Multi-dimensional queue-reactive model and signal-driven models: a unified framework
We present a Markovian market model driven by a hidden Brownian efficient price. In particular, we extend the queue-reactive model, making its dynamics dependent on the efficient price. Our study focuses on two sub-models: a signal-driven price model where the mid-price jump rates depend on the efficient price and an observable signal, and the usual queue-reactive model dependent on the efficient price via the intensities of the order arrivals. This way, we are able to correlate the evolution of limit order books of different stocks. We prove the stability of the observed mid-price around the efficient price under natural assumptions. Precisely, we show that at the macroscopic scale, prices behave as diffusions. We also develop a maximum likelihood estimation procedure for the model, and test it numerically. Our model is them used to backest trading strategies in a liquidation context.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Deep Learning Meets Queue-Reactive: A Framework for Realistic Limit Order Book Simulation
The Queue-Reactive model introduced by Huang et al. (2015) has become a standard tool for limit order book modeling, widely adopted by both researchers and practitioners for its simplicity and effectiveness. We present t…
Computational EfficiencyA Novel Approach to Queue-Reactive Models: The Importance of Order Sizes
In this article, we delve into the applications and extensions of the queue-reactive model for the simulation of limit order books. Our approach emphasizes the importance of order sizes, in conjunction with their type an…
Exploring DMD-type Algorithms for Modeling Signalised Intersections
This paper explores a novel data-driven approach based on recent developments in Koopman operator theory and dynamic mode decomposition (DMD) for modeling signalized intersections. Vehicular flow and queue formation on s…
Vocal Bursts Type PredictionQueue-reactive Hawkes models for the order flow
In this work we introduce two variants of multivariate Hawkes models with an explicit dependency on various queue sizes aimed at modeling the stochastic time evolution of a limit order book. The models we propose thus in…
Reinforcement Learning in Queue-Reactive Models: Application to Optimal Execution
We investigate the use of Reinforcement Learning for the optimal execution of meta-orders, where the objective is to execute incrementally large orders while minimizing implementation shortfall and market impact over an …
Reinforcement Learning