Introduction to Algorithmic Trading Using Python - How to Create & Test Trading Algorithm

#python #algorithmic #trading
How to create a Trading Algorithm - Algorithmic Trading Using Python

Learn how to develop a momentum strategy trading algorithm with Python

Learn how to download manipulate and test data for trading

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Learn algorithmic trading using Python. Algorithms are short programming logic that allow the automation of trading decisions.

Complete overview of training and testing a trading algorithm. The first step in any automated trading strategy is to find a signal or signals that indicate when a trader should be entered. This video contains a complete discussion of identifying that algorithmic signal and testing the resulting profitability. While the signals vary the implementation of adding signals and testing is fairly constant, so while we may not identify the best strategy, you will be able to use the techniques discussed to test your own strategies quickly and easily. Discussion of drawbacks and limitations.

* Note the information contained in this video is for educational purposes only and should not be construed as investment advice

[PatrickBenitez]

Exceptional tutorial! I spent the past couple days researching how to calculate proper cumulative returns based on your short, long, hold signal strategy and luckily the YT algo brought your video to my home screen. Keep up the great work!

[sudzbyte]

Great vid, especially the reminder about shifting rows. Thanks!

[kingkong]

Excellent. I'm about to watch all the excel, python, and mysql videos on your channel. Great teacher.

[BLKDOLPHNDK]

Python beginner thanks every tip helps

[larrygranda]

Brilliant I'm falling off my chair. I tried TradeWindow etc now testing PlutoHQ Trading

[zayb]

Great and Awesome video. Just created my first momentum strategy with python; and I look forward to creating more strategies using python. Very useful skill for the FinTech industry.

[bsab]

Really useful.Thank you for your sharing.Clear explanation and nice tutorial.

[swingtrader]

Thank you for this great tutorial! Liked and subscribed.

I'm trying to learn python but trading tutorials that are any good are difficult to find, so your tutorials are very much appreciated.

[SidhanthKumar-nr]

This is awesome, thank you so much for sharing!

[tomjohnson]

can you make a video of how pandas performs the actual buy or sell orders ?

[stevensun]

the code is simple and beautiful. love it!

[adeebazia]

thankyou for the video @Matt Macarty, I didn't get the last part what is system return?

[munivoltarc]

Hi, you explained very well, could you please make a video on price action kind of trading, not using lagging indicators, then it would be great to see your coding, and is it possible to do a multitime frame price action trading, if so please give the code.

[aspirantrade]

Wow, this video was a game-changer for me! It made creating my own trading bot a breeze. Highly recommend it!

Also, check out "Algorithmic Trading Tutorial Python | Build Trading Algorithm from Scratch" by QuantInsti - another awesome video that helped me understand the fundamentals of algorithmic trading and build my own algorithm. Super helpful and definitely worth watching!

Big thanks to both videos for giving me the knowledge and confidence to create my trading bot. Can't wait to see what it can do! 😄🚀

[bettinabautista]

thanks for the vid! was looking for some help on testing system returns and this vid helped

[eddsoniko]

wow simplemente gracias, he aprendido mucho con sus tutoriales, podría hacer un video sobre la gamma positiva y gamma negativa? saludos

[israelvtvita]

Everything works great. Thanks for the soft

[rishim]

Nice video, thanks.

A quick question - Why would you use numpy log to calculate returns? I reckon there is a more accurate pct_change() function that can be used directly. Also, numpy log also needs a diff..

Also, could you explain how taking natural log (numpy log) and diff together end up coming close to the pct_change function result, which seems more intuitive for returns calculation?

Update: Okay, it turned out that I didn't know about log returns till now. I went and did my homework :)
But should we use log returns here when investment and returns are actually for discrete periods (1, 2, 3...n days)?

[beqodia]

Great video, thank you a lot !!!
I have a question for you Math if you don't mind of course about the trading algorithm in cryptocurrencies, my algorithm works pretty well using technical analysis RSI and CCI but I want to improve it using machine learning for merging technical analysis and fundamental analysis what can I do here? what kind of machine learning models or algorithms do I have to look at?
my second question: I took a look at the holt winter method forecasting but I think this method will not work cause of the randomness of cryptocurrencies to change over time, is it true what I just said ? or this is a method for extracting trends and seasonality in any kind of time series

[ahmadz]

thank you for the video . i think the look ahead is not a problem here if you take a decision at the end of the day . right ?
I am creating a complex AI model and i am generating features depending on SMA and EMA . It would be important for me to know what is the best practice in this regard . i am taking decision at the end of each 1 hour candle .