Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/21697
Title: Investment Portfolio Optimization with Garch Models
Authors: Doku-Amponsah, K.
Mettle, F. O.
Siaw, R. O.
University of Ghana, College of Basic and Applied Sciences, School of Physical and Mathematical Sciences, Department of Statistics
Keywords: Optimality
ARMA-GARCH model
ARMA- DCC GARCH model
Autoregressive Moving Average (ARMA)
Univariate
Issue Date: Jun-2014
Publisher: University of Ghana
Abstract: Since the introduction of the Markowitz mean-variance optimization model, several extensions have been made to improve optimality. This study examines the application of two models - the ARMA-GARCH model and the ARMA- DCC GARCH model - for the Mean-VaR optimization of funds managed by HFC Investment Limited. Weekly prices of the above mentioned funds from 2009 to 2012 were examined. The funds analysed were the Equity Trust Fund, the Future Plan Fund and the Unit Trust Fund. The returns of the funds are modelled with the Autoregressive Moving Average (ARMA) whiles volatility was modelled with the univariate Generalised Autoregressive Conditional Heteroskedasticity (GARCH) as well as the multivariate Dynamic Conditional Correlation GARCH (DCC GARCH). This was based on the assumption of non-constant mean and volatility of fund returns. In this study the risk of a portfolio is measured using the value-at-risk. A single constrained Mean-VaR optimization problem was obtained based on the assumption that investors’ preference is solely based on risk and return. The optimization process was performed using the Lagrange Multiplier approach and the solution was obtained by the Kuhn-Tucker theorems. Conclusions which were drawn based on the results pointed to the fact that a more efficient portfolio is obtained when the value-at-risk (VaR) is modelled with a multivariate GARCH.
Description: Thesis (MPhil.) - University of Ghana, 2014
URI: http://hdl.handle.net/123456789/21697
Appears in Collections:Department of Statistics

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