scholarly journals Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models

2015 ◽  
Author(s):  
Antonello D'Agostino ◽  
Domenico Giannone ◽  
Michele Lenza ◽  
Michele Modugno
Keyword(s):  
Business Cycles ◽  
Bayesian Approach ◽  
Factor Models ◽  
Heterogeneous Factor

scholarly journals Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models

2015 ◽  
Vol 2015 (066) ◽  
pp. 1-25
Author(s):  
Antonello D’Agostino ◽  
◽  
Domenico Giannone ◽  
Michele Lenza ◽  
Michele Modugno
Keyword(s):  
Business Cycles ◽  
Bayesian Approach ◽  
Factor Models ◽  
Heterogeneous Factor

scholarly journals Nowcasting Business Cycles: A Bayesian Approach to Dynamic Heterogeneous Factor Models

2015 ◽  
Author(s):  
Antonello D'Agostino ◽  
Domenico Giannone ◽  
Michele Lenza ◽  
Michele Modugno
Keyword(s):  
Business Cycles ◽  
Bayesian Approach ◽  
Factor Models ◽  
Heterogeneous Factor

Measuring Chinese business cycles with dynamic factor models

2009 ◽  
Vol 20 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Jin-ming Wang ◽  
Tie-mei Gao ◽  
Robert McNown
Keyword(s):  
Business Cycles ◽  
Factor Models ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Chinese Business

Heterogeneous factor analysis models: A bayesian approach

Psychometrika ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 49-77 ◽  
Author(s):  
Asim Ansari ◽  
Kamel Jedidi ◽  
Laurette Dube
Keyword(s):  
Factor Analysis ◽  
Bayesian Approach ◽  
Analysis Models ◽  
Heterogeneous Factor

scholarly journals A Bayesian Approach for Large Asset Allocation

2020 ◽  
Vol 10 (1) ◽  
pp. 58
Author(s):  
Mihnea S. Andrei ◽  
John S. J. Hsu
Keyword(s):  
Sensitivity Analysis ◽  
Bayesian Approach ◽  
Asset Allocation ◽  
Historical Data ◽  
Factor Models ◽  
Memory Allocation ◽  
Multivariate Normal ◽  
Confidence Levels ◽  
Conduct Sensitivity Analysis ◽  
Bayesian Factor

The Black-Litterman model combines investor’s personal views with historical data and gives optimal portfolio weights. In (Andrei & Hsu, 2020), they reviewed the original Black-Litterman model and modified it in order to fit it into a Bayesian framework, when a certain number of assets is considered. They used the idea by (Leonard & Hsu, 1992) for a multivariate normal prior on the logarithm of the covariance matrix. When implemented and applied to a large number of assets such as all the S&P500 companies, they ran into memory allocation and running time issues. In this paper, we reduce the dimensions by considering Bayesian factor models, which solve the asset allocation problems for a large number of assets. In addition, we will conduct sensitivity analysis for the confidence levels that the investors have to input.

LONG-RANGE DEPENDENT COMMON FACTOR MODELS: A BAYESIAN APPROACH

2001 ◽  
Vol 30 (6) ◽  
pp. 1047-1061 ◽  
Author(s):  
Nan-Jung Hsu ◽  
Bonnie K. Ray ◽  
F. Jay Breidt
Keyword(s):  
Long Range ◽  
Bayesian Approach ◽  
Common Factor ◽  
Factor Models ◽  
Common Factor Models
Sign in / Sign up

Export Citation Format

Share Document