Riskalyze

Do you want to make money fast? Well Riskalyze is a beginner friendly investing risk analysis platform that can help start your investing career!

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Inspiration

As many members in our group are inexperienced with investing in general, we thought it would be great experience to learn about investing and to make it easier for others also lacking investment experience and know-how. We set out to conquer the Goldman-Sachs and Capital One challenges and create a tool that would be not only useful to us, but many in the community!

What it does

Riskalyze is a risk analysis platform first! Our data models aid users in selecting assets appropriate for the risk/reward ratio they are comfortable with. In this volatile, and recently downward trending market, it's imperative that new investors are not discouraged by loss.

How we built it

Our tech stack leverages the React JavaScript library for responsible frontend design. This is aided by the Formik and Material UI plugins that allow us to craft a functional UI that looks good with a relatively low amount of effort.

The backend is a Node.js server using the Express framework to easily handle server-side computation, and expose REST API endpoints for the frontend to connect to. This is paired with a MongoDB server for rapid development of our data models.

We containerized the backend services in Docker containers to allow for easy configuration, deployment, and scaling of our critical services. This model ensures we encounter fewer issues deploying server side code at scale.

Using flexible and easy-to-use technologies was critical for success in this event. With less than 24 hours to write and entire application, moving quickly and spending less time re-factoring and making infrastructure changes is a must!

Challenges we ran into

By far the most challenging part of this Hackathon was sourcing a reliable API to pull market data from. The free APIs that we tried gave is problems with rate limiting and high latency. Once me moved to a paid API platform, our data collection became a much more manageable task.

In addition to the technical challenges, we also faced the issue of a limited understanding of statistical models used for market analysis. We spent a lot of time researching and testing different ways to model our data.

Accomplishments that we're proud of

By the end of the Hack, we were able to create our own models for the risk of publicly traded stocks, cryptocurrencies, and foreign exchange markets relative to the market average. This will aid our users in selecting assets that are best suited for their risk tolerance.

What we learned

We learned a ton of information about financing and investing. Going through many articles on these topics, we learned a lot about asset classes and their differences, how to compute the risk of assets, and how to diversify a portfolio to hedge against losses.

What's next for Riskalyze

In the future, Riskalyze would like to provide guides about how the different asset classes and market spaces work in order to better educate the end user on the underlying systems behind their investments. Riskalyze would also like to provide users with a questionnaire to provide better data to users based on their risk tolerance, liquidity needs, and overall fiscal goals. Overall, we would love to create a beginner friendly platform for investors of all ages!

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