This is a python enabled command line interface that analyzes the performance of an exchange-traded fund (ETF) portfolio.
Lately,due to technology disruption investors are more inclined to passive investing.Passive investing is a buy and hold portfolio stretegy for long term investment with minimal trading in the market.Investors invest in a basket of assets like stocks or bonds called exchange traded fund(ETF).Exchange traded funds let you invest in lots of securities all at once,adds more diversification and are traded more easily too. It saves your time researching individual stocks or companies or take risk of investing in a single stock.
This analysis consists of:
A Jupyter notebook that contains the following:
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AN analysis of the ETF data that a SQL database stores
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Interactive visualizations
A video of the web application created by deploying Jupyter notebook via the Voilà library
The Fintech ETF consists of four stocks: GOST, GS, PYPL, and SQ. To analyze the performance of the ETF the following tasks are perfomed:
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Analyzing a single asset in the ETF,
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Optimizing data access with Advanced SQL queries,
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Analyzing the ETF portfolio; and
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Deploying the notebook as a web application.
This project runs on python 3.7 and includes the following libraries and dependencies:
- Pandas
- Numpy
- hvPlot
- sqlalchemy
- SQL
- Jupyter Notebook
- Voilà
To use the application you need to install the following dependencies.
pip install SQLAlchemy
conda install -c pyviz hvplot
conda install -c conda-forge voila
When the installation completes, confirm it by running the following command:
conda list sqlalchemy
conda list hvplot
conda list voila
- Make sure to use hvPlot version 0.7.0 or later.
To use this application just clone the repository and run the jupyterlab by running the following command on your terminal:
jupyterlab
Upon launching the application on jupyter lab run the file by clicking on the play button on top of the notebook.
Screen.Recording.2022-07-31.at.6.47.53.PM.mov
Manisha Lal
07/31/2022
copyright 2022