Topological Data Analysis Ball Mapper for Finance

Pawel Dlotko; Wanling  Qiu; Simon Rudkin

Topological Data Analysis Ball Mapper for Finance

Pawel Dlotko, Wanling Qiu, Simon Rudkin

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Research output: Contribution to conference › Paper

Abstract

Finance is heavily influenced by data-driven decision-making. Meanwhile, our ability to comprehend the full informational content of data sets remains impeded by the tools we apply in analysis, especially where the data is high-dimensional. Presenting the Topological Data Analysis Ball Mapper algorithm this paper illuminates a new means of seeing the detail in data from data shape. With comparisons to existing approaches and illustrative examples, the value of the new tool is shown. Directions for employing Ball Mapper in practice are given and the benefits are reviewed.

Original language	English
Publication status	Published - 8 Jun 2022

Keywords

Topological data analysis
Finance

Access to Document

https://arxiv.org/abs/2206.03622

Cite this

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title = "Topological Data Analysis Ball Mapper for Finance",

abstract = "Finance is heavily influenced by data-driven decision-making. Meanwhile, our ability to comprehend the full informational content of data sets remains impeded by the tools we apply in analysis, especially where the data is high-dimensional. Presenting the Topological Data Analysis Ball Mapper algorithm this paper illuminates a new means of seeing the detail in data from data shape. With comparisons to existing approaches and illustrative examples, the value of the new tool is shown. Directions for employing Ball Mapper in practice are given and the benefits are reviewed.",

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T1 - Topological Data Analysis Ball Mapper for Finance

AU - Dlotko, Pawel

AU - Qiu, Wanling

AU - Rudkin, Simon

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N2 - Finance is heavily influenced by data-driven decision-making. Meanwhile, our ability to comprehend the full informational content of data sets remains impeded by the tools we apply in analysis, especially where the data is high-dimensional. Presenting the Topological Data Analysis Ball Mapper algorithm this paper illuminates a new means of seeing the detail in data from data shape. With comparisons to existing approaches and illustrative examples, the value of the new tool is shown. Directions for employing Ball Mapper in practice are given and the benefits are reviewed.

AB - Finance is heavily influenced by data-driven decision-making. Meanwhile, our ability to comprehend the full informational content of data sets remains impeded by the tools we apply in analysis, especially where the data is high-dimensional. Presenting the Topological Data Analysis Ball Mapper algorithm this paper illuminates a new means of seeing the detail in data from data shape. With comparisons to existing approaches and illustrative examples, the value of the new tool is shown. Directions for employing Ball Mapper in practice are given and the benefits are reviewed.

KW - Topological data analysis

KW - Finance

M3 - Paper

ER -

Topological Data Analysis Ball Mapper for Finance

Abstract

Keywords

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