Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications · HackerPapers discussions

Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — HN submission

Mon, 02 Sep 2024 03:08:06 GMT

Statistical Consequences of Fat Tails [pdf]

2 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by mjburgess

Thu, 09 May 2024 18:13:35 GMT

Specifically for the area mentioned: https://gwern.net/doc/genetics/heritable/2015-burt.pdf But if you want a general criticism of these academic linear methods of observational analysis: https://arxiv.org/abs/2001.10488

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by kubeia

Thu, 20 Jul 2023 21:34:22 GMT

From the Statistical Consequences of Fat Tails (N. Taleb): "We will address ad nauseam the central limit theorem but here is the initial intuition. It states that n-summed independent random variables with finite second moment end up looking like a Gaussian distribution. Nice story, but how fast? Power laws on paper need an infinity of such summands, meaning they never really reach the Gaussian. Chapter 7 deals with the limiting distributions and answers the central question: "how fast?" both for CLT and LLN. How fast is a big deal because in the real world we have something different from n…

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — HN submission

Mon, 02 Aug 2021 20:57:12 GMT

Statistical Consequences of Fat Tails (2020)

3 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by xvilka

Fri, 23 Oct 2020 02:06:09 GMT

More on this subject is Statistical Consequences of Fat Tails book[1]. [1] https://arxiv.org/abs/2001.10488

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by stblack

Sun, 11 Oct 2020 04:46:41 GMT

The latest on this is “Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications” by Nassim Taleb. I liked this PDF so much I bought the book. https://arxiv.org/abs/2001.10488

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by danharaj

Sun, 17 May 2020 04:03:18 GMT

I don't bother with his pop books and I read his tweets for amusement (and hard calculus problems). His papers and technical write-ups are worth something. Like I'm sure if he had an editor they would hate his latest book- it's god awfully written- but the mathematics is good I swear. I've studied a couple of his references. https://arxiv.org/abs/2001.10488 I don't think his fund is structured to beat the market. If his fund is structured for extraordinary events then I would expect it to underperform strategies that are optimized for typical conditions. I would expect his fund to be used as…

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by jpdus

Mon, 13 Apr 2020 12:56:48 GMT

> more likely to be coal or nuclear Nuclear. Naive probability matters relatively little here. The risk of coal plants due to CO2 is a thin-tailed long term risk. No single coal plant will ever cause a headline (or an event) like this. Thin-tailed long-term risks can be mitigated and planned for and the result is always a sum of many smaller choices (albeit global warming is an existential risk for sure!). Nuclear is different. 99,999% of time it's cheaper and cleaner than coal. Doesn't matter. The tail-risk is what matters and that's also, why (conventional) nuclear can't ever be…

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by alpineidyll3

Sun, 29 Mar 2020 22:57:44 GMT

Taleb has made a career out of popularizing common financial statistics with historical flavor. He usually presents himself as a polymath/oracle in this writing although he has never developed any interesting ideas in the area. His work is mostly a pop-sci rehash of non-gaussian wikipedia stats formatted in Mathematica with a helping of cringey memes. For an especially embarrassing example see https://arxiv.org/abs/2001.10488. All of this serves the purpose of juicing Universa, a fund which charges a generous incentive fee for holding a rolling SPX put, something which I think a dog could do.…

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by cinquemb

Sat, 14 Mar 2020 07:26:27 GMT

"Ray Dalio says 'cash is trash' and advises investors hold a global, diversified portfolio" - Jan 21 2020 Had you have listened to him, you would have just been taken out back, shot, and put in one of wuhans finest crematoriums… better off reading "Statistical Consequences of Fat Tails"[0] [0] https://arxiv.org/abs/2001.10488

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — mentioned by thesz

Sat, 01 Feb 2020 02:48:27 GMT

And next to that is a link to https://arxiv.org/abs/2001.10488 "Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications" by Nassim Taleb which states "Many "biases" found in psychology become entirely rational under more sophisticated probability distributions". May be "hardwiredness" is not all that hard wired. Or, put it other way, the hardwiredness is not in humans under study but in humans who study them. I don't think that humans would achieve what we have today being hardwired to dismiss facts that don't fit their worldview.

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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications — HN submission

Fri, 31 Jan 2020 23:21:13 GMT

Statistical Consequences of Fat Tails by Nassim Nicholas Taleb

89 points; 31 discussion replies on HN. Paper and source history. A submission is not an endorsement.