Asset Analyzer — Analyzing Financial Products

3 min readApr 13, 2022


This project was carried out as part of the TechLabs “Digital Shaper Program” in Münster (winter term 2021/22).


The stock market is characterized by ups and downs of share prices. The goal was to develop a tool to analyze and compare different financial products. The tool should allow variable inputs of the selection time and output the data in real time. In a first step an interface to Yahoo Finance was created to extract the data. Afterwards the information was stored and the desired data got displayed in a chart.


Why invest? High inflation rates and low interest rates should lead to a rethink of one’s financial situation. Investing is a good way to put your money to work and grow your wealth over the long term. The capital market offers countless opportunities to invest your money profitably. But which products have been profitable? And how did certain circumstances affect share prices?
To address these questions, we wanted to develop a tool for analyzing and predicting share prices. This should primarily output the development of different share prices in real time. Furthermore, there should be the variable possibility to compare several financial products with each other by entering the symbol of the desired shares.
In the next step, various circumstances should be identified that can have an influence on the courses. This data subsequently can be used to check whether recurring events have the same effect on a particular course. Accordingly, a forecast of share prices should then be drawn up.


The present project was completed with the help of the Data Science track.
The program Visual Studio Code was used for the implementation. This source code editor supports the programming language Python, which was used for programming. In addition, the program offered the possibility of integrating the code hosting platform GitHub. This gave us the possibility to program collaboratively on one project.
Regarding the procedure, at first, the corresponding data needed to be imported. The data was extracted from Yahoo Finance, which is one of the most popular finance websites, providing extensive information about most of the listed financial products. Therefore, the Yahoo Finance API was implemented. This was set up so that sharing the project was possible without passing the private key. In addition, a json package was imported. This allowed a conversion from the text into a Python dictionary. At the very beginning, the symbols, respectively our financial products, needed to be selected and the possibility to determine the selection period was implemented. Theoretically, countless stocks can be picked and the data selection time can stretch over hours or the entire term. Now the data can be plotted. In this context, matplotlib gives us the opportunity to show the plots. In addition, the seaborn style was selected as a suitable design. Furthermore, a method for adding each symbol to the plot was implemented. Finally, the diagram can be plotted and will pop up in an additional window.

Result of the Project

Result of the project is a tool which compares any number of financial products. This allows the user to visualize a huge comparison in one surface and output the data in real time. Furthermore, the tool enables a quick adjustment of the data selection period and correspondingly the amount of data.
Unfortunately, there was not enough time to finish the project by myself. Therefore, the product is only a tool which compares different financial products. In a next step, data about different internal and external circumstances need to be extracted and analyzed. With the help of the Deep Learning track, an algorithm to forecast courses under the given conditions can be developed.

The team

Marcel Gößling Data Science (LinkedIn)

Roles inside the team

Since all members chose the Data Science Track, the tasks could have been split evenly.

Envisaged allocation of tasks:

  • Establish interface and encrypt API
  • Import and store data
  • Plot chart

Unfortunately, all other members have cancelled the project due to time constraints.


Marcus Cramer




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