Taleb says that in The Black Swan he warned against some classes of risk people don't understand and against risk managers' tools that could not fully capture the properties of the world in which we live.
Mostly true True in substance, wrong in a detail.
Factual: Statements about the present or the past, checked against the record: did they hold up?
The second judge would not resolve this claim; the verdict shown is the first judge's.
What would count as true or false
Judge on the text of The Black Swan (2007 first edition, or editions published before 2009-01-12). True: the book contains explicit warnings about classes of risk that people misunderstand (rare, high-impact events, fat tails) and explicit criticism of the standard tools of risk managers (for example Gaussian or bell-curve models, VaR, or similar quantitative methods) as unable to capture real-world properties. Mostly true: both warnings are present, but the criticism of risk managers' tools is framed mainly as a criticism of economists or forecasters in general, with risk management mentioned only in passing. Mixed: only one of the two warnings appears clearly. Mostly false: the book only touches on these themes vaguely and the claim substantially overstates them. False: the book contains no such warnings.
Set before the research began.
Evidence (4)
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E1 Risk 07: modern portfolio theory should be ditched, says Taleb - Risk.net Risk.net · 12 June 2007
“Taleb argued that models based on bell-curve assumptions, such as the Gaussian distribution model, fail to capture reality.”
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E2 [PDF] Risk Mismanagement - What Led to the Financial Meltdown The New York Times (Joe Nocera, reprinted by faculty.runi.ac.il) · 4 January 2009
“Yet even faulty historical data isn’t Taleb’s primary concern. What he cares about, with standard VaR, is not the number that falls within the 99 percent probability. He cares about what happens in the other 1 percent, at the extreme edge of the curve.”
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E3 [PDF] Risk Mismanagement - What Led to the Financial Meltdown The New York Times (Joe Nocera, reprinted by faculty.runi.ac.il) · 4 January 2009
““This argument is addressed in ‘The Black Swan,’ ” Taleb retorted.”
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E4 The Black Swan: The Impact of the Highly Improbable (book review) Notices of the AMS (review by David Aldous, UC Berkeley) · March 2011
“Taleb is scathing about stock prediction models based on Brownian motion (Black-Scholes and variants) and of the whole idea of measuring risk by standard deviation [p. 232]: You cannot use one single measure for randomness called standard deviation (and call it “risk”); you cannot expect a simple answer to characterize uncertainty.”
Reasoning
I rated this mostly true because a book review quotes the text directly, though the evidence is thin on edition and coverage. Aldous's review of The Black Swan (E4) quotes the book (p. 232) criticising the use of standard deviation as a single measure of "risk". The review also says the book is "scathing" about stock prediction models based on Brownian motion, such as Black-Scholes (E4). The book's subtitle, "The Impact of the Highly Improbable", and Nocera's account (E2) of Taleb's concern with the extreme 1 percent tail under standard VaR are consistent with the claimed warning about misunderstood classes of risk; E3 reports Taleb saying an argument raised with him is addressed in the book. However, the review dates from 2011, so it does not confirm whether the quoted page comes from a pre-2009 edition. E1 is about a 2007 talk, not the book. Little of the book's text itself is in evidence.
Cite this claim
Nassim Taleb, “Taleb says that in The Black Swan he warned against some classes of risk people don't understand and against risk managers' tools that could not fully capture the properties of the world in which we live.” (said 12 January 2009). Verdict: mostly true. Reliability API, claim c_4ae138dc3a76, method 0.1.0+28da144b, dataset release v1.1.2. https://epistacklabs.com/claims/c_4ae138dc3a76
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
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Verdicts are made automatically; how verdicts are made.