Free Lévy matrices and financial correlations
✍ Scribed by Zdzisław Burda; Jerzy Jurkiewicz; Maciej A. Nowak; Gabor Papp; Ismail Zahed
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 231 KB
- Volume
- 343
- Category
- Article
- ISSN
- 0378-4371
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✦ Synopsis
We consider a covariance matrix composed of asymmetric and free random LÃ evy matrices. We use the results of free random variables to derive an algebraic equation for the resolvent and solve it to extract the spectral density. For an appropriate choice of asymmetry and LÃ evy index =2 = 3 4 the free eigenvalue spectrum is in remarkable agreement with the one obtained from the covariance matrix of the SP500 ÿnancial market. Our results are of interest to a number of stochastic systems with power law noise.
📜 SIMILAR VOLUMES
Using Random Matrix Theory one can derive exact relations between the eigenvalue spectrum of the covariance matrix and the eigenvalue spectrum of its estimator (experimentally measured correlation matrix). These relations will be used to analyze a particular case of the correlations in financial ser
In this paper, we construct a Le vy area process for the free Brownian motion and in this way, a typical geometric rough path (in the sense of T. Lyons (1998, Rev. Mat. Iberoamer. 14, 215 310)), lying above the free Brownian path. Thus, the general results of Lyons on differential equations driven b
Previously we have put forward that the sluggish convergence of truncated LÃ evy ights to a Gaussian (Phys. Rev. Lett. 73 (1994Lett. 73 ( ) 2946) ) together with the scaling power laws in their probability of return to the origin (Nature 376 (1995) 46) can be explained by autocorrelation in data (Ph