<jupyter_start><jupyter_text><a  href="https://colab.research.google.com/github/LearnPythonWithRune/FinancialDataAnalysisWithPython/blob/main/colab/starter/06 - Simple Calculations - Volatility, SMA, and EMA.ipynb" target="_parent"><img  src="https://colab.research.google.com/assets/colab-badge.svg"alt="Open In Colab"/>  Calculating simple - Pct change- Log returns- Standard deviation (Volatility)- Rolling    - Simple Moving Avarage    - Exponential Moving Average  Standard deviation- $\sigma_{p} = \sigma_{daily}\times \sqrt{p}$- $\sigma_{annually} = \sigma_{daily}\times \sqrt{252}$     *(252 trading days per year)*<jupyter_code>import pandas as pd
import matplotlib.pyplot as plt
%matplotlib notebook
remote_file = "https://raw.githubusercontent.com/LearnPythonWithRune/FinancialDataAnalysisWithPython/main/files/AAPL.csv"
data = pd.read_csv(remote_file, index_col=0, parse_dates=True)<jupyter_output><empty_output>
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