The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Dynamic Trading with Predictable Returns and Transaction Costs
Open accessAbstract
We derive a closed‐form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean‐reversion speeds. The optimal strategy is characterized by two principles: (1) aim in front of the target, and (2) trade partially toward the current aim. Specifically, the optimal updated portfolio is a linear combination of the existing portfolio and an “aim portfolio,” which is a weighted average of the current Markowitz portfolio (the moving target) and the expected Markowitz portfolios on all future dates (where the target is moving). Intuitively, predictors with slower mean‐reversion (alpha decay) get more weight in the aim portfolio. We implement the optimal strategy for commodity futures and find superior net returns relative to more naive benchmarks.
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Cites
Markowitz, H. (1952) · The Journal of Finance · doi:10.1111/j.1540-6261.1952.tb01525.x · Cited by 5,641
Asset pricing and the bid-ask spread
Amihud, Y., & Mendelson, H. (1986) · Journal of Financial Economics · doi:10.1016/0304-405x(86)90065-6 · Cited by 5,090
Asset pricing with liquidity risk
ACHARYA, V, & PEDERSEN, L. (2005) · Journal of Financial Economics · doi:10.1016/j.jfineco.2004.06.007 · Cited by 2,773
Self-citationASNESS, C. S., MOSKOWITZ, T. J., & PEDERSEN, L. H. (2013) · The Journal of Finance · doi:10.1111/jofi.12021 · Cited by 2,147
Self-citationFads, Martingales, and Market Efficiency
Lehmann, B. N. (1990) · The Quarterly Journal of Economics · doi:10.2307/2937816 · Cited by 1,568
Liquidity and Market Structure
GROSSMAN, S. J., & MILLER, M. H. (1988) · The Journal of Finance · doi:10.1111/j.1540-6261.1988.tb04594.x · Cited by 1,493
Portfolio Selection with Transaction Costs
Davis, M. H. A., & Norman, A. R. (1990) · Mathematics of Operations Research · doi:10.1287/moor.15.4.676 · Cited by 1,311
Strategic Asset Allocation: Portfolio Choice for Long-Term Investors
Campbell, J. Y., & Viceira, L. M. (2002) · doi:10.1093/0198296940.001.0001 · Cited by 1,270
Capital Market Equilibrium with Transaction Costs
Constantinides, G. M. (1986) · Journal of Political Economy · doi:10.1086/261410 · Cited by 1,095
The Strategic and Tactical Value of Commodity Futures
Erb, C. B., & Harvey, C. R. (2006) · Financial Analysts Journal · doi:10.2469/faj.v62.n2.4084 · Cited by 1,027
Cited by
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012) · Journal of Financial Economics · doi:10.1016/j.jfineco.2011.11.003 · Cited by 1,431
Self-citation60 Years of portfolio optimization: Practical challenges and current trends
Kolm, P. N., Tütüncü, R., & Fabozzi, F. J. (2014) · European Journal of Operational Research · doi:10.1016/j.ejor.2013.10.060 · Cited by 632
Risk Everywhere: Modeling and Managing Volatility
Bollerslev, T., Hood, B., Huss, J., & Pedersen, L. H. (2018) · The Review of Financial Studies · doi:10.1093/rfs/hhy041 · Cited by 359
Self-citationMacro, Finance, and Macro Finance: Solving Nonlinear Models in Continuous Time with Machine Learning
Duarte, V. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3012602 · Cited by 9
Emissions trading with transaction costs
Baudry, M., Faure, A., & Quemin, S. (2021) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2021.102468 · Cited by 5
Metadata
- Authors
- GÂRLEANU, N., & PEDERSEN, L. H.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2013-11-12
- Volume
- 68
- Issue
- 6
- Pages
- 2309-2340
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3123718809
- Cited by
- 560
- References
- 25
- FWCI
- 69.22
- Type
- journal article
- Language
- en
- Open access
- bronze
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
