Did you know that Radico Khaitan🍻 has consistently outperformed the Indian Alcohol industry in terms of volumes:

2019 it grew at 10.8% vs 9.2%, in 2020 at 12.5% vs 0.4% growth of the industry. In 2021, industry degrew by 14% and Radico by 8%. Focus on the right alcohol co 🥃🥃

New iPad Pro has Face ID, thinner bezels, squared off edges. A new touch sensitive Pencil that magnetically attaches to the edges. Thin enough to have a camera bump. Uses the XR's LCD cornering techniques.

The new 12.9" iPad Pro is physically smaller than the old one with the same screen size. It's roughly the same size as an 8.5 x 11 piece of paper. 5.9mm thick.

10 billion transistors in the A12X. 8-core CPU. 7-Core GPU. 35% faster single-core performance. 1000x faster GPU. iPad Pro is Xbox One S class GPU performance in "94% smaller" package, Ternus jokes.

Apple's silicon team is just dropping bombs every event.

live shot of Apple's silicon team

iPad Pro gets USB-C for up to 5K external displays and enables charging out to iPhones. Wild.

Let me tell you an amazing story...

In the 1990s, a maverick breast surgeon at @TataMemorial (fresh from his return from the UK) stepped up to do research. Now, to understand the situation, you should go back 30 years, when research was not as big as it is now, and certainly not from surgeons.

Surgeons, and especially cancer surgeons, were renowned for their technical prowess, and their sheer bravado – "wherever the cancer, however advanced, I will take it out". So, our surgeon-researcher was ridiculed for even attempting clinical research

For a surgeon, he couldn’t have chosen a worse topic to research on: early detection; nothing to do with surgery, or even treatment. Remember, this was the 1990s. Cowboy surgery was celebrated, and research ridiculed

Being a breast surgeon, he was troubled with women consistently coming with advanced cancers, and he set out to see if he could work on picking them up at an earlier stage. But community-based early detection needs money, and he just didn’t have it.

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.

Technical Analysis Masterclass- Part 2

'Entering the trade'

Entering a trade without ascertaining a certain things is gambling.

In this masterclass we will learn the pre-requisites to enter a trade.

DON'T ENTER A TRADE WITHOUT DETERMINNG THE FOLLOWING.

Please share.

We understand what reward to risk (popularly called risk to reward) is.
It will be denoted by R:R.

We will also try to bust a few myths about R:R and how to avoid losing trades.

Before entering a trade, you need to determine 3 things.

1. Entry trigger
2. Stop loss
3. Target

1. Entry trigger = Reasons for entering a trade. There could be multiple reasons or a single reason for entry.

Generally a set of reasons AKA confluence is a higher probability trade and a generally a safer entry.

Example of an entry trigger.

2. Stop Loss.

The price in the opposite direction of the trade where the trade is exited, at a loss.

At this level, the reason for the entry becomes invalidated according to TA and the price can then move in the opposite direction, probabilistically.

3. Target is the possible price level that the asset might touch based on previous trends or confluence AND where a possible reversal could occur.

Target is the next path of least resistance from where the price might reverse.

We will always ONLY use TA to determine all 3.