#HDFC - Risk Reward In Favour - TradingView -

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.

For fun I made a Robinhood account. It took me 5 minutes to sign up, get approved and transfer funds for trading...

Here's some details... Read on.

...it took me another 5 minutes to get qualified for options.

If I share a sign up I get "free shares" and I can share as much as I want up to 500$ worth.

The main UI has a prepopulated "list" of stocks/crypto to watch and links to news.

Clicking a stock opens a "trade" button that looks like this.

Notice options is first, buy second.

Options took me to an approval process (which took about a minute) and now away I go trading Baba options.

Buying stock looks like this. It emphasizes fractional shares.

They’re shooting into the chamber.

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.