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

Version 1.0.0.0 (4.27 KB) by Mel
Uses RMT to create a filtered correlation matrix from a set of financial time series price data
559 Downloads
Updated 10 Jan 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

Cite As

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. Retrieved .

MATLAB Release Compatibility
Created with R2013a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0.0