This project analyzes the stocks in the S&P500 Securities Fund and recommends the top 50 stocks based on various evaluation metrics including Quantitative Momentum, Quantitative Value, Financials (balance sheet, income statement, and cash flow), Analyst Consensus, and Sentiment in news headlines. Final output is an excel spreadsheet with stock information and algorithm scores.
Key concepts used: Rest APIs, Data Analysis, Web Scraping (using BeautifulSoup), NLP, and Machine Learning with Stacked LSTM model.
Get values for stock symbol from various endpoints
GET /stock/{symbol}/quote/
GET /stock/{symbol}/stats/
GET /stock/{symbol}/financials/
GET /time-series/CORE_ESTIMATES/{symbol?}| Parameter | Type | Description |
|---|---|---|
{symbol} |
string |
Required. Ticker of stock |
Get close and open prices for stock symbol
GET daily/<ticker>/prices| Parameter | Type | Description |
|---|---|---|
<ticker> |
string |
Required. Ticker of stock |
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Install python 3 and pycharm from cmd
$ sudo snap install pycharm-community --classic msiexec /i python<version>.msi
- Sample Stock Forecast Chart
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Sample Excel Output Snip