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.
☆511Updated 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…☆573Updated last year
- ☆206Updated 2 years ago
- This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (…☆258Updated 2 years ago
- Deep Learning Statistical Arbitrage☆242Updated 3 years ago
- experiments with pair trading☆321Updated 10 months ago
- Benchmark Dataset of Limit Order Book in China Markets☆213Updated 4 years ago
- Using tabular and deep reinforcement learning methods to infer optimal market making strategies☆225Updated 2 years ago
- ☆422Updated 4 years ago
- Code implementation of the Quantigic 101 Formulaic Alphas☆608Updated 6 years ago
- Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.☆238Updated 3 years ago
- GPU-accelerated Factors analysis library and Backtester☆745Updated 6 months ago
- High frequency trading (HFT) framework built for futures using machine learning and deep learning techniques☆512Updated 3 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.☆200Updated last year
- Market Making via Reinforcement Learning☆336Updated 5 years ago
- Avellaneda-Stoikov HFT market making algorithm implementation☆595Updated 2 years ago
- Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models☆452Updated 2 years ago
- High Frequency Market Making☆598Updated 2 years ago
- An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implemen…☆373Updated 7 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆124Updated 5 years ago
- GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hed…☆288Updated 4 years ago
- ☆353Updated 2 years ago
- Limit Order Book data analysis and modeling using LSTM network☆137Updated 6 years ago
- Performance analysis of predictive (alpha) stock factors☆494Updated last month
- Collection of algorithms for online portfolio selection☆836Updated last month
- Mining technical factors based on symbolic regression via genetic algorithm☆196Updated 2 years ago
- Transformers for limit order books☆116Updated 5 years ago
- Implementation of Reinforcement Learning in Pair Trading☆11Updated 3 months ago
- trend / momentum and other patterns in financial timeseries☆277Updated 4 years ago
- All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.☆763Updated last year
- World Quant 101 alphas的计算和策略化☆299Updated 8 years ago