Analysis and generation of random vectors with copulas

Johann Christoph Strelen · Feras Nassaj

32 citations0/0 files storedWinter Simulation Conference

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Risk and Volatility Modeling Stochastic processes and financial applications Probability and Risk Models

Abstract

Copulas are used in finance and insurance for modeling stochastic dependency. They comprehend the entire dependence structure, not only the correlations. Here they are estimated from measured samples of random vectors. The copula and the marginal distributions of the vector elements define a multivariate distribution of the sample which can be used to generate random vectors with this distribution. This can be applied as well to time series. A programmed algorithm is proposed. It is fast and allows for random vectors with high dimension, for example 100.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 32 citations exist upstream.

References

1999Simulation modeling and analysis 1996Autoregressive to anything: Time-series input processes for simulation 2003Modeling and generating multivariate time-series input processes using a vector autoregressive technique

Cited by

2022Alternatives to Large VAR, Varma and Multivariate Stochastic Volatility Models 2022Toward stochastic multiscale methods in continuum solid mechanics 2014Reliability-Based Robust Design of Mechanical Components with Correlated Failure Modes Based on Moment Method

Imported from OpenAlex (CC0) — nothing here is generated.