An Intuitively Valid Algorithm for Adjusting the Correlation Matrix in Risk Management and Option Pricing

2012 ◽  
Author(s):  
Kawee Numpacharoen ◽  
Kornkanok Bunwong
Keyword(s):  
Risk Management ◽  
Option Pricing ◽  
Correlation Matrix

RANDOM MATRIX THEORY AND FINANCIAL CORRELATIONS

2000 ◽  
Vol 03 (03) ◽  
pp. 391-397 ◽  
Author(s):  
LAURENT LALOUX ◽  
PIERRE CIZEAU ◽  
MARC POTTERS ◽  
JEAN-PHILIPPE BOUCHAUD
Keyword(s):  
Time Series ◽  
Risk Management ◽  
Theoretical Prediction ◽  
Correlation Matrix ◽  
Matrix Theory ◽  
Financial Time Series ◽  
Statistical Structure ◽  
Correlation Matrices ◽  
Financial Time ◽  
Remarkable Agreement

We show that results from the theory of random matrices are potentially of great interest when trying to understand the statistical structure of the empirical correlation matrices appearing in the study of multivariate financial time series. We find a remarkable agreement between the theoretical prediction (based on the assumption that the correlation matrix is random) and empirical data concerning the density of eigenvalues associated to the time series of the different stocks of the S&P500 (or other major markets). Finally, we give a specific example to show how this idea can be sucessfully implemented for improving risk management.

scholarly journals GARCH vs. stochastic volatility: Option pricing and risk management

2002 ◽  
Vol 26 (2-3) ◽  
pp. 323-345 ◽  
Author(s):  
Alfred Lehar ◽  
Martin Scheicher ◽  
Christian Schittenkopf
Keyword(s):  
Risk Management ◽  
Option Pricing ◽  
Stochastic Volatility

A new methodology to create valid time-dependent correlation matrices via isospectral flows

2020 ◽  
Vol 54 (2) ◽  
pp. 361-371
Author(s):  
Long Teng ◽  
Xueran Wu ◽  
Michael Günther ◽  
Matthias Ehrhardt
Keyword(s):  
Risk Management ◽  
Correlation Matrix ◽  
Time Dependent ◽  
Correlation Matrices ◽  
Know How ◽  
Initial Correlation ◽  
Valid Time ◽  
Dependent Correlation

In many areas of finance and of risk management it is interesting to know how to specify time-dependent correlation matrices. In this work we propose a new methodology to create valid time-dependent instantaneous correlation matrices, which we called correlation flows. In our methodology one needs only an initial correlation matrix to create these correlation flows based on isospectral flows. The tendency of the time-dependent matrices can be controlled by requirements. An application example is presented to illustrate our methodology.

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