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Credit spreads and the term structure of interest rates
In: Working paper
In: D 00,14
Implied volatility of interest rate options: an empirical investigation of the market model
In: Working paper
In: D 00,1
Macroeconomic announcement effects on the covariance structure of bond returns
In: Working paper 99,7
Does Fiction Reading Make Us Better People? Empathy and Morality in a Literary Empowerment Programme
In: Ethnos: journal of anthropology, Band 88, Heft 5, S. 994-1013
ISSN: 1469-588X
Rhythms of Writing. An Anthropology of Irish Literature: by Helena Wulff, London, UK, Bloomsbury, 2017, 184 pp., £85.00 (hardback), ISBN: 978-1-4742-4413-8
In: Ethnos: journal of anthropology, Band 84, Heft 5, S. 930-932
ISSN: 1469-588X
SSRN
Working paper
A Review of the Active Management of Norway's Government Pension Fund Global
In: Bauer , R , Christiansen , C & Doskeland , T 2022 , A Review of the Active Management of Norway's Government Pension Fund Global . Norwegian Ministry of Finance .
In this review, we evaluate the active management by Norges Bank Investment Management (NBIM) of the Norwegian Government Pension Fund Global (the Fund). In this executive summary, we provide an overview of the main observations and suggestions. More details on the quantitative and qualitative analysis, the methodology, and our observations and suggestions can be found in the full version of the report.
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Working paper
Predicting bond betas using macro-finance variables
In: Aslanidis , N , Christiansen , C & Cipollini , A 2019 , ' Predicting bond betas using macro-finance variables ' , Finance Research Letters , vol. 29 , pp. 193-199 . https://doi.org/10.1016/j.frl.2018.07.007
We predict bond betas conditioning on a number of macro-finance variables. We explore differences across long-term government bonds, investment grade corporate bonds, and high yield corporate bonds. We conduct out-of-sample forecasting using the new approach of combining predictor variables through complete subset regressions (CSR). We consider the robustness of CSR forecasts across the 1-month, 3-month, and 12-month forecasting horizons. The CSR method performs well in predicting bond betas.
BASE
Predicting Bond Betas using Macro-Finance Variables
In: Aslanidis , N , Christiansen , C & Cipollini , A 2017 ' Predicting Bond Betas using Macro-Finance Variables ' Institut for Økonomi, Aarhus Universitet , Aarhus .
We conduct in-sample and out-of-sample forecasting using the new approach of combining explanatory variables through complete subset regressions (CSR). We predict bond CAPM betas and bond returns conditioning on various macro-fi…nance variables. We explore differences across long-term government bonds, investment grade corporate bonds, and high-yield corporate bonds. The CSR method performs well in predicting bond betas, especially in-sample, and, mainly high-yield bond betas when the focus is out-of-sample. Bond returns are less predictable than bond betas.
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Working paper