Monte Carlo Methods in Financial Engineering

Glasserman, P. (2004). Monte Carlo Methods in Financial Engineering. Springer.

Type

Book

Intellectual base

Review or monograph

Year

2004

Link

https://archive.org/details/montecarlomethod00glas_182matched

Cited from

statistics_experimental_design

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Monte Carlo Simulation
  • Prior to 2019, the carrier's catastrophe exposure modeling relied on a vendor catastrophe model (AIR, RMS) that produced summary statistics — 1-in-100-year and 1-in-250-year probable maximum loss (PML) numbers — which the reinsurance team used to negotiate reinsurance-program attachment points and limits

    This sourceGlasserman financial applications derivatives pricing portfolio risk.

Domain-specific

• Control variates
  • … base estimator, control variables and known expectations, joint sampling, coefficient estimation, covariance and achieved variance, bias conditions and uncertainty estimate are explicit. to An applied instance preserves the same invariant under changed scale, notation, jurisdiction, dataset, or implementation..

Verification

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