Portfolio Selection via Topological Data Analysis

• URL: http://arxiv.org/abs/2308.07944v1
• Date: Tue, 15 Aug 2023 09:36:43 GMT
• Title: Portfolio Selection via Topological Data Analysis
• Authors: Petr Sokerin, Kristian Kuznetsov, Elizaveta Makhneva, Alexey Zaytsev
• Abstract summary: We present a two-stage method for constructing an investment portfolio of common stocks. The method involves the generation of time series representations followed by their subsequent clustering. Experimental results show that our proposed system outperforms other methods.
• Score: 2.3901301169141056
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Portfolio management is an essential part of investment decision-making. However, traditional methods often fail to deliver reasonable performance. This problem stems from the inability of these methods to account for the unique characteristics of multivariate time series data from stock markets. We present a two-stage method for constructing an investment portfolio of common stocks. The method involves the generation of time series representations followed by their subsequent clustering. Our approach utilizes features based on Topological Data Analysis (TDA) for the generation of representations, allowing us to elucidate the topological structure within the data. Experimental results show that our proposed system outperforms other methods. This superior performance is consistent over different time frames, suggesting the viability of TDA as a powerful tool for portfolio selection.

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