Auto-detect Support and Resistance in Python

[@k2icc]

Definitely a great job there and a very nice tutorial. I love technical indicators, but Python has given me a lot when it comes to manipulate or handle data for a visual presentation.

[@DMInverse]

Great explanation of the technique. I used to do a function examining if the high was equal to the max highs of each candle and the two candles on each side of it, and same for the lows, but this seems more efficient. Cheers!

[@anilmm2005]

Thanks lot Chad can you confirm how to get the code shown in the video?

[@jorgeplaza7938]

Thanks for the video! Tried many aproaches to this matter and certainly yours is the best. KDE is a very interesting concept I now fully understand.

[@daymaker_trading]

Wow, this is gold! Thanks so much for sharing your knowledge ❤

[@paulbrown5839]

Very solid piece of work this Chad. I've just been through it again and will take some of your innovative ideas from it. Cheers.

[@whatsthememe2913]

This exactly what I was looking for! Chad you’re a lifesaver. Next step would be to create a strategy on this information in python!

[@ThinAirElon]

High Quality Channel on Algo

[@ChadThackray]

Thanks!

[@proexcept]

Thanks for a great food for thought!

[@TavoPlus]

Excellent, I tried and personalized your code. Thank you, it helped me a lot!

[@segunda_parte]

Thank you very much for the video. How can I make the volume be taken into account to give more relevance to the candles that have greater volume?

[@GlebKretinin]

Great job Chad! Thank you for sharing!

[@BeyondTheHodl]

great video! Just wondering once you get the horizontal lines like you did at 13:38 how would I go about creating code so that the horizontal line stops once price hits it/crosses it?

[@eige2992]

hello, great concept! i was in a confusion when I had to decide how to group the extrema values, but the concept of KDE in your video was very helpful. I guess you could try to find the peaks and trough separately instead of combining them together and running separate KDE algorithms to both of those values to differentiate support and resistance lines?

[@UnbenutzerKanalname]

i was trying to use a simple histogram for the min/max values, but the kernel is a great idea. thanks!

[@rabbitgomes5817]

hey Chad! nice video, and awesome approach with signal processing and kde! Can you supply the code behind the "draw_candle_chart" function? I believe thats in the top of the notebook, but can't see it clearly on the video.

[@ChadThackray]

If you lookup "How to Create a Candlestick Chart Using Matplotlib in Python" that's the code I used. At some point I'm planning on going through and linking all the code from my videos, but will take a few months

[@MaheraSALALAMANDIMBYHASINA]

Hi, how you difine which of the line is support and which is resistance? beacause the algorithm seems to draw only the, but what about the classification? need help

[@valueray]

where is the jupyter?

[@mohitgarg4168]

Fantastic work Chad..!! Can you please share a link to download this Jupyter notebook.

[@davidberry8511]

Great video, support and resistance is a big topic to code since it is so subjective. Where can I download the your code fom this lesson?

[@mehranhub8312]

you are amazing man please keep going on your educations😍

[@2907866]

Great information and tutorial!

[@karlbooklover]

was just thinking about codifying patterns into vectorbt, this should work to implement as a strategy, thanks! :)

[@brich8110]

Really really helpfull video, also what a great idea that you can try is to use some AI to learn with a volume indicator (for example) what support and res are more likely to be "respected". Thansk alot for the vid (Pretty sure you can do it with scikit

[@SkyRiderJavelin]

Brilliant work Chad

[@zacharyperryman8663]

Do you ever post your code so that followers can mess around on their own? Thanks!

[@kurdmanpar5706]

Thank you for your good video. If this project is more complete to clearly define the lines of resistance and support, it will be very valuable. sincerely.

[@rickymacharm3437]

lovely video. for the interval could you test with ATR or standard deviation so it works with the present volatility of the asset

[@ChadThackray]

This is a good idea!

[@SY41LENDRA]

i dont undesrtand about phyton coding, can you tell me what is the logic how to draw horisontal lines support and resistant in candlestick chart, i saw your video 14 minutes, i dont get the points

[@TwelfthRoot2]

i think weighting the S/R by volume could be helpful. great video.

[@siddharththakur5978]

Why aren't we using moving average instead of kernel density?

[@orderflow2322]

it would be cool to see how to determine the flat algorithmically on python

[@rowanans]

very beautiful, Chad!

[@dimayasnohurskyi2805]

Do you have something similar for another TA stuffs, like triangles and etc?

[@ChadThackray]

Not yet!

[@teddyperera8531]

Thank you

[@tilttrader]

awesome video.

[@misaghesh4963]

Thank you for your good video

[@kailee-st2mf]

good job

[@paulbrown5839]

What we want is the strongest support and resistance levels. There are rules about which level is strong, and which is weak. Apply those to filter the levels down to the best ones.

[@FilSerge]

What qre these rules?

[@paulbrown5839]

​@@FilSerge You can find them on YT..for example, a level near a round number is good, eg. 1.0850.

[@monkeyloopingtrading2013]

thank you ! i like it! but please help me. Why this error? NameError Traceback (most recent call last) Input In [131], in () ----> 1 draw_candle_chart(sample_df, price_range[peaks]) NameError: name 'draw_candle_chart' is not defined. i'm so frustrated🙃😊

[@ChadThackray]

You'll need to define a function to draw a candle chart, it's not built in. I copy-pasted the one from a website called statology and it worked pretty well

[@CptnYarface]

He used a function called 'draw_candle_chart' to make the final plots with the support levels included. Statology has an example of how a candlestick chart can be made, but to overlay the support levels and create the "error bars," you will have to adapt the code yourself and create your own plotting function.. or maybe ChatGPT can help. I use mpf.plot(df, type='candle') to make candle charts, where df is a DataFrame with 'Open', 'High', 'Low', and 'Close' prices for the stock. Would have been nice to see the code for his function, for sure, but it will be an adventure trying to figure it out, at least lol

[@akbarboghani1]

Thanks Chad.

[@rezasadeghi2520]

thank you :)

[@DailyGameMoments7]

Find it difficult to comprehend the logic and codes

[@GohOnLeeds]

1) By specifying 2-4 peaks, you are forcing data to conform to something which it might well not be. For any timeseries, you simply don't know it is going to contain 2-4 peaks, right? Could be 2, could be 50. That's for the data to dictate. 2) Any support/resistance algo should take trading volume into account. All price points are not created equal! 3) Doing SR using your method doesn't allow you to bias more recent peaks.

[@anthonychung8112]

AWS settings demo \

[@bikramssharemarkettradingc7366]

Your video is great, but there is. Some theory part. Not very easy for persons new to machine learning

[@FilSerge]

There's no ML, just pure statistics.