6. Portfolio Simulation
In this video tutorial we will see how we can simulate a simple equally weighted portfolio of our basket of stocks backwards in time.
Tutorial videos, posts, and instructions on using finance data in SuperSet
In this video tutorial we will see how we can simulate a simple equally weighted portfolio of our basket of stocks backwards in time.
In this video tutorial we will look at stocks that have grown the most since 2020. We can further filter stocks by current market capitalization, and sort them in descending order.
In this video we will create a top down chart of all publicly available stocks in the Tesseract Analytics database and plot them against each other by their last stock price, and earnings per share (EPS) to find a relationship between how company stocks are prices, and their profitability.
In this video tutorial we will briefly analyze META, previously known as Facebook. We will create different charts looking at stock price, market capitalization, net income, revenue, cash flows, assets and liabilities.
In this video we will learn how to create a list of all the companies available in the Tesseract Analytics Apache SuperSet dataset, how to filter and search for the company that we are interested in. Then how to find if there is more than one stock symbol associated with that company, how to plot the stock prices of those symbols, and EPS (Earnings Per Share). Then we will validate that data against SEC Edgar reports to data quality validation.
In this tutorial we will learn how to register, log-in to Apache SuperSet, and connect to the Quarterly Finance data-set. We will then create a simple graphical chart as an example.
As the first blog post, I would first highly recommend going through the Apache SuperSet tutorials on YouTube and learning how to use the tool.
You will also learn how to use the tool through our tutorials, but they are more focused on understanding the data rather than using Apache SuperSet.