2026-06-27T22:42:13Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1010562025-08-27T17:47:08Zcom_20.500.14352_14col_20.500.14352_15

Alva Chávez, Kenedy Pedro Romo Urroz, Juan José Ruiz Ortega, Esther 2024-02-09T19:04:49Z 2024-02-09T19:04:49Z 2009 2387-0303 https://hdl.handle.net/20.500.14352/101056 http://hdl.handle.net/10016/3879 We propose recent functional data analysis techniques to study the intra-daily volatility. In particular, the volatility extraction is based on functional principal components and the volatility prediction on functional AR(1) models. The estimation of the corresponding parameters is carried out using the functional equivalent to OLS. We apply these ideas to the empirical analysis of the IBEX35 returns observed each _ve minutes. We also analyze the performance of the proposed functional AR(1) model to predict the volatility along a given day given the information in previous days for the intra-daily volatility for the firms in the IBEX35 Madrid stocks index. eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 International Modelling intra-daily volatility by functional data analysis: an empirical application to the spanish stock market working paper