Nicholas Nassim Taleb's The Black Swan
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Nicholas Nassim Taleb's The Black Swan

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Overview of Chapter 12 and 13 in The Black Swan: humans are not good at predicting, so therefore we should minimize downside risk exposure and maximize upside risk exposure

Overview of Chapter 12 and 13 in The Black Swan: humans are not good at predicting, so therefore we should minimize downside risk exposure and maximize upside risk exposure

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Nicholas Nassim Taleb's The Black Swan Presentation Transcript

  • 1. The Black Swan Chapter 12 (Human can’t predict) and Chapter 13 (Go to parties!) BCIG National Institutes of Health Bethesda MD June 28, 2007 Melanie Swan, Futurist MS Futures Group 415-505-4426 melanie@melanieswan.com http://www.melanieswan.com http://futurememes.blogspot.com
  • 2. Bio – Melanie Swan  Educational background:     Professional experience    Futurist: speaker, researcher, business advisor Hedge Fund Manager: Wall Street, proprietary Current projects     BA French & Economics, Georgetown University MBA Finance & Accounting, Wharton, Univ. of Pennsylvania Current course work in Physics & Computer Science OpenBasicResearch.org del.icio.us for people Issues in running Historical Simulations Interests: science fiction, travel BCIG June 28, 2007 2
  • 3. Ch 12 Summary: Humans can’t predict  Continued theme of inability to predict, inability to comprehend uncertainty  The Past has a Past: problems with the past    We do not learn from the past Future blindness and future autism Epistemic arrogance BCIG June 28, 2007 3
  • 4. Ch 12: The Past has a Past: problems with the past   History is not facts, but ex-post narrative The past is very difficult to predict     Humans cannot understand uncertainty     Ice cube melting “Butterfly in India” paradigm The Iliad: Helenus Do not learn from the past Cannot understand a future mixed with chance Black Swan asymmetry allows confidence in what is wrong “Our problem is not just that we don’t know the future, we don’t know much of the past either…” BCIG June 28, 2007 4
  • 5. Ch 12: Future blindness  Humans are not natural skeptics     Disbelief requires more energy No cognitive science research on future blindness Happiness research: overestimation of both pleasant and unpleasant events Epistemocracy, epistemic arrogance, epistemic humility  Advice: skeptical-empiricism like Monsieur de Montaigne Michel de Montaigne BCIG June 28, 2007 5
  • 6. Ch 12: Why humans can’t predict   Epistemic arrogance and corresponding future blindness Fooled by reductions   Flawed tools of inference, especially from Black Swan-free Mediocristan    Especially told by people wearing neckties E.g.; perception that the exceptional is inconsequential Confirmation bias Casnova / survivor bias BCIG June 28, 2007 6
  • 7. Ch 13 Summary: Go to parties!   Phenomenon: low volatility = high risk Action in the face of the Black Swan   Be fooled in small matters not large Benefit from unpredictability     Embrace trial and error Manage exposure to Black Swans Be prepared and seize opportunity Central theme: Asymmetric outcomes  Uncertainty: prepare for possible consequences (knowable) vs. the probability of occurrence (unknowable) BCIG June 28, 2007 7
  • 8. Ch 13: Phenomenon: low volatility = high risk  People engage in strategies that produce low volatility but have the risk of large loss     Long-time corporate employee vs. consultant Seemingly stable dictatorship (Saudi Arabia) vs. democracy Bankers, lenders Achilles heel of capitalism: the fittest looking company is the most exposed for a negative Black Swan  Enron, IBM, telecoms, etc. BCIG June 28, 2007 8
  • 9. Ch 13: Manage your Black Swan exposure Distinguish between positive and negative contingencies Act against errors in prediction and risk perception     Lopsided barbell: increase exposure to positive Black Swans, decrease exposure to negative Black Swans Financial investments: 85-90% in T-bills (safest), 10-15% in as many as possible options/private equity (riskiest) Positive Black Swan Industries      Scientific Research Biotech Movies Publishing Venture Capital Negative Black Swan Industries     Military Catastrophe insurance Homeland security Banking, lending BCIG June 28, 2007 9
  • 10. Ch 13: Be prepared and seize opportunity  Don’t look for the precise and the local   Seize opportunity    Pasteur “Chance favors the prepared” Collect non-lottery tickets (openended payoffs) Gain exposure to the envelope of serendipity: go to parties Beware of forecasters  Public and private sector equally bad at forecasting - “paid forecasters are institutionalized fraud” BCIG June 28, 2007 10
  • 11. Ch 12-13 Summary: Don’t predict, go to parties Why humans can’t predict     Epistemic arrogance Fooled by reductions Flawed tools of inference from Mediocristan Mediocristan      Gaussian Linear (easier to predict) Experts Exceptional is inconsequential     Black Swans Non-linear (impossible to predict) No experts Exception matters Central theme of the book: Asymmetric outcomes   Extremistan Uncertainty: focus on the consequences (knowable) vs. the probability of occurrence (unknowable) Use preparedness and serendipity to manage Black Swan exposure BCIG June 28, 2007 11
  • 12. Thank you Melanie Swan, Futurist MS Futures Group 415-505-4426 melanie@melanieswan.com http://www.melanieswan.com http://futurememes.blogspot.com