Empyrial VS The-Oracle

Compare Empyrial vs The-Oracle and see what are their differences.

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Empyrial The-Oracle
7 9
864 30
- -
8.1 5.1
3 months ago over 2 years ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Empyrial

Posts with mentions or reviews of Empyrial. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-15.

The-Oracle

Posts with mentions or reviews of The-Oracle. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-29.

What are some alternatives?

When comparing Empyrial and The-Oracle you can also consider the following projects:

Riskfolio-Lib - Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

goplan-app - An intuitive portfolio mangaer !

quantstats - Portfolio analytics for quants, written in Python

Statmetrics-Android - Mobile App Solution for Portfolio Analytics and Investment Management

alphalens - Performance analysis of predictive (alpha) stock factors

market-monitor - Monitor tool for stocks and cryptocurrencies that includes twitter sentiment analysis on key accounts

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

Beibo - 🤖 Predict the stock market with AI 用AI预测股票市场

Finance - Study resources for quantitative finance

Stock-Prediction-Neural-Network-and-Machine-Learning-Examples - Examples of python neural net and ML stock prediction methods with sample stock data.