Journey

Inspiration

Everyone understands that predicting the future of investment can be a real hurdle in managing risk in a portfolio; however, few understand the sheer volume of factors that go into determining the risk of a portfolio, including the separate factors that affect risk for savings, bonds, stocks, real estate, and more. A lot of people utilize a few factors in determining the future of their investments, so we wanted to create an app that analyzes the risk level of a portfolio from as many perspectives as possible.

What it does

We ask the user questions about the distribution of their investments as well as the specifics of each asset. Using this data, we are able to quantify the risk level, from 1-10, associated with an investor's portfolio. Then, we analyze the user's risk tolerance with a short, guided questionnaire, and compare the risk level of the user's portfolio to their risk tolerance. If a major discrepancy is found, then we recommend investing in either safer or riskier assets based on whether risk tolerance is lower or higher than the risk level of their portfolio.

How we built it

We programmed the app in R and C++ and then used multiple APIs and databases to draw our data to analyze risk level of portfolio. We also used blood, sweat, tears, and a major lack of sleep to bring this into fruition :)

Challenges we ran into

A lot of APIs and databases were blocked by a paywall, so we had to make do with what data we could scrounge up. We also wanted to implement as many factors in determining risk as possible, but we did not have the time to implement everything we wanted to.

Accomplishments that we're proud of

We are proud that we were able to create a rather successful algorithm in determining risk of a portfolio; particularly, we are proud that the risk of a portfolio was determined by a wide array of factors and considerations.

What we learned

We learned that inputting large streams of data is harder than it looks (especially if you don't have money to spend on APIs!). We also learned that determining risk is incredibly complicated; the more factors that one considers, the more nuanced and accurate their prediction of risk will be.

What's next for Journey

Given more time, we plan to clean up our app by adding a wider array of factors considered. In a perfect world, we would have to ask the user for as little information as possible and and determine the risk level by pulling each factor's data from an API, database, or the web. We would like to incorporate as many factors in risk determination as possible, including risk of the company's products becoming obsolete, measuring the publicity level of the company, measuring the company's credit rating, and more.