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Smart Rebalancing
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OA
AI
DOI：10.1080/0015198X.2024.2317323.png)
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Abstract
En 中文
The sometimes vast gap between live results and paper portfolio performance is caused in part by trading costs, discontinuous trading, and missed trades or other frictions, along with asset management fees. Smart beta and factor strategies are not exempt from this sort of implementation shortfall. This paper provides new evidence on the efficacy of prioritizing transactions so as to focus portfolio turnover on the trades that offer the strongest signals and hence the highest potential performance impact. Rebalancing filters of this sort can capture much of the factor premia for a long-only paper portfolio while cutting turnover and trading costs relative to a fully rebalanced portfolio.
Keywords:
alpha
factor premia
implementation shortfall
portfolio turnover
rebalancing methods
risk premia
trading costs
trading signals
2.0
Journal
F
IF:
2.2
Papers:
1.2K
Citations:
3.1K
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