Oct
24

## Nearest correlation matrix

Correlation matrix exists almost everywhere for derivative pricing and risk management, especially when Monte Carlo simulation is applied, for instance, to simulate correlated random numbers via Cholesky decomposition of correlation matrix. However, one strong requirement of Cholseky decomposition on correlation matrix is positive semi-definite, in other words, eigenvalues must be positive. Another example of positive semi-definite correlation matrix requirement is for risk management measurement, otherwise the volatility calculated might be negative, which is non-acceptable.

In practice, sometimes we need to change correlation matrix to our forecasting values, even minor change might lead to invalid matrix, for this problem, http://www.maths.manchester.ac.uk/~nareports/narep369.pdf details the way to overcome it, accompanying Matlab code can also be found at http://www.maths.manchester.ac.uk/~clucas/near_cor.m and http://www.maths.manchester.ac.uk/~clucas/eig_mex.c.

Hot posts:

15 Incredibly Stupid Ways People Made Their Millions

Online stock practice

World Changing Mathematical Discoveries

Ino.com: Don't Join Marketclub until You Read This MarketClub Reviews

Value at Risk xls

Random posts:

Monte Carlo Pricer of Barrier, Knock in and out Options with Jump-Diffusion

Mean Reversion Speed Estimation - What Am I Missing?

Handling Large Datasets in R

Frequently Asked Questions in Quantitative Finance

Statistical Arbitrage in the U.S. Equities Market

In practice, sometimes we need to change correlation matrix to our forecasting values, even minor change might lead to invalid matrix, for this problem, http://www.maths.manchester.ac.uk/~nareports/narep369.pdf details the way to overcome it, accompanying Matlab code can also be found at http://www.maths.manchester.ac.uk/~clucas/near_cor.m and http://www.maths.manchester.ac.uk/~clucas/eig_mex.c.

**People viewing this post also viewed:**

Hot posts:

Random posts: