[🕹️] Created notebook to Analyze Market Volatility Using Historical Data

[manya706]

closes #6718

Analyze Market Volatility Using Historical Data

This pull request adds a new notebook for analyzing market volatility using historical stock data with the OpenBB. It includes data retrieval for multiple stocks, along with various visualizations such as scatter plots, box plots, and Bollinger Bands to enhance understanding of stock performance and volatility.

[CLAassistant]

All committers have signed the CLA.

[deeleeramone]

This entire block can be consolidated as:

symbols = ["AAPL", "GOOG", "MSFT", "NVDA"]
data = obb.equity.price.historical(symbol=symbols, start_date="2010-01-01", provider="yfinance")
df = data.to_df()

[deeleeramone]

We can also use the openbb-charting extension to make interactive charts with Plotly. But, I understand if you just want consistency throughout all the charts.

# `data` is the original response object.
# pip install openbb-charting

df = data.to_df().pivot(columns="symbol", values="close")
data.charting.to_chart(
    data=df,
    y=df.columns.tolist(),
    title="Historical Closing Price",
    scatter_kwargs=dict(hovertemplate="<b>$%{y}</b>")
)

[manya706]

hey! i tried using this but it was causing some problems with either my python environment or dependencies, it wasn't
recognizing openbb-charting

[deeleeramone]

This chart is a little funky, can we present this differently?

[manya706]

sure! i'll make the changes and update it. thanks for the feedback :)

[deeleeramone]

Hello, and thanks for jumping in and contributing!

I left a couple of comments with suggestions. Additionally, can you please take a look at the deprecation warnings generated by some Pandas syntax? If we can avoid any, we should.

Thanks!