If you like stocks and are careful with the way you spend your money, (me saying it seems counter-intuitive given that I bought GME at the peak, I know) you know how much time goes into buying shares of stock.
Check out the Gamestonk Terminal GitHub Link
Before Investing in Stocks, you need to:
… the list goes on.
Which led me to the idea during X'mas break to spend the time creating my own terminal. I introduce you to “Gamestonk Terminal” (probably should’ve sent 1 tweet every day to Elon Musk for copyright permission heh heh).
As someone mentioned, this is meant to be like a swiss army knife for finance.
My Gamestonk Terminal contains the following features/functionalities:
Discover New Stocks: Some features are: Top gainers; Sectors performance; upcoming earnings releases; top high shorted interest stocks; top stocks with low float; top orders on fidelity; and some SPAC websites with news/calendars.
Gauge Market Sentiment: Main features are: Scrolling through Reddit main posts, and most tickers mentions; Extracting trending symbols on stocktwits, or even stocktwit sentiment based on bull/bear flags; Twitter in-depth sentiment prediction using AI; Google mentions over time.
Research Web pages: List of good pages to do research on a stock, e.g. macroaxis, zacks, macrotrends, ..
Fundamental Analysis: Read financials from a company from Market Watch, Yahoo Finance, Alpha Vantage, and Financial Modeling Prep API. Since I only rely on free data, I added the information from all of these, so that the user can get it from the source it trusts the most. Also exports management team behind stock, along with their pages on Google, to speed up research process.
Technical Analysis: The usual technical indicators: sma, rsi, macd, adx, bbands, and more.
Due Diligence: It has several features that I found to be really useful. Some of them are: Latest news of the company; Analyst prices and ratings; Price target from several analysts plot over time vs stock price; Insider activity, and these timestamps marked on the stock price historical data; Latest SEC fillings; Short interest over time; A check for financial warnings based on Sean Seah book.
Prediction Techniques: The one I had more fun with. It tries to predict the stock price, from simple models like sma and arima to complex neural network models, like LSTM. The additional capability here is that all of these are easy to configure. Either through command line arguments, or even in form of a configuration file to define your NN. It also allows backtesting.
Reports: Allows you to run several jobs functionalities and write daily notes on a stock, so that you can assess what you thought about the stock in the past, to perform better decisions.
Comparitive Analysis: Allows you to compare different stocks.
On the ROADMAP: Cryptocurrencies, Portfolio Analysis, Credit Analysis. Feel free to add the features you'd like and we would happily work on it.
This project will always remain open-source, and the idea is that it can grow substantially over-time so that more and more people start taking advantage of it.
Feel free to contribute to the project.
Feedback is extremely welcome!