Objective: Picking up the best stocks to buy! Start from today 28th of September 2021 DATA!
First of all, this project has 3 stages. I hope this idea will be able to come out with the most potential stocks for all of us.
Stage 1 – Trading View Rating Comparison. (Which I just completed the coding to sort it out)
• To check how well is the Rating recommendations to us.
• Which Sectors are the highest Bull (Go up %) base on all the Ratings.
• * Something like if you choose all the stocks with ‘Strong Buy’, what happened on the next day.
So, what I’m going to show it here are:
a) Which sectors have the highest go up %.
b) Which Rating is the highest go up %.
c) Which Rating is the highest go up % in each sector.
d) Which Sectors is the highest go up % in each Rating.
Stage 2 – Banker Enter. (Institutional Investor action)
• Base on the ‘Daei MCDX’ indicator. The Red Bar will show that the Banker had entered the stock. Without the Red Bar, the stock price will just have small changes on the stock price.
• So, I wish to use the calculation to filter out the stocks that have the Red Bar by using the stocks that I sort out from Stage 1. (Of course to exclude those stocks that Banker is leaving. (Red Bar going down))
• *I’m still figuring out how to scrap it out using python; I can scrap the data from Trading View but not the Indicator.
Stage 3 – Volume Analysis. (Volume Profile)
• As you can see that there are 3 types of trade; (I’m using WEBULL, Buy, Sell, Neutral)
o Green Color, Buy (people buy at the ASK, very keen to have the stock),
o Red Color, Sell (people sell at the BID, very keen to let go),
o Gray Color, Neutral (people just buy at Last Price).
• I wish to check which price level that the Last stock price is currently at; and then,
• Calculate the total of Buy, Sell, Neutral volume Ratio that stay above or below the Last Price.
• Lastly, will sort out which Price Level with what Volume Ratio has the highest go up % tomorrow.
• For example:
o Last Price of Stock ABC = 10
o 10.20: Buy vol = 20k, Sell vol = 10k, Neutral vol = 15k
o 10.10: Buy vol = 10k, Sell vol = 30k, Neutral vol = 15k
o 9.90: Buy vol = 5k, Sell vol = 30k, Neutral vol = 10k
o 9.80: Buy vol = 5k, Sell vol = 30k, Neutral vol = 20k
• So, end up, this ABC Stock is currently at a Price Level that having a ratio of 3:4:3 above and 1:6:3 below.
• After categorizing all the Stocks into those Price Levels, then we will see the result day by day.
• * Unfortunately, I am still unable to get the volume analysis Data from any platform. Do let me know if anyone knows where to get it! Highly appreciate.
• Alpha Vantage, Nasdaq Data Link, Polygon, IEX platform’s API doesn’t have the breakdown volume data.
• I had tried several python libraries to sort out the Buy, Sell, Neutral volume, but still couldn’t make it.
• I believe there must be some hidden message of market behavior in this Stage 3 analysis. I wish to find it out and share it with everyone.
Anyhow, let's check out the Stage 1 Data!
a) Which sectors have the highest go up %.
b) Which Rating is the highest go up %. (You may ignore the '--' Rating as only have a few data)
c) Which Rating is the highest go up % in each sector.
d) Which Sectors is the highest go up % in each Rating. (You may ignore the '--' Rating as only have a few data)
FYI
**Total stocks on 28th - 9631
**Total stocks on 29th - 9636
**Only 9623 stocks were matched to use for the analysis above.
First of all, this project has 3 stages. I hope this idea will be able to come out with the most potential stocks for all of us.
Stage 1 – Trading View Rating Comparison. (Which I just completed the coding to sort it out)
• To check how well is the Rating recommendations to us.
• Which Sectors are the highest Bull (Go up %) base on all the Ratings.
• * Something like if you choose all the stocks with ‘Strong Buy’, what happened on the next day.
So, what I’m going to show it here are:
a) Which sectors have the highest go up %.
b) Which Rating is the highest go up %.
c) Which Rating is the highest go up % in each sector.
d) Which Sectors is the highest go up % in each Rating.
Stage 2 – Banker Enter. (Institutional Investor action)
• Base on the ‘Daei MCDX’ indicator. The Red Bar will show that the Banker had entered the stock. Without the Red Bar, the stock price will just have small changes on the stock price.
• So, I wish to use the calculation to filter out the stocks that have the Red Bar by using the stocks that I sort out from Stage 1. (Of course to exclude those stocks that Banker is leaving. (Red Bar going down))
• *I’m still figuring out how to scrap it out using python; I can scrap the data from Trading View but not the Indicator.
Stage 3 – Volume Analysis. (Volume Profile)
• As you can see that there are 3 types of trade; (I’m using WEBULL, Buy, Sell, Neutral)
o Green Color, Buy (people buy at the ASK, very keen to have the stock),
o Red Color, Sell (people sell at the BID, very keen to let go),
o Gray Color, Neutral (people just buy at Last Price).
• I wish to check which price level that the Last stock price is currently at; and then,
• Calculate the total of Buy, Sell, Neutral volume Ratio that stay above or below the Last Price.
• Lastly, will sort out which Price Level with what Volume Ratio has the highest go up % tomorrow.
• For example:
o Last Price of Stock ABC = 10
o 10.20: Buy vol = 20k, Sell vol = 10k, Neutral vol = 15k
o 10.10: Buy vol = 10k, Sell vol = 30k, Neutral vol = 15k
o 9.90: Buy vol = 5k, Sell vol = 30k, Neutral vol = 10k
o 9.80: Buy vol = 5k, Sell vol = 30k, Neutral vol = 20k
• So, end up, this ABC Stock is currently at a Price Level that having a ratio of 3:4:3 above and 1:6:3 below.
• After categorizing all the Stocks into those Price Levels, then we will see the result day by day.
• * Unfortunately, I am still unable to get the volume analysis Data from any platform. Do let me know if anyone knows where to get it! Highly appreciate.
• Alpha Vantage, Nasdaq Data Link, Polygon, IEX platform’s API doesn’t have the breakdown volume data.
• I had tried several python libraries to sort out the Buy, Sell, Neutral volume, but still couldn’t make it.
• I believe there must be some hidden message of market behavior in this Stage 3 analysis. I wish to find it out and share it with everyone.
Anyhow, let's check out the Stage 1 Data!
a) Which sectors have the highest go up %.
b) Which Rating is the highest go up %. (You may ignore the '--' Rating as only have a few data)
c) Which Rating is the highest go up % in each sector.
d) Which Sectors is the highest go up % in each Rating. (You may ignore the '--' Rating as only have a few data)
FYI
**Total stocks on 28th - 9631
**Total stocks on 29th - 9636
**Only 9623 stocks were matched to use for the analysis above.