Double Smoothed Volatility Estimation of Potentially Non-stationary Jump-diffusion Model of Shibor,Journal of Time Series Analysis

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Double Smoothed Volatility Estimation of Potentially Non-stationary Jump-diffusion Model of Shibor
Journal of Time Series Analysis ( IF 1.2 ) Pub Date : 2021-04-23 , DOI: 10.1111/jtsa.12592
Yuping Song ₁ , Weijie Hou ₂ , Zhengyan Lin ₃

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The occurrence-50 of economic policies and other sudden and large shocks often bring out jumps in financial data, which can be characterized through continuous-time jump-diffusion model. In this article, we present the double smoothed non-parametric approach for infinitesimal conditional volatility of jump-diffusion model based on high frequency data. Under certain minimal conditions, we obtain the strong consistency and asymptotic normality for the estimator as the time span T → ∞ and the sample interval

Δ_{n} \to 0

. The procedure and asymptotic behavior can be applied for both Harris recurrent and positive Harris recurrent processes. The finite sample properties of the underlying double smoothed volatility estimator are verified through Monte Carlo simulation and Shanghai Interbank Offered Rate in China for application.

更新日期：2021-04-23

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