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Showing 1 to 2 of 2 for “"Conditional Autoregressive Value at Risk (CAViaR)"”.

  1. Applications of quantile regression to estimation and detection of some tail characteristics

    The statistical inference based on the ordinary least squares regression is sub-optimal when the distributions are skewed or when the quantity of interest is the upper or lower tail of the distributions. For example, the changes in Total Sharp Scores (TSS), the primary measurements of the treatment …

    uiuc Repository record for Applications of quantile regression to estimation and detection of some tail characteristics (opens in a new tab)

  2. Robust Inference with Quantile Regression in Stochastic Volatility Models with application to Value at Risk calculation

    Stochastic Volatility (SV) models play an integral role in modeling time varying volatility, with widespread application in finance. Due to the absence of a closed form likelihood function, estimation is a challenging problem. In the presence of outliers, and the high kurtosis prevalent in …

    ncsu Repository record for Robust Inference with Quantile Regression in Stochastic Volatility Models with application to Value at Risk calculation (opens in a new tab)