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Thread 🧵explaining #ROE & #ROCE and its use in #FundamentalAnalysis

(Must read for #FA learners)

🙏Like & RT to spread learning with all 🙏

Views Welcome 👉 @dmuthuk @Vivek_Investor @datta_arvind @caniravkaria @FI_InvestIndia @AdityaD_Shah

#FundamentalAnalysis #StockMarket

1⃣

Return on Equity (#ROE) and Return on Capital Employed (#ROCE) are two important Financial Ratios used in #FundamentalAnalysis of Stocks.

#StockMarket #Investing

2⃣

Return on Equity (ROE) is the ratio of Net Income (Net Profit) of a company and it’s Total Equity (Shareholder's Equity).

Here - Shareholders Equity = Share Capital + Reserves & Surplus.

#StockMarket #Investing #FundamentalAnalysis

3⃣

#ROE is a measure of how much net profit a company is making for every rupee invested by its shareholders in the company.

It can be said that higher the ROE, better it is for the equity shareholders. It tells shareholders about how effectively their money is being used.

4⃣

However, you should not trust high ROE blindly. Biggest drawbacks or weaknesses of ROE is that it completely ignores debt.

Hence for companies having high levels of debt, ROE will give a higher but misleading value & therefore we need to look at #ROCE along with #ROE.

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.

THREAD: 15 of the most useful razors and rules I've found.

Rules of thumb that simplify decisions.

Bezos' Razors:

• If unsure what action to take, let your 80-year-old self make it.

• If unsure who to work with, pick the person that has the best chances of breaking you out of a 3rd world prison.

Skinner's Law:

• If procrastinating on an item, you only have 2 options:

1. Make the pain of not doing it greater than the pain of doing it.

2. Make the pleasure of doing it greater than the pleasure of not doing it.

Luck Razor:

• If stuck with 2 equal options, pick the one that feels like it will produce the most luck later down the line.

I used this razor to go for drinks with a stranger rather than watch Netflix.

In hindsight, it was the highest ROI decision I've ever made.

Bragging Razor:

• If someone brags about their success or happiness, assume it’s half what they claim.

• If someone downplays their success or happiness, assume it’s double what they claim.

The map is not the terrain.