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The first and third authors acknowledge the support of Grant ECO2015-66593-P of MINECO/FEDER/UE.

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De Blas, CsAuthorGarcia, AeCorresponding Author

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Forecasting financial short time series

Publicated to:Electronic Journal Of Applied Statistical Analysis. 11 (1): 42-57 - 2018-04-01 11(1), DOI: 10.1285/i20705948v11n1p42

Authors: Alonso, Andres M; de Blas, Clara Simon; Garcia, Ana Elizabeth; Ciprian, Mauricio; Correas, Teresa; Maestre, Roberto; Peinado, Luis

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Abstract

In the present paper, we study the application of time series forecasting methods to massive datasets of financial short time series. In our example, the time series arise from analyzing monthly expenses and incomings personal financial records. Unlike from traditional time series forecasting applications, we work with series of very short depth (as short as 24 data points), which does not allow us to use classical exponential smoothing methods. However, this shortcoming is compensated by the size of our dataset: millions of time series. This allows us to tackle the problem of time series prediction from a pattern recognition perspective. Specifically, we propose a method for short time series prediction based on time series clustering and distance-based regression. We experimentally show that this strategy leads to improved accuracy compared to exponential smoothing methods. In addition, we describe the underlying big data platform developed to carry out the efficient forecasting, since we perform millions of item comparisons in near real-time.

Keywords

Big dataClusteringConditional meanFinancial time seriesForecastingHolt winterWeighted moving averages

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Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Electronic Journal Of Applied Statistical Analysis due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2018, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Modeling and Simulation.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-05-29:

  • Scopus: 1

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-29:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 4 (PlumX).

Leadership analysis of institutional authors

the author responsible for correspondence tasks has been García Sipols, Ana Elizabeth.