Volatility by means of Functional Data

• Autores: Kenedy Pedro Alva Chavez, Juan José Romo Urroz , Esther Ruiz Ortega
• Localización: XXXI Congreso Nacional de Estadística e Investigación Operativa ; V Jornadas de Estadística Pública: Murcia, 10-13 de febrero de 2009 : Libro de Actas, 2009, ISBN 978-84-691-8159-1
• Idioma: inglés
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• Resumen

  • We propose a method to predict the intra-day volatility for the whole day given past volatilities. We consider model di usion for the daily stock process to extract the volatility, means by functional principal components (FPC). The FPC scores are calculated by numerical integration and cross validation. The model to predict is an extension of the stochastic volatility model for one dimensional time series. This is a functional rst order autoregressive model for the volatility.