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A Study on Portfolio Value-at-Risk
Year Of Publication: 2004
Month Of Publication: May
Pages: 13
Download Count: 42
View Count: 1832
Comment Num: 0
Language: English
Who Can Read: Free
Date: 4-4-2010
Publisher: Administrator
In this paper, we propose an integrated method to compute PVaR from a weaker set of assumptions that may be more robust and representative of the returns distributions encountered in practice. The proposed approach combines the generalized Pareto (GP) distribution function and empirical density function (EDF) to model the return
distributions for each asset in the portfolio. We then use a copula function to form the joint distribution of the correlated returns for the set of assets in the portfolio, and we use Monte Carlo sampling methods to form PVaR estimates. We use backtesting and stress testing to compare the validity and performance of the proposed method relative to other popular methods, including the variance-covariance approach, Monte Carlo simulation, historical simulation, and the Jorion approach (Jorion 2001). We also derive some fundamental properties and the associated implications of PVaR, including the selection of the appropriate confidence level, the evaluation of P
Liu, Wei-Han Sign in to follow this author
Miller, Douglas Sign in to follow this author
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