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Modeling pricing strategies using game theory and support vector machines

Modeling pricing strategies using game theory and support vector machines
Modeling pricing strategies using game theory and support vector machines
Data Mining is a widely used discipline with methods that are heavily supported by statistical theory. Game theory, instead, develops models with solid economical foundations but with low applicability in companies so far. This work attempts to unify both approaches, presenting a model of price competition in the credit industry. Based on game theory and sustained by the robustness of Support Vector Machines to structurally estimate the model, it takes advantage from each approach to provide strong results and useful information. The model consists of a market-level game that determines the marginal cost, demand, and efficiency of the competitors. Demand is estimated using Support Vector Machines, allowing the inclusion of multiple variables and empowering standard economical estimation through the aggregation of client-level models. The model is being applied by one competitor, which created new business opportunities, such as the strategic chance to aggressively cut prices given the acquired market knowledge
0302-9743
323-337
Bravo, Cristian
b22c4145-644e-40ee-85d8-431c59c3c71b
Figueroa, Nicolás
c07f74f0-c271-41ee-bb8e-c3cf9658182e
Weber, Richard
da9918d6-bc84-4c98-8ffe-2aaf7b58cf1b
Bravo, Cristian
b22c4145-644e-40ee-85d8-431c59c3c71b
Figueroa, Nicolás
c07f74f0-c271-41ee-bb8e-c3cf9658182e
Weber, Richard
da9918d6-bc84-4c98-8ffe-2aaf7b58cf1b

Bravo, Cristian, Figueroa, Nicolás and Weber, Richard (2010) Modeling pricing strategies using game theory and support vector machines. Lecture Notes in Computer Science, 6171, 323-337. (doi:10.1007/978-3-642-14400-4_25).

Record type: Article

Abstract

Data Mining is a widely used discipline with methods that are heavily supported by statistical theory. Game theory, instead, develops models with solid economical foundations but with low applicability in companies so far. This work attempts to unify both approaches, presenting a model of price competition in the credit industry. Based on game theory and sustained by the robustness of Support Vector Machines to structurally estimate the model, it takes advantage from each approach to provide strong results and useful information. The model consists of a market-level game that determines the marginal cost, demand, and efficiency of the competitors. Demand is estimated using Support Vector Machines, allowing the inclusion of multiple variables and empowering standard economical estimation through the aggregation of client-level models. The model is being applied by one competitor, which created new business opportunities, such as the strategic chance to aggressively cut prices given the acquired market knowledge

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Published date: 2010
Organisations: Southampton Business School

Identifiers

Local EPrints ID: 396683
URI: https://eprints.soton.ac.uk/id/eprint/396683
ISSN: 0302-9743
PURE UUID: 008f60dc-5ac4-4380-a313-e6f6b6dfca83
ORCID for Cristian Bravo: ORCID iD orcid.org/0000-0003-1579-1565

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Date deposited: 10 Jun 2016 10:39
Last modified: 06 Jun 2018 12:35

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Contributors

Author: Cristian Bravo ORCID iD
Author: Nicolás Figueroa
Author: Richard Weber

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