QuantJourneyOrg / qj_technical_indicatorsLinks
High-performance technical indicators library for financial analysis, optimized with Numba
☆12Updated 3 months ago
Alternatives and similar repositories for qj_technical_indicators
Users that are interested in qj_technical_indicators are comparing it to the libraries listed below
Sorting:
- Implementing a comprehensive Quantitative Momentum Strategy to optimize portfolio allocation. The strategy integrates two key financial i…☆14Updated 2 years ago
- This project implements an advanced pairs trading strategy using statistical arbitrage techniques. It leverages Bayesian optimization to …☆42Updated last year
- Financial AI with Python☆99Updated 2 months ago
- Navigating Markets with Intelligent Exploration.☆29Updated 5 months ago
- ☆153Updated 2 years ago
- ☆141Updated 2 years ago
- Quantreo's Quant Library☆88Updated 3 months ago
- Created a continuous, homogeneous, and structured 10 GB dataset from self obtained collections of unstructured intraday financial data. G…☆75Updated 5 years ago
- The toolbox for developing systematic trading strategies. It includes datasets and strategy ideas to assist in developing and backtesting…☆49Updated this week
- An investment portfolio of stocks is created using Long Short-Term Memory (LSTM) stock price prediction and optimized weights. The perfor…☆34Updated 2 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.☆216Updated last year
- A dockerized Jupyter quant research environment.☆230Updated this week
- ☆51Updated last year
- To classify trades into buyer- and seller-initiated.☆154Updated 3 years ago
- A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.☆58Updated 2 years ago
- A sentiment analyzer package for financial assets and securities utilizing GPT models.☆190Updated last year
- This repository is used to extract the constituents of ETFs into a pandas DataFrame which could be used for further data exploration.☆27Updated last month
- Features and labels engineering of raw data of quotes of several stocks.☆32Updated 6 years ago
- Feature Engineering and Feature Importance in Machine Learning for Financial Markets☆195Updated last year
- Entropy Pooling views and stress-testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.☆281Updated this week
- Time Series Prediction of Volume in LOB☆60Updated last year
- Python library for asset pricing☆126Updated last year
- Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices☆122Updated 3 months ago
- Realtime Algorithmic Trading Using Deep Reinforcement Learning☆39Updated 11 months ago
- mbt_gym is a module which provides a suite of gym environments for training reinforcement learning (RL) agents to solve model-based high-…☆167Updated 2 years ago
- Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.☆124Updated 2 years ago
- calculates standard deviation from OHLCV data☆14Updated 2 years ago
- Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.☆140Updated last year
- Code base for the meta-labeling papers published with the Journal of Financial Data Science☆97Updated 2 years ago
- Montecarlo simulations/analysis for finance (equity simulator)☆50Updated 2 years ago