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On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?

机译:关于设置日前股票交易风险限额:市场关闭或打开时的VaR预测?

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Abstract This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR) forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et al. that constructs the forecast at the market close instead and, accordingly, it models separately the daytime and overnight return processes and their covariance. For a small cap portfolio, the bivariate VaR approach affords superior predictive ability than the ex post overnight VaR approach whereas for a large cap portfolio the results are reversed. The contrast indicates that price discovery at the market open is less efficient for small capitalization, thinly traded stocks. View Full-Text
机译:摘要本文研究了提前一天股权风险价值(VaR)预测的事后隔夜回报的信息内容。为此,我们部署了单变量VaR建模方法,该方法构建了市场开放时的预测,并相应地利用了可用的隔夜开放价格变化。基准是Ahoniemi等人提出的双变量VaR建模方法。而是在市场收盘时构造预测,因此,它分别对日间和隔夜收益过程及其协方差建模。对于小型股票投资组合,二元VaR方法提供的预测能力要优于隔夜VaR方法,而对于大型股票投资组合,结果却相反。对比表明,对于小额资本,稀少交易的股票,开盘价发现的效率较低。查看全文

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