Volatility by means of Functional Data
- Alva Chavez, Kenedy Pedro
- Romo Urroz, Juan José
- Ruiz Ortega, Esther
Argitaletxea: Universidad de Murcia. Departamento de Estadística e Investigación Operativa
ISBN: 978-84-691-8159-1
Argitalpen urtea: 2009
Biltzarra: Congreso Nacional de Estadística e Investigación Operativa (31. 2009. Murcia)
Mota: Biltzar ekarpena
Laburpena
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.