A Review of Control Variates in Simulation

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This paper provides a review and practical assessment of the Control variates method, a variance reduction technique widely employed in Monte Carlo simulation.
This paper provides a review and practical assessment of the Control variates method, a variance reduction technique widely employed in Monte Carlo simulation and discusses its theoretical underpinnings, benefits, limitations, assumptions, and mathematical framework. Additionally, this paper exposes an analysis using the R programming language, illustrating a case with substantial variance reduction. The analysis also highlights critical factors affecting performance, such as correlation, estimator bias, and variance behavior.

Autor*in

Johann Markus Schauerhuber
During his studies and academic resp. professional activities Prof. Dr. Dr. Johann Markus Schauerhuber has been intensively involved in statistical programming, stochastic, risk theory, simulation and mathematical modeling. Most of his professional experience has been gained in the university domain as an academic director, postdoc lecturer / researcher and in government authorities. Email: jm_schauerhuber@gmx.at

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