One of the best Guide on Stoploss

So I was talking to @gewt about Job: A Comedy of Justice and I came up with a theory that I think explains why Heinlein's late-period work is so kinda-terrible and why I still enjoy it so much

So Heinlein had always been very interesting in the short parts of his novels, like the little snippets inside chapters. He had a very fun writing style, and wrote some fun dialogue with fun characters, right?>
It probably comes from how much of his early stuff was short fiction

And I think what happened with a lot of his longer works is that he'd just start writing fun bits and hope it would end up going somewhere or having a bigger plot by the end. like eventually he'd figure out where this was going, then go back and rewrite it into a cohesive whole

and I'm sure he had editors that'd help this process. No editor would let you publish something as rambly and changing-gears-every-other-chapter as The Number Of The Beast, for example... unless you were God-King Of Science Fiction 1980s Robert Heinlein.

so basically I think what happened is that by the 80s (when he was in his seventies!!) he lost the drive to go back and rewrite and he was too Untouchable for editors to make him.

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

(Must read for #FA learners)

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

#FundamentalAnalysis #StockMarket

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

#StockMarket #Investing

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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

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#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.

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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.

Donna Strickland, one of this year's Nobel Laureates, was not considered "notable enough" for Wikipedia as late as this May—reported by a number of sites, including the Independent. I dug into this a little. Here's the data—

This is the first deletion, back in 2014. A bit hard to read between the lines, but the basic story that an admin had Stickland's page "speedy deleted"—i.e., deleted without debate. The method was something called Copyright Jujitsu.

In particular, the admin had the page deleted not because of notability, but because it included a photograph of Strickland that had ambiguous copyright status. This is a method that people developed to get rid of content they didn't want, but also didn't want to debate.

"Copyright Jujitsu" because it is usually used against spam from companies; a PR officer uploads promotional material to Wikipedia. Instead of debating whether it's neutral, the admin can say "we'd love to have it, but the material appears to violate your company's copyright".

Usually the PR office and the IP office are separate in a company, and the idea of releasing promotional material under public domain is such a legal nightmare that the PR person goes away.

A thing which I unironically and enthusiastically believe which is unpopular among smart people of my acquaintance: financial engineering has in the recent past and present contributed substantially to human welfare. We should hope to see more of it.

Maybe more geeks need to meet someone who says “My job is teleporting value across time and space.”

Financial engineering is sort of a squishy term. I don’t primarily mean payments infrastructure or financial rails, although both of those involve substantial engineering.

I mean more “We took a thing and performed some alchemy, and now have a new thing.”

Except instead of alchemy it is generally quite a bit of math, a huge amount of contract law and due diligence, often an impressive amount of ops work, and a dusting of technology that web devs would recognize as such.

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.