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Universal portfolios with side information
Abstract
We present a sequential investment algorithm, the /spl mu/-weighted universal portfolio with side information, which achieves, to first order in the exponent, the same wealth as the best side-information dependent investment strategy (the best state-constant rebalanced portfolio) determined in hindsight from observed market and side-information outcomes. This is an individual sequence result which shows the difference between the exponential growth wealth of the best state-constant rebalanced portfolio and the universal portfolio with side information is uniformly less than (d/(2n))log (n+1)+(k/n)log 2 for every stock market and side-information sequence and for all time n. Here d=k(m-1) is the number of degrees of freedom in the state-constant rebalanced portfolio with k states of side information and m stocks. The proof of this result establishes a close connection between universal investment and universal data compression.
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Cited by
Online portfolio selection strategy based on combining experts' advice
Zhang, Y., & Yang, X. (2017) · Computational Economics · doi:10.1007/s10614-016-9585-0 · Cited by 38
Decomposing information into copying versus transformation
Kolchinsky, A., & Corominas-Murtra, B. (2020) · Journal of The Royal Society Interface · doi:10.1098/rsif.2019.0623 · Cited by 5
Metadata
- Authors
- Cover, T. M., & Ordentlich, E.
- Venue
- IEEE Transactions on Information Theory
- Published
- 1996-03
- Volume
- 42
- Issue
- 2
- Pages
- 348-363
- ISSN
- 0018-9448 (ISSN-L)
- OpenAlex
- W2120499560
- Cited by
- 347
- References
- 0
- FWCI
- 18.72
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Universal portfolios with side information. https://app.cochat.ai/papers/10.1109/18.485708
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- Cover, T. M., & Ordentlich, E. (1996). Universal portfolios with side information. IEEE Transactions on Information Theory. https://doi.org/10.1109/18.485708
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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).
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