ICICIPRULI
Double Top Buy & Super Pattern - Bullish above 637.63 daily close on 1% Box Size chart. https://t.co/s0Y1Li88Aj

ICICIPRULI
— Saket Reddy (@saketreddy) June 30, 2020
DTB Above 432!
Counts open till 450 and 500! https://t.co/gf7JF9w5DM pic.twitter.com/WcnhlDKeO7
More from Saket Reddy
SAREGAMA
Today's closing is a monthly close and this is done & dusted, we now have a solid monthly close above the 10 year supply zone.
If the stock has broken out from a 10 year supply zone & a 20 year peak, surely something would've changed!
Do study the industry structure! https://t.co/zA3qztFzon
Today's closing is a monthly close and this is done & dusted, we now have a solid monthly close above the 10 year supply zone.
If the stock has broken out from a 10 year supply zone & a 20 year peak, surely something would've changed!
Do study the industry structure! https://t.co/zA3qztFzon

SAREGAMA at a very important juncture now on the monthly chart considering today's close is also a monthly close.
— Saket Reddy (@saketreddy) May 31, 2021
Nearing a breakout from over a 10 year supply zone! https://t.co/qpsSn3obrE pic.twitter.com/1xTmB6WvhK
In these kind of stocks, ATH Breakout is usually the best entry.
Don't try bottom fishing and value buying as time correction can take away a lot of opportunity cost.
Just let it give a monthly or weekly close above ATH.
Don't try bottom fishing and value buying as time correction can take away a lot of opportunity cost.
Just let it give a monthly or weekly close above ATH.
ABBOTINDIA
— Saket Reddy (@saketreddy) May 8, 2021
A breakout in the offing? pic.twitter.com/rnpcsQ616a
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Nano Course On Python For Trading
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
