---
title: Optimal Trading with Costs and Predictability
url: https://www.ml-quant.com/papers/ssrn/4466658/
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: SSRN 4466658
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4466658
featured: 2025-12-28
citations: unknown
topic: Trading, Microstructure & Execution
---


# Optimal Trading with Costs and Predictability

It establishes optimal trading rules for multiple assets with predictable returns, showing performance benefits through simulations.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4466658
- Identifier: SSRN 4466658
- Released: 2023-06-04
- First featured: Quant Letter No. 124 (2025-12-28): https://www.ml-quant.com/issues/2025-12-28/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Trading, Microstructure & Execution

## Related

- [FAST: Efficient Action Tokenization for Vision-Language-Action Models](https://www.ml-quant.com/papers/arxiv/2501.09747/): A new tokenization scheme, Frequency-space Action Sequence Tokenization (FAST), has been proposed for robot actions, facilitating the training of vision-language action policies for complex and high-frequency tasks.
- [Deep Reinforcement Learning for Active High Frequency Trading](https://www.ml-quant.com/papers/arxiv/2101.07107/): A new Deep Reinforcement Learning framework has been developed for high frequency stock trading, showing potential for profitable long-term strategies.
- [Romania's Roadmap to a Greener Financial System: An analysis of Environmental, Social and Governance Reporting on the Bucharest Exchange Trading Index](https://www.ml-quant.com/papers/ssrn/4440516/): Romania struggles to attract sustainable investments because its major companies have low transparency and high greenhouse gas emissions.
- [Robust insurance pricing and liquidity management](https://www.ml-quant.com/papers/arxiv/2510.15709/): Accounting for model uncertainty makes insurers set higher, more conservative prices and liquidity buffers, widens capacity ranges, and produces much longer underwriting cycles with more time in low‑capacity states.
- [TradeFM: A Generative Foundation Model for Trade-flow and Market Microstructure](https://www.ml-quant.com/papers/arxiv/2602.23784/): A Model for Trade-Flow in Market Microstructure: TradeFM is a new AI model that improves the analysis of market structures by studying billions of trade events in stocks, leading to better simulations of financial returns.
- [A Microstructure Analysis of Coupling in CFMMs](https://www.ml-quant.com/papers/arxiv/2510.06095/): The article investigates the impact of smart contract protocols on market dynamics, focusing on their influence on price drift, trade size, and market depth in coupled markets.