A Review of Moment Matching in Simulation

Beschreibung

Moment matching is a classical variance reduction technique in Monte Carlo simulation whereby simulated samples are adjusted to conform to known population moments.
Moment matching is a classical variance reduction technique in Monte Carlo simulation whereby simulated samples are adjusted to conform to known population moments (e.g., mean, variance). The method enhances estimator efficiency by reducing sampling variability (Glasserman, 2003). This paper covers the theoretical foundations, mathematical formulation, assumptions, advantages and disadvantages.

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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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