In this paper, several classification methods are applied for modeling financial time series with the aim to predict the trend of successive prices. By using a suitable embedding technique, a pattern of past prices is assigned a class if the variation of the next price is over, under or stable with respect to a given threshold. Furthermore, a sensitivity analysis is performed in order to verify if the value of such a threshold influences the prediction accuracy. The experimental results on the case study of WTI crude oil commodity show a good classification accuracy of the next (predicted) trend, and the best performance is achieved by the K-Nearest Neighbors classification strategy.

A classification approach to modeling financial time series / Altilio, Rosa; Andreasi, Giorgio; Panella, Massimo. - (2019), pp. 97-106. - SMART INNOVATION, SYSTEMS AND TECHNOLOGIES. [10.1007/978-3-319-95098-3_9].

A classification approach to modeling financial time series

Altilio, Rosa;Andreasi, Giorgio;Panella, Massimo
2019

Abstract

In this paper, several classification methods are applied for modeling financial time series with the aim to predict the trend of successive prices. By using a suitable embedding technique, a pattern of past prices is assigned a class if the variation of the next price is over, under or stable with respect to a given threshold. Furthermore, a sensitivity analysis is performed in order to verify if the value of such a threshold influences the prediction accuracy. The experimental results on the case study of WTI crude oil commodity show a good classification accuracy of the next (predicted) trend, and the best performance is achieved by the K-Nearest Neighbors classification strategy.
2019
Smart Innovation, Systems and Technologies
978-3-319-95097-6
978-3-319-95098-3
Costs; crude oil; financial data processing; nearest neighbor search; Decision Sciences (all); Computer Science (all)
02 Pubblicazione su volume::02a Capitolo o Articolo
A classification approach to modeling financial time series / Altilio, Rosa; Andreasi, Giorgio; Panella, Massimo. - (2019), pp. 97-106. - SMART INNOVATION, SYSTEMS AND TECHNOLOGIES. [10.1007/978-3-319-95098-3_9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1209026
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