Equity Portfolio Optimization Using Mean-CVaR Method Considering Symmetric and Asymmetric Autoregressive Conditional Heteroscedasticity
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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Objective

Risk management is one of the most important areas of study in finance, and its vital role in the field has attracted the attention of managers and investors in in various sectors of the industry. Especially in recent years, with the onset of financial crises, the importance and necessity of accurate studies in this area has doubled. The main purpose of this study is to provide a model for a more accurate measurement of equity portfolio risk.

Methods

To conduct this research, adjusted closing prices of a sample of thirty listed companies have been used. CVaR is the main model and four other models are formulated using different methods of variance modeling. The first method calculates conditional value at risk using constant variance and in the other three methods, variance is modeled on GARCH, E-GARCH and T-GARCH approaches.

Results

Ultimately, the results have been evaluated using appropriate statistical tests, namely paired t test and Wilcoxon signed rank test. The results obtained from both tests suggest that the method used to model variance has a significant effect on attaining a better optimal portfolio.

Conclusion

Considering results of the research, which approve the tested hypothesis, one can conclude, taking into account the heteroscedasticity in Iranian capital market, would result in a better optimized portfolio. Moreover, the results illustrated that the use of CVaR model, for risk measurement, rather than previously used traditional models, can be effective in improving the performance, in optimizing stock portfolios, significantly.

Language:
Persian
Published:
Financial Research, Volume:22 Issue: 58, 2020
Pages:
149 to 159
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