---
title: Adaptive Online Portfolio Selection with Transaction Costs
url: https://www.ml-quant.com/papers/repec/taf-quantf-v-24-y-2023-i-1-p-59-82/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:taf:quantf:v:24:y:2023:i:1:p:59-82
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F14697688.2023.2287134%3Bh%3Drepec%3Ataf%3Aquantf%3Av%3A24%3Ay%3A2023%3Ai%3A1%3Ap%3A59-82
featured: 2024-02-14
citations: unknown
topic: Portfolio & Allocation
---


# Adaptive Online Portfolio Selection with Transaction Costs

The research proposes a new algorithm for online portfolio selection that improves return prediction accuracy by considering peer impact.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fhdl.handle.net%2F10.1080%2F14697688.2023.2287134%3Bh%3Drepec%3Ataf%3Aquantf%3Av%3A24%3Ay%3A2023%3Ai%3A1%3Ap%3A59-82
- Identifier: RePEc:taf:quantf:v:24:y:2023:i:1:p:59-82
- Released: 2023-02-06
- First featured: Quant Letter No. 37 (2024-02-14): https://www.ml-quant.com/issues/2024-02-14/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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