Optimal market-Making strategies under synchronised order arrivals with deep neural networks

Choi, So Eun; Jang, Hyun Jin; Lee, Kyung Sub; Zheng, Harry

doi:10.1016/j.jedc.2021.104098

Cited by 7 publications

(2 citation statements)

References 67 publications

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“…The research interest in high-frequency trading is not limited to the above discussion; it extends to the optimal strategies of market makers and investors based on high-frequency trading (Avellaneda and Stoikov, 2008;Guilbaud and Pham, 2013;Cartea and Jaimungal, 2013;Cartea et al, 2018;Choi et al, 2021) and limit order book modeling (Cont and de Larrard, 2013;Toke, 2015). Bouchaud et al (2002), Hollifield et al (2004), andHuang et al (2015) describe the statistical properties of limit order books.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling bid and ask price dynamics with an extended Hawkes process and its empirical applications for high-frequency stock market data

Lee,

Seo

2022

Preprint

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This study proposes a versatile model for the dynamics of the best bid and ask prices using an extended Hawkes process. The model incorporates the zero intensities of the spreadnarrowing processes at the minimum bid-ask spread, spread-dependent intensities, possible negative excitement, and nonnegative intensities. We apply the model to high-frequency best bid and ask price data from US stock markets. The empirical findings demonstrate a spread-narrowing tendency, excitations of the intensities caused by previous events, the impact of flash crashes, characteristic trends in fast trading over time, and the different features of market participants in the various exchanges.

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Section: Literature Reviewmentioning

confidence: 99%

Modeling bid and ask price dynamics with an extended Hawkes process and its empirical applications for high-frequency stock market data

Lee,

Seo

2022

Preprint

Self Cite

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“…Although the Hawkes model can be used in various fields of finance, such as credit risk analysis (Errais et al, 2010;Aït-Sahalia et al, 2015;Ma and Xu, 2016;Ketelbuters and Hainaut, 2022) and optimal execution (Choi et al, 2021;Da Fonseca and Malevergne, 2021;Jusselin, 2021;Gašperov and Kostanjčar, 2022), studies focusing on price dynamics, such as our study, are also abundant. To mention a few, Bacry et al (2013a) used the multivariate Hawkes model for the tick dynamics of asset prices with the applications of microstructure noise analysis.…”

Section: Introductionmentioning

confidence: 99%

Multi-kernel property in high-frequency price dynamics under Hawkes model

Lee¹

2023

Preprint

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This study investigates and uses multi-kernel Hawkes models to describe a highfrequency mid-price process. Each kernel represents a different responsive speed of market participants. Using the conditional Hessian, we examine whether the numerical optimizer effectively finds the global maximum of the log-likelihood function under complicated modeling. Empirical studies that use stock prices in the US equity market show the existence of multi-kernels classified as ultra-high-frequency (UHF), very-high-frequency (VHF), and high-frequency (HF). We estimate the conditional expectations of arrival times and the degree of contribution to the high-frequency activities for each kernel.

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Application of Hawkes Volatility in the Observation of Filtered High‐Frequency Price Process in Tick Structures

Lee

2024

Appl Stoch Models Bus & Ind

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The Hawkes model is suitable for describing self and mutually exciting random events. In addition, the exponential decay in the Hawkes process allows us to calculate the moment properties of the model. However, owing to the complexity of the model and formula, few studies have examined the Hawkes volatility. In this study, we derive a variance formula that is directly applicable under the general settings of both unmarked and marked Hawkes models for tick‐level price dynamics. In the marked model, the linear impact function and possible dependency between the marks and underlying processes are considered. The Hawkes volatility is applied to the mid‐price process filtered at 0.1‐s intervals to show reliable results. Furthermore, intraday estimation is expected to widely utilized in real‐time risk management. We also note the increasing predictive power of the intraday Hawkes volatility over time and examine the relationship between futures and stock volatilities.

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Optimal market-Making strategies under synchronised order arrivals with deep neural networks

Cited by 7 publications

References 67 publications

Modeling bid and ask price dynamics with an extended Hawkes process and its empirical applications for high-frequency stock market data

Modeling bid and ask price dynamics with an extended Hawkes process and its empirical applications for high-frequency stock market data

Multi-kernel property in high-frequency price dynamics under Hawkes model

Application of Hawkes Volatility in the Observation of Filtered High‐Frequency Price Process in Tick Structures

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