|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Moneymanagerex||1,315||16 hours ago||325||gpl-2.0||C++|
|Money Manager Ex is an easy to use, money management application built with wxWidgets|
|A fast, simple and cross-platform(html5 react-native weex wechat-applet) stock chart library created using canvas.|
|Reddit Sentiment Analysis||203||2 days ago||mit||Python|
|This program goes thru reddit, finds the most mentioned tickers and uses Vader SentimentIntensityAnalyzer to calculate the ticker compound value.|
|Open Source Option Analytics Platform.|
|Stocksensation||146||4 years ago||1||apache-2.0||Python|
|Dash Stock Tickers Demo App||123||a year ago||10||mit||CSS|
|Dash Demo App - Stock Tickers|
|Stock Market Prediction Via Google Trends||38||a year ago||1||mit||Python|
|Attempt to predict future stock prices based on Google Trends data.|
|Stock Option Analytics||21||a year ago||7||Python|
|Stocks and options picking. Tries to contain predictive analytics, recommendations, and calculators.|
|Tutorials||19||4 years ago||Jupyter Notebook|
|Machine Learning Tutorials & Fundamentals|
|Canvas Desktop||19||2 months ago||mit||C#|
|Cross-platform real-time financial charts for Desktop apps with built-in pan and zoom support.|
Project source can be downloaded from https://github.com/SBZed/Stock-Market-Analysis.git
Investment Bankers, CA's, Hedge Fund / Portfolio Managers, Forex traders, Commodities Analysts.
These have been historically considered to be among the most coveted professions of all time. Yet, if one fails to keep up with the demands of the day, one would find one's skills to be obsolete in this era of data analysis. Data Science has inarguably been the hottest domain of the decade, asserting its need in every single sphere of corporate life. It was not long ago when we discovered the massive potential of incorporating ML/AI in the financial world. Now, the very idea of the two being disjointed sounds strange. Data Science has been incremental in providing powerful insights ( which people didn't even know existed ) and helped massively increase efficiency, helping everyone from a scalp trader to a long term debt investor. Accurate predictions, unbiased analysis, powerful tools that run through millions of rows of data in the blink of an eye have transformed the industry in ways we could've never imagined.
If you are new to Python,This YouTube series is best for you.
Basics of Financial Markets:
The very first step in solving a problem is understanding the problem. To tackle the questions and problem statements that await us, it's suggested that you first go through above link (it's a PDF "Basics of Financial Markets" documentation) and get introduced to the basic concepts that we'd coming across in the following modules to come.
Introduction to Stock Markets:
Now read and understand Chapter 6,7 and 8 from this link.
The Stock Market Documentary:
If you Don't know what is stock markets, how it works and want to know about it for fun. Then check out this documentary.
All Stock Datadirectory.
. ... Module # Each Module/Topic/Chapter Questions # Queries/Questions related to chapter | | .ipynb # Questions Jupyter notebook Solutions # Solved Queries - Answers to all Questions | | .ipynb # Questions Jupyter notebook | | .csv # CSV file / Dataset for stocks | images # Images used in Jupyter notebook, Just for seek of representation Resource Matrial # Different reference matrial(txt, doc, pdf) ...
All other known bugs and fixes can be sent to "[email protected]" with the subject "stock market analysis Suggestion". Reported bugs/fixes will be submitted to correction.