Introducing shrinkage in heavy-tailed state space models to predict equity excess returns
Year of publication: |
2025
|
---|---|
Authors: | Huber, Florian ; Kastner, Gregor ; Pfarrhofer, Michael |
Subject: | Dynamic regression | Fundamental factors | Non-Gaussian models | S&P 500 | Stochastic volatility | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Theorie | Theory | Zustandsraummodell | State space model | Kapitaleinkommen | Capital income | Stochastischer Prozess | Stochastic process | Regressionsanalyse | Regression analysis | CAPM |
-
Modeling tail risks of inflation using unobserved component quantile regressions
Pfarrhofer, Michael, (2022)
-
Chapter 7 Forecasting with Unobserved Components Time Series Models
Harvey, Andrew, (2006)
-
Gagliardini, Patrick, (2017)
- More ...
-
Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models
Huber, Florian, (2018)
-
Sparse Bayesian vector autoregressions in huge dimensions
Kastner, Gregor, (2020)
-
Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models
Huber, Florian, (2019)
- More ...