Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps
Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps
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DOI：
10.1111/jtsa.12423
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发表时间：
2018-02
影响因子：
0.9
通讯作者：
Yuping Song;Ying Chen;Zhouwei Wang
中科院分区：
文献类型：
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作者：
Yuping Song;Ying Chen;Zhouwei Wang
在这篇文章中，局部线性估计适用于与跳跃连续时间资产收益模型相关的未知无穷小系数，由于其简单的偏差表示，可以自动校正偏差。主要研究了带跳跃的积分扩散模型，特别是带无限活动跳跃的积分扩散模型。在较弱的条件下，利用条件Lindeberg定理证明了当时间跨度T→∞，样本区间Δ n →0时，模型的弱相合性和渐近正态性.此外，我们的方法显示出的优势，通过模拟偏差校正跳跃属于有限活动的情况下或无限活动的情况。最后，通过5分钟高采样频率下的股票指数收益率对估计量进行了实证说明，以供真实的应用。
In this article, local linear estimators are adapted for the unknown infinitesimal coefficients associated with continuous‐time asset return models with jumps, which can correct the bias automatically due to their simple bias representation. The integrated diffusion models with jumps, especially infinite activity jumps, are mainly investigated. In addition, under mild conditions, the weak consistency and asymptotic normality are provided through the conditional Lindeberg theorem as the time span T→∞ and the sample interval Δ n →0. Furthermore, our method presents advantages in bias correction through simulation whether jumps belong to the finite activity case or infinite activity case. Finally, the estimators are illustrated empirically through the returns of stock index under 5‐minute high sampling frequency for real application.