Python for Finance

I get many questions about how to analyze the Stock Market with Python. I am creating a new playlist of videos that will completely cover Python for Finance. In this first video I cover :

• Numpy
• Pandas
• Matplotlib
• Matplotlib Finance
• Downloading & Saving Stock Data for Free
• Making Numerous Calculations
• Merging & Masking Data
• Plotting & Plot Styling
• Variance
• Standard Deviation
• Coefficient of Variation

MY UDEMY COURSES ARE 87.5% OFF TIL February 13th ($9.99) One is FREE

This is Not Investment Advice! I'm not implying that investing this way will guarantee anything. All investing is risky and you should always take advice from someone who can assess your specific situation. I do however believe you would benefit greatly by buying my Python Course on Udemy!

#Python for Finance #Data Science #Python

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THANK YOU TO MY PATREON SUPPORTERS LIKE :

[batyrashyrov]

I am so glad that finally saw your face😃 I graduated from school with help of your you-tube progrraming tutorials. Thank you a lot🙏🏽. They are not just programming tutorial videos, thay have been part of our life for long time. Young developers owe you a lot. Thanks again 👏

[upafterdark_]

I watched your videos throughout uni and prior, it's been nearly 10 years and seeing Derek Banas' face after all this time hits hard (positively)

anyway, thanks for getting me through university and making programming fun!

[SouhaibD]

I totally disagree with those who said you look old. I was following you since 2015 or so and your great voice was giving me the impression that you are 60+ years old but you actually look much younger and you're definitely not old! Keep it up Derek! Thank you for your great tutorials!

[EranM]

Derek +1 and *1000 for not putting a stupid intro video after the opening speech. You're a real pro.

[taqi]

Mr Derek, you have become more experience than your old video, i hope you stay healthy. Time really fly fast, thanks for teaching

[terraflops]

A) yay! Derek Banas is back!!! Also nice background setup, cool lights!
B) My Python skills have dropped off since i started using R, but having your new series using Python (don't personally care about the stock market) will be a fun thing to keep my Python skills from atrophy.
c) your videos truly make me happy, 100% serious. I love this channel and all of your hard work. THANK YOU

[evanparrish]

Hey Derek, I just want to say thank you for the quality content you've created over the years! I first watched your programming tutorials in 2015, and any time I'm stepping into a new language or framework you're one of the first sources I check. I'm a professional developer now, and I still enjoy learning from you. This course is a perfect intersection of things I'm learning about. Very exciting!!

[yt_bharat]

Let me just say that this is the most underrated YouTube channel ever, with amazing playlists and deep learning stuff. I ve been a fan since ur inkscape series and the way u teach is phenomenal. Please keep up the good work, there are tonnes of people like me who value such content. Please help the world with amazing education you are already offering for free.

My sincere gratitude Mr. Derek, regards from India

[marvmiller]

Thank You, Derek...the man who never stops learning and sharing the good stuff!

[divyanshsingh]

you've changed so many lives by your videos. Thanks You 🙏

[jlitodelcid]

This series will be interesting, exactly what I was looking for. Thank you for the upload.

[hemanthkotagiri]

Oh My God. I never thought you'd look like this. Your voice is so young, but you look like a double Ph.D. candidate. Anyhow, All that doesn't matter, and thank you for your videos.

[soliderarmatang]

Thank you so much for all your videos! They've helped me a ton over the years!

[Espfs]

Never seen your face before, glad I did finally. You’ve been inspirational to many! Keep it buddy!

[darcydonelle]

Great video! However, at 18:26, this does not calculate total return, as it ignores compounding. 4 day returns of 20%, 20.83%, 17.24%, 17.65% generate a total return of 100%. However, the mean return is 18.93%. Multiplied by 4, this results in a total return of only 75%, well short of 100%.

[yhddjzx]

Great Idea! Thank you so much. I learned a lot over the years from you. Please don't stop!

[edwinoko]

I have watched so many of your vids in my university days 😎👌. Thank you so much!

[RedFlagMobileDotCom]

Hey Derek-- thanks for all the great stuff year after year !!! You are, in my opinion one of the best code teachers in the world && I know I am not alone in that opinion. Happy Holidays && kind regards, mark-p.

[pmathieu]

Very good tutorial, I appreciate the way you proceed. The only problem is the way you calculate the annualized return. Is is clearly not given by : mean (daily return *number of trading days) since the daily returns are compounded each trading days so it is given by the product of all 253 terms like that: (1 + daily_ret(day one)) *(1 +daily_ret(day two)*...(1+daily_ret(day 253)) but also much more easily calculated by adj_close(last day)/adj_close (first day) = 0.715971 for AMZN in the year 2020 far from .18

[ahafeel]

Thank you Derek.... Im an equity analyst.. Absolutely love your work. Stay safe and healthy. God bless.