[HTML][HTML] Reinforcement learning approaches to optimal market making
Market making is the process whereby a market participant, called a market maker,
simultaneously and repeatedly posts limit orders on both sides of the limit order book of a …
simultaneously and repeatedly posts limit orders on both sides of the limit order book of a …
Deep LOB trading: Half a second please!
We introduce an expert deep-learning system for limit order book (LOB) trading for markets
in which the stock tick frequency is longer than or close to 0.5 s, such as the Chinese A …
in which the stock tick frequency is longer than or close to 0.5 s, such as the Chinese A …
[HTML][HTML] Predicting high-frequency stock movement with differential transformer neural network
S Lai, M Wang, S Zhao, GR Arce - Electronics, 2023 - mdpi.com
Predicting stock prices has long been the holy grail for providing guidance to investors.
Extracting effective information from Limit Order Books (LOBs) is a key point in high …
Extracting effective information from Limit Order Books (LOBs) is a key point in high …
From uniform models to generic representations: stock return prediction with pre-training
J You, T Han, L Shen - 2022 International Joint Conference on …, 2022 - ieeexplore.ieee.org
The emergence of deep learning has cast new light on the century-old problem of stock
return prediction. For single stock return prediction, incorporating peripheral data such as …
return prediction. For single stock return prediction, incorporating peripheral data such as …
Kernel Market Impact Analysis in China A-Share Markets.
H Chou, J Han, C Huang… - Journal of Financial Data …, 2023 - search.ebscohost.com
With transaction-level market data for stocks in China A-share markets, the authors construct
individual stocks' kernel functions of market impact and analyze their statistical properties …
individual stocks' kernel functions of market impact and analyze their statistical properties …
OCET: One-Dimensional Convolution Embedding Transformer for Stock Trend Prediction
Due to the strong data fitting ability of deep learning, the use of deep learning for quantitative
trading has gradually sprung up in recent years. As a classical problem of quantitative …
trading has gradually sprung up in recent years. As a classical problem of quantitative …
[PDF][PDF] Reinforcement Learning Approaches to Optimal Market Making. Mathematics 2021, 9, 2689
Market making is the process whereby a market participant, called a market maker,
simultaneously and repeatedly posts limit orders on both sides of the limit order book of a …
simultaneously and repeatedly posts limit orders on both sides of the limit order book of a …