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arXiv · 1502.05090

Real time clustering of time series using triangular potentials

Aldo Pacchiano·Oliver Williams
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Abstract

Motivated by the problem of computing investment portfolio weightings we investigate various methods of clustering as alternatives to traditional mean-variance approaches. Such methods can have significant benefits from a practical point of view since they remove the need to invert a sample covariance matrix, which can suffer from estimation error and will almost certainly be non-stationary. The general idea is to find groups of assets which share similar return characteristics over time and treat each group as a single composite asset. We then apply inverse volatility weightings to these new composite assets. In the course of our investigation we devise a method of clustering based on triangular potentials and we present associated theoretical results as well as various examples based on synthetic data.

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Aldo Pacchiano, Oliver Williams. 2015-02-18. Real time clustering of time series using triangular potentials. https://arxiv.org/abs/1502.05090

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