Inspiration
Two team members were interested in finances, so we decided to accept challenge from Thomson Reuters. Also two other team member were inspired by opportunities offered by DialogFlow.
What it does
Our bot takes human queries about the current quotes, statistics or forecasts of stock prices and currencies, and responds appropriately. The beauty is that you don't have to use special order of query - just send a message to a bot as if you sent it to your friend!
Also having a time series with changes in stock prices and using the least squares method to them, we constructed a regression line, which was used as a model to predict stock prices the next step.
How we built it
To proceed human-like queries we used DialogFlow from Google.
To get information about quotes and prices we used integration between DialogFlow, our own back-end system on Flask and given API by Thomson Reuters.
Challenges we ran into
It was first time all of us met DialogFlow, so it was challenging to set it up correctly for all our use-cases. Also we found difficult to build an integration between systems.
Accomplishments that we're proud of
We proud we made a real working bot, that you can use already!
What we learned
For 8 hours that we were building Stepka we learned a lot! DialogFlow, integration between systems, webhooks.
What's next for Stepka 1.0:
We also made a data analysis and tried to make a prognosis on stock prices using least squares method. Since we had not much time, we didn't integrate it to our bot, but we sure we can do it!
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