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Oct 17

MATLAB  routines for risk and portfolio management

Posted by abiao at 20:40 | Code » Matlab | Comments(1) | Reads(18132)
These routines support the book "Risk and Asset Allocation" Springer Finance, by A. Meucci.

The routines include many new features:
- more uni-, multi- and matrix-variate distributions
- more copulas
- more graphical representations
- more analyses in terms of the location-dispersion ellipsoid.
- best replication / best factor selection
- FFT-based projection of a distribution to the investment horizon
- caveats about delta/gamma pricing
- step-by-step evaluation of a generic estimator
- non-parametric estimators
- multivariate elliptical maximum-likelihood estimators
- shrinkage estimators: Stein and Ledoit-Wolf, Bayesian classical equivalent
- robust estimators: Hubert M, high-breakdown minimum volume ellipsoid
- missing-data techniques: EM algorithm, uneven-series conditional estimation
- stochastic dominance
- extreme value theory for VaR
- Cornish-Fisher approximation for VaR
- kernel-based contribution to VaR and expected shortfall from different risk-factors
- mean-variance analysis and pitfalls (different horizons, compounded vs. linear returns, etc...)
- Bayesian estimation (multivariate analytical, Monte Carlo Markov Chains, priors for correlation matrices)
- estimation risk evaluation: opportunity cost of estimation-based allocations
- Black Litterman allocation
- robust optimization (calls SeDuMi to perform cone programming)
- robust Bayesian allocation
- more...

sample chapter and codes can be downloaded at http://www.symmys.com/AttilioMeucci/Book/Downloads/Downloads

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