As Promised here is the setup
1. Strategy is meant to trade only on Wed and Thu.
2. At 9.30AM Sell 1 lot of nifty ATM and 2 lot of nifty OTM1 CE and PE.
3. Suppose nifty spot is trading at 17500 then sell 1 lot of 17500CE and 17500PE(Straddle). 2 lot of 17550CE and 17450PE.

4. Put 50%SL on CE and PE.
5. On Wed trail your SL by 10 points. It means if any leg comes in profit by 10 points then reduce the SL of that leg by 10 points. on Thu no need to trail SL
6. if SL hit in any leg than continue with remain leg.
7. Either exit at 3.10 or if SL hit
8. Capital required to do 1 set (1 lot ATM and 2 lot OTM1) is 4Lakh or something. People buy hedge of 10 strike away. After hedge required capital will be 2 to 2.5 Lakh. Everyone is doing this strategy with hedge only.
As I said I learnt it from Vishal Mehta. In his webinar he said I tried with 50% SL you can find better version of it by trying SL from 40-50%. Inspired by his words I kept searching something good from this strategy.
Biggest drawback of any stockmock kind of strategy is "Double Side SL" so is with this strategy. I felt the heat of double side SL of this strategy many times but everytime its come out from DD like a winner. In Jan 2022 this strategy hit 3 times double SL.
You can do following this to find a better version.
1. Try back testing it from 40-50% SL
2. Try back testing it with MTM Level SL. Suppose you are trading it with 2.5Lakh capital and don't want risk more than 2% of your capital then backtest if with 5K MTM SL.
3. If you want to do multiple sets say 3 sets then try backtesting one set at 9.20,9.30 and 11am or whatever time u like.
4. Execution:- You can subscribe to @Quantiply_tech algo to execute any stock mock strategy.
5. As I said I learnt this strategy by attending @vishalmehta29 Webinar and algo of this strategy is available for subscription on his platform. Name of Strategy is TSS .For charges You can visit his website.
If you want to check the stats of this strategy then simply refill your @stockmock_in and run the backtest.
Run 5-7 backtest with different different parameter like SL from 40-50%, MTM level SL etc.
This strategy work like a charm. Find out your version of this strategy

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कुंडली में 12 भाव होते हैं। कैसे ज्योतिष द्वारा रोग के आंकलन करते समय कुंडली के विभिन्न भावों से गणना करते हैं आज इस पर चर्चा करेंगे।
कुण्डली को कालपुरुष की संज्ञा देकर इसमें शरीर के अंगों को स्थापित कर उनसे रोग, रोगेश, रोग को बढ़ाने घटाने वाले ग्रह


रोग की स्थिति में उत्प्रेरक का कार्य करने वाले ग्रह, आयुर्वेदिक/ऐलोपैथी/होमियोपैथी में से कौन कारगर होगा इसका आँकलन, रक्त विकार, रक्त और आपरेशन की स्थिति, कौन सा आंतरिक या बाहरी अंग प्रभावित होगा इत्यादि गणना करने में कुंडली का प्रयोग किया जाता है।


मेडिकल ज्योतिष में आज के समय में Dr. K. S. Charak का नाम निर्विवाद रूप से प्रथम स्थान रखता है। उनकी लिखी कई पुस्तकें आज इस क्षेत्र में नए ज्योतिषों का मार्गदर्शन कर रही हैं।
प्रथम भाव -
इस भाव से हम व्यक्ति की रोगप्रतिरोधक क्षमता, सिर, मष्तिस्क का विचार करते हैं।


द्वितीय भाव-
दाहिना नेत्र, मुख, वाणी, नाक, गर्दन व गले के ऊपरी भाग का विचार होता है।
तृतीय भाव-
अस्थि, गला,कान, हाथ, कंधे व छाती के आंतरिक अंगों का शुरुआती भाग इत्यादि।

चतुर्थ भाव- छाती व इसके आंतरिक अंग, जातक की मानसिक स्थिति/प्रकृति, स्तन आदि की गणना की जाती है


पंचम भाव-
जातक की बुद्धि व उसकी तीव्रता,पीठ, पसलियां,पेट, हृदय की स्थिति आंकलन में प्रयोग होता है।

षष्ठ भाव-
रोग भाव कहा जाता है। कुंडली मे इसके तत्कालिक भाव स्वामी, कालपुरुष कुंडली के स्वामी, दृष्टि संबंध, रोगेश की स्थिति, रोगेश के नक्षत्र औऱ रोगेश व भाव की डिग्री इत्यादि।
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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MASTER THREAD on Short Strangles.

Curated the best tweets from the best traders who are exceptional at managing strangles.

• Positional Strangles
• Intraday Strangles
• Position Sizing
• How to do Adjustments
• Plenty of Examples
• When to avoid
• Exit Criteria

How to sell Strangles in weekly expiry as explained by boss himself. @Mitesh_Engr

• When to sell
• How to do Adjustments
• Exit


Beautiful explanation on positional option selling by @Mitesh_Engr
Sir on how to sell low premium strangles yourself without paying anyone. This is a free mini course in


1st Live example of managing a strangle by Mitesh Sir. @Mitesh_Engr

• Sold Strangles 20% cap used
• Added 20% cap more when in profit
• Booked profitable leg and rolled up
• Kept rolling up profitable leg
• Booked loss in calls
• Sold only


2nd example by @Mitesh_Engr Sir on converting a directional trade into strangles. Option Sellers can use this for consistent profit.

• Identified a reversal and sold puts

• Puts decayed a lot

• When achieved 2% profit through puts then sold