In this challenge, I used data preparation, analysis and visualization techniques to gather insights into Google Trends for Mercado Libre ($MELI) and compare them to the stock's price and volatility trends.
Later, I developed two time series model using Facebook Prophet.
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A model to forecast future search trends of Mercado Libre.
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A model to produce a daily sales forecast for the next quarter.
pandas - For data structuring and analysis.
hvplot - For interactive visualizations
fbprophet - For time series forecasting
1- Manipulated time series data by using Pandas.
2- Built time series models, including ones that can make predictions across different time frequencies or time zones.
3- Visualized and analyzed time series data for decision making.
4- Analyzed time series data by using correlation to recognize and quantify relationships.
5- Identified seasonal patterns in time series data.
6- Performed time series forecasting by creating models to predict the future.
Aquiba Benarroch, CFA aquiba.me