---
title: HighFrequency Trading Impact
url: https://www.ml-quant.com/papers/repec/kap-fmktpm-v-33-y-2019-i-2-d-10-1007-s11408-019-00331-6/
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:kap:fmktpm:v:33:y:2019:i:2:d:10.1007_s11408-019-00331-6
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11408-019-00331-6%3Bh%3Drepec%3Akap%3Afmktpm%3Av%3A33%3Ay%3A2019%3Ai%3A2%3Ad%3A10.1007_s11408-019-00331-6
featured: 2025-10-24
citations: unknown
topic: Trading, Microstructure & Execution
---


# HighFrequency Trading Impact

The paper discusses the effects of high-frequency trading on market factors like volatility, transaction costs, and liquidity, indicating varied opinions in the financial sector.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs11408-019-00331-6%3Bh%3Drepec%3Akap%3Afmktpm%3Av%3A33%3Ay%3A2019%3Ai%3A2%3Ad%3A10.1007_s11408-019-00331-6
- Identifier: RePEc:kap:fmktpm:v:33:y:2019:i:2:d:10.1007_s11408-019-00331-6
- Released: 2019-01-05
- First featured: Quant Letter No. 116 (2025-10-24): https://www.ml-quant.com/issues/2025-10-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Trading, Microstructure & Execution

## Related

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- [High-Frequency Trading, Asset Pricing, and Market Microstructure](https://www.ml-quant.com/papers/ssrn/4858807/): A study using high-frequency trading data provides insights into asset pricing, transaction costs, investor liquidity asymmetry, and seasonality effects.
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- [Superhuman Speed in Futures Trading Requires Stricter Regulation](https://www.ml-quant.com/papers/ssrn/4580566/): A study suggests that high-frequency traders' use of low-latency trading algorithms for arbitrage opportunities increases execution costs for other market participants, proposing batch auctions as a solution.
- [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.
