---
title: Statistical Modeling of High-Frequency Trading Data
url: https://www.ml-quant.com/papers/repec/spr-sankhb-v-85-y-2023-i-1-d-10-1007-s13571-022-00280-7/
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:spr:sankhb:v:85:y:2023:i:1:d:10.1007_s13571-022-00280-7
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs13571-022-00280-7%3Bh%3Drepec%3Aspr%3Asankhb%3Av%3A85%3Ay%3A2023%3Ai%3A1%3Ad%3A10.1007_s13571-022-00280-7
featured: 2023-05-24
citations: unknown
topic: Trading, Microstructure & Execution
---


# Statistical Modeling of High-Frequency Trading Data

The paper discusses statistical modeling approaches for analyzing high-frequency trading data.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs13571-022-00280-7%3Bh%3Drepec%3Aspr%3Asankhb%3Av%3A85%3Ay%3A2023%3Ai%3A1%3Ad%3A10.1007_s13571-022-00280-7
- Identifier: RePEc:spr:sankhb:v:85:y:2023:i:1:d:10.1007_s13571-022-00280-7
- Released: 2023-05-24
- First featured: Quant Letter No. 1 (2023-05-24): https://www.ml-quant.com/issues/2023-05-24/
- 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.
- [Estimation of an Order Book Dependent Hawkes Process for Large Datasets](https://www.ml-quant.com/papers/arxiv/2307.09077/): A new high-frequency trading model uses a Hawkes process and high-dimensional functions from the order book, capable of handling billions of data points and tested on four NYSE stocks.
- [Approximately optimal trade execution strategies under fast mean-reversion](https://www.ml-quant.com/papers/arxiv/2307.07024/): A study models market quality using uncertain volatility and liquidity, studying optimal strategy approximations and providing estimation methods for the model using high-frequency data.
- [Are Large Traders Harmed by Front-running HFTs?](https://www.ml-quant.com/papers/arxiv/2211.06046/): The paper concludes that high-frequency traders always front-run and large traders benefit when there is enough high-speed noise trading and the high-frequency trader's prediction is unclear.
- [Microstructure-Empowered Stock Factor Extraction and Utilization](https://www.ml-quant.com/papers/arxiv/2308.08135/): A new model has been suggested to better predict stock trends and improve order execution by analyzing high-frequency order flow data in stock investment.
