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stonks-scraper's Introduction

Stonks-Scraper

A personal project that tracks my personal investments and scrapes the internet for information on securities (stocks and funds) and cryptocurrencies. The idea of this project is to evaluate and compare different securities and cryptocurrencies with each other and find good sources of investments through the concept of value investing. The entire information is scraped using functions in Google Sheets and Google Script due to its interactivity with Google Finance API. Additional functions in Google Sheets (IMPORTHTML and IMPORTXML) are used to supplement additional data by scraping information that is not found in Google Finance from other financial tracking websites. A Jupyter Notebook containing the fbprophet library is used to forecast future prices of any security or cryptocurrency in the Yahoo Finance API database.

Potential idea expansion: Apply other ML models like Linear Regression, SVM, Random Forest etc to predict future value, Monte Carlo simulation and solver analysis to graph the Efficient Frontier and find the best investment portfolio with highest potential returns and lowest risk via the Sharpe Ratio.

Websites Scraped:

  1. https://www.google.com/finance/
  2. https://finance.yahoo.com/
  3. https://finviz.com/
  4. https://www.marketwatch.com/

Other Websites Referenced:

  1. https://companiesmarketcap.com/
  2. https://coinmarketcap.com/
  3. https://www.coingecko.com/en

Google Sheets

  • Description: This Google Sheet tracks my personal investments and contains the overall portfolio summary (with data visualizations) and the ledger that contains my buying and selling transactions. This sheet also has a Google Script attached to it that automates my position for each security and cryptocurrency every time I update the sheet with a new transaction.
  • Description: This Google Sheet scrapes information about various stocks, and organized it based on their sectors. The Control Panel tab dictates which sector of stocks will be viewed based on user choice, and the Stocks Analyses tab display the list of stocks that matches the sector choice and the stocks' associated information, supported with data visualizations.
  • Description: This Google Sheet scrapes information about various mutual, index, and exchange-traded funds and organized them based on their type (Equity, Money Market, etc), and sub-type (Large-cap, sector-based, etc). The Control Panel tab dictates which umbrella of funds will be viewed based on user choice, and the Funds Analyses tab display the list of funds that matches that filter choice and the fund's associated information, supported with data visualizations. The Deep Dive tab scrapes information about a chosen fund's portfolio and its exact distribution of securities. This sheet also has a Google Script attached to it that serves to dynamically change the bordering of the tables on the Deep Dive tab whenever the fund ticker is changed.
  • Description: This Google Sheet scrapes information about various cryptocurrencies and display their associated information, supported with data visualizations. This sheet also has a Google Script attached to it that automatically sorts the crypto tickers according to their market capitalization value in ascending order.
  • Description: This Google Sheet scrapes information about a company's financial statements and calculates its intrinsic value based on certain assumptions through various models (DCF, DDM, and EPS). The purpose of this sheet is to determine the valuation of a stock based on a reasonable margin of safety and help me decide if a particular stock is a good buy or not. This sheet is used in conjunction with the Technical Analysis Dashboard to determine if and when a stock is a good buy.
  • Description: This Google Sheet scrapes the Google Finance API for any security in its database and pulls the historical price and volume of that security from any time period and calculates various technical indicators that is then mapped into charts in a dashboard. The purpose of this sheet is to determine optimal buy and sell signals for a certain security and is used in conjunction with the Fundamental Analysis Calculator to determine if and when a stock is a good buy.

Jupyter Notebooks

Machine Learning Analysis

  • Time-series Analysis using fbprophet.ipynb: A notebook that utilizes the fbprophet library to forecast future data on a security or cryptocurrency based on its historical data, taking into account seasonality in the calculations.

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