secref-data VS FinanceToolkit

Compare secref-data vs FinanceToolkit and see what are their differences.

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secref-data FinanceToolkit
1 63
24 2,397
- -
10.0 9.7
over 2 years ago 17 days ago
JavaScript Python
Apache License 2.0 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.

secref-data

Posts with mentions or reviews of secref-data. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-08.

FinanceToolkit

Posts with mentions or reviews of FinanceToolkit. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-17.

What are some alternatives?

When comparing secref-data and FinanceToolkit you can also consider the following projects:

FinanceDatabase - This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.

yfinance - Download market data from Yahoo! Finance's API

AlgorithmicTrading - This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.

OpenBBTerminal - Investment Research for Everyone, Everywhere.

fundamental-analysis - Screen stocks on fundamentals and estimate their intrinsic value

langchain-stock-screener - LangChain agent usable tool to screen stock data

FundamentalAnalysis - Transparent and Efficient Financial Analysis [Moved to: https://github.com/JerBouma/FinanceToolkit]

financial-machine-learning - A curated list of practical financial machine learning tools and applications.

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