Volatility Viewer

Federal Funds Rate Data
Historic CPI Data
CPI vs Volatility Data
S&P500 and Volatility Correlation
About Page

Inspiration

2022 is an unprecedented year in financial markets, from FED hikes, to rapidly climbing interest rates, and pandemic recovery. Learning about market volatility is now more important than ever. We hope Volatility Viewer serves as a window into volatility studies.

What it does

Volatility Viewer is a data visualization and exploration platform that aims to educate investors about market volatility and its impacts along with insights on how volatility can alter their own portfolio management.

How we built it

Frontend: Dash + Plotly

We used Python’s Dash along with Plotly to create a visually appealing UI with fully interactive and extendable studies that showcase various financial data.

Theming: Bootstrap

We used Bootstrap to create responsive UI elements and reusable components.

Data processing: Pandas/Numpy/Matplotlib/Statsmodels

We procured and analyzed publicly available financial data on the Consumer Price Index (CPI), the federal funds rate, and equity markets to model the role of important economic indicators on market volatility.

Challenges we ran into

One of the key technical challenges we faced on the front end was allowing user interaction with graphs and getting our UI to respond dynamically to user inputs on multiple pages. Furthermore, we struggled and gained much experience in a first endeavor with data processing and analysis in Python.

Accomplishments that we're proud of

We are proud to have created a scalable, visually appealing, and interactive financial dashboard for studying the behavior of market volatility from the eyes of an investor. We are proud to be able to contribute a unique, open-source software for analyzing financial data.

What we learned

We gained much experience in using Python for data processing, static visualization, and data analysis using well-known Python packages such as Pandas, NumPy, and Statsmodels. Furthermore, we gained much experience in front-end visualization and responsive design by gaining experience in creating dashboards with Dash and Plotly. Lastly, we gained experience in financial literature and vocabulary.

What's next for Volatility Viewer

Up next for Volatility Viewer, we hope to incorporate real-time updates and analytics. With more time, we hope to involve more advanced financial models and procure more granular financial data.