Berlin 2024 – wissenschaftliches Programm
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 24: Financial Markets and Risk Management
SOE 24.3: Vortrag
Freitag, 22. März 2024, 10:30–10:45, MA 001
Multivariate distributions of correlated returns in nonstationary stock markets — Efstratios Manolakis, •Anton J. Heckens, and Thomas Guhr — Universität Duisburg-Essen, Lotharstr. 1, 47048 Duisburg
Risk assessment for rare events is very important for understanding systemic stability. Since financial markets are highly correlated, it is essential to study multivariate distributions of stocks, i.e. the joint probability density functions. To the best of our knowledge, we are the first to empirically study multivariate distributions for a large number of correlated stocks [1]. To this end, we compare empirical distributions with the results of a random matrix model [2]. First, our model separates different time scales: smaller time intervals, so-called epochs, that are assumed to be stationary and large scales on which the nonstationarity of the market is relevant and strong. Second, our model treats nonstationary fluctuations of measured correlation matrices by averaging over random matrices.
[1] Efstratios Manolakis, Anton J. Heckens and Thomas Guhr, Analysis of Aggregated Return Distributions for Stock Markets. Available at SSRN: https://ssrn.com/abstract=4462276
[2] Thomas Guhr and Andreas Schell 2021 J. Phys. A: Math. Theor. 54 125002
Keywords: Stock Markets; Correlations; Nonstationarity; Multivariate Return Distributions; Random Matrix Model