fooltrader
Empyrial
| fooltrader | Empyrial | |
|---|---|---|
| 1 | 7 | |
| 1,124 | 864 | |
| - | - | |
| 0.0 | 8.1 | |
| 12 months ago | 3 months ago | |
| Python | Python | |
| MIT License | MIT License |
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fooltrader
Empyrial
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Are there any good tools for Quantitative analysis of stocks ?
I created a python library called Empyrial (https://github.com/ssantoshp/Empyrial) might help for doing that. Tell me what you think about it and don't hesitate to DM me ;)
- Empyrial, Python library for portfolio risk and performance analysis
- Empyrial, portfolio management library for portfolio risk and performance analysis
- Empyrial makes portfolio management and analysis faster and easier
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What are the top Python finance libraries?
I created a python library called Trafalgar which has for goal to help to make quantitative and portfolio analysis. You can check it out here : https://github.com/ssantoshp/trafalgar
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Trafalgar: a python library to make quantitative finance and portfolio analysis faster and easier
Thanks, yes I'm planning it but for the moment I don't think it's my priority on this project you can just download the file and type pip install + the file name. You can find more info about how to download in the article or here: https://github.com/ssantoshp/trafalgar.
What are some alternatives?
financial-machine-learning - A curated list of practical financial machine learning tools and applications.
Riskfolio-Lib - Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
zvt - modular quant framework.
quantstats - Portfolio analytics for quants, written in Python
Stock-Market-Sentiment-Analysis - Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka
alphalens - Performance analysis of predictive (alpha) stock factors
senate-stock-watcher-data - Data repository of JSON files that are filed by US Senators on efdsearch.senate.gov where they must report their stock trades. This is the same data as on senatestockwatcher.com
goplan-app - An intuitive portfolio mangaer !
The-Oracle - 🤖 Predict the stock market with AI 用AI预测股票市场 [Moved to: https://github.com/ssantoshp/Beibo]
Finance - Study resources for quantitative finance
Statmetrics-Android - Mobile App Solution for Portfolio Analytics and Investment Management
option-pricer - Option pricing using Black-Scholes model, Bachelier model, Binomial Trees and Monte Carlo simulation under different stochastic processes