论文标题
实现的拉普拉斯转换的大偏差原理
Large Deviation principles of Realized Laplace Transform of Volatility
论文作者
论文摘要
在高频数据的情况下，\ citet {tt2012a}提出了对挥发率的实现拉普拉斯变换的一致估计量，并且已经确定了相关的中央限制定理。在本文中，我们研究了经验实现的挥发性拉普拉斯转变（ERLTV）的渐近尾巴行为。我们为ERLTV建立了较大的偏差原理和中等偏差原理。大偏差原理的良好速率函数在整个真实空间中得到了很好的定义，这表明ERLTV的归一化对数尾巴概率有限制。此外，我们还得出了ERLTV的功能级较大和中等偏差原理。
Under scenario of high frequency data, consistent estimator of realized Laplace transform of volatility is proposed by \citet{TT2012a} and related central limit theorem has been well established. In this paper, we investigate the asymptotic tail behaviour of the empirical realized Laplace transform of volatility (ERLTV). We establish both large deviation principle and moderate deviation principle for the ERLTV. The good rate function for the large deviation principle is well defined in the whole real space, which indicates a limit for the normalized logarithmic tail probability of the ERLTV. Moreover, we also derive the function-level large and moderate deviation principles for ERLTV.
