Pandora's Risk

Pandora's Risk: Uncertainty at the Core of Finance

KENT OSBAND
Copyright Date: 2011
Pages: 304
https://www.jstor.org/stable/10.7312/osba15172
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  • Book Info
    Pandora's Risk
    Book Description:

    Author of the acclaimed work Iceberg Risk: An Adventure in Portfolio Theory, Kent Osband argues that uncertainty is central rather than marginal to finance. Markets don't trade mainly on changes in risk. They trade on changes in beliefs about risk, and in the process, markets unite, stretch, and occasionally defy beliefs. Recognizing this truth would make a world of difference in investing. Belittling uncertainty has created a rift between financial theory and practice and within finance theory itself, misguiding regulation and stoking huge financial imbalances.

    Sparking a revolution in the mindset of the investment professional, Osband recasts the market as a learning machine rather than a knowledge machine. The market continually errs, corrects itself, and makes new errors. Respecting that process, without idolizing it, will promote wiser investment, trading, and regulation. With uncertainty embedded at its core, Osband's rational approach points to a finance theory worthy of twenty-first-century investing.

    eISBN: 978-0-231-52541-1
    Subjects: Business, Finance

Table of Contents

  1. Front Matter
    (pp. i-vi)
  2. Table of Contents
    (pp. vii-viii)
  3. PREFACE
    (pp. ix-xiv)
  4. ACKNOWLEDGMENTS
    (pp. xv-xvi)
  5. ABBREVIATIONS
    (pp. xvii-xx)
  6. 1 Introduction
    (pp. 1-13)

    This is a book about the most important risk we face in finance. It’s the risk that comes from learning about risk. I call it Pandora’s risk in honor of legend’s prime culprit. If she hadn’t opened the box of wealth and woe, we’d have no hunger to learn.

    Other fields involve learning too. Since the observer never fully understands the observed, there’s always something to learn. Occasionally, learning overturns some core beliefs. That’s how scientific revolutions occur.

    Finance stands out in that the core objects of study are themselves observers. Market participants rarely know the true value of what...

  7. 2 The Ultimate Confidence Game
    (pp. 14-27)

    Financial markets chronically confuse beliefs with reality. That’s their job, along with unwinding the confusion and helping make beliefs real. They’re so pervasive that we ordinarily take their smooth operation for granted.

    To rekindle our sense of wonder, this chapter focuses on the safest thing we know in finance: cold hard cash. What is it? What makes it safe? How does it evolve? As we will see, uncertainty and learning permeate what we think we know best.

    To give is better than to receive. This is especially true of money. I give you some ciphers; you give me something I...

  8. 3 Great Expectations
    (pp. 28-39)

    Money symbolizes wealth at hand. However, most wealth isn’t at hand, and we couldn’t consume it now if we tried. It is a claim on future value. We can never measure future value. We can measure only past value, current trends, and expectations for the future.

    Expectations can’t be consistently right, because no one can predict the future. Expectations won’t be consistently wrong, because markets part fools from their money. We scramble between error and error correction. It’s called learning.

    Learning rocks and rolls our wealth. Between 2003 and 2006, most Americans stopped saving out of income, because their houses...

  9. 4 Sustainable Debt
    (pp. 40-52)

    Mammon, the false god of finance, is justly derided for avarice and injustice. Still, one has to admire his sense of humor. At one extreme he helps scrip pass for real wealth. At the other he buffets real wealth as if it were scrip.

    Debt falls in between. As a deferred claim, it sacrifices the immediacy of cash. As a claim on money rather than proit, it insulates from many business hazards. Servicing should be semiautomatic, except when wealth falls short and forces default. Salvage ater default should follow clear rules.

    Nevertheless, Mammon manages to turn a square deal into...

  10. 5 The Midas Touch
    (pp. 53-65)

    A grateful Bacchus, the god of intoxication, offered King Midas a reward of his choosing. Midas, likely intoxicated himself, asked that everything he touched turn to gold. It was a tragic error. What makes gold money is the ease of transforming it back into commodities. What Midas thought he gained he really lost.

    Ever since, finance has sought to perfect the Midas touch. Imbue everything with “moneyness” simply by easing resale. Then extract a broker’s fee for these services, or trade on speculation about future moneyness.

    This intermediary role is both useful and suspect. Making assets more liquid gives more...

  11. 6 Safety in Numbers
    (pp. 66-78)

    Modern bond markets are highly sensitive to perceived default risk.Credit spreads are normally measured in basis points (bps), which are one–hundredth of percentage points. While default might not trigger complete loss, the residual or salvage value of a defaulted claim is often less than half the nominal value. Ideally the market wants a 1 or 2 bps accuracy in its estimates of default risk per annum.

    There is no way to achieve that degree of accuracy for the debtors we care most about. Knowledge is always rooted in directly relevant observation, and we don’t have nearly enough. So analysts branch into indirectly...

  12. 7 When God Changes Dice
    (pp. 79-91)

    For all his genius, Albert Einstein never accepted the randomness inherent in quantum theory. He repeatedly denied that God would play dice with the universe (Born 2005). Modern physicists ind these denials endearing, because it gives them an opportunity to feel cleverer than Einstein. Few doubt that chance is central.

    Standard finance theory thinks it is clever because it allows for risk. But it tends to ignore the uncertainty enveloping risk, which is often the chance that most matters. Rarely does it note the dearth of relevant observations, much less the implications for pricing and risk management.

    This chapter addresses...

  13. 8 Credit–ability
    (pp. 92-104)

    The marvel is less that public confidence in Western finance occasionally plummets than that so much persists and rebuilds. It’s like a starfish growing back arms. One of the confidence boosters is credit rating.

    Credit rating proper is associated with regulators and with major credit rating agencies like Moody’s and Standard & Poor’s (S&P). By convention, credits are assigned letter grades. Triple-A (Aaa for Moody’s, AAA for S&P) is the highest rating, followed by double-A, single- A, triple-B (or Baa), and so on down to C. Grades below triple- A are subdivided by number or plus-or-minus sign and sometimes attach warnings...

  14. 9 Insecuritization
    (pp. 105-118)

    Readers who have been fretting the dearth of moneymaking advice in this book need look no further. This chapter will demonstrate how to rake in fortunes through creative statistical fraud. Granted, others have beaten us to much booty. Still, foolish regulations, negligent rating practices, and irresponsible fiduciaries invite more ill-gotten gains.

    Here is a basic recipe:

    Take a big bunch of different credit risks, just like a normal bank does, only with far less supervision.

    Repackage the claims in tranches ranked by seniority, and give them impressive names like Collateralized Debt Obligations (CDOs).

    Let the lowest tranches shoulder the mean...

  15. 10 Risks in Value–at–Risk
    (pp. 119-131)

    Most financial assets ofer a much broader range of outcomes than pay-or-don’t-pay. Estimating all the probabilities directly is cumbersome and imprecise. Instead we formulate summary statistics like mean and standard deviation.

    Risk analysts worry a lot about big losses, so they often supplement mean and standard deviation with measures of (lower) tail risk. That is where Value at Risk (VaR) comes in. The name appeals, as it suggests a definite cap on losses.

    In fact, VaR is closer to a loor than a cap. There’s nothing definite about it. And if calculated in the standard way, it is grossly inferior...

  16. 11 Resizing Risks
    (pp. 132-144)

    While VaR lost every tournament described in Chapter 10, conventional standard deviation estimators didn’t win. Estimators based on daily trading range walloped both. This chapter will explain how they work and show some useful things we can do with them.

    Range estimators are a formalization of what good traders have done for generations. Uncertainty is center stage for traders, and their livelihoods depend on managing it right, unlike a host of other risk managers who just report measures to others. So it makes sense that traders would evolve useful, intuitively appealing techniques.

    In saying that, I have violated one of...

  17. 12 Conclusions
    (pp. 145-156)

    Pygmalion held such high standards for women that none could meet them. Driven crazy with loneliness, he sculpted what he thought was an ideal woman of ivory. He clothed it, wedded it, and took it to bed. Aphrodite, taking pity on him, substituted a real woman for the sculpture and blinded him to her imperfections.

    Unfortunately, Pygmalion’s blessing made him insufferable. Bragging of his intolerance for flaw, he encouraged wave after wave of idolatry. People clung to their narrow images of perfection and begged the gods to make them real. They forgot that reality transcends imagination.

    For those of us...

  18. APPENDIX
    (pp. 157-262)
  19. REFERENCES
    (pp. 263-274)
  20. INDEX
    (pp. 275-284)