Alternative Random Matrix Approach in Analysis of Correlations in Financial Data

• Authors: M. Sawa , D. Grech
• Languages of publication: EN

Abstracts

EN

We present an alternative method based on random matrix approach that enables to distinguish the respective role of temporal autocorrelations inside given time series and cross correlations between various time series. The proposed algorithm is based on the properties of Wigner eigenspectrum of random matrices instead of commonly used Wishart eigenspectrum methodology. It is then qualitatively and quantitatively applied to financial data of stocks building WIG 30 - the main Warsaw Stock Exchange Index.

Keywords

EN

05.45.Tp; 02.60.-x; 89.20.-a; 89.75.-k; 89.65.Gh; 89.75.Fb

Discipline

• 89.75.-k: Complex systems(for complex chemical systems, see 82.40.Qt; for biological complexity, see 87.18.-h)
• 05.45.Tp: Time series analysis
• 89.20.-a: Interdisciplinary applications of physics
• 89.65.Gh: Economics; econophysics, financial markets, business and management(for economic issues regarding production and use of renewable energy, see 88.05.Lg)
• 02.60.-x: Numerical approximation and analysis
• 89.75.Fb: Structures and organization in complex systems

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2015
• Volume: 127
• Issue: 3A
• Pages: A-118-A-122

Dates

published

2015-03

Contributors

author

M. Sawa

• Institute of Theoretical Physics, University of Wrocław, Econophysics and Time Series Analysis Group (ETSA), pl. M. Borna 9, PL-50204 Wrocław, Poland

author

D. Grech

• Institute of Theoretical Physics, University of Wrocław, Econophysics and Time Series Analysis Group (ETSA), pl. M. Borna 9, PL-50204 Wrocław, Poland

References

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Identifiers

DOI

10.12693/APhysPolA.127.A-118