Fl.ock

Inspiration

We were inspired by Rain Mann, a previous hackMIT project, which used weather data to inform stock trading decisions.

What it does

It found a strong positive correlation between flight traffic and stock values over the past 7 years, and then will use that correlation along with current flight data to inform stock trading decisions.

How we built it

We took stock data from alphaventure and flight data from amadeus and graphed them both separately and together to show that there's a relatively strong positive correlation between the two variables, and then aggregated real-time flight data that we would then use to determine trading decisions

Challenges we ran into

Figuring out how to use APIs and incorporate the data we need was definitely a challenge.

Accomplishments that we're proud of

We're proud of the website that we built, figuring out how to successfully get the data we need from the larger pools that we found, and learning how to create visual representations of that data.

What we learned

We learned how to use APIs, plot graphs in python, use dictionaries and convert dictionaries into lists, and more.

What's next for Fl.ock

The next step would be incorporating a Markov Chain so that we can have a legitimate prediction system that could actually have a good hand at predicting stock patterns

Built With

• amadeus
• html
• python