Sign in
Author

Conference

Journal

Organization

Year

DOI
Look for results that meet for the following criteria:
since
equal to
before
between
and
Search in all fields of study
Limit my searches in the following fields of study
Agriculture Science
Arts & Humanities
Biology
Chemistry
Computer Science
Economics & Business
Engineering
Environmental Sciences
Geosciences
Material Science
Mathematics
Medicine
Physics
Social Science
Multidisciplinary
Keywords
(14)
Forecast Accuracy
High Frequency
High Frequency Data
Integrated Volatility
Market Microstructure
Market Microstructure Noise
Microstructure Noise
Model Development
Quadratic Form
Realized Volatility
Sampling Frequency
Stochastic Volatility
Stochastic Volatility Model
Volatility Forecasting
Related Publications
(7)
The CrossSection of Volatility and Expected Returns
DeltaHedged Gains and the Negative Market Volatility Risk Premium
Variance Trading and Market Price of Variance Risk
Expected Stock Returns and Variance Risk Premia
Variance Risk Premium Dynamics
Subscribe
Academic
Publications
Realized volatility forecasting and market microstructure noise
Realized volatility forecasting and market microstructure noise,10.1016/j.jeconom.2010.03.032,Journal of Econometrics,Torben G. Andersen,Tim Bollersle
Edit
Realized volatility forecasting and market microstructure noise
(
Citations: 26
)
BibTex

RIS

RefWorks
Download
Torben G. Andersen
,
Tim Bollerslev
,
Nour Meddahi
We extend the analytical results for reduced form
realized volatility
based forecasting in ABM (2004) to allow for
market microstructure
frictions in the observed highfrequency returns. Our results build on the eigenfunction representation of the general
stochastic volatility
class of models developed byMeddahi (2001). In addition to traditional
realized volatility
measures and the role of the underlying sampling frequencies, we also explore the forecasting performance of several alternative volatility measures designed to mitigate the impact of the microstructure noise. Our analysis is facilitated by a simple unified
quadratic form
representation for all these estimators. Our results suggest that the detrimental impact of the noise on
forecast accuracy
can be substantial. Moreover, the linear forecasts based on a simpletoimplement ‘average’ (or ‘subsampled’) estimator obtained by averaging standard sparsely sampled
realized volatility
measures generally perform on par with the best alternative robust measures.
Journal:
Journal of Econometrics  J ECONOMETRICS
, vol. 160, no. 1, pp. 220234, 2011
DOI:
10.1016/j.jeconom.2010.03.032
Cumulative
Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
(
www.sciencedirect.com
)
(
linkinghub.elsevier.com
)
(
www.sciencedirect.com
)
Citation Context
(5)
...
2009
)...
Mathieu Rosenbaum
.
A new microstructure noise index
...Andersen, Bollerslev, and Meddahi
(2006)
as well as Ghysels and Sinko
(2006)
study best sampling approaches in the context of forecasting realized variance...
Daniel Djupsjöbacka
.
Implications of market microstructure for realized variance measuremen...
...Related recent work with a focus on the properties of modelfree implied volatility and its relation to general asset market dynamics include
Andersen, Frederiksen and Staal (2006)
, Ang, Hodrick, Xing and Zhang (2006), Bakshi and Kapadia (2003), Bakshi and Madan (2006), Bliss and Panigirtzoglou (2004), Bollerslev, Gibson and Zhou (2007), Bollerslev and Zhou (2007), Bondarenko (2007), Carr and Wu (2004), Duan and Yeh (2007), Todorov (2007) ...
Torben G. Andersen
,
et al.
Construction and Interpretation of ModelFree Implied Volatility
...pti = p ∗ ti + εti, (
6
) where εti is assumed (at least initially) to be an i.i.d...
...7 Although the kernel estimator is introduced within the context of general semimartingales, the properties of the estimator are demonstrated under the assumption of a model without random jumps (i.e. with κ(t )=0 in (
6
))...
Gael M. Martin
,
et al.
Does the Option Market Produce Superior Forecasts of NoiseCorrected V...
...We begin by focusing on unconditional choices ((
3
) through (6))...
...We begin by focusing on unconditional choices ((3) through (6)). The onestep estimator in (
3
) performs...
...optimal frequency in (
3
)) for all realized variance entries...
...count for the presence of a timevarying bias directly, perform better than unconditional varianceoptimal bandwidth choices (as in (
3
))...
...Here, the divergence between the unconditional choices in (2) and (
3
) is possibly due to a timevarying bias...
Federico M. Bandi
,
et al.
REALIZED VOLATILITY FORECASTING in the PRESENCE of TIMEVARYING NOISE
References
(56)
Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts
(
Citations: 520
)
Torben G. Andersen
,
Tim Bollerslev
Published in 1998.
Forecasting financial market volatility: Sample frequency visàvis forecast horizon
(
Citations: 109
)
Torben G. Andersen
,
Tim Bollerslev
,
Steve Lange
Journal:
Journal of Empirical Finance  J EMPIR FINANC
, vol. 6, no. 5, pp. 457477, 1999
Analytic Evaluation of Volatility Forecasts
(
Citations: 75
)
T. G. Andersen
,
T. Bollerslev
,
N. Meddahi
Published in 2004.
Multivariate realised kernels: consistent positive semidefinite estimators of the covariation of equity prices with noise and nonsynchronous trading
(
Citations: 26
)
Ole E. BarndorffNielsen
,
Peter Reinhard Hansen
,
Asger Lunde
,
Neil Shephard
Published in 2008.
Nonlinear Principal Components and Longrun Implications of Multivariate Diffusions
(
Citations: 2
)
Xioahong Chen
,
Lars Peter Hansen
,
Jose Scheinkman
Journal:
Annals of Statistics  ANN STATIST
, vol. 37, no. 6B, pp. 42794312, 2009
Sort by:
Citations
(26)
Realized volatility forecasting and market microstructure noise
(
Citations: 26
)
Torben G. Andersen
,
Tim Bollerslev
,
Nour Meddahi
Journal:
Journal of Econometrics  J ECONOMETRICS
, vol. 160, no. 1, pp. 220234, 2011
Volatility forecasting and microstructure noise
(
Citations: 11
)
Eric Ghysels
,
Arthur Sinko
Journal:
Journal of Econometrics  J ECONOMETRICS
, vol. 160, no. 1, pp. 257271, 2011
Databased ranking of realised volatility estimators
(
Citations: 1
)
Andrew J. Patton
Journal:
Journal of Econometrics  J ECONOMETRICS
, vol. 161, no. 2, pp. 284303, 2011
Inspiratory Muscle Training Can Increase Lower Esophageal Sphincter Pressure in GERD Patients – A Sham Controlled Trial
Renata C. Sousa
,
Milena M. Suesada
,
Fabiane Polisel
,
Cláudia C. de Sá
,
Joaquim P. MoraesFilho
,
Ricardo C. Barbuti
,
Jaime N. Eisig
,
Decio Chinzon
,
Tomas NavarroRodriguez
Journal:
Gastroenterology
, vol. 140, no. 5, pp. S303S303, 2011
A new microstructure noise index
Mathieu Rosenbaum
Journal:
Quantitative Finance  QUANT FINANC
, vol. 11, no. 6, pp. 883899, 2011