analysis-sharing VS zvt

Compare analysis-sharing vs zvt and see what are their differences.

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analysis-sharing zvt
1 1
45 2,930
- 4.3%
6.2 5.5
3 months ago 7 days ago
Jupyter Notebook 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.

analysis-sharing

Posts with mentions or reviews of analysis-sharing. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning analysis-sharing yet.
Tracking mentions began in Dec 2020.

zvt

Posts with mentions or reviews of zvt. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-09.

What are some alternatives?

When comparing analysis-sharing and zvt you can also consider the following projects:

Algo-Trading - This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it!

MachineLearningStocks - Using python and scikit-learn to make stock predictions

awesome-systematic-trading - A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资

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

awesome-systematic-trading - A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading. [Moved to: https://github.com/paperswithbacktest/awesome-systematic-trading]

FinanceExamplesPy - Financial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir). [Moved to: https://github.com/mrtkp9993/QuantitaveFinanceExamplesPy]

fwoba - Frequency Weighted OrderBook Analysis

streamlit-stock-performance - Analyze financial instruments' past performances with a just few clicks.

TAcharts - Apply popular TA tools and charts to candlestick data with NumPy.

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

dwxconnect - Seamlessly link any Trading Strategy in ANY programming language to Darwinex liquidity via MetaTrader 4 or 5. DWX Connect is your very own, fully customizable Trading API!

Stock.Indicators - Stock Indicators for .NET is a C# NuGet package that transforms raw equity, commodity, forex, or cryptocurrency financial market price quotes into technical indicators and trading insights. You'll need this essential data in the investment tools that you're building for algorithmic trading, technical analysis, machine learning, or visual charting.