期刊
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
卷 22, 期 4, 页码 367-381出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/073500104000000370
关键词
nonlinear regression quantile; risk management; specification testing
Value at risk (VaR) is the standard measure of market risk used by financial institutions. Interpreting the VaR as the quantile of future portfolio values conditional on current information, the conditional autoregressive value at risk (CAViaR) model specifies the evolution of the quantile over time using an autoregressive process and estimates the parameters with regression quantiles. Utilizing the criterion that each period the probability of exceeding the VaR must be independent of all the past information, we introduce a new test of model adequacy, the dynamic quantile test. Applications to real data provide empirical support to this methodology.
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