Stock Forecasting - Addepar

Background experience in various stock exchanges was the driving factor behind choosing this

Forecasts trends in different stock indices worldwide and recommends to investors which index they should opt in/out of. To forecast, the model takes into consideration the past trends in close, volume, month and GDP, which was gathered from a different dataset.

Gathered stock index data corresponding to every day of the year for the years 2010-2022. This included Open, Close, Adj. Close, High, Low, Volume, Date.

The other dataset used corresponded to GDP of each country. This was used to obtain the GDP of the country which each index belonged to and account for that in the forecast

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Stock Forecasting - Addepar

Built With

• lstm
• python
• sklearn