Long memory of financial time series and hidden Markov models with time‐varying parameters
| Year of publication: |
December 2017
|
|---|---|
| Authors: | Nystrup, Peter ; Madsen, Henrik ; Lindström, Erik |
| Published in: |
Journal of forecasting. - Chichester : Wiley, ISSN 0277-6693, ZDB-ID 783432-9. - Vol. 36.2017, 8, p. 989-1002
|
| Subject: | hidden Markov models | daily returns | long memory | adaptive estimation | time‐varying parameters | Markov-Kette | Markov chain | Zeitreihenanalyse | Time series analysis | ARCH-Modell | ARCH model | Schätztheorie | Estimation theory | Kapitaleinkommen | Capital income | Volatilität | Volatility | Stochastischer Prozess | Stochastic process |
-
Optimal filter approximations for latent long memory stochastic volatility
Yap, Grace Lee Ching, (2020)
-
Maruotti, Antonello, (2019)
-
l 1 - penalized likelihood smoothing of volatility processes allowing for abrupt changes
Neto, David, (2009)
- More ...
-
Dimensionality reduction in forecasting with temporal hierarchies
Nystrup, Peter, (2021)
-
Temporal hierarchies with autocorrelation for load forecasting
Nystrup, Peter, (2020)
-
Multi-period portfolio selection with drawdown control
Nystrup, Peter, (2019)
- More ...