Jump detection and noise separation by a singular wavelet method for predictive analytics of high-frequency data
Year of publication: |
2019
|
---|---|
Authors: | Chen, Yi-Ting ; Lai, Wan Ni ; Sun, Edward W. |
Published in: |
Computational economics. - Dordrecht [u.a.] : Springer, ISSN 0927-7099, ZDB-ID 1142021-2. - Vol. 54.2019, 2, p. 809-844
|
Subject: | Convex optimization | Forecasting | High-frequency data | Jump detection | Reinforcement learning | Wavelet | Prognoseverfahren | Forecasting model | Theorie | Theory | Zustandsraummodell | State space model | Zeitreihenanalyse | Time series analysis | Volatilität | Volatility | Stochastischer Prozess | Stochastic process |
-
l 1 - penalized likelihood smoothing of volatility processes allowing for abrupt changes
Neto, David, (2009)
-
Large mixed-frequency VARs with a parsimonious time-varying parameter structure
Götz, Thomas B., (2018)
-
Combining long memory and level shifts in modelling and forecasting the volatility of asset returns
Varneskov, Rasmus Tangsgaard, (2018)
- More ...
-
Generalized optimal wavelet decomposing algorithm for big financial data
Sun, Edward W., (2015)
-
Improving model performance with the integrated wavelet denoising method
Chen, Yi-Ting, (2015)
-
Risk assessment with wavelet feature engineering for high-frequency portfolio trading
Chen, Yi-Ting, (2018)
- More ...