Category:Decision theory

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Decision theory is included in JEL classification codes:

Decision theory is the study of optimal actions, as determined by considering the probability and utility of different outcomes.


This category has the following 10 subcategories, out of 10 total.









Pages in category "Decision theory"

The following 159 pages are in this category, out of 159 total. This list may not reflect recent changes (learn more).





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List of cognitive biases

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A cognitive bias is a pattern of deviation in judgment that occurs in particular situations (see also cognitive distortion and the lists of thinking-related topics). Implicit in the concept of a "pattern of deviation" is a standard of comparison; this may be the judgment of people outside those particular situations, or may be a set of independently verifiable facts. The existence of some of these cognitive biases has been verified empirically in the field of psychology.

Cognitive biases are instances of evolved mental behavior. Some are presumably adaptive, for example, because they lead to more effective actions or enable faster decisions. Others presumably result from a lack of appropriate mental mechanisms, or from the misapplication of a mechanism that is adaptive under different circumstances.



Decision-making and behavioral biases

Many of these biases are studied for how they affect belief formation, business decisions, and scientific research.

Biases in probability and belief

Many of these biases are often studied for how they affect business and economic decisions and how they affect experimental research.

Social biases

Most of these biases are labeled as attributional biases.

Memory errors

Common theoretical causes of some cognitive biases

See also

Psychology portal
Thinking portal


  1. ^ Pronin, Emily; Matthew B. Kugler (July 2007). "Valuing thoughts, ignoring behavior: The introspection illusion as a source of the bias blind spot". Journal of Experimental Social Psychology (Elsevier) 43 (4): 565–578. doi:10.1016/j.jesp.2006.05.011. ISSN 0022-1031. 
  2. ^ Why We Spend Coins Faster Than Bills by Chana Joffe-Walt. All Things Considered, 12 May 2009.
  3. ^ (Hsee & Zhang, 2004)
  4. ^ (Kahneman, Knetsch, and Thaler 1991: 193) Richard Thaler coined the term "endowment effect."
  5. ^ M. Jeng, "A selected history of expectation bias in physics", American Journal of Physics 74 578-583 (2006)
  6. ^ (Kahneman, Knetsch, and Thaler 1991: 193) Daniel Kahneman, together with Amos Tversky, coined the term "loss aversion."
  7. ^ Kruglanski, 1989; Kruglanski & Webster, 1996
  8. ^ Edwards, W. (1968). Conservatism in human information processing. In: B. Kleinmutz (Ed.), Formal Representation of Human Judgment. (pp. 17-52). New York: John Wiley and Sons.
  9. ^ (Kahneman, Knetsch, and Thaler 1991: 193)
  10. ^ a b c Tversky, Amos; Daniel Kahneman (September 27, 1974). "Judgment under Uncertainty: Heuristics and Biases". Science (American Association for the Advancement of Science) 185 (4157): 1124–1131. 
  11. ^ Darley, John M.; Paget H. Gross (2000). "A Hypothesis-Confirming Bias in Labelling Effects". in Charles Stangor. Stereotypes and prejudice: essential readings. Psychology Press. p. 212. ISBN 9780863775895. 
  12. ^ Kahneman, Daniel; Shane Frederick (2002). "Representativeness Revisited: Attribute Substitution in Intuitive Judgment". in Thomas Gilovich, Dale Griffin, Daniel Kahneman. Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge: Cambridge University Press. pp. 49–81. ISBN 9780521796798. OCLC 47364085. 
  13. ^ Slovic, Paul; Melissa Finucane, Ellen Peters, Donald G. MacGregor (2002). "The Affect Heuristic". in Thomas Gilovich, Dale Griffin, Daniel Kahneman. Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge University Press. pp. 397–420. ISBN 97805219796798. 


Taleb distribution

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In economics and finance, a Taleb distribution is a probability distribution in which there is a high probability of a small gain, and a small probability of a very large loss, which more than outweighs the gains. In these situations the expected value is (very much) less than zero, but this fact is camouflaged by the appearance of low risk and steady returns. It is a combination of kurtosis risk and skewness risk: overall returns are dominated by extreme events (kurtosis), which are to the downside (skew). The corresponding situation is also known as the peso problem.

The term is therefore increasingly used in the financial markets to describe dangerous or flawed trading strategies. The Taleb distribution is named for Nassim Taleb, based on ideas outlined in his Fooled by Randomness.[1]



Criticism of trading strategies

Pursuing a trading strategy with a Taleb distribution yields a high probability of steady returns for a time, but with a near certainty of eventual ruin. This is done consciously by some as a risky trading strategy, while some critics argue that it is done either unconsciously by some, unaware of the hazards ("innocent fraud"), or consciously by others, particularly in hedge funds.

Risky strategy

If done consciously, with one's own capital or openly disclosed to investors, this is a risky strategy, but appeals to some: one will want to exit the trade before the rare event happens. This occurs for instance in a speculative bubble, where one purchases an asset in the expectation that it will likely go up, but may plummet, and hopes to sell the asset before the bubble bursts.

This has also been referred to as "picking up pennies in front of a steamroller".[2]

"Innocent fraud"

John Kay has likened securities trading to bad driving, as both are characterized by Taleb distributions.[3] Drivers can make many small gains in time by taking risks such as overtaking on the inside and tailgating, however, they are then at risk of experiencing a very large loss in the form of a serious traffic accident. Kay has described Taleb Distributions as the basis of the carry trade and has claimed that along with mark-to-market accounting and other practices, constitute part of what JK Galbraith has called "innocent fraud".[4]

Moral hazard

Some critics of the hedge fund industry claim that the compensation structure generate high fees for investment strategies that follow a Taleb distribution, creating moral hazard.[5] In such a scenario, the fund can claim high asset management and performance fees until they suddenly 'blow up', losing the investor significant sums of money and wiping out all the gains to the investor generated in previous periods; however, the fund manager keeps all fees earned prior to the losses being incurred – and ends up enriching himself in the long run because he does not pay for his losses.


Taleb distributions pose several fundamental problems, all possibly leading to risk being overlooked:

presence of extreme adverse events
The very presence or possibility of adverse events may pose a problem per se, which is ignored by only looking at the average case – a decision may be good in expectation (in the aggregate, in the long term), but a single rare event may ruin the investor: one is courting disaster.
unobserved events
This is Taleb's central contention, which he calls black swans – because extreme events are rare, they have often not been observed yet, and thus are not included in scenario analysis or stress testing.
hard-to-compute expectation
A subtler issue is that expectation is very sensitive to assumptions about probability: a trade with a $1 gain 99.9% of the time and a $500 loss 0.1% of the time has positive expected value; while if the $500 loss occurs 0.2% of the time it has approximately 0 expected value; and if the $500 loss occurs 0.3% of the time it has negative expected value. This is exacerbated by the difficulty of estimating the probability of rare events (in this example one would need to observe thousands of trials to estimate the probability with confidence), and by the use of financial leverage: mistaking a small loss for a small gain and magnifying by leverage yields a hidden large loss.

More formally, while the risks for a known distribution can be calculated, in practice one does not know the distribution: one is operating under uncertainty, in economics called Knightian uncertainty.


A number of mitigants have been proposed, by Taleb and others.  These include:

not exposing oneself to large losses
For instance, only buying options (so one can at most lose the premium), not selling them.
performing sensitivity analysis on assumptions
This does not eliminate the risk, but identifies which assumptions are key to conclusions, and thus meriting close scrutiny.
scenario analysis and stress testing
Widely used in industry, they do not include unforeseen events but emphasize various possibilities and what one stands to lose, so one is not blinded by absence of losses thus far.
using non-probabilistic decision techniques
While most classical decision theory is based on probabilistic techniques of expected value or expected utility, alternatives exist which do not require assumptions about the probabilities of various outcomes, and are thus robust. These include minimax, minimax regret, and info-gap decision theory.

See also


  1. ^ Martin Wolf, Why today’s hedge fund industry may not survive, Financial Times, 18 March 2008
  2. ^ Taleb, p. 19
  3. ^ John Kay "A strategy for hedge funds and dangerous drivers", Financial Times, 16 January 2003.
  4. ^ John Kay "Banks got burned by their own ‘innocent fraud’", Financial Times, 15 October 2008.
  5. ^ Are hedge funds a scam? Naked Capitalism/Financial Times, March 2008.

Privatizing profits and socializing losses

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In political discourse, the term privatizing profits and socializing losses refers to the alleged tendency of some firms to benefit (privately) from profits, but not suffer from losses, instead pushing the losses onto society at large, particularly via the government.




The notion that banks privatize profits and socialize losses dates at least to the 19th century, as in this 1834 quote of Andrew Jackson:

I have had men watching you for a long time and I am convinced that you have used the funds of the bank to speculate in the breadstuffs of the country. When you won, you divided the profits amongst you, and when you lost, you charged it to the Bank. ... You are a den of vipers and thieves.
Andrew Jackson, 1834, on closing the Second Bank of the United States;
(unabridged form, extended citation)


Large firms and banks have been accused of this, as a form of crony capitalism and corporate welfare, and some bailouts are cited as examples of this: a bailout socializes a company's losses.

It has been argued that in the current economic system, especially in the U.S., large corporations and wealthy parts of society policies can commonize costs and privatize profits, with the effect of a further concentration of wealth. In particular, government sponsoring and bailouts such as the federal takeover of Fannie Mae and Freddie Mac and the proposed bailout of the U.S. financial system in the economic crisis of 2008 have frequently been referred to in the U.S. as “private gains and public losses”[1] or “privatization of profits and socialization of losses”.[2][3][4] Economic policies which favor such concentration of capital have frequently been criticized as socialism for the rich and capitalism for the poor.[5]


In game theory, this is formalized as the CC–PP game.

In the financial language of options, "socializing losses" corresponds to private firms having a put option from the government: if they lose, the government will cover their losses. The most famous example of this is the Greenspan put.

In the black swan theory of Nassim Nicholas Taleb, he criticizes this as one of his Ten Principles for a Black Swan Robust World,[6] writing as his second principle:

2. No socialisation of losses and privatisation of gains.


While the term is generally used to critique, some have argued that socializing losses, while politically unpopular, is in fact economically desirable in the case of a financial crisis:

What is ineluctably needed involves socializing the losses of a banking system – both conventional banking and shadow banking – after the spectacular winnings of the Forward Minsky Journey were privatized.
Paul McCulley[7]

See also

Related concepts


  1. ^ Robert Reich: A Modest Proposal for Ending Socialized Capitalism, July 15, 2008
  2. ^ Bloomberg Addresses Pending Financial Job Losses,, September 15, 2008
  3. ^ What Should Uncle Sam Do?,, July 28, 2008
  4. ^ Prudent reform needed for Fannie, Freddie, July 16, 2006
  5. ^ Interview with Jon Stewart, The Daily Show, Oct 16, 2008: Available at The Daily Show Site
  6. ^ Ten Principles for a Black Swan Robust World
  7. ^ Comments Before the Money Marketeers Club: Playing Solitaire with a Deck of 51, with Number 52 on Offer, by Paul McCulley

External links

Too Big to Fail

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"Too Big to Fail" is a phrase referring to the idea that in economic regulation, the largest and most interconnected businesses are so large that a government cannot allow them to declare bankruptcy because said failure would have a disastrous effect on the overall economy.

This results in reckless behavior of the institution since the government will intervene (e.g. by bailing out the company) in the event the institution is going to fail.[1] The phrase has also been more broadly applied to refer to a government's policy to bail out any corporation. It raises the issue of moral hazard in business operations.

The term is back to centre stage since the start of the financial meltdown. One of the biggest US companies referred to as too big to fail is American International Group (AIG).

Some critics see the policy as wrong and counterproductive. They think big banks should be left to fail if their risk management was not effective.[2][3] For example, in the international context, the "too big to fail" policy has been explicitly refuted in the People's Republic of China.[4]



Regulatory basis

Before 1950, U.S. federal bank regulators had essentially two options for resolving an insolvent institution: closure, with liquidation of assets and payouts for insured depositors, or purchase and assumption, encouraging the acquisition of assets and assumption of liabilities by another firm. A third option was made available by the Federal Deposit Insurance Act of 1950: providing assistance, the power to support an institution through loans or direct federal acquisition of assets, until it could recover from its distress. The statute limited the "assistance" option to cases where "continued operation of the bank is essential to provide adequate banking service." Regulators shunned this third option for many years, fearing that if regionally- or nationally-important banks were thought to be generally immune to liquidation, markets in their shares would be distorted. Thus the assistance option was never employed during the period 1950-1969, and very seldom thereafter.[5]

Continental Illinois case


The Continental Illinois National Bank and Trust Company experienced a fall in its overall asset quality during the early 1980s. Tight money, Mexico's default and plunging oil prices followed a period when the bank had aggressively pursued commercial lending business, Latin American syndicated loan business, and loan participations in the energy sector. Complicating matters further, the bank's funding mix was heavily dependent on large CDs and foreign money markets, which meant its depositors were more risk-averse than average retail depositors in the US.

Payments crisis

The bank held significant participation in highly-speculative oil and gas loans of Oklahoma's Penn Square Bank. When Penn Square failed in July 1982, the Continental's distress became acute, culminating with press rumors of failure and an investor-and-depositor run in early May 1984. In the first week of the run, the Fed permitted the Continental Illinois discount window credits on the order of $3.6 billion. Still in significant distress, the management obtained a further $4.5 billion in credits from a syndicate of money center banks the following week. These measures failed to stop the run, and regulators were confronted with a crisis.

Regulatory crisis

The seventh-largest bank in the nation by deposits would very shortly be unable to meet its obligations. Regulators faced a tough decision about how to resolve the matter. Of the three options available, only two were seriously considered. Even banks much smaller than the Continental were deemed unsuitable for resolution by liquidation, owing to the disruptions this would have inevitably caused. The normal course would be to seek a purchaser (and indeed press accounts that such a search was underway contributed to Continental depositors' fears in 1984). However, in the tight-money financial climate of the early 1980s, no purchaser was forthcoming.

Besides generic concerns of size, contagion of depositor panic and bank distress, regulators feared the significant disruption of national payment and settlement systems. Of special concern was the wide network of correspondent banks with high percentages of their capital invested in the Continental Illinois. Essentially, the bank was deemed "too big to fail," and the "provide assistance" option was reluctantly taken. The dilemma now became, how to provide assistance without significantly unbalancing the nation's banking system?

Stopping the run

To prevent immediate failure, the Federal Reserve announced categorically that it would meet any liquidity needs the Continental might have, while FDIC gave depositors and general creditors a full guarantee (not subject to the $100,000 FDIC deposit-insurance limit) and provided direct assistance of $2 billion (including participations). Money center banks assembled an additional $5.3 billion unsecured facility pending a resolution and resumption of more-normal business. These measures slowed, but did not stop, the outflow of deposits.


In a United States Senate hearing afterwards, the then Comptroller of the Currency C. T. Conover defended his position by admitting the regulators will not let the largest 11 banks fail[6]. Regulatory agencies (FDIC, Office of the Comptroller of the Currency, the Fed, etc.) feared this may cause widespread financial complications and a major bank run that may easily spread by financial contagion. The implicit guarantee of too-big-to-fail has been criticized by many since then for its preferential treatment of large banks[citation needed]. Simultaneously, the perception of too-big-to-fail may diminish healthy market discipline, and may have influenced the decisions behind insolvency of the Washington Mutual in 2008. For example, large depositors in banks not covered by the policy tend to have a strong incentive to monitor the bank's financial condition, and/or withdraw in case the bank's policies exposes them to high risks, since FDIC guarantees have an upper limit. However, large depositors in a "too big to fail" bank would have less incentive, since they'd expect to be bailed out in the event of failure.

The Federal Deposit Insurance Corporation Improvement Act was passed in 1991, giving the FDIC the responsibility to rescue an insolvent bank by the least costly method. The Act had the implicit goal of eliminating the widespread belief among depositors that a loss of depositors and bondholders will be prevented for large banks. However, the Act included an exception in cases of systemic risk, subject to the approval of two-thirds of the FDIC Board of Directors, the Federal Reserve Board of Governors, and the Treasury Secretary.[7]

Effect on banks' cost of capital

Since the full amount of the deposits and debts of "too big to fail" banks are effectively guaranteed by the government, large depositors view deposits with these banks as a safer investment than deposits with smaller banks. Therefore, large banks are able to pay lower interest rates to depositors than small banks are obliged to pay. In October 2009, Sheila Bair, the current Chairperson of the FDIC, commented that "'Too big to fail' has become worse. It's become explicit when it was implicit before. It creates competitive disparities between large and small institutions, because everybody knows small institutions can fail. So it's more expensive for them to raise capital and secure funding.".[8] A study conducted by the Center for Economic and Policy Research found that the difference between the cost of funds for banks with more than $100 billion in assets and the cost of funds for smaller banks widened dramatically after the formalization of the "too big to fail" policy in the U.S. in the fourth quarter of 2008.[9] This shift in the large banks' cost of funds gave an indirect "too big to fail" subsidy of $34.1 billion per year to the 18 U.S. banks with more than $100 billion in assets.

"Too big to fail is too big"

Mervyn King, the governor of the Bank of England, called for banks that are "too big to fail" to be cut down to size, as a solution to the problem of banks having taxpayer-funded guarantees for their speculative investment banking activities. "If some banks are thought to be too big to fail, then, in the words of a distinguished American economist, they are too big. It is not sensible to allow large banks to combine high street retail banking with risky investment banking or funding strategies, and then provide an implicit state guarantee against failure."[10]

However, Alastair Darling disagreed; "Many people talk about how to deal with the big banks – banks so important to the financial system that they cannot be allowed to fail. But the solution is not as simple, as some have suggested, as restricting the size of the banks".[10]

Too big to fail tax

Willem Buiter proposes a tax to internalize the massive external costs inflicted by "too big to fail" institution. "When size creates externalities, do what you would do with any negative externality: tax it. The other way to limit size is to tax size. This can be done through capital requirements that are progressive in the size of the business (as measured by value added, the size of the balance sheet or some other metric). Such measures for preventing the New Darwinism of the survival of the fattest and the politically best connected should be distinguished from regulatory interventions based on the narrow leverage ratio aimed at regulating risk (regardless of size, except for a de minimis lower limit)."[11]

See also


  1. ^ Federal Reserve Bank of Richmond Economic Quarterly Volume 91/2 Spring 2005 by Ennis, Huberto M.; Malek, H.S
  2. ^ Alton E. Drew, The Business Week, retrieved on March 20, 2009
  3. ^ Benton E. Gup, ed (2003-12-30). Too Big to Fail: Policies and Practices in Government Bailouts. Westport, Connecticut: Praeger Publishers. pp. 368. doi:10.1336/1567206212. ISBN 1-567-20621-2. OCLC 52288783. Retrieved 2008-02-20. "The doctrine of laissez-faire seemingly has been revitalized as Republican and Democratic administrations alike now profess their firm commitment to policies of deregulation and freemarkets in the new global economy. -- Usually associated with large bank failures, the phrase too big to fail, which is a particular form of government bailout, actually applies to a wide range of industries, as this volume makes clear. Examples range from Chrysler to Lockheed Aircraft and from New York City to Penn Central Railroad. Generally speaking, when a corporation, an organization, or an industry sector is considered by the government to be too important to the overall health of the economy, it will not be allowed to fail. Government bailouts are not new, nor are they limited to the United States. This book presents the views of academics, practitioners, and regulators from around the world (e.g., Australia, Hungary, Japan, Europe, and Latin America) on the implications and consequences of government bailouts." 
  4. ^ Chang, T.K. (2001-01-12). "Ten Lessons of the GITIC Bankruptcy". Asian Wall Street Journal. Retrieved 2009-08-01. 
  5. ^ Heaton, Hal B., Riegger, Christopher. "Commercial Banking Regulation", Class discussion notes.
  6. ^ Conover, Charles (1984), "Testimony", Inquiry Into the Continental Illinois Corp. and Continental National Bank: Hearing Before the Subcommittee on Financial Institutions Supervision, Regulation, and Insurance of the Committee on Banking, Finance, and Urban Affairs, U.S. House of Representatives, 98th Congress, 2nd Session, 18-19 September and 4 October, pp. 98–111 
  7. ^ Bradley, Christine; Craig, Valentine V. (2007), "Privatizing Deposit Insurance: Results of the 2006 FDIC Study", FDIC Quarterly 1 (2): 23–32, 
  8. ^ Wiseman, Paul; Gogoi Pallavi (2009-10-19). "FDIC chief: Small banks can't compete with bailed-out giants". USA Today. Retrieved 2009-10-22. 
  9. ^ Baker, Dean; Travis McArthur (September 2009). "The Value of the 'Too Big to Fail' Big Bank Subsidy". Center for Economic and Policy Research Issue Brief. Retrieved 2009-10-22. 
  10. ^ a b Treanor, Jill (2009-06-17). "King calls for banks to be 'cut down to size'". The Guardian. Retrieved 2009-06-18. 
  11. ^ Buiter, Willem (June 24, 2009). "Too big to fail is too big". The Financial Times. Retrieved 2009-11-22. 

Further reading

External links