Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics

By Ole E. Barndorff-Nielsen, N. Shephard. 2001

2,035 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/2f3e29f0d3476ccf75daf7ec6e6bf22e3b8f065c

How researchers see this paper

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

In Economics and Econometrics

1. Tim Bollerslev
2. V. Todorov
3. N. Shephard
4. Andrew J. Patton
5. Torben G. Andersen
6. Ole E. Barndorff-Nielsen
7. Asger Lunde
8. George Tauchen

In Finance

1. V. Todorov
2. Tim Bollerslev
3. N. Shephard
4. Ole E. Barndorff-Nielsen
5. Andrew J. Patton
6. Torben G. Andersen
7. George Tauchen
8. Asger Lunde

Citations in the corpus

• A Jump-Diffusion Model for Option Pricing (2002, neutral): “fractal Brownian motion, and stable processes; see, for example, Mandelbrot (1963), Rogers (1997), Samorodnitsky and Taqqu (1994); (b) generalized hyperbolic models, including log t model and log hyperbolic model; see, for example, Barndorff-Nielsen and Shephard (2001), Blattberg and Gonedes (1974);”
• HETEROSKEDASTIC TIME SERIES WITH A UNIT ROOT (2009, background): “(10) The right member of (10) is argued to be the leading special case of the nonGaussian OU volatility model of Barndorff-Nielsen and Shephard (2001) where the homogeneous Lévy process driving volatility is a compound Poisson process with positive increments; see Roberts, Papaspiliopoulos, and…”
• Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH‐NIG model (2002, background): “…realized volatilities are subject to measurement error vis-à-vis the true daily latent volatilities (see, for instance, Andreou and Ghysels, 2002; Barndorff-Nielsen and Shephard, 2001b, 2002b; Meddahi, ‘A theoretical comparison between integrated and realized volatilities’, unpublished…”
• Bayesian analysis of single‐molecule experimental data (2005, background): “Barndorff-Nielsen and Shephard (2001) introduced a class of stochastic volatility models where the (latent) volatility is modelled as an Ornstein–Uhlenbeck process, driven by a positive Lévy process without Gaussian component.”
• Recent results in the theory and applications of CARMA processes (2014, methodology): “(12) of Barndorff-Nielsen and Shephard (2001) who used it to choose the Lévy process (i.e. ζ(θ)) required to generate a specified marginal distribution for the corresponding CARMA(1,0) process.”
• Analysis of variance based instruments for Ornstein–Uhlenbeck type models: swap and price index (2017, neutral): “This model is introduced in various works (see Barndorff-Nielsen 2001; Barndorff-Nielsen and Shephard 2001a, b) of Barndorff-Nielsen and Shephard and is known inmodern literature as the BN-Smodel. In Benth et al. (2007) investigate swaps written on powers of realized volatility in the stochastic vol”
• Econometric analysis of jump-driven stochastic volatility models (2011, methodology): “…in closed form moments of returns associated with continuous-time stochastic volatility 2To generate richer autocorrelation structure of the stochastic variance, Barndorff-Nielsen and Shephard (2001) propose also superpositions of Lévy-driven OU processes for modeling the stochastic variance.”
• Gibbs sampling methods for Bayesian quantile regression (2011, background): “and Kν(·) is a modified Bessel function of the third kind [14].”