Quantile Estimation When Applying Conditional Monte Carlo

Marvin K. Nakayama

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Paper

Quantile Estimation When Applying Conditional Monte Carlo

Topics: Computer Simulation Techniques; Energy and Power Systems; Performance Analysis; Risk Analysis; Stochastic Modeling and Simulation

In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications SIMULTECH - Volume 1, 280-285, 2014 , Vienna, Austria

Author: Marvin K. Nakayama

Affiliation: New Jersey Institute of Technology, United States

Keyword(s): Quantile, Value-at-Risk, Variance Reduction, Conditional Monte Carlo, Confidence Interval.

Related Ontology Subjects/Areas/Topics: Application Domains ; Computer Simulation Techniques ; Energy and Power Systems ; Formal Methods ; Performance Analysis ; Risk Analysis ; Simulation and Modeling ; Simulation Tools and Platforms ; Stochastic Modeling and Simulation

Abstract: We describe how to use conditional Monte Carlo (CMC) to estimate a quantile. CMC is a variance-reduction technique that reduces variance by analytically integrating out some of the variability. We show that the CMC quantile estimator satisfies a central limit theorem and Bahadur representation. We also develop three asymptotically valid confidence intervals (CIs) for a quantile. One CI is based on a finite-difference estimator, another uses batching, and the third applies sectioning. We present numerical results demonstrating the effectiveness of CMC.

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Paper citation in several formats:

K. Nakayama, M. (2014). Quantile Estimation When Applying Conditional Monte Carlo. In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH; ISBN 978-989-758-038-3; ISSN 2184-2841, SciTePress, pages 280-285. DOI: 10.5220/0005109702800285

@conference{simultech14,
author={Marvin {K. Nakayama}.},
title={Quantile Estimation When Applying Conditional Monte Carlo},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH},
year={2014},
pages={280-285},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005109702800285},
isbn={978-989-758-038-3},
issn={2184-2841},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH
TI - Quantile Estimation When Applying Conditional Monte Carlo
SN - 978-989-758-038-3
IS - 2184-2841
AU - K. Nakayama, M.
PY - 2014
SP - 280
EP - 285
DO - 10.5220/0005109702800285
PB - SciTePress