Tracking High-Frequency Trading Activity in China and Its Effects on Market Quality
Auteurs : Li Guo, Frank Weikai Li, Ding Qi, Lijian Sun
Résumé scientifique
We develop a new order-level proxy for high-frequency trading (HFT) activity based on precise order placement and study its effects on market quality. With quotes updating multiple times per second, millisecond-level order-book access makes high-frequency traders more likely to submit active exact-match orders, defined as limit orders priced exactly at the prevailing best opposite-side quote. Using Shenzhen Stock Exchange data, we validate the proxy: active exact-match orders respond faster to quote updates, cancel more rapidly, concentrate when depth imbalance is favorable and spreads are narrow, and predict mid-quote returns from 100 milliseconds through ten minutes. A difference-in-differences design exploiting cross-channel variation in order dissemination latency at the market open shows that lower latency increases active exact-match shares. This variation yields plausibly causal evidence that latency-induced HFT raises short-horizon price variation, wide-spread incidence, and adverse-selection exposure, while realized spreads decline and pricing error falls modestly. Unlike developed markets, China's T+1 constraint, absence of maker-taker rebates, and limits on rapid quote revision tilt speed advantages toward directional liquidity taking, highlighting how market design shapes the channel through which speed affects market quality.
Les articles autour de lui, par date et par proximité
Plus haut, c’est plus proche de cet article ; à gauche, c’est plus ancien. Les traits relient les articles proches entre eux : les groupes de traits sont des sous-thèmes. Sélectionnez un point pour voir pourquoi il est là. Retour au résumé de cet article
Les articles autour de celui-ci
Classés selon la proximité de leur titre et de leur résumé avec ceux de cet article. Sélectionnez-en pour les lire ensemble.
Les articles les plus proches
-
The Importance of Low Latency to Order Book Imbalance Trading StrategiesDavid Byrd, Sruthi Palaparthi, Maria Hybinette et al. · 2020 · Trading and Market Microstructure · preprint, non relu par les pairs · cité 4 fois · Résumé IA disponible
The study measures how order-book access latency affects the profitability of imbalance strategies, tandis que l’article relie la latence à l’activité HFT et à la qualité du marché.
Résumé scientifique
There is a pervasive assumption that low latency access to an exchange is a key factor in the profitability of many high-frequency trading strategies. This belief is evidenced by the "arms race" undertaken by certain financial firms to co-locate with exchange servers. To the best of our knowledge, our study is the first to validate and quantify this assumption in a continuous double auction market with a single exchange similar to the New York Stock Exchange. It is not feasible to conduct this exploration with historical data in which trader identity and location are not reported. Accordingly, we investigate the relationship between latency of access to order book information and profitabili…
-
Analysis of trade packages in Chinese stock marketFei Ren, Wei-Xing Zhou · 2011 · Quantitative Finance 13 (7), 1071-1089 (2013) · cité 6 fois · Résumé IA disponible
L’étude caractérise des séquences d’achats ou de ventes de 23 titres chinois selon leur durée et leur volume, sans examiner la latence ni le HFT.
Résumé scientifique
This paper conducts an empirically study on the trade package composed of a sequence of consecutive purchases or sales of 23 stocks in Chinese stock market. We investigate the probability distributions of the execution time, the number of trades and the total trading volume of trade packages, and analyze the possible scaling relations between them. Quantitative differences are observed between the institutional and individual investors. The trading profile of trade packages is investigated to reveal the preference of large trades on trading volumes and transaction time of the day, and the different profiles of two types of investors imply that institutions may be more informed than individua…
-
Enhanced fill probability estimates in institutional algorithmic bond trading using statistical learning algorithms with quantum computersAxel Ciceri, Austin Cottrell, Joshua Freeland et al. · 2025 · Quantum Physics · cité 8 fois · Pas encore résumé
L’étude estime les probabilités d’exécution d’ordres algorithmiques sur obligations d’entreprise, plutôt que les effets de la latence sur les actions.
Résumé scientifique
The estimation of fill probabilities for trade orders represents a key ingredient in the optimization of algorithmic trading strategies. It is bound by the complex dynamics of financial markets with inherent uncertainties, and the limitations of models aiming to learn from multivariate financial time series that often exhibit stochastic properties with hidden temporal patterns. In this paper, we focus on algorithmic responses to trade inquiries in the corporate bond market and investigate fill probability estimation errors of common machine learning models when given real production-scale intraday trade event data, transformed by a quantum algorithm running on IBM Heron processors, as well a…
-
Portfolio liquidation under transient price impact -- theoretical solution and implementation with 100 NASDAQ stocksYing Chen, Ulrich Horst, Hoang Hai Tran · 2019 · Mathematical Finance · cité 12 fois · Résumé IA disponible
L’étude modélise la liquidation optimale et l’impact de marché à partir de carnets NASDAQ, sans mesurer l’activité HFT liée à la latence.
Résumé scientifique
We derive an explicit solution for deterministic market impact parameters in the Graewe and Horst (2017) portfolio liquidation model. The model allows to combine various forms of market impact, namely instantaneous, permanent and temporary. We show that the solutions to the two benchmark models of Almgren and Chris (2001) and of Obizhaeva and Wang (2013) are obtained as special cases. We relate the different forms of market impact to the microstructure of limit order book markets and show how the impact parameters can be estimated from public market data. We investigate the numerical performance of the derived optimal trading strategy based on high frequency limit order books of 100 NASDAQ s…
-
Market Making under a Weakly Consistent Limit Order Book ModelBaron Law, Frederi Viens · 2019 · Trading and Market Microstructure · cité 14 fois · Résumé IA disponible
Le modèle décrit le market making haute fréquence dans un carnet d’ordres, tandis que l’article exploite les données de carnet pour étudier le HFT.
Résumé scientifique
We develop a new market-making model, from the ground up, which is tailored towards high-frequency trading under a limit order book (LOB), based on the well-known classification of order types in market microstructure. Our flexible framework allows arbitrary order volume, price jump, and bid-ask spread distributions as well as the use of market orders. It also honors the consistency of price movements upon arrivals of different order types. For example, it is apparent that prices should never go down on buy market orders. In addition, it respects the price-time priority of LOB. In contrast to the approach of regular control on diffusion as in the classical Avellaneda and Stoikov [1] market-m…
-
Learning the Spoofability of Limit Order Books With Interpretable Probabilistic Neural NetworksTimothée Fabre, Damien Challet · 2025 · Trading and Market Microstructure · cité 3 fois · Résumé IA disponible
L’étude détecte le spoofing dans des carnets de crypto-actifs avec des variables de flux d’ordres, au lieu d’identifier le HFT chinois par ses ordres.
Résumé scientifique
This paper investigates real-time detection of spoofing activity in limit order books, focusing on cryptocurrency centralized exchanges. We first introduce novel order flow variables based on multi-scale Hawkes processes that account both for the size and placement distance from current best prices of new limit orders. Using a Level-3 data set, we train a neural network model to predict the conditional probability distribution of mid price movements based on these features. Our empirical analysis highlights the critical role of the posting distance of limit orders in the price formation process, showing that spoofing detection models that do not take the posting distance into account are ina…
-
Exploring the Advantages of Transformers for High-Frequency TradingFazl Barez, Paul Bilokon, Arthur Gervais et al. · 2023 · Statistical Finance · cité 8 fois · Résumé IA disponible
L’étude applique des modèles d’apprentissage aux séries haute fréquence pour prévoir les rendements Bitcoin, tandis que l’article analyse des données milliseconde du carnet.
Résumé scientifique
This paper explores the novel deep learning Transformers architectures for high-frequency Bitcoin-USDT log-return forecasting and compares them to the traditional Long Short-Term Memory models. A hybrid Transformer model, called \textbf{HFformer}, is then introduced for time series forecasting which incorporates a Transformer encoder, linear decoder, spiking activations, and quantile loss function, and does not use position encoding. Furthermore, possible high-frequency trading strategies for use with the HFformer model are discussed, including trade sizing, trading signal aggregation, and minimal trading threshold. Ultimately, the performance of the HFformer and Long Short-Term Memory model…
-
Profitability of simple stationary technical trading rules with high-frequency data of Chinese Index FuturesJing-Chao Chen, Yu Zhou, Xi Wang · 2017 · Statistical Finance · cité 14 fois · Résumé IA disponible
L’étude évalue des règles techniques sur des données haute fréquence de contrats à terme chinois, sans étudier la latence ni la qualité du carnet.
Résumé scientifique
Technical trading rules have been widely used by practitioners in financial markets for a long time. The profitability remains controversial and few consider the stationarity of technical indicators used in trading rules. We convert MA, KDJ and Bollinger bands into stationary processes and investigate the profitability of these trading rules by using 3 high-frequency data(15s,30s and 60s) of CSI300 Stock Index Futures from January 4th 2012 to December 31st 2016. Several performance and risk measures are adopted to assess the practical value of all trading rules directly while ADF-test is used to verify the stationarity and SPA test to check whether trading rules perform well due to intrinsic…
Aller plus loin
Comment ces articles sont-ils trouvés ?
Nous comparons le titre et le résumé de cet article avec ceux de tous les articles résumés sur ce site, et avec les articles que Semantic Scholar recommande, ceux qu’il cite et ceux qui le citent (pour un article très cité, ses citations les plus récentes et, depuis OpenAlex, les plus citées). Parmi les travaux antérieurs et les suites, les articles qui s’utilisent en profondeur, une méthode qu’il utilise et les suites très citées remontent un peu. Les niveaux (très proche, proche, apparenté) viennent de la similarité des textes, pas d’un jugement de qualité ; * signale un article sans résumé, comparé par son titre. La phrase sous un article est écrite par une IA à partir des deux résumés : vérifiez-la dans les articles. Un article jugé hors sujet par trois lecteurs quitte la liste.
Mis à jour le 2 novembre 2026.