GARCH multivariati e approccio di Black.Litterman nell'asset allocation tattica: un'analisi empirica
Author
Abstract
Suggested Citation
Download full text from publisher
More about this item
Keywords
GARCH multivariati; approccio Black-Litterman; asset allocation tattica;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:anc:wpaper:185. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Maurizio Mariotti (email available below). General contact details of provider: https://edirc.repec.org/data/deancit.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.