1. Survivorship Bias https://store.theartofservice.com/the-survivorship-bias-toolkit.html

2. Risks to civilization, humans, and planet Earth 1 Despite the importance of existential risks, it is a difficult subject to study directly since humanity has never been destroyed before; while this does not mean that it will not be in the future, it does make modelling existential risks difficult, due in part to survivorship bias. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

3. Equity premium puzzle - Denial of equity premium 1 *Survivorship bias of exchanges: exchanges often go bust (just as governments default; for example, Shanghai stock exchange during 1949 communist takeover), and this risk needs to be included – using only exchanges which have survived for the long-term overstates returns. Exchanges close often enough for this effect to matter. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

4. Risks to civilization, humans and planet Earth 1 Human extinction is a difficult subject to study directly since humanity has never been destroyed before; while this does not mean that it will not be in the future, it does make modelling existential risks difficult, due in part to survivorship bias. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

5. Hedge funds - Non-investable indices 1 The short lifetimes of many hedge funds means that there are many new entrants and many departures each year, which raises the problem of Attrition bias|survivorship bias. If we examine only funds that have survived to the present, we will overestimate past returns because many of the worst-performing funds have not survived, and the observed association between fund youth and fund performance suggests that this bias may be substantial. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

6. Private equity - Private equity fund performance 1 This analysis may actually overstate the returns because it relies on voluntarily reported data and hence suffers from survivorship bias (i.e https://store.theartofservice.com/the-survivorship-bias-toolkit.html

7. Online participation - Participation in the social web 1 Often, feedbacks, opinions and editorials are posted from those users who have stronger feelings towards the matter than most others; thus it is often the case that some posts online are not in fact representative of the entire population leading to what is call the Survivorship bias https://store.theartofservice.com/the-survivorship-bias-toolkit.html

8. Rags to riches - Criticism 1 The concept of Rags to riches has been criticised by social reform movement|reformers, revolutionaries, essayists and statisticians, who argue that only a handful of exceptionally capable and/or mainly Luck|lucky persons are actually able to travel the rags to riches road, being the great publicity given to such cases a natural Survivorship bias illusion,Taleb, 2001 https://store.theartofservice.com/the-survivorship-bias-toolkit.html

9. Jensen's alpha - History 1 Since Eugene Fama, many academics believe financial markets are too Efficient- market hypothesis|efficient to allow for repeatedly earning positive Alpha, unless by chance. To the contrary, empirical studies of mutual funds spearheaded by Russ Wermers usually confirm managers' stock-picking talent, finding positive Alpha, however this work has been criticized. Among the criticisms is survivorship bias. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

10. Fooled by Randomness - Thesis 1 * Survivorship bias. We see the winners and try to learn from them, while forgetting the huge number of losers. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

11. Survivorship bias 1 'Survivorship bias', or 'survival bias', is the logical error of concentrating on the people or things that survived some process and inadvertently overlooking those that did not because of their lack of visibility. This can lead to false conclusions in several different ways. The survivors may be actual people, as in a medical study, or could be companies or research subjects or applicants for a job, or anything that must make it past some selection process to be considered further. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

12. Survivorship bias 1 Survivorship bias can lead to overly optimistic beliefs because failures are ignored, such as when companies that no longer exist are excluded from analyses of financial performance https://store.theartofservice.com/the-survivorship-bias-toolkit.html

13. Survivorship bias 1 Survivorship bias is a type of selection bias. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

14. Survivorship bias - In finance 1 In finance, survivorship bias is the tendency for failed companies to be excluded from performance studies because they no longer exist https://store.theartofservice.com/the-survivorship-bias-toolkit.html

15. Survivorship bias - In finance 1 In this paper the researchers eliminate survivorship bias by following the returns on all funds extant at the end of 1976 https://store.theartofservice.com/the-survivorship-bias-toolkit.html

16. Survivorship bias - In finance 1 To use the current 500 members only and create a historical equity line of the total return of the companies that met the criteria, would be adding survivorship bias to the results https://store.theartofservice.com/the-survivorship-bias-toolkit.html

17. Survivorship bias - In finance 1 Financial writer Nassim Taleb called the survivorship bias silent evidence in his book The Black Swan. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

18. Survivorship bias - In the military 1 During World War II, the statistician Abraham Wald took survivorship bias into his calculations when considering how to minimize bomber losses to enemy fire https://store.theartofservice.com/the-survivorship-bias-toolkit.html

19. Survivorship bias - In cats 1 Another possible explanation for this phenomenon would be survivorship bias. The fact that cats who die in falls are less likely to be brought to a veterinarian than injured cats, and thus many of the cats killed in falls from higher buildings are not reported in studies of the subject. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

20. Survivorship bias - As a general experimental flaw 1 Survivorship bias (or survivor bias) is a statistical artifact (error)|artifact in applications outside finance, where studies on the remaining population are fallaciously compared with the historic average despite the survivors having unusual properties. Mostly, the unusual property in question is a track record of success (like the successful funds). https://store.theartofservice.com/the-survivorship-bias-toolkit.html

21. Survivorship bias - As a general experimental flaw 1 A major criticism which surfaced against his calculations was the possibility of unconscious survivorship bias in subject selections. He was accused of failing to take into account the large effective size of his sample (all the people he rejected as not being strong telepaths because they failed at an earlier testing stage). Had he done this he might have seen that, from the large sample, one or two individuals would probably achieve the track record of success he had found purely by chance. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

22. Survivorship bias - As a general experimental flaw 1 Survivorship bias is one of the issues discussed in the provocative 2005 paper Why Most Published Research Findings Are False. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

23. Survivorship bias - In business law 1 Survivorship bias can raise Truth in advertising|truth-in-advertising problems when the success rate advertised for a product or service is measured with respect to a population whose makeup differs from that of the target audience whom the company offering that product or service targets with advertising claiming that success rate. These problems become especially significant when https://store.theartofservice.com/the-survivorship-bias-toolkit.html

24. Global catastrophic risks 1 Researchers experience difficulty in studying human extinction directly, since humanity has never been destroyed before. While this does not mean that it will not be in the future, it does make modelling existential risks difficult, due in part to survivorship bias. https://store.theartofservice.com/the-survivorship-bias-toolkit.html

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