|
Archive@NYU >
Stern School of Business >
Finance Working Papers >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/26356
|
| Title: | HIGH DIMENSION DYNAMIC CORRELATIONS |
| Authors: | Robert, Engle |
| Issue Date: | 23-Aug-2007 |
| Series/Report no.: | FIN-07-045 |
| Abstract: | This paper develops time series methods for forecasting correlations in
high dimensional problems. The Dynamic Conditional Correlation model is
given a new convenient estimation approach called the MacGyver method.
It is compared with the FACTOR ARCH model and a new model called the
FACTOR DOUBLE ARCH model. Finally the latter model is blended with the
DCC to give a FACTOR DCC model. This family of models is estimated with
daily returns from 18 US large cap stocks. Economic loss functions
designed to form optimal portfolios and optimal hedges are used to
compare the performance of the methods. The best approach invariably is
the FACTOR DCC and the next best is the FACTOR DOUBLE ARCH. |
| URI: | http://hdl.handle.net/2451/26356 |
| Appears in Collections: | Finance Working Papers
|
All items in Faculty Digital Archive are protected by copyright, with all rights reserved.
|
