Independent Factor Autoregressive Conditional Density Model
AbstractIn this paper, we propose a novel Independent Factor Autoregressive Conditional Density (IFACD) model able to generate time-varying higher moments using an independent factor setup. Our proposed framework incorporates dynamic estimation of higher comovements and feasible portfolio representation within a non elliptical multivariate distribution. We report an empirical application, using returns data from 14 MSCI equity index iShares for the period 1996 to 2011, and we show that the IFACD model provides superior VaR forecasts and portfolio allocations with respect to the CHICAGO and DCC models.
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Bibliographic InfoPaper provided by University of Pavia, Department of Economics and Management in its series DEM Working Papers Series with number 021.
Length: 28 pages
Date of creation: Nov 2012
Date of revision:
Independent Factor Model; GO-GARCH; Independent Component Analysis; Timevarying Co-moments;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-24 (All new papers)
- NEP-ECM-2012-11-24 (Econometrics)
- NEP-ETS-2012-11-24 (Econometric Time Series)
- NEP-FOR-2012-11-24 (Forecasting)
- NEP-RMG-2012-11-24 (Risk Management)
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