Dynamic Portfolio Optimization Using Generalized Dynamic Conditional Heteroskedastic Factor Models
نویسندگان
چکیده
منابع مشابه
A generalized Dynamic Conditional Correlation model for portfolio risk evaluation
We propose a generalization of the Dynamic Conditional Correlation multivariate GARCH model of Engle (2002) and of the Asymmetric Dynamic Conditional Correlation model of Cappiello et al. (2006). The model we propose introduces a block structure in parameter matrices that allows for interdependence with a reduced number of parameters. Our model nests the Flexible Dynamic Conditional Correlation...
متن کاملGeneralized spatial dynamic factor models
This paper introduces a new class of spatio-temporal models for measurements belonging to the exponential family of distributions. In this new class, the spatial and temporal components are conditionally independently modeled via a latent factor analysis structure for the (canonical) transformation of the measurements mean function. The factor loadings matrix is responsible for modeling spatial...
متن کاملBayesian Dynamic Factor Models and Portfolio Allocation
We discuss the development of dynamic factor models for multivariate financial time series, and the incorporation of stochastic volatility components for latent factor processes. Bayesian inference and computation is developed and explored in a study of the dynamic factor structure of daily spot exchange rates for a selection of international currencies. The models are direct generalizations of...
متن کاملDynamic Portfolio Optimization Using Evolution Strategy
● The classic Markowitz model that optimizes for the Sharpe ratio has proven to be suboptimal. ○ Summary is used directly as prediction. ○ Variance is not a good risk measurement since it penalizes positive shocks and says little about tail risks ● Other risk measurements such as Value-at-Risk and Expected Shortfall introduce non-linear, non-convex risk constraints and render the mean-variance ...
متن کاملVariational Bayesian Autoregressive Conditional Heteroskedastic Models
A variational Bayesian autoregressive conditional heteroskedastic (VB-ARCH) model is presented. The ARCH class of models is one of the most popular for economic time series modeling. It assumes that the variance of the time series is an autoregressive process. The variational Bayesian approach results in an approximation to the full posterior distribution over ARCH model parameters, and provide...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: JOURNAL OF THE JAPAN STATISTICAL SOCIETY
سال: 2010
ISSN: 1348-6365,1882-2754
DOI: 10.14490/jjss.40.145