In this paper the factorial structure of some asset returns quoted at the Milan stock exchange is analyzed in order to detect the presence of a dynamic component. The maximum likelihood estimates of the dynamic model, for which a space-state representation and the Kalman filter were used, are compared with the estimates of the static model via the information criteria. There is no evidence of dynamic factors underlying the analyzed samples of asset returns, while one static factor seems to be relevant. © 1994 Societa Italiana di Statistica.
Costa M. (1994). Dynamic component detection in a multifactor model for stock returns. JOURNAL OF THE ITALIAN STATISTICAL SOCIETY, 3(1), 25-36 [10.1007/BF02589038].
Dynamic component detection in a multifactor model for stock returns
Costa M.
1994
Abstract
In this paper the factorial structure of some asset returns quoted at the Milan stock exchange is analyzed in order to detect the presence of a dynamic component. The maximum likelihood estimates of the dynamic model, for which a space-state representation and the Kalman filter were used, are compared with the estimates of the static model via the information criteria. There is no evidence of dynamic factors underlying the analyzed samples of asset returns, while one static factor seems to be relevant. © 1994 Societa Italiana di Statistica.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
