundation of the USV property is addressed. Formal definitions of unspanned factors and USV are developed, generalising ones tentatively proposed in the literature. Several results from these definitions and the accompanying framework are derived. Particularly, the ability to hedge general claims (i.e., the completeness or lack thereof) of these models is examined in detail. Examples are given to illustrate the features of the proposed framework and the necessity of the generalised definitions.Secondly, the empirical issue of whether USV models are necessary to plausibly represent ob- served interest-rate markets is interrogated. An empirical derivative-hedging approach is adopted, the results of which are contextualised by also treating data simulated from models with USV and non-USV versions. It is shown that hedging effectiveness is relatively robust to the presence of USV, which resolves the apparent conflict between the two studies that have taken a hedging approach to this question. Despite the cross-sectional hedging effects being surprisingly minor, further regression results show that USV models are needed to model the time series of market interest rates.Finally, the thesis addresses a certain class of models that exhibit USV: those with one spanned factor (driving interest-rate variation) and one unspanned, volatility-related factor. Being the simplest non-trivial USV models, these bivariate USV models are fundamental, and -- like one- factor models in general settings -- are helpful in introducing and comparing higher-factor models when simple ones are insufficient. These models are shown to exist (contradicting a claim in the literature); to share a particular affine form for their bond pricing functions; and to necessarily exhibit a short-term interest rate with dynamics of a certain type. A specific bivariate USV model is then proposed, which is analysed and compared to others in the literature.


Estimation of Affine Term Structure Models with Spanned Or Unspanned Stochastic Volatility

Estimation of Affine Term Structure Models with Spanned Or Unspanned Stochastic Volatility
Author: Drew D. Creal
Publisher:
Total Pages: 67
Release: 2014
Genre: Economics
ISBN:

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We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating parameters from the objective function that cause problems for conventional methods. We find that spanned models capture the cross-section of yields well but not volatility while unspanned models fit volatility at the expense of fitting the cross-section.


Estimation of Affine Term Structure Models with Spanned Or Unspanned Stochastic Volatility

Estimation of Affine Term Structure Models with Spanned Or Unspanned Stochastic Volatility
Author: Drew Creal
Publisher:
Total Pages: 61
Release: 2017
Genre:
ISBN:

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We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating parameters from the objective function that cause problems for conventional methods. We find that spanned models capture the cross-section of yields well but not volatility while unspanned models fit volatility at the expense of fitting the cross-section.


Term Structure and Volatility

Term Structure and Volatility
Author: Ruslan Bikbov
Publisher:
Total Pages: 65
Release: 2004
Genre:
ISBN:

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We evaluate the ability of several affine models to explain the term structure of the interest rates and option prices. Since the key distinguishing characteristic of the affine models is the specification of conditional volatility of the factors, we explore models which have critical differences in this respect: Gaussian (constant volatility), stochastic volatility, and unspanned stochastic volatility models. We estimate the models based on the Eurodollar futures and options data. We find that both Gaussian and stochastic volatility models, despite the differences in the specifications, do a great job matching the conditional mean and volatility of the term structure. When these models are estimated using options data, their properties change, and they are more successful in pricing options and matching higher moments of the term structure distribution. The unspanned stochastic volatility (USV) model fails to resolve the tension between the futures and options fits. Unresolved tension in the fits points to additional factors or, even more likely, jumps, as ways to improve the performance of the models. Our results indicate that Gaussian and stochastic volatility models cannot be distinguished based on the yield curve dynamics alone. Options data are helpful in identifying the differences. In particular, Gaussian models cannot explain the relationship between implied volatilities and the term structure observed in the data.


Unspanned Stochastic Volatility Term Structure Model Applied in Negative Interest Rate Environment

Unspanned Stochastic Volatility Term Structure Model Applied in Negative Interest Rate Environment
Author: Jan Sedlak
Publisher:
Total Pages: 50
Release: 2016
Genre:
ISBN:

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The interest rate transition from the positive environment, into the negative territory questions the consensus of interest rates and opens up a wide field of unresearched areas. To cope with the changing interest rate environment as well as satisfying regulatory criteria, a model following the Heath-Jarrow-Morton framework with Unspanned Stochastic Volatility is implemented. The model is constructed to match shocks to the level, slope and curvature of the term structure. Estimation is performed with Libor rates, Government rates and Swaption ATM normal implied volatilities from 2006-01-01 to 2015-03-12. The model is backtested both in sample and out of sample and compared to a Normal model and a Log Normal model. The model shows a good quantile fit to the medium and long end of the term structure and performs relatively better then the two challenger models.


Spanned Stochastic Volatility in Bond Markets

Spanned Stochastic Volatility in Bond Markets
Author: Don H. Kim
Publisher:
Total Pages: 46
Release: 2007
Genre: 1996-2008
ISBN:

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This paper reexamines the issue of unspanned stochastic volatility (USV) in bond markets and the puzzle of poor relative pricing between bonds and bond options. I make a distinction between the "weak USV" and the "strong USV" scenarios, and analyze the evidence for each of them. I argue that the poor bonds/options relative pricing in the extant literature is not necessarily evidence for the strong USV scenario, and show that a maximally flexible 2-factor quadratic-Gaussian model (a non-USV model) estimated without bond options data can capture much of the movement in bond option prices. Dropping the positive-definiteness requirement for nominal interest rates and adopting "regularized" estimations turn out to be important for obtaining sensible results.


Identification and Estimation of 'Maximal' Affine Term Structure Models

Identification and Estimation of 'Maximal' Affine Term Structure Models
Author: Pierre Collin-Dufresne
Publisher:
Total Pages: 62
Release: 2011
Genre:
ISBN:

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We propose a canonical representation for affine term structure models where the state vector is comprised of the first few Taylor-series components of the yield curve and their quadratic (co-)variations. With this representation: (i) the state variables have simple physical interpretations such as level, slope and curvature, (ii) their dynamics remain affine and tractable, (iii) the model is by construction 'maximal' (i.e., it is the most general model that is econometrically identifiable), and (iv) model-insensitive estimates of the state vector process implied from the term structure are readily available. (Furthermore, this representation may be useful for identifying the state variables in a squared-Gaussian framework where typically there is no one-to-one mapping between observable yields and latent state variables). We find that the 'unrestricted' A1(3) model of Dai and Singleton (2000) estimated by 'inverting' the yield curve for the state variables generates volatility estimates that are negatively correlated with the time series of volatility estimated using a standard GARCH approach. This occurs because the 'unrestricted' A1(3) model imposes the restriction that the volatility state variable is simultaneously a linear combination of yields (i.e., it impacts the cross-section of yields), and the quadratic variation of the spot rate process (i.e., it impacts the time-series of yields). We then investigate the A1(3) model which exhibits 'unspanned stochastic volatility' (USV). This model predicts that the cross section of bond prices is independent of the volatility state variable, and hence breaks the tension between the time-series and cross-sectional features of the term structure inherent in the unrestricted model. We find that explicitly imposing the USV constraint on affine models significantly improves the volatility estimates, while maintaining a good fit cross-sectionally.


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

A General Stochastic Volatility Model for the Pricing of Interest Rate Derivatives
Author: Anders B. Trolle
Publisher:
Total Pages: 66
Release: 2016
Genre:
ISBN:

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We develop a tractable and flexible stochastic volatility multi-factor model of the term structure of interest rates. It features unspanned stochastic volatility factors, correlation between innovations to forward rates and their 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 finitedimensional 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.


Information in (and Not In) Treasury Options

Information in (and Not In) Treasury Options
Author: Hoyong Choi
Publisher:
Total Pages: 60
Release: 2017
Genre:
ISBN:

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This paper studies the impact of variance risk in the Treasury market on both term premia and the shape of the yield curve. Under minimal assumptions shared by standard structural and reduced-form asset pricing models, I show that an observable proxy of variance risk in the Treasury market can be constructed via a portfolio of Treasury options. The observable variance risk has the ability to explain the time variation in term premia, but is largely unrelated to the shape of the yield curve. Using the observable variance risk, I also propose a new representation of no-arbitrage term structure models. All the pricing factors in the model are observable, tradable, and hence economically interpretable. The representation can also accommodate both unspanned macro risks and unspanned stochastic volatility in the term structure literature.