nymath / torchqtmLinks
TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative financial analysis.
☆50Updated 2 years ago
Alternatives and similar repositories for torchqtm
Users that are interested in torchqtm are comparing it to the libraries listed below
Sorting:
- X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies☆86Updated last year
- This repo contains some codes and outputs of my implementation of DeepLOB model.☆90Updated 4 years ago
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆94Updated 2 years ago
- HFT & Stochastic control numerical implementations from "Optimal high frequency trading with limit and market orders" (GUILBAUD & PHAM)☆36Updated last year
- Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio…☆137Updated 3 years ago
- Literature survey of order execution strategies implemented in python☆44Updated 5 years ago
- 🚂💨 Deep Momentum Networks for Time Series Strategies☆125Updated 5 years ago
- Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'☆59Updated 2 years ago
- A genetic programming algorithm used for generating alpha factors in the multi-factor investment strategy☆66Updated 5 years ago
- alpha投研示例☆88Updated 3 months ago
- Implementing 'Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation' based on …☆14Updated 2 years ago
- High Frequency Analysis Based On Level-2 Data(Limit Order Book& Transaction Data)☆113Updated last year
- High Frequency Trading Strategies☆48Updated 8 years ago
- Calibrates microprice model to BitMEX quote data☆61Updated 4 years ago
- Notes on Advances in Financial Machine Learning☆82Updated 7 years ago
- Backtest result archive for Momentum Trading Strategies☆65Updated 6 years ago
- LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data. 🤖📈☆115Updated last year
- Here I go through the processing of prototyping a mean reversion trading strategy using statistical concepts, then test it in backtrader.☆69Updated 3 years ago
- ☆123Updated 8 years ago
- ☆53Updated 4 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
- ☆32Updated 2 years ago
- CS7641 Team project☆97Updated 5 years ago
- Pytorch implementation of TransLOB from Transformer for limit order books☆29Updated 2 years ago
- Some Python codes for explorating High Frequency Data, Generating and Estimating Hawkes Processes and Simulating Limit Order Books.☆50Updated 5 years ago
- Implementation of HFT backtesting simulator and Stoikov strategy☆141Updated 2 years ago
- ☆208Updated 2 years ago
- The Short-Term Predictability of Returns in Order Book Markets: A Deep Learning Perspective.☆58Updated 2 years ago
- A study on volume-price factor stock selection model based on wavelet transform and multitask self-attention network☆96Updated 7 months ago
- ☆65Updated 11 months ago