Value at Risk (VaR) In Python: Monte Carlo Method

Discover the power of Python for risk analysis in our tutorial 'Value at Risk (VaR) In Python: Monte Carlo Method.' We delve deep into the world of financial risk, breaking down the complex Monte Carlo method and its application in calculating VaR. Whether you're a financial analyst, data scientist, or Python enthusiast, this video will provide you with practical, actionable knowledge. Get ready to master the art of risk prediction using Monte Carlo simulations in Python!

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Chapters:
0:00 - Intro to "Value at Risk (VaR) In Python"
0:15 - Installing Necessary Libraries
0:43 - Set Time Range of Historical Returns
1:54 - Choose You're Stock Tickers
2:34 - Download Adjusted Close Prices from yFinance
4:14 - Calculate Daily Log Returns
6:06 - Calculate Portfolio Expected Return
7:52 - Calculate Portfolio Standard Deviation
10:11 - Create an Equally Weighted Portfolio
11:35 - Determine Z-Scores Randomly
12:25 - Calculate Scenario Gains & Losses
14:20 - Run 10,000 Simulations (Monte Carlo Method)
15:35 - Specify Confidence Interval Level & Calculate VaR
17:49 - Plot the Results on a Bell Curve

*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC