Testing The Black- Litterman Model: Sensitivity of Weight Vector to the Variance of Views
(2011) NEKM07 20111Department of Economics
- Abstract
- The paper investigates sensitivity of the optimal portfolio obtained from the Black Litterman model to the specification of the inputs. Specifically estimation methods of the variances of the views are employed and the results are analysed. For this purpose the MSCI indices of 14 European countries are experienced. The result shows very weak response of the weight vector to the estimation method of the variance matrix of views. Further research suggests the sensitivity analysis concentrated on the prior specification of the equilibrium returns as the beginning point for the Black Litterman model.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/2155310
- author
- Prysyazhnyuk, Yuliya LU and Ojagverdiyeva, Saida LU
- supervisor
- organization
- course
- NEKM07 20111
- year
- 2011
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Black- Litterman model, views, portfolio optimization, variance-covariance matrix
- language
- English
- id
- 2155310
- date added to LUP
- 2011-09-27 09:22:51
- date last changed
- 2011-09-27 09:22:51
@misc{2155310, abstract = {{The paper investigates sensitivity of the optimal portfolio obtained from the Black Litterman model to the specification of the inputs. Specifically estimation methods of the variances of the views are employed and the results are analysed. For this purpose the MSCI indices of 14 European countries are experienced. The result shows very weak response of the weight vector to the estimation method of the variance matrix of views. Further research suggests the sensitivity analysis concentrated on the prior specification of the equilibrium returns as the beginning point for the Black Litterman model.}}, author = {{Prysyazhnyuk, Yuliya and Ojagverdiyeva, Saida}}, language = {{eng}}, note = {{Student Paper}}, title = {{Testing The Black- Litterman Model: Sensitivity of Weight Vector to the Variance of Views}}, year = {{2011}}, }