Combining Penalization and Adaption in High Dimension with Application in Bond Risk Premia Forecasting
Year of publication: |
2020
|
---|---|
Authors: | Li, Xinjue |
Other Persons: | Zboňáková, Lenka (contributor) ; Wang, Weining (contributor) ; Härdle, Wolfgang K. (contributor) |
Publisher: |
[2020]: [S.l.] : SSRN |
Subject: | Risikoprämie | Risk premium | Prognoseverfahren | Forecasting model | Anleihe | Bond | Prognose | Forecast | Theorie | Theory |
Extent: | 1 Online-Ressource (50 p) |
---|---|
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 1, 2019 erstellt |
Other identifiers: | 10.2139/ssrn.3657337 [DOI] |
Classification: | C4 - Econometric and Statistical Methods: Special Topics ; C5 - Econometric Modeling ; E4 - Money and Interest Rates ; G1 - General Financial Markets |
Source: | ECONIS - Online Catalogue of the ZBW |
-
Anchoring the yield curve using survey expectations
Altavilla, Carlo, (2013)
-
Does realized volatility help bond yield density prediction?
Shin, Minchul, (2015)
-
Does Realized Volatility Help Bond Yield Density Prediction?
Shin, Minchul, (2018)
- More ...
-
Li, Xinjue, (2019)
-
Penalized Adaptive Forecasting With Large Information Sets and Structural Changes
Zboňáková, Lenka, (2018)
-
Penalized adaptive method in forecasting with large information set and structure change
Li, Xinjue, (2017)
- More ...