Limit Order Books (LOBs) serve as a mechanism for buyers and sellers to interact with each
other in the financial markets. Modelling and simulating LOBs is quite often necessary} for …

Hawkes Process has been used to model Limit Order Book (LOB) dynamics in several ways
in the literature however the focus has been limited to capturing the inter-event times while …

This study investigates the development of an optimal execution strategy through
reinforcement learning, aiming to determine the most effective approach for traders to buy …

Simulation methods have always been instrumental in finance, and data-driven methods
with minimal model specification, commonly referred to as generative models, have attracted …

We build a time-causal variational autoencoder (TC-VAE) for robust generation of financial
time series data. Our approach imposes a causality constraint on the encoder and decoder …

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 …

In this paper, we show how $ K $-nearest neighbor ($ K $-NN) resampling, an off-policy
evaluation method proposed in\cite {giegrich2023k}, can be applied to simulate limit order …

The ability to accurately simulate financial markets is crucial, as it allows researchers and
practitioners to rigorously test and refine trading strategies without the high risks associ-ated …

Recent advancements in machine learning have opened up new possibilities for algorithmic
trading, enabling the optimization of trading strategies in complex market environments. This …

This thesis focuses on the statistical modeling of order flow in limit order markets and the
development data-driven approaches for the simulation of limit order book dynamics. In the …