Random Matrix Theory (RMT) Filtering of Financial Time Series for Community Detection

Versión 1.0.0.0 (4,27 KB) por Mel
Uses RMT to create a filtered correlation matrix from a set of financial time series price data
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Actualizado 10 ene 2015

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This function eigendecomposes a correlation matrix of financial time series and filters out the Market Mode Component and Noise Component, leaving only the components of the correlation matrix that correspond to mesoscopic structure in the set of original time series.
The function is intended to be used in conjunction with a community detection algorithm (such as the Louvain method) to allow for community detecion on time series based networks

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Mel (2024). Random Matrix Theory (RMT) Filtering of Financial Time Series for Community Detection (https://www.mathworks.com/matlabcentral/fileexchange/49011-random-matrix-theory-rmt-filtering-of-financial-time-series-for-community-detection), MATLAB Central File Exchange. Recuperado .

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Se creó con R2013a
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Versión Publicado Notas de la versión
1.0.0.0