Range-Based Estimation of Stochastic Volatility Models

By S. Alizadeh, Michael W. Brandt, Francis X. Diebold. 2002

1,236 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/1c11cc3bd13f886b422b12fc9433ba047430ceb0

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Citations in the corpus

A Multiple Indicators Model for Volatility Using Intra-Daily Data (2003, background): “Many authors (Taylor, 1987; Rogers and Satchell, 1991; Gallant et al., 1999; Chou, 2001; Alizadeh et al., 2002; Brandt and Jones, 2002; Brandt and Diebold, 2003) have devoted considerable attention to the informational content of range data extending the relationship it has to the volatility paramet”
Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models (2006, methodology): “, 2003; Barndorff-Nielsen and Shephard, 2002), hi-lo quotes (Alizadeh et al., 2002) or option prices (Jones, 2003; Koopman et al., 2005). This paper demonstrates tools for likelihood-based analysis of standard one- and two-factor SV models used in finance, building on work by Kim et al. (1998), Shep”
Demystifying Time‐Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations (2020, neutral): “The volatility estimators that make use of open, high, low and close prices are known in the literature as range estimators and have been shown to offer additional robustness against microstructure noise such as bid-ask bounce and asynchronous trading and therefore increase the efficiency of the est”
Realized range-based estimation of integrated variance (2007, neutral): “Thus, the log-variance of spot prices evolves as a mean reverting Ornstein-Uhlenbeck process with mean ω , mean reversion parameter θ and volatility η (see, e.g., Gallant et al. (1999), Alizadeh et al. (2002), and Andersen, Benzoni & Lund (2002)).”
The intertemporal capital asset pricing model with dynamic conditional correlations (2010, background): “As pointed out by Alizadeh et al. (2002) and Brandt and Diebold (2006), Eq.”
Properties of Range-Based Volatility Estimators (2012, neutral): “To do this, we use numerical evaluation of h, l and c data, which are simulated according to the process (1) (.”
Measuring Dynamic Connectedness with Large Bayesian VAR Models (2018, neutral): “The US sample includes 8 commercial banks, 5 investment banks, two mortgage companies, one credit card company and one insurance company.5 The 4 On range-based volatility, see, for example, Alizadeh et al. (2002).”
The MIDAS Touch: Mixed Data Sampling Regression Models (2004, neutral): “by Alizadeh, Brandt, and Diebold (2002) , Chacko and Viceira (1999), Gallant, Hsu, and”
Volatility Components, Affine Restrictions and Non-Normal Innovations (2008, neutral): “In the special case where v = 2, we get κ(2) = Γ( 52)Γ( 1 2) Γ( 32) 2 = 3, θ (2) = μ 2−1Γ( 12) Γ( 32) ¶1 2 = 1 and because Γ ¡ 1 2 ¢ = √ π we get g2(ζ) = 1 √ 2π exp μ −(1) 2 ζ(2) ¶”