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TimeSerie analysis for stock volatility forecast and DTW clustering

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TimeSerie analysis for stock volatility forecast and DTW clustering

Part 1: Timeserie analysis and forecast of US drugs and pharmacies monthly sales

This notebook intends to illustrate a few techniques and models to analyze TimeSeries and make forecast predictions.

Part 2: Stock volatility analysis and forecast

This notebook illustrates how TimeSerie analysis and modelization can be used to evaluate and forecast volatility trends in Stocks, index, bonds or any financial products.

Part 3: Dynamic Time Warping analysis for unsupervised Stock clustering

The goal of this notebook is to evaluate TimeSeries similitudes for a large number of stocks (either manually selected or from the S&P500) and cluster those Timeseries using Dynamic Time Warping into a given number (predefined) of clusters.

Note: The S&P500 (Standard and Poor's 500) stock market index is tracking the stock performance of 500 large companies listed on exchanges in the United States.

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