WEBVTT

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Welcome to coding exercise.

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Twelve feet here on the tuba the dashboard and our exercises file this on our desktop

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and we are in part two and we select the two put a notebook for exercise twelve

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and starting with coding exercise twelve for the coding exercises are a bit different than before.

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So far the focus was on Panda's coding and starting from coding exercise twelve.

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The focus is on solving real world problems and tasks in the finance and investment industry and therefore

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you have two options.

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So you have option number one self guided and you can find some high level questions.

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So first of all you should import to the U.S. stocks dataset and select the adjusted.

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Clothes for a particular time period and then you should visualize the adjusted clothes for the six

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stocks and also visualize the normalized prices over time and then you start to calculate monthly returns

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and based on that monthly returns you are asked to calculate the annualized the mean return and the

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annualized standard deviation of returns.

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So to say risk and return.

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And finally you should also visualize the risk and return in a total risk return framework with the

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standard deviation on the x axis and the mean return on the y axis and you should also be able to identify

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the best performing and the worst performing stocks in terms of total risk and return.

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And finally you should also visualize the correlation matrix of monthly returns with a seaborne heat

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map and you should identify the stock pair with the highest positive correlation of monthly returns.

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So that's the self guided option and essentially you have to find your very own code but you can also

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select the option to guide it and instructed and here you can find for each and every exercise a question

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a detailed guide and instruction.

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What to code here.

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And finally you can also find at the very end.

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The hint section so feel free to select that option that best fits your learning style and hope you

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have fun and also have a look at the solution by.
