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“Although the transaction cost models of Bollerslev et al. (2018) and Koijen et al. (2018) are quite conservative, we follow an even more cautious approach and deduct 57 bps from each portfolio's monthly excess returns.”
From Empirical asset pricing via machine learning: evidence from the European stock market (2021) · cites this paper as Koijen et al. (2018)
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Metadata
- Authors
- Koijen, R. S. J., Moskowitz, T. J., Pedersen, L. H., & Vrugt, E. B.
- Affiliations
- National Bureau of Economic Research (US)
- Copenhagen Business School (DK)
- Vrije Universiteit Amsterdam (NL)
- Corresponding author
- Koijen, Ralph S.J.
- ORCID
- Pedersen, Lasse Heje
- Venue
- Journal of Financial Economics
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 127
- Issue
- 2
- Pages
- 197-225
- ISSN
- 0304-405X (ISSN-L)
- OpenAlex
- W4234492972
- Cited by
- 286
- References
- 64
- Citations by year
- 2026: 22 · 2025: 36 · 2024: 22 · 2023: 46 · 2022: 40 · 2021: 42 · 2020: 22 · 2019: 24 · 2018: 24
- FWCI
- 30.18
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Financial Economics (publishedVersion)
- VU Research Portal (publishedVersion)
- CBS Research Portal (Copenhagen Business School) (acceptedVersion, cc-by-nc-nd)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- European Research Council (338082, 312417)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Market Dynamics and Volatility
- Keywords
- carry, return predictability, asset pricing, uncovered interest parity, expectations hypothesis, risk premium, recession risk, liquidity risk, volatility risk, cross-section of returns, equity, bonds, commodities, options, credit
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