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The Dynamics of Stochastic Volatility: Evidence from Underlying and Option Markets
, 2000
"... This paper proposes and estimates a more general parametric stochastic variance model of equity index returns than has been previously considered using data from both underlying and options markets. The parameters of the model under both the objective and riskneutral measures are estimated simultane ..."
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Cited by 159 (3 self)
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This paper proposes and estimates a more general parametric stochastic variance model of equity index returns than has been previously considered using data from both underlying and options markets. The parameters of the model under both the objective and riskneutral measures are estimated simultaneously. I conclude that the square root stochastic variance model of Heston (1993) and others is incapable of generating realistic returns behavior and find that the data are more accurately represented by a stochastic variance model in the CEV class or a model that allows the price and variance processes to have a timevarying correlation. Specifically, I find that as the level of market variance increases, the volatility of market variance increases rapidly and the correlation between the price and variance processes becomes substantially more negative. The heightened heteroskedasticity in market variance that results generates realistic crash probabilities and dynamics and causes returns to display values of skewness and kurtosis much more consistent with their sample values. While the model dramatically improves the fit of options prices relative to the square root process, it falls short of explaining the implied volatility smile for shortdated options.
Modeling Sovereign Yield Spreads: A Case Study of Russian Debt
 JOURNAL OF FINANCE
, 2003
"... We construct a model for pricing sovereign debt that accounts for the risks of both default and restructuring, and allows for compensation for illiquidity. Using a new and relatively efficient method, we estimate the model using Russian dollardenominated bonds. We consider the determinants of the R ..."
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Cited by 136 (9 self)
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We construct a model for pricing sovereign debt that accounts for the risks of both default and restructuring, and allows for compensation for illiquidity. Using a new and relatively efficient method, we estimate the model using Russian dollardenominated bonds. We consider the determinants of the Russian yield spread, the yield differential across different Russian bonds, and the implications for market integration, relative liquidity, relative expected recovery rates, and implied expectations of different default scenarios.
Estimating Stochastic Volatility Diffusion Using Conditional Moments of Integrated Volatility
, 2000
"... We exploit the distributional information contained in highfrequency intraday data in constructing a simple conditional moment estimator for stochastic volatility diffusions. The estimator is based on the analytical solutions of the first two conditional moments for the integrated volatility, which ..."
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Cited by 107 (10 self)
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We exploit the distributional information contained in highfrequency intraday data in constructing a simple conditional moment estimator for stochastic volatility diffusions. The estimator is based on the analytical solutions of the first two conditional moments for the integrated volatility, which is effectively approximated by the quadratic variation of the process. We successfully implement the resulting GMM estimator with highfrequency fiveminute foreign exchange and equity index returns. Our simulation evidence and actual empirical results indicate that the method is very reliable and accurate. The computational speed of the procedure compares very favorably to other existing estimation methods in the literature.
Continuoustime methods in finance: A review and an assessment
 Journal of Finance
, 2000
"... I survey and assess the development of continuoustime methods in finance during the last 30 years. The subperiod 1969 to 1980 saw a dizzying pace of development with seminal ideas in derivatives securities pricing, term structure theory, asset pricing, and optimal consumption and portfolio choices. ..."
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Cited by 52 (0 self)
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I survey and assess the development of continuoustime methods in finance during the last 30 years. The subperiod 1969 to 1980 saw a dizzying pace of development with seminal ideas in derivatives securities pricing, term structure theory, asset pricing, and optimal consumption and portfolio choices. During the period 1981 to 1999 the theory has been extended and modified to better explain empirical regularities in various subfields of finance. This latter subperiod has seen significant progress in econometric theory, computational and estimation methods to test and implement continuoustime models. Capital market frictions and bargaining issues are being increasingly incorporated in continuoustime theory. THE ROOTS OF MODERN CONTINUOUSTIME METHODS in finance can be traced back to the seminal contributions of Merton ~1969, 1971, 1973b! in the late 1960s and early 1970s. Merton ~1969! pioneered the use of continuoustime modeling in financial economics by formulating the intertemporal consumption and portfolio choice problem of an investor in a stochastic dynamic programming setting.
Efficient Method of Moments
, 2001
"... We describe a computationally intensive methodology for the estimation and analysis of partially observable nonlinear systems. An example from epidemiology is the SEIR model, which is a system of differential equations with random coefficients that describes a population in terms of four state vari ..."
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Cited by 2 (0 self)
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We describe a computationally intensive methodology for the estimation and analysis of partially observable nonlinear systems. An example from epidemiology is the SEIR model, which is a system of differential equations with random coefficients that describes a population in terms of four state variables: those susceptible to a disease, those exposed to it, those infected by it, and those recovered from it. Only those infected by the disease are known to public health officials. An example from nance is the continuoustime stochastic volatility model, which is a system of stochastic differential equations that describes a security's price and instantaneous variance. Only the security's price can be observed directly. System parameters are estimated by a variant of simulated method of moments known as efficient method of moments (EMM). The idea is to the match moments implied by the system to moments implied by the transition density for observables. System analysis is accomplished by reprojection. Reprojection is carried out by projecting a long simulation from the estimated system onto an appropriate representation of
EMM Estimation of Affine and Nonaffine Term Structure Models
, 2000
"... We use the Efficient Method of Moments (EMM) of Gallant and Tauchen (1996) to estimate a three factor term structure model which is affine under the riskneutral probability distribution, but nonaffine under the true probability distribution. Unlike most previous research, in which the model is aff ..."
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Cited by 1 (0 self)
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We use the Efficient Method of Moments (EMM) of Gallant and Tauchen (1996) to estimate a three factor term structure model which is affine under the riskneutral probability distribution, but nonaffine under the true probability distribution. Unlike most previous research, in which the model is affine under both distributions, this allows us to retain the analytical convenience for pricing of this class of model, while allowing greater flexibility in matching the observed timeseries properties of interest rates. We find that the fully affine specification is statisticallyr ejected in favor of the more flexible alternative. We also shed new light on the implementation of EMM for estimating models using high dimensional, very persistent series such as term structure models. We find, in particular, that the auxiliary model most commonly used in conjunction with EMM, the SNP model of Gallant and Tauchen (1992), has serious problems in this environment, and that substantially better results ...
Nonparametric Estimation of Multifactor Continuous Time Interest Rate Models
, 1999
"... This paper studies the finite sample properties of the kernel regression method of Boudoukh, Richardson, Stanton and Whitelaw (1998) for estimating multifactor continuoustime term structure models. Monte Carlo simulations are employed, with a gridsearch technique to find the optimal kernel ba ..."
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This paper studies the finite sample properties of the kernel regression method of Boudoukh, Richardson, Stanton and Whitelaw (1998) for estimating multifactor continuoustime term structure models. Monte Carlo simulations are employed, with a gridsearch technique to find the optimal kernel bandwidth. The performance of the estimator is also studied under model misspecification. Irrelevant regressors reduce e#ciency and induce additional biases in the estimates. Using Treasury bill data, I test whether the estimates produced by the nonparametric estimator are statistically distinguishable from estimates obtained under a parametric model. The kernel regressions pick up nonlinearities that the parametric model cannot capture. 2 In a series of recent papers, researchers in finance have developed nonparametric methods for estimating the drift and di#usion functions of continuous time stochastic processes. Stanton (1997) pioneered a method based on the theory of weak approxima...
Journal of Economic Dynamics & Control
, 2000
"... www.elsevier.com/locate/econbase Do we need multicountry models to explain exchange rate and interest rate and bond return dynamics? ..."
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www.elsevier.com/locate/econbase Do we need multicountry models to explain exchange rate and interest rate and bond return dynamics?