The cash strategy 👇☢️👇
1⃣ #stock selection process - always choose that stock which are consolidating near all time high.
(Because whenever stock will give all time high breakout then it will easily give 20/30% return in 1/2 months
U can use trading view scanner for that.
How I turned 7lac account to 33lac in just 1 year only by cash trading.
— Vikrant (@Trading0secrets) October 14, 2021
Soon going to make full thread about my strategy of cash by which this happened.
And for cash hedging I started option selling in different a/c.
How many of u intrested for that thread? \U0001f499\U0001f49b\U0001f499 pic.twitter.com/wIyfE8fwfw
And, your 3/4 stocks must be from different different sectors.
If you hold 3 stocks out of them 2 will give 40% then ur portfolio impact is 25%
(Here time period is 1/3 months)
If any stocks is out of nifty sector then u can open stock scanner website and check their peer charts. If out of 5 , 3 are strong then u can select that company.
7⃣ sl rule - don't risk more then 4/6% in your one trade. ( u have to exit at sl anyhow)
And your cash and fno account must be different .
Because #small & #mid can correct little. ( at support of index I will add more)
#bepl
#Jamnaauto
More from Vikrant
Here is simple trick for finding upper circuit call 👇
First check top gainer of today 6% to 20% in (small/mid cap) stocks👇
https://t.co/4pJtazcOYH
Then use that 5 filters for find out next days UC calls 👇
1⃣stock must be near all time high or 52 week high.
Ex - #Smartlink after BO all time high blasted 💥💣
#BGRENERGY recently broke 52 weeks high .
2⃣ Stock should be low market cap less then 10K CR
Ex - #smatlink - 1833 CR
3⃣ Stock should face least resistance after BO ( not major resistance after BO)
Ex - #apollomicro
4⃣ It's sector or peers companies must be strong 💪
Ex - #NiftyIT / #apollomicro
U can check their peer companies here👇
https://t.co/rVBUAp3LOE
First check top gainer of today 6% to 20% in (small/mid cap) stocks👇
https://t.co/4pJtazcOYH
Then use that 5 filters for find out next days UC calls 👇
1⃣stock must be near all time high or 52 week high.
Ex - #Smartlink after BO all time high blasted 💥💣
#BGRENERGY recently broke 52 weeks high .
2⃣ Stock should be low market cap less then 10K CR
Ex - #smatlink - 1833 CR
3⃣ Stock should face least resistance after BO ( not major resistance after BO)
Ex - #apollomicro
4⃣ It's sector or peers companies must be strong 💪
Ex - #NiftyIT / #apollomicro
U can check their peer companies here👇
https://t.co/rVBUAp3LOE
The cash strategy 👇☢️👇
1⃣ #stock selection process - always choose that stock which are consolidating near all time high
(Because whenever stock will give all time high breakout then it will easily give 20/30% return in 1/2 months
You can also choose 52 week high stocks , if stock going to give BO more then 3 years of range .
For finding all time high or 52 week high stocks you can use trading view scanner or indmoney scanner .
Here is threads of both
2⃣volume analysis - In that consolidating period volume should be high of up move days then down move days. And last 3/4 month volume of accumulation is much higher.
Here is 👇 volume thread🧵 in details
3️⃣ fund diversification - always deploy your capital in 3/4 stocks, not more then that or not less then 3.
And, your 3/4 stocks must be from different different sectors.
4⃣comunding magic - If you hold 10 stocks then if 2 stocks will give 100% return then portfolio impact is 20% only. (here time period is 8/15 months)
If you hold 3 stocks out of them 2 will give 40% then ur portfolio impact is 25%
(Here time period is 1/3 months)
1⃣ #stock selection process - always choose that stock which are consolidating near all time high
(Because whenever stock will give all time high breakout then it will easily give 20/30% return in 1/2 months
You can also choose 52 week high stocks , if stock going to give BO more then 3 years of range .
For finding all time high or 52 week high stocks you can use trading view scanner or indmoney scanner .
Here is threads of both
Trading view scanner process -
— Vikrant (@Trading0secrets) October 23, 2021
1 - open trading view in your browser and select stock scanner in left corner down side .
2 - touch the percentage% gain change ( and u can see higest gainer of today) https://t.co/GGWSZXYMth
2⃣volume analysis - In that consolidating period volume should be high of up move days then down move days. And last 3/4 month volume of accumulation is much higher.
Here is 👇 volume thread🧵 in details
Full #volume anlaysis thread \U0001f9f5
— Vikrant (@Trading0secrets) October 20, 2021
One thing which big player can never hide - VOLUME https://t.co/MjtFq384N0
3️⃣ fund diversification - always deploy your capital in 3/4 stocks, not more then that or not less then 3.
And, your 3/4 stocks must be from different different sectors.
4⃣comunding magic - If you hold 10 stocks then if 2 stocks will give 100% return then portfolio impact is 20% only. (here time period is 8/15 months)
If you hold 3 stocks out of them 2 will give 40% then ur portfolio impact is 25%
(Here time period is 1/3 months)
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)
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)
