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On the use of Nearest Neighbors in finance

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  • Dominique Guégan
  • Nicolas Huck

Abstract

Nearest Neighbors are a non linear non parametric forecasting method often used in finance. This work focus on the way Nearest Neighbors are applied in the existing literature. We observe that the selection?s methods of the embedding dimension and of the number of neighbors via phase space reconstruction and in sample predictions lead to distort the idea underlying the Nearest Neighbors approach. Propositions for a better usage of Nearest Neighbors are given.

Suggested Citation

  • Dominique Guégan & Nicolas Huck, 2005. "On the use of Nearest Neighbors in finance," Finance, Presses universitaires de Grenoble, vol. 26(2), pages 67-86.
    • Handle: RePEc:cai:finpug:fina_262_0067
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    Cited by:

    1. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Documents de travail du Centre d'Economie de la Sorbonne 10065, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
    3. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00511979, HAL.
    4. Sermpinis, Georgios & Stasinakis, Charalampos & Theofilatos, Konstantinos & Karathanasopoulos, Andreas, 2015. "Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms—Support vector regression forecast combinations," European Journal of Operational Research, Elsevier, vol. 247(3), pages 831-846.
    5. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," PSE-Ecole d'économie de Paris (Postprint) halshs-00511979, HAL.
    6. Dominique Guegan & Patrick Rakotomarolahy, 2010. "Alternative methods for forecasting GDP," Post-Print halshs-00505165, HAL.
    7. Sermpinis, Georgios & Stasinakis, Charalampos & Rosillo, Rafael & de la Fuente, David, 2017. "European Exchange Trading Funds Trading with Locally Weighted Support Vector Regression," European Journal of Operational Research, Elsevier, vol. 258(1), pages 372-384.
    8. Dominique Guegan & Patrick Rakotomarolahy, 2009. "The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting," Post-Print halshs-00423871, HAL.

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