Stock Screeners is an integral part of doing homework post market hours.

Most of us use screeners to filter buzzing stocks out of 1000+ stock and it saves lot of times.

Here is the list of top screeners:

Also, last screener is one of my favourite to pick early momentum stocks.

1/ Volume Buzzer:

This can be used on daily time frame and it identifies all the stocks where volume action was very high.

https://t.co/ueUHHUHdhu
2/ Bullish Divergence:

This screener will help you find all the stocks that has given bullish divergence. Traders who like to trade reversal stocks that are in downtrend can use this screener. This can be used at the end of the day.

https://t.co/vsILtsHC9M
3/ Bearish Divergence:

This screener will help you find all the stocks that has given bearish divergence. Traders who like to trade reversal stocks that are in uptrend can use this screener. This can be used at the end of the day.

https://t.co/7vLS5Y2ehG
4/ Nimblr F2F:

This screener was designed from @Deishma F2F video:
https://t.co/apaQYVbAlq

This screener helps in identifying momentum and indecisive candles on daily time frame.

https://t.co/vJ96Vn9hrl
5/ Volatility Contraction (Daily):

This screener can help you in picking early breakout stocks that can give good returns if bought before breakout. It focus on consolidation phase of a stock. It should be used at the end of the day.

https://t.co/qS9kRZKXyd
6/ Manas Arora Elearnmarket:

This screener was designed from @iManasArora F2F video:
https://t.co/N4lvipLKjr

This screener will help in picking stocks that can give good returns after breakout. This screener should be used on weekends.

https://t.co/8SBbv13idc
7/ Bullish Divergence (Weekly):

This screener will help you find all the stocks that has given bullish divergence on weekly time frame. Traders who like to trade reversal on weekly tf can use this for positional trade.
This needs to be used on weekend.

https://t.co/Q4ZA34m8ST
8/ Volatility Contraction (Weekly):

This screener can help you in picking early breakout stocks on weekly tf and that can give big move and good returns if bought before breakout. It focus on consolidation phase and should be used at the end of the day.

https://t.co/gSNTFDZhxN
These 8 screeners I have personally created for my personal use to trim down stock list. I am sharing it so that it will benefit others in their trading.

If you found this useful, please do RT the first tweet.

Follow @YMehta_ for more such learning.

https://t.co/Ku6Mhik6Tc

More from Yash Mehta

More from All

How can we use language supervision to learn better visual representations for robotics?

Introducing Voltron: Language-Driven Representation Learning for Robotics!

Paper: https://t.co/gIsRPtSjKz
Models: https://t.co/NOB3cpATYG
Evaluation: https://t.co/aOzQu95J8z

🧵👇(1 / 12)


Videos of humans performing everyday tasks (Something-Something-v2, Ego4D) offer a rich and diverse resource for learning representations for robotic manipulation.

Yet, an underused part of these datasets are the rich, natural language annotations accompanying each video. (2/12)

The Voltron framework offers a simple way to use language supervision to shape representation learning, building off of prior work in representations for robotics like MVP (
https://t.co/Pb0mk9hb4i) and R3M (https://t.co/o2Fkc3fP0e).

The secret is *balance* (3/12)

Starting with a masked autoencoder over frames from these video clips, make a choice:

1) Condition on language and improve our ability to reconstruct the scene.

2) Generate language given the visual representation and improve our ability to describe what's happening. (4/12)

By trading off *conditioning* and *generation* we show that we can learn 1) better representations than prior methods, and 2) explicitly shape the balance of low and high-level features captured.

Why is the ability to shape this balance important? (5/12)

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