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The Signal and the Noise: The Art and Science of Prediction

Silver, Nate
As Nassim Nicholas Taleb detailed in The Black Swan and as Fama also discussed in his thesis, the movement of stock prices does not follow a gentle bell-curve distribution. Instead, stock-price movements are characterized by very occasional but very large swings up or down. The distribution of stock-market crashes can also be modeled fairly well by a power-law distribution, which is the same function that governs the frequency of earthquakes.
The Signal and the Noise: The Art and Science of Prediction - Silver, Nate Location 10154-10157 - Your Highlight on Page iv | Added on Tuesday, 16 July 13 02:48:39
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Jay Rosen, ?The View from Nowhere: Questions and Answers,? Jay Rosen?s Press Think, November 10, 2010. http://pressthink.org/2010/11/the-view-from-nowhere-questions-and-answers/
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This is just a personal reflection?not an empirical observation?but I am being somewhat literal about this point. When I was working on this book and came across a thorny problem that I couldn?t quite resolve, I found it much more productive to walk around, subjecting my brain to random inputs, than to stare at my computer screen or sit in a coffee shop. One of the advantages of living in New York is that it offers 24/7 access to the spontaneous behavior of eight million human beings who might jog your mind or your memory.
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Joel Mokyr, The Gifts of Athena: Historical Origins of the Knowledge Economy (Princeton: Princeton University Press, Kindle Edition), location 160?162.
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Tomasso Poggio and Federico Girosi, ?A Theory of Networks for Approximation and Learning,? Massachusetts Institute of Technology Artificial Intelligence Laboratory and Center for Biological Information Processing, Whitaker College, A.I. Memo 1140, C.B.I.P. Paper 31, July 1989. http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA212359
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Sarah Lichtenstein and Baruch Fischhoff, ?Training for Calibration,? prepared for U.S. Army Research Institute for the Behavioral and Social Sciences, ARI Technical Report TR-78-A32; November 1978. http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA069703
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Christopher J. Gill, Lora Sabin and Christopher H. Schmidt, ?Why Clinicians Are Natural Bayesians,? British Medical Journal, vol. 330; May 7, 2005. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC557240/
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Thomas C. Peterson, William M. Connolley, and John Fleck, ?The Myth of the 1970s Global Cooling Scientific Consensus,? Bulletin of the American Meteorological Society, September 2008. http://scienceblogs.com/stoat/Myth-1970-Global-Cooling-BAMS-2008.pdf
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Nate Silver, ?Despite Protests, Some Reason for Optimism in Copenhagen,? FiveThirtyEight.com, December 9, 2009. http://www.fivethirtyeight.com/2009/12/despite-protests-some-reasons-for.html.
The Signal and the Noise: The Art and Science of Prediction - Silver, Nate Location 9451-9454 - Your Highlight on Page 504 | Added on Tuesday, 16 July 13 02:16:59
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Specifically, a linear regression of the sign of that day?s stock price (1 indicating a positive movement and ?1 indicating a negative movement) on the previous day?s stock price. The trend is also highly statistically significant if you take a regression of the percentage change in the stock price on the previous day?s percentage change. Note, however, that standard forms of regression analysis assume that errors are normally distributed, whereas the stock market does not obey a normal distribution. Economists like Fama think this is a problem when applying standard statistical tests to analyze patterns in stock prices.
The Signal and the Noise: The Art and Science of Prediction - Silver, Nate Location 9188-9192 - Your Highlight on Page 498 | Added on Tuesday, 16 July 13 02:12:19
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Contrast this with a sport like tennis, where the structure of the game is such that even modest differences in skill level manifest themselves very quickly. The very best players in the world, like Rafael Nadal and Novak Djokovic, win only about 55 percent of the points they play?barely more than half. However, hundreds of points are played over the course of a single match, while baseball players might get just four or five at-bats. It would be silly to conclude that Nadal is better at tennis than Josh Hamilton is at baseball. But Nadal almost always wins while Hamilton has plenty of nights when he goes 0-for-4. In tennis, you reach the long run much more quickly.
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David H. Krantz, ?The Null Hypothesis Testing Controversy in Psychology,? Journal of the American Statistical Association, 44, no. 448 (December 1999). http://www.jstor.org/discover/10.2307/2669949?uid=3739832&uid=2&uid=4&uid=3739256&sid=47698905120317.
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William M. Briggs, ?It Is Time to Stop Teaching Frequentism to Non-Statisticians,? arXiv.org, January 13, 2012. http://arxiv.org/pdf/1201.2590.pdf
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David R. Anderson, Kenneth P. Burnham, and William L. Thompson, ?Null Hypothesis Testing: Problems, Prevalence, and an Alternative,? Journal of Wildlife Management, 64, 4 (2000), pp. 912?923. http://cat.inist.fr/%3FaModele%3DafficheN%26cpsidt%3D792848.
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Jeff Gill, ?The Insignificance of Null Hypothesis Significance Testing,? Political Research Quarterly, 52, 3 (September 1999), pp. 647?674. http://www.artsci.wustl.edu/~jgill/papers/hypo.pdf
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Although there are several different formulations of the steps in the scientific method, this version is mostly drawn from ?APPENDIX E: Introduction to the Scientific Method,? University of Rochester. http://teacher.pas.rochester.edu/phy_labs/appendixe/appendixe.html.
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Andrew Gelman and Cosma Tohilla Shalizi, ?Philosophy and the Practice of Bayesian Statistics,? British Journal of Mathematical and Statistical Psychology, pp. 1?31, January 11, 2012. http://www.stat.columbia.edu/~gelman/research/published/philosophy.pdf
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Raymond S. Nickerson, ?Null Hypothesis Significance Testing: A Review of an Old and Continuing Controversy,? Psychological Methods, 5, 2 (2000), pp. 241?301. http://203.64.159.11/richman/plogxx/gallery/17/%E9%AB%98%E7%B5%B1%E5%A0%B1%E5%91%8A.pdf.
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Jeremy Kahn, ?The Man Who Would Have Us Bet on Terrorism?Not to Mention Discard Democracy and Cryogenically Freeze Our Heads?May Have a Point (About the Betting, We Mean),? Fortune magazine via CNN Money, September 15, 2003.
The Signal and the Noise: The Art and Science of Prediction - Silver, Nate Location 8478-8480 - Your Highlight on Page 483 | Added on Monday, 15 July 13 21:04:11
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Glenn Gunzelmann and Kevin A. Gluck, ?Knowledge Tracing for Complex Training Applications: Beyond Bayesian Mastery Estimates,? Air Force Research Laboratory,; Proceedings of the Thirteenth Conference on Behavior Representation in Modeling and Simulation, 2004, pp. 383?84. http://act-r.psy.cmu.edu/papers/710/gunzelmann_gluck-2004.pdf
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Specifically, the fit line in figure 5-6c is generated by a technique called Lowess regression. This technique is fine for many things and does not inherently lead to overfitting, but it requires you to set a smoothness parameter that will model anything from a very tight fit to a very loose one. In this case, obviously, I?ve chosen an implausibly tight fit.
The Signal and the Noise: The Art and Science of Prediction - Silver, Nate Location 8261-8263 - Your Highlight on Page 478 | Added on Monday, 15 July 13 14:47:51
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Corruption Perceptions Index 2011,? Transparency.org. http://cpi.transparency.org/cpi2011/
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The mental shortcut that Daniel Kahneman calls the availability heuristic39?we tend to overrate the likelihood of events that are nearer to us in time and space and underpredict the ones that aren?t?may have clouded our judgment.
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at least this flawed type of thinking would have involved some thinking. If we had gone through the thought process, perhaps we could have recognized how loose our assumptions were. Schelling suggests that our problems instead run deeper. When a possibility is unfamiliar to us, we do not even think about it.
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Nate Silver, ?Lies, Damned Lies: Projection Reflection,? Baseball Prospectus, October 11, 2006. http://www.baseballprospectus.com/article.php?articleid=5609.
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The Unfamiliar and the Improbable Rumsfeld?s favorite part of Wohlstetter?s book is the foreword, composed by the Nobel Prize?winning economist Thomas Schelling, who was instrumental in translating John Nash?s early work on game theory into national-security contexts. Schelling writes of our propensity to mistake the unfamiliar for the improbable: There is a tendency in our planning to confuse the unfamiliar with the improbable. The contingency we have not considered seriously looks strange; what looks strange is thought improbable; what is improbable need not be considered seriously.
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Nate Silver, ?Models Based on ?Fundamentals? Have Failed at Predicting Presidential Elections,? FiveThirtyEight, New York Times, March 26, 2012.
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A conspiracy theory might be thought of as the laziest form of signal analysis. As the Harvard professor H. L. ?Skip? Gates says, ?Conspiracy theories are an irresistible labor-saving device in the face of complexity.?
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Why is this the case? ?For most of the U.S., land is abundant,? Anil Kashyap explained in a note to me. ?So the value of a house and a plot of land is about what the cost of construction would be. With all the technical progress in building, construction costs have fallen steadily. So expecting appreciation is doubtful. The big exception is places where there are building restrictions. One way to see this is to notice that Texas had almost no bubble. Why? Because there is no zoning and few natural limitations.?
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Hedge funds and other sophisticated investors generally do not have these requirements: they will do their own due diligence on a security, happy to bet against a ratings agency?s forecast when warranted (as it often is). But public pension funds and other institutional investors like college endowments are stuck. Jane?s retirement savings and Johnny?s college scholarship are dependent on the accuracy of the ratings agencies, while a hedge fund leaves itself the flexibility to make the big short.
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Although the polling on the bailout bills was somewhat ambiguous at the time they were passed, later statistical analyses suggested that members of Congress who had voted for the bailout were more likely to lose their seats. See for example: Nate Silver, ?Health Care and Bailout Votes May Have Hurt Democrats,? FiveThirtyEight, New York Times, November 16, 2011. http://fivethirtyeight.blogs.nytimes.com/2010/11/16/health-care-bailout-votes-may-have-hurt-democrats/
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http://fivethirtyeight.blogs.nytimes.com/2012/03/26/models-based-on-fundamentals-have-failed-at-predicting-presidential-elections/
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William Nordhaus, ?The Challenge of Global Warming: Economic Models and Environmental Policy,? 2007. http://nordhaus.econ.yale.edu/dice_mss_072407_all.pdf.
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. Richard B. Rood, Maria Carmen Lemos, and Donald E. Anderson, ?Climate Projections: From Useful to Usability,? University of Michigan, December 15, 2010. http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cts=1330695376711&ved=0CCsQFjAB&url=http%3A%2F%2Fclimateknowledge.org%2Fopenclimate%2Fdoclink%2F20101211_Projections_Usability_AGU_2010.ppt&ei=xcxQT7HYNoPg0QHNoMDqDQ&usg=AFQjCNH0X_mGc24M3bWTlVusJeItaZm_bA&sig2=bfPJPgcKUTj6czOP-WnegQ
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Taken together, Schmidt told me, these three types of uncertainty tend to be at a minimum at a period of about twenty or twenty-five years in advance of a climate forecast. This is close enough that we know with reasonable certainty how much CO2 there will be in the atmosphere?but far enough away that the effects of ENSO and volcanoes and the solar cycle should have evened out.
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The level of industrial activity is fairly constant, but CO2 circulates quickly into the atmosphere and remains there for a long time. (Its chemical half-life has been estimated at about thirty years.61) Even if major industrialized countries agreed to immediate and substantial reductions in CO2 emissions, it would take years to reduce the growth rate of CO2 in the atmosphere, let alone to actually reverse it. ?Neither you nor I will ever see a year in which carbon dioxide concentrations have gone down, not ever,? Schmidt told me. ?And not your children either.?
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On the other hand, if you had asserted that there was just a 1 percent chance that temperatures would fail to increase over the decade, your theory is now in much worse shape because you are claiming that this was a more definitive test. Under Bayes?s theorem, the probability you would attach to the global warming hypothesis has now dropped to just 28 percent. When we advance more confident claims and they fail to come to fruition, this constitutes much more powerful evidence against our hypothesis. We can?t really blame anyone for losing faith in our forecasts when this occurs; they are making the correct inference under Bayesian logic.
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as when trading stock options or wagering on an NBA team, you may be able to place bets on your ability to forecast the uncertainty accurately. However, there is another reason to quantify the uncertainty carefully and explicitly. It is essential to scientific progress, especially under Bayes?s theorem.
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there is another reason to quantify the uncertainty carefully and explicitly. It is essential to scientific progress, especially under Bayes?s theorem.
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this book encourages readers to think carefully about the signal and the noise and to seek out forecasts that couch their predictions in percentage or probabilistic terms. They are a more honest representation of the limits of our predictive abilities. When a prediction about a complex phenomenon is expressed with a great deal of confidence, it may be a sign that the forecaster has not thought through the problem carefully, has overfit his statistical model, or is more interested in making a name for himself than in getting at the truth.
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