Volatility by means of Functional Data
- Alva Chavez, Kenedy Pedro
- Romo Urroz, Juan José
- Ruiz Ortega, Esther
Éditorial: Universidad de Murcia. Departamento de Estadística e Investigación Operativa
ISBN: 978-84-691-8159-1
Année de publication: 2009
Congreso: Congreso Nacional de Estadística e Investigación Operativa (31. 2009. Murcia)
Type: Communication dans un congrès
Résumé
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.