RT Journal Article
T1 Early prediction of Ibex 35 movements
A1 Miranda García, Isabel Marta
A1 Segovia Vargas, María Jesús
A1 Mori, Usue
A1 Lozano, José
AB In this paper, we examine the early predictability of the market's directional movement using intraday high‐frequency data (695,764 observations) from an stock index (Ibex 35 Index) to provide, either private or institutional investors, an early warning system based on an “early indicator” of the financial market fluctuations with an optimal combination of the two more relevant variables for this strategy, accuracy, and earliness. A novel supervised machine learning early classification technique (Artificial Intelligence) has been applied, for the first time, to the high‐frequency time series of both price and certain technical indicators. The results obtained allow us to assert that the intraday movement of the Ibex 35 can be predicted with acceptable levels of accuracy 24 min after the start of the session and to establish certain informative intraday hourly patterns. Consequently, different indicators of precision and earliness in the session are generated, obtaining that, after a certain point in the session, no gains in precision are generated.
PB Wiley
SN 0277-6693
YR 2022
FD 2022
LK https://hdl.handle.net/20.500.14352/91947
UL https://hdl.handle.net/20.500.14352/91947
LA eng
NO Miranda García, I. Marta, María‐Jesús Segovia‐Vargas, Usue Mori, y José A. Lozano. «Early Prediction of Ibex 35 Movements». Journal of Forecasting 42, n.o 5 (agosto de 2023): 1150-66. https://doi.org/10.1002/for.2933.
NO Universidad Pablo de Olavide
NO Eusko Jaurlaritza
NO Ministerio de Ciencia, Innovación y Universidades (España)
DS Docta Complutense
RD 13 abr 2025