Testing for jumps based on high-frequency data : a method exploiting microstructure noise
Year of publication: |
2020
|
---|---|
Authors: | Liu, Guangying ; Xiang, Jing ; Cang, Yuquan |
Published in: |
Quantitative finance. - London : Taylor & Francis, ISSN 1469-7696, ZDB-ID 2027557-2. - Vol. 20.2020, 11, p. 1795-1809
|
Subject: | Edgeworth expansion | High-frequency data | Microstructure noise | Price jumps | Testing for jumps | Marktmikrostruktur | Market microstructure | Volatilität | Volatility | Stochastischer Prozess | Stochastic process | Noise Trading | Noise trading | Schätztheorie | Estimation theory | Zeitreihenanalyse | Time series analysis | Nichtparametrisches Verfahren | Nonparametric statistics | Optionspreistheorie | Option pricing theory | Monte-Carlo-Simulation | Monte Carlo simulation |
-
Identifying the underlying components of high-frequency data : pure vs jump diffusion processes
Hizmeri, Rodrigo, (2025)
-
Jump variation estimation with noisy high frequency financial data via wavelets
Zhang, Xin, (2016)
-
Estimating spot volatility under infinite variation jumps with dependent market microstructure noise
Liu, Qiang, (2024)
- More ...
-
Economic transformation and new employment
Jing, Xiang, (2020)
-
China's rural industrialization and urbanization : 40 years of urban and rural labor transfer
Jing, Xiang, (2022)
-
Bayesian variance changepoint detection in linear models with symmetric heavy-tailed errors
Kang, Shuaimin, (2018)
- More ...