mirhossein mousavi; Hossein Raghfar; Mansooreh Mohseni
Volume 18, Issue 54 , April 2013, , Pages 119-152
Abstract
The traditional approaches for estimating VAR assume that the joint distribution is well-known and the most commonly used normality of the joint distribution of the assets return. In reality, the financial asset return distribution has fatter tails than normal distributions. On the other hand, the use ...
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The traditional approaches for estimating VAR assume that the joint distribution is well-known and the most commonly used normality of the joint distribution of the assets return. In reality, the financial asset return distribution has fatter tails than normal distributions. On the other hand, the use of linear correlation to model the dependence structure shows many disadvantages. Therefore, the problem raised from normality could lead to an inadequate VaR estimate. In order to overcome these problems, this paper resorts to the copula theory which allows the joint distribution of the portfolio to be free from any normality and linear correlation. Combining copula and the forecast function of the GARCH model, this paper proposes a new method, called conditional copula-GARCH, to compute the VaR of portfolios. Examined data in this study includes daily price of selected portfolio, composed of 17 equities for 1082 days in Tehran stock exchange. Presented model compared with traditional methods (including the historical simulation method & variance_covariance method). the results show that conditional copula-GARCH model captures the VaR more successfully at 95% confidence.
Zahra Nasrollahi; Mina Shahviri,
Volume 15, Issue 44 , October 2010, , Pages 199-230
Abstract
Management of Foreign exchange reserves is important for every country. This matter is also of particular interest for Iran as an Oil exporting developing country. This paper designs an optimal portfolio for that part of foreign exchange incomes which is used for investment. Using the data on foreign ...
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Management of Foreign exchange reserves is important for every country. This matter is also of particular interest for Iran as an Oil exporting developing country. This paper designs an optimal portfolio for that part of foreign exchange incomes which is used for investment. Using the data on foreign exchange daily returns, for the period 2000-2008, and applying univariate and multivariate Garch models, we estimate a model which maximizes expected returns subject to a Value-at-Risk constraint. The results are examined using Backtesting, and then the most acceptable model is suggested. The results that the multivariate GARCH model is the most efficient method for selecting the foreign exchange optimal portfolio in Iran.