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Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps
Author(s) -
Song Yuping,
Chen Ying,
Wang Zhouwei
Publication year - 2019
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12423
Subject(s) - mathematics , estimator , asymptotic distribution , econometrics , consistency (knowledge bases) , infinitesimal , strong consistency , statistics , mathematical analysis , discrete mathematics
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.