zcakhaa / DeepLOB-Deep-Convolutional-Neural-Networks-for-Limit-Order-BooksLinks
This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.
☆526Updated 4 years ago
Alternatives and similar repositories for DeepLOB-Deep-Convolutional-Neural-Networks-for-Limit-Order-Books
Users that are interested in DeepLOB-Deep-Convolutional-Neural-Networks-for-Limit-Order-Books are comparing it to the libraries listed below
Sorting:
- This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.o…☆592Updated 2 years ago
- ☆208Updated 2 years ago
- Deep Learning Statistical Arbitrage☆251Updated 3 years ago
- This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (…☆264Updated 3 years ago
- High frequency trading (HFT) framework built for futures using machine learning and deep learning techniques☆541Updated 3 years ago
- Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.☆249Updated 3 years ago
- Benchmark Dataset of Limit Order Book in China Markets☆214Updated 4 years ago
- Market Making via Reinforcement Learning☆338Updated 6 years ago
- ☆430Updated 4 years ago
- GPU-accelerated Factors analysis library and Backtester☆757Updated 8 months ago
- experiments with pair trading☆327Updated last year
- Using tabular and deep reinforcement learning methods to infer optimal market making strategies☆233Updated 2 years ago
- Code implementation of the Quantigic 101 Formulaic Alphas☆643Updated 6 years ago
- We release `LOBFrame', a novel, open-source code base which presents a renewed way to process large-scale Limit Order Book (LOB) data.☆210Updated last year
- Avellaneda-Stoikov HFT market making algorithm implementation☆617Updated 2 years ago
- High Frequency Market Making☆604Updated 2 years ago
- An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implemen…☆378Updated 7 years ago
- PyTorch-based framework for Deep Hedging☆332Updated last year
- ☆362Updated 2 years ago
- Implementation of Reinforcement Learning in Pair Trading☆11Updated 5 months ago
- GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hed…☆295Updated 4 years ago
- Mining technical factors based on symbolic regression via genetic algorithm☆208Updated 2 years ago
- All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.☆783Updated last year
- Collection of algorithms for online portfolio selection☆845Updated 3 months ago
- Limit Order Book data analysis and modeling using LSTM network☆137Updated 6 years ago
- Performance analysis of predictive (alpha) stock factors☆521Updated last week
- Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent☆940Updated 3 years ago
- Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models☆455Updated 2 years ago
- World Quant 101 alphas的计算和策略化☆309Updated 8 years ago
- Mostly experiments based on "Advances in financial machine learning" book☆561Updated 5 years ago