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A GMM approach to estimate the roughness of stochastic volatility
v1v2v3v4 (latest)

A GMM approach to estimate the roughness of stochastic volatility

9 October 2020
Anine Eg Bolko
Kim Christensen
Mikko S. Pakkanen
Bezirgen Veliyev
ArXiv (abs)PDFHTML

Papers citing "A GMM approach to estimate the roughness of stochastic volatility"

6 / 6 papers shown
Title
A nonparametric test for diurnal variation in spot correlation processes
A nonparametric test for diurnal variation in spot correlation processes
Kim Christensen
Ulrich Hounyo
Zhi Liu
34
0
0
05 Aug 2024
Estimating the roughness exponent of stochastic volatility from discrete
  observations of the realized variance
Estimating the roughness exponent of stochastic volatility from discrete observations of the realized variance
Xiyue Han
A. Schied
43
0
0
05 Jul 2023
Statistical inference for rough volatility: Central limit theorems
Statistical inference for rough volatility: Central limit theorems
Carsten H. Chong
M. Hoffmann
Yanghui Liu
M. Rosenbaum
Grégoire Szymanski
80
18
0
03 Oct 2022
On the universality of the volatility formation process: when machine
  learning and rough volatility agree
On the universality of the volatility formation process: when machine learning and rough volatility agree
M. Rosenbaum
Jianfei Zhang
OODAIFinAI4TS
57
7
0
28 Jun 2022
Optimal estimation of the rough Hurst parameter in additive noise
Optimal estimation of the rough Hurst parameter in additive noise
Grégoire Szymanski
58
6
0
25 May 2022
Rough volatility: fact or artefact?
Rough volatility: fact or artefact?
R. Cont
Purba Das
25
39
0
24 Mar 2022
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