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• W2943563408 abstract "Value-at-Risk (VaR) is one of the best known and most heavily used measures of financial risk. In this paper, we introduce a non-iterative semiparametric model for VaR estimation called the single index quantile regression time series (SIQRTS) model. To test its performance, we give an application to four major US market indices: the S&P 500 Index, the Russell 2000 Index, the Dow Jones Industrial Average, and the NASDAQ Composite Index. Our results suggest that this method has a good finite sample performance and often outperforms a number of commonly used methods." @default.
• W2943563408 created "2019-05-09" @default.
• W2943563408 creator A5049418599 @default.
• W2943563408 creator A5062646928 @default.
• W2943563408 date "2019-03-24" @default.
• W2943563408 modified "2023-10-13" @default.
• W2943563408 title "Estimation of value-at-risk using single index quantile regression" @default.
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• W2943563408 doi "https://doi.org/10.1080/02664763.2019.1597028" @default.
• W2943563408 hasPublicationYear "2019" @default.
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