DataStacks

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Portfolio Analysis
Finance Introduction
Risk Analysis

Inspiration

DataStacks was inspired by other dashboard-based solutions, such as Databricks and Snowflake. However, not many Risk-Analysis focused platforms exist, and we wanted to create a robust model to address the complexities involved in it.

What it does

DataStacks is a comprehensive data platform that utilizes a full-fledged, complex mathematical model to forecast the risk predictions for a given user's portfolio.

On a more technical level,

Calculating Risk

We measure volatility of assets using Average True Range(ATR) values.

Risk Parity Portfolio:

We optimize dollar weightage to have a balanced-risk portfolio, also known as an Equal Risk Contribution Portfolio.

In doing these, we visualize risk and show how to maximize profits while minimizing risk, and thus reduce a heavy burden for the everyday person - finding out which financial vehicles to invest in.

How we built it

We used scipy for numerical analysis, the AlphaVantage API for stock information, Streamlit for the frontend, and pure Python for the backend. Images and assets were drawn in Inkscape.

Accomplishments that we're proud of

We haven't worked in quantitative analysis or financial technology before. As a result, it was an endeavor learning about how risk analysis is calculated. We're proud to have learnt quite a bit in less than 24 hours.

Challenges we ran into/What we learned

We learnt and built a mathematical model that uses optimizations for mathematical analysis. Somehow, that was easier than learning React JavaScript in a day! 😅

We also learnt that React isn't the only frontend alternative out there; Streamlit proved to be more than beneficial to our cause, being able to integrate with standard Python.

What's next for DataStacks

We hope to use more accurate models; hopefully ones that don't come with a hefty price tag! Also, a general market analytics dashboard would be very helpful.