Everyone speaks about when to buy a stock. Hardly anyone speaks on when to "Sell".
Thread on when to sell a stock🧵
More from Stocklearnings
Compilation of the best learnings from @BankniftyA through his tweets.
Have compiled his:
1. Expiry day trading.
2. Trade logics.
3. Multiple Charts analysis.
3. BTST criteria for stocks.
Share if you find it helpful so that everyone can benefit.
A pdf of his moneycontrol article where you can read about his journey and how he trades.
Advice on how to not let your mood influence your decisions.
Expiry day Trading:
How to become better?
When I had spoken to him on phone he advised me to backtest all expiries and rigorously practice them again and again to develop conviction. Superb advice!
Acts based on support and resistance levels from charts
Have compiled his:
1. Expiry day trading.
2. Trade logics.
3. Multiple Charts analysis.
3. BTST criteria for stocks.
Share if you find it helpful so that everyone can benefit.
A pdf of his moneycontrol article where you can read about his journey and how he trades.
— Harsh (@HarshAsserts) September 11, 2020
Advice on how to not let your mood influence your decisions.
When trading,moods will want to influence ur decisions
— Banknifty Addict (Gaurav) (@BankniftyA) December 29, 2019
How to minimize:
-Have a backtested plan/system
-Know yourself(emotion and panic levels)
So trade size is important to keep ur emotions in check
-dont focus too much on pnl
-have a back up plan ready
& last stay positive!!
Expiry day Trading:
How to become better?
When I had spoken to him on phone he advised me to backtest all expiries and rigorously practice them again and again to develop conviction. Superb advice!
Backtest the complete expiry and practice again and again till u develop conviction
— Banknifty Addict (Gaurav) (@BankniftyA) November 5, 2020
Acts based on support and resistance levels from charts
Support and resistance levels based on technical charts on various time frames.
— Banknifty Addict (Gaurav) (@BankniftyA) December 19, 2019
Breaking any of the above, leads to a direction
and then only directional play.
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Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.