This document is an ongoing review on the state of the art of clustering financial time series and the study of correlation and other interaction networks. This preliminary document is intended for researchers in this field so that they can feedback to allow amendments, corrections and addition of new material unknown to the authors of this review. The aim of the document is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the quantitative researcher to play with this alternative modeling of the financial time series , and the decision maker to leverage the insightsobtained from these methods. We hope that this document will form a basis for implementation of an open toolbox of standard tools to study correlations, hierarchies, networks and clustering in financial markets.
We review the state of the art of clustering financial time series and the study of their correlations alongside other interaction networks. The aim of this review is to gather in one place the relevant material from different fields, e.g. machine learning, information geometry, econophysics, statistical physics, econometrics, behavioral finance. We hope it will help researchers to use more effectively this alternative modeling of the financial time series . Decision makers and quantitative researchers may also be able to leverage its insights. Finally, we also hope that this review will form the basis of an open toolbox to study correlations, hierarchies, networks and clustering in financial markets.
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This preliminary document is intended for researchers in this field so that they can feedback to allow amendments, corrections and addition of new material unknown to the authors of this review.
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from different fields, e.g. machine learning, information geometry, econophysics, statistical physics, econometrics, behavioral finance. We hope it will help researchers to use more effectively
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