An Eigenfunction Approach for Volatility Modeling

By Nour Meddahi. 2001

114 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5059df117153fb60f53afb3b07dd8c54c1d08853

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Alternative models for stock price dynamics (2003, unknown): “For example, Meddahi (2001) proposes to model the diiusion coeecient as a ÿnite order expansion based on the eigenfunctions of the expectations of the state variables.”
ESTIMATING THE PERSISTENCE AND THE AUTOCORRELATION FUNCTION OF A TIME SERIES THAT IS MEASURED WITH ERROR (2013, unknown): “Meddahi (2003) deduced the value, π = 0.”
ARMA representation of integrated and realized variances (2003, methodology): “Example 3 (ESV Model, Meddahi (2001)).”
Impact of jumps on returns and realised variances: econometric analysis of time-deformed Lévy processes (2006, background): “Andersen, Bollerslev, and Meddahi (2002a) and Andersen, Bollerslev, and Meddahi (2002b) have studied in detail other properties of these estimators in the Brownian motion time-deformation case.”
Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities (2005, methodology): “discussed in Andersen, Bollerslev and Meddahi (2004). This is especially noteworthy in so far the parameter values for this model are based on the identical DM-dollar sample”
Forecasting Volatility Using High-Frequency Data (2011, background): “This feature arises quite naturally in the eigenfunction approach to volatility model (see Meddahi (2001)) because the absolute return is more closely related to the first eigenfunction than is squared returns in certain models.”
Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation (2009, unknown): “Meddahi (2001) shows that a necessary and sufficient condition for P2m(x) to be positive is that it can be written as the sum of two squared polynomials of order m.”
A theoretical comparison between integrated and realized volatility (2002, unknown): “In this section, we recap the main properties of the Eigenfunction Stochastic Volatility (ESV) models introduced in Meddahi (2001a).”
Is there a risk–return trade‐off? Evidence from high‐frequency data (2006, unknown): “Barndorff-Nielsen and Shephard (2002) provide general asymptotic distributional results for the size of the measurement error, while Meddahi (2001) presents explicit expressions for the class of eigenfunction stochastic volatility models.”
Realized Volatility: A Review (2008, background): “In a recent article, Corradi and Distaso (2006) proposed a procedure to test for the correct specification of the functional form of the volatility process based on the class of eigenfunction stochastic volatility models of Meddahi (2001).”
Semi-Parametric Comparison of Stochastic Volatility Models using Realized Measures (2006, methodology): “Following Meddahi (2001) it is then possible to define α and the unobservable state variable ft by α = 2κµ η2 −1, ft (θ ) = 2κ η2 σ 2t (θ ) .”
Realized volatility forecasting and market microstructure noise (2011, background): “We follow ABM (2004) in assuming that the spot volatility process belongs to the Eigenfunction Stochastic Volatility (ESV) class introduced by Meddahi (2001).”
Bayesian semiparametric stochastic volatility modeling (2010, unknown): “However, parametric SVmodels have not fully captured the asymmetries and leptokurtotic behavior present in return data (see Gallant et al., 1997; Mahieu and Schotman, 1998; Liesenfeld and Jung, 2000; Meddahi, 2001; Durham, 2006).”
VOLATILITY AND CORRELATION FORECASTING (2006, background): “-36The modeling of asset returns in continuous time stems from the financial economics literature where early contributions to portfolio selection by Merton (1969) and option pricing by Black and Scholes (1973) demonstrated the analytical power of the diffusion framework in handling dynamic asset al”