Limit Order Book Simulations: A Review
SSRN Electronic Journal(2024)
摘要
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 calibrating and fine-tuning the automated
trading strategies developed in algorithmic trading research. The recent AI
revolution and availability of faster and cheaper compute power has enabled the
modelling and simulations to grow richer and even use modern AI techniques. In
this review we \highlight{examine} the various kinds of LOB simulation models
present in the current state of the art. We provide a classification of the
models on the basis of their methodology and provide an aggregate view of the
popular stylized facts used in the literature to test the models. We
additionally provide a focused study of price impact's presence in the models
since it is one of the more crucial phenomena to model in algorithmic trading.
Finally, we conduct a comparative analysis of various qualities of fits of
these models and how they perform when tested against empirical data.
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