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| The '''St. Petersburg lottery''' or '''St. Petersburg paradox'''<ref>Conceptual foundations of risk theory. By [[Michael D. Weiss]], United States. Dept. of Agriculture. Economic Research Service. [http://books.google.com/books?id=v33W8lKfOo0C&pg=PA36 p36]</ref> is a [[paradox]] related to [[probability theory|probability]] and [[decision theory]] in [[economics]]. It is based on a particular (theoretical) [[lottery]] game that leads to a [[random variable]] with infinite [[expected value]] (i.e., infinite expected payoff) but nevertheless seems to be worth only a very small amount to the participants. The St. Petersburg paradox is a situation where a naive decision criterion which takes only the expected value into account predicts a course of action that presumably no actual person would be willing to take. Several resolutions are possible.
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| The paradox is named from [[Daniel Bernoulli]]'s presentation of the problem and his solution, published in 1738 in the ''Commentaries of the Imperial Academy of Science of [[Saint Petersburg]]'' {{harv|Bernoulli|1738}}. However, the problem was invented by Daniel's cousin [[Nicolaus I Bernoulli|Nicolas Bernoulli]] who first stated it in a letter to [[Pierre Raymond de Montmort]] on September 9, 1713 {{harv|de Montmort|1713}}.
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| == The paradox ==
| | Hi there. The author's name is [http://www.encyclopedia.com/searchresults.aspx?q=Eusebio Eusebio] so he never really [https://www.google.com/search?hl=en&gl=us&tbm=nws&q=beloved&btnI=lucky beloved] that name. In his professional life he can be a people manager. He's always loved living located in Guam and he gives you everything that he needs there. To drive is one of that this things he loves virtually. He's been working in his website for some people time now. Check one out here: http://prometeu.net<br><br>Also visit my blog [http://prometeu.net hack clash of clans android apk] |
| A casino offers a [[game of chance]] for a single player in which [[Coin flipping|a fair coin is tossed]] at each stage. The pot starts at 1 dollar and is doubled every time a head appears. The first time a tail appears, the game ends and the player wins whatever is in the pot. Thus the player wins 1 dollar if a tail appears on the first toss, 2 dollars if a head appears on the first toss and a tail on the second, 4 dollars if a head appears on the first two tosses and a tail on the third, 8 dollars if a head appears on the first three tosses and a tail on the fourth, and so on. In short, the player wins 2<sup>''k''</sup> dollars, where ''k'' heads are tossed before the first tail appears. What would be a fair price to pay the casino for entering the game?
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| To answer this, we need to consider what would be the average payout: With probability 1/2, the player wins 1 dollar; with probability 1/4 the player wins 2 dollars; with probability 1/8 the player wins 4 dollars, and so on. The [[expected value]] is thus
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| :<math>E=\frac{1}{2}\cdot 1+\frac{1}{4}\cdot 2 + \frac{1}{8}\cdot 4 + \frac{1}{16}\cdot 8 + \cdots</math>
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| ::<math>=\frac{1}{2} + \frac{1}{2} + \frac{1}{2} + \frac{1}{2} + \cdots</math>
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| ::<math>=\sum_{k=1}^\infty {1 \over 2}=\infty \,.</math>
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| Assuming the game can continue as long as the coin toss results in heads and in particular that the casino has unlimited resources, this sum [[unbounded|grows without bound]] and so the expected win for repeated play is an infinite amount of money. Considering nothing but the expectation value of the net change in one's monetary wealth, one should therefore play the game at any price if offered the opportunity. Yet, in published descriptions of the game, many people expressed disbelief in the result. Martin quotes [[Ian Hacking]] as saying "few of us would pay even $25 to enter such a game" and says most commentators would agree.<ref>{{harv|Martin|2004}}.</ref> The paradox is the discrepancy between what people seem willing to pay to enter the game and the infinite expected value.
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| == Solutions of the paradox ==
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| Several approaches have been proposed for solving the paradox.
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| === Expected utility theory ===
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| The classical resolution of the paradox involved the explicit introduction of a [[Utility|utility function]], an [[expected utility hypothesis]], and the presumption of [[Marginal_utility#Diminishing_marginal_utility|diminishing marginal utility]] of money. | |
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| In Daniel Bernoulli's own words:
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| :The determination of the value of an item must not be based on the price, but rather on the utility it yields…. There is no doubt that a gain of one thousand [[ducat]]s is more significant to the pauper than to a rich man though both gain the same amount.
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| A common utility model, suggested by Bernoulli himself, is the [[logarithm|logarithmic function]] ''U''(''w'') = ln(''w'') (known as [http://www.econterms.com/glossary.cgi?query=log+utility “log utility”]). It is a function of the gambler’s total wealth ''w'', and the concept of diminishing marginal utility of money is built into it. The expected utility hypothesis posits that a utility function exists whose expected net change is a good criterion for real people's behavior. For each possible event, the change in utility ln(''wealth after the event'') - ln(''wealth before the event'') will be weighted by the probability of that event occurring. Let ''c'' be the cost charged to enter the game. The expected utility of the lottery now converges to a finite value:
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| :<math>E(U)=\sum_{k=1}^\infty\frac{(\ln(w+2^{k-1}-c) - \ln(w))}{2^k} < \infty \,.</math>
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| This formula gives an implicit relationship between the gambler's wealth and how much he should be willing to pay to play (specifically, any ''c'' that gives a positive expected utility). For example, with log utility a millionaire should be willing to pay up to $10.94, a person with $1000 should pay up to $5.94, a person with $2 should pay up to $2, and a person with $0.60 should borrow $0.87 and pay up to $1.47.
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| Before Daniel Bernoulli published, in 1728, another Swiss mathematician, [[Gabriel Cramer]], had already found parts of this idea (also motivated by the St. Petersburg Paradox) in stating that
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| :the mathematicians estimate money in proportion to its quantity, and men of good sense in proportion to the usage that they may make of it.
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| He demonstrated in a letter to Nicolas Bernoulli [http://www.cs.xu.edu/math/Sources/Montmort/stpetersburg.pdf#search=%22Nicolas%20Bernoulli%22] that a square root function describing the diminishing marginal benefit of gains can resolve the problem. However, unlike Daniel Bernoulli, he did not consider the total wealth of a person, but only the gain by the lottery.
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| This solution by Cramer and Bernoulli, however, is not completely satisfying, since the lottery can easily be changed in a way such that the paradox reappears. To this aim, we just need to change the game so that it gives the (even larger) payoff <math>e^{2^k}</math>. Again, the game should be worth an infinite amount. More generally, one can find a lottery that allows for a variant of the St. Petersburg paradox for every unbounded utility function, as was first pointed out by Menger {{harv|Menger|1934}}.
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| Recently, expected utility theory has been extended to arrive at more [[Behavioral finance|behavioral decision models]]. In some of these new theories, as in [[cumulative prospect theory]], the St. Petersburg paradox again appears in certain cases, even when the utility function is concave, but not if it is bounded {{harv|Rieger|Wang|2006}}.
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| === Probability weighting ===
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| Nicolas Bernoulli himself proposed an alternative idea for solving the paradox. He conjectured that people will neglect unlikely events {{harv|de Montmort|1713}}. Since in the St. Petersburg lottery only unlikely events yield the high prizes that lead to an infinite expected value, this could resolve the paradox. The idea of probability weighting resurfaced much later in the work on [[prospect theory]] by [[Daniel Kahneman]] and [[Amos Tversky]]. However, their experiments indicated that, very much to the contrary, people tend to overweight small probability events. Therefore the proposed solution by Nicolas Bernoulli is nowadays not considered to be satisfactory.{{whom?|date=June 2013}}
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| [[Cumulative prospect theory]] is one popular generalization of [[expected utility theory]] that can predict many behavioral regularities {{harv|Tversky|Kahneman|1992}}. However, the overweighting of small probabilities introduced in cumulative prospect theory may restore the St. Petersburg paradox. Cumulative prospect theory avoids the St. Petersburg paradox only when the power coefficient of [[utility]] function is lower than the power coefficient of probability weighting function {{harv|Blavatskyy|2005}}. Intuitively, utility function must not simply be concave, but it must be concave relative to probability weighting function to avoid the St. Petersburg paradox.
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| === Rejection of mathematical expectation === | |
| Various authors, including [[Jean le Rond d'Alembert]] and [[John Maynard Keynes]], have rejected maximization of expectation (even of utility) as a proper rule of conduct.<!-- d'Alembert, Jean le Rond; Opuscules mathématiques (1768), vol iv,
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| p 284-5. --><!-- Keynes, John Maynard; A Treatise on Probability (1921), Pt IV Ch XXVI §9. --> Keynes, in particular, insisted that the ''relative risk'' of an alternative could be sufficiently high to reject it even were its expectation enormous.
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| === Finite St. Petersburg lotteries ===
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| The classical St. Petersburg lottery assumes that the casino has infinite resources. This assumption is unrealistic, particularly in connection with the paradox, which involves the reactions of ordinary people to the lottery. Of course, the resources of an actual casino (or any other potential backer of the lottery) are finite. More importantly, the expected value of the lottery only grows logarithmically with the resources of the casino. As a result, the expected value of the lottery, even when played against a casino with the largest resources realistically conceivable, is quite modest. If the total resources (or total maximum jackpot) of the casino are ''W'' dollars, then ''L'' = 1 + floor(log<sub>2</sub>(''W'')) is the maximum number of times the casino can play before it no longer covers the next bet. The expected value ''E'' of the lottery then becomes:
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| ::<math>\begin{align}
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| E &= \sum_{k=0}^\infty \frac{1}{2^{k+1}}\cdot \min(2^k, W) \\
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| &= \sum_{k=0}^{L-1} \frac{1}{2^{k+1}}\cdot 2^k ~+~ \sum_{k=L}^\infty \frac{1}{2^{k+1}}\cdot W \\
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| &= \frac{L}{2} ~+~ \frac{W}{2^L}\,\,.
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| \end{align}</math>
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| The following table shows the expected value ''E'' of the game with various potential bankers and their bankroll ''W'' (with the assumption that if you win more than the bankroll you will be paid what the bank has):
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| {|class="wikitable" align=center
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| | ''Banker'' || ''Bankroll'' || ''Expected value of lottery''
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| | Friendly game || $100 || $4.28
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| | Millionaire || $1,000,000 || $10.95
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| | Billionaire || $1,000,000,000 || $15.93
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| | [[Bill Gates]] (2008) || $67,000,000,000 || $21.77
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| | [[List of countries by GDP (nominal)|U.S. GDP]] (2007) || $13.8 trillion || $22.78
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| | [[List of countries by GDP (nominal)|World GDP]] (2007) || $54.3 trillion || $23.77
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| |-
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| | Googolaire || $10<sup>100</sup> || $166.50
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| |}
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| <small>Notes:
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| The estimated net worth of Bill Gates is from [[Forbes]]. The GDP data are as estimated for 2007 by the [[International Monetary Fund]], where one trillion dollars equals $10<sup>12</sup> (one million times one million dollars). A “googolaire” is a hypothetical person worth a [[googol]] dollars ($10<sup>100</sup>).</small>
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| A rational person might not find the lottery worth even the modest amounts in the above table, suggesting that the naive decision model of the expected return causes essentially the same problems as for the infinite lottery. Even so, the possible discrepancy between theory and reality is far less dramatic.
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| The assumption of infinite resources can produce other apparent paradoxes in economics. See [[martingale (roulette system)]] and [[gambler's ruin]].
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| == Recent discussions ==
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| Although this paradox is three centuries old, papers with new and fresh ideas on how to resolve it still pop up.
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| === Samuelson ===
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| Samuelson resolves the paradox by arguing that, even if an entity had infinite resources, the game would never be offered. If the lottery represents an infinite expected gain to the player, then it also represents an infinite expected loss to the host. No one could be observed paying to play the game because it would never be offered. As [[Paul Samuelson]] describes the argument:
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| :Paul will never be willing to give as much as Peter will demand for such a contract; and hence the indicated activity will take place at the equilibrium level of zero intensity. {{harv|Samuelson|1960}}
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| === Peters ===
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| Ole Peters thinks that the St. Petersburg paradox can be solved by using concepts and ideas from [[ergodic theory]] {{harv|Peters|2011a}}. In [[statistical mechanics]] it is a central problem to understand whether time averages resulting from a long observation of a single system are equivalent to expectation values. This is the case only for a very limited class of systems that are called "[[ergodic]]" there. For non-ergodic systems there is no general reason why expectation values should have any relevance.
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| Peters points out that computing the naive expected payout is mathematically equivalent to considering multiple outcomes of the same lottery in parallel universes. This is irrelevant to the individual considering whether to buy a ticket since he exists in only one universe and is unable to exchange resources with the others. It is therefore unclear why expected wealth should be a quantity whose maximization should lead to a sound decision theory. Indeed, the St. Petersburg paradox is only a paradox if one accepts the premise that rational actors seek to maximize their expected wealth. The classical resolution is to apply a utility function to the wealth, which reflects the notion that the "usefulness" of an amount of money depends on how much of it one already has, and then to maximise the expectation of this. The choice of utility function is often framed in terms of the individual's risk preferences and may vary between individuals: it therefore provides a somewhat arbitrary framework for the treatment of the problem.
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| An alternative premise, which is less arbitrary and makes fewer assumptions, is that the performance ''over time'' of an investment better characterises an investor's prospects and, therefore, better informs his investment decision. In this case, the passage of time is incorporated by identifying as the quantity of interest the average ''rate'' of exponential growth of the player's wealth in a single round of the lottery,
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| :<math>\bar{g}(w,c) = \sum_{k=1}^\infty p_k \ln \left(\frac{w-c+D_k}{w}\right)</math>
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| per round, where <math>D_k</math> is the <math>k</math>th (positive finite) payout and <math>p_k</math> is the (non-zero) probability of receiving it. In the standard St. Petersburg lottery, <math>D_k=2^{k-1}</math> and <math>p_k=2^{-k}</math>.
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| Although this is an expectation value of a growth rate, and may therefore be thought of in one sense as an average over parallel universes, it is in fact equivalent to the time average growth rate that would be obtained if repeated lotteries were played over time {{harv|Peters|2011a}}. While <math>\bar{g}</math> is identical to the rate of change of the expected logarithmic utility, it has been obtained without making any assumptions about the player's risk preferences or behaviour, other than that he is interested in the rate of growth of his wealth.
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| Under this paradigm, an individual with wealth <math>w</math> should buy a ticket at a price <math>c</math> provided
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| :<math>\bar{g}(w,c)>0.</math> | |
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| This strategy counsels against paying any amount of money for a ticket that admits the possibility of bankruptcy, i.e.
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| :<math>w-c+D_k = 0,</math> | |
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| for any <math>k</math>, since this generates a negatively divergent logarithm in the sum for <math>\bar{g}</math> which can be shown to dominate all other terms in the sum and guarantee that <math>\bar{g}<0</math>. If we assume the smallest payout is <math>D_1</math>, then the individual will always be advised to decline the ticket at any price greater than
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| :<math>c_\mathrm{max} = w+D_1,</math>
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| ''regardless'' of the payout structure of the lottery. The ticket price for which the expected growth rate falls to zero will be less than <math>c_\mathrm{max}</math> but may be greater than <math>w</math>, indicating that borrowing money to purchase a ticket for more than one's wealth can be a sound decision. This would be the case, for example, where the smallest payout exceeds the player's current wealth, as it does in Menger's game.
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| It should also be noted in the above treatment that, contrary to Menger's analysis, no higher-paying lottery can generate a paradox which the time resolution - or, equivalently, Bernoulli's or Laplace's logarithmic resolutions - fail to resolve, since there is ''always'' a price at which the lottery should not be entered, even though for especially favourable lotteries this may be greater than one's worth.
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| == Further discussions ==
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| The St. Petersburg paradox and the theory of marginal utility have been highly disputed in the past. For a discussion from the point of view of a philosopher, see {{harv|Martin|2004}}.
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| == See also ==
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| *[[Ellsberg paradox]]
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| *[[Exponential growth]]
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| *[[Gambler's ruin]]
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| *[[Kelly criterion]]
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| *[[Martingale (betting system)]]
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| *[[Two envelopes problem]]
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| *[[Zeno's paradoxes]]
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| == References and notes ==
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| ;Citations
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| {{reflist}}
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| ;Works cited
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| * {{cite journal
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| | last = Arrow
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| | first = Kenneth J.
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| | authorlink = Kenneth Arrow
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| |date=February 1974
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| | title = The use of unbounded utility functions in expected-utility maximization: Response
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| | journal=[[Quarterly Journal of Economics]]
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| | volume = 88
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| | issue = 1
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| | pages = 136–138
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| | id = Handle: RePEc:tpr:qjecon:v:88:y:1974:i:1:p:136-38
| |
| | url = http://ideas.repec.org/a/tpr/qjecon/v88y1974i1p136-38.html
| |
| | format = PDF
| |
| | doi = 10.2307/1881800
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| | ref = harv
| |
| | jstor = 1881800
| |
| | publisher=The MIT Press
| |
| }}
| |
| | |
| * {{cite journal
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| | last = Bernoulli
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| | first = Daniel
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| | authorlink = Daniel Bernoulli
| |
| | coauthors = Originally published in 1738; translated by Dr. Louise Sommer.
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| |date=January 1954
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| | title = Exposition of a New Theory on the Measurement of Risk
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| | journal=[[Econometrica]]
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| | volume = 22
| |
| | issue = 1
| |
| | pages = 22–36
| |
| | url = http://www.math.fau.edu/richman/Ideas/daniel.htm
| |
| | accessdate = 2006-05-30
| |
| | doi = 10.2307/1909829
| |
| | ref = CITEREFBernoulli1738
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| | jstor = 1909829
| |
| | publisher=The Econometric Society
| |
| }}
| |
| * {{cite journal
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| |last=Blavatskyy
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| |first=Pavlo
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| |title=Back to the St. Petersburg Paradox?
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| |journal=[[Management Science (journal)|Management Science]]
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| |date=April 2005
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| |volume=51
| |
| |issue=4
| |
| |pages=677–678
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| | ref = harv
| |
| }}
| |
| | |
| * {{cite book
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| |last= de Montmort
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| |first= Pierre Remond
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| |authorlink= Pierre Raymond de Montmort
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| |title= {{lang|fr|Essay d'analyse sur les jeux de hazard}}
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| |trans_title= Essays on the analysis of games of chance
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| |edition= Second
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| |year= 1713
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| |publisher=[[American Mathematical Society]]
| |
| |type = Reprinted in 2006
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| |location= Providence, Rhode Island
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| |language= {{Fr}}
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| |isbn= 978-0-8218-3781-8
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| | ref = harv
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| }} as translated and posted at {{cite web
| |
| | url = http://www.cs.xu.edu/math/Sources/Montmort/stpetersburg.pdf
| |
| | format = {{PDFlink|​|88 KB}}
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| | title = Correspondence of Nicolas Bernoulli concerning the St. Petersburg Game
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| | first = Richard J
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| | last = Pulskamp
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| | accessdate = July 22, 2010
| |
| }}
| |
| | |
| * {{cite book
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| |last= Laplace
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| |first= Pierre Simon
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| |authorlink= Pierre Simon de Laplace
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| |title= {{lang|fr|Théorie analytique des probabilités}}
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| |trans_title= Analytical theory of probabilities
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| |edition= Second
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| |year= 1814
| |
| |publisher=[[Ve. Courcier]]
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| |location= Paris
| |
| |language= {{Fr}}
| |
| | ref = harv
| |
| }}
| |
| | |
| * {{cite encyclopedia
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| | last = Martin
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| | first = Robert
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| | editor = Edward N. Zalta
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| | encyclopedia = The Stanford Encyclopedia of Philosophy
| |
| | title = The St. Petersburg Paradox
| |
| | url = http://plato.stanford.edu/archives/fall2004/entries/paradox-stpetersburg/
| |
| | accessdate = 2006-05-30
| |
| | edition = Fall 2004
| |
| | year = 2004
| |
| | publisher=Stanford University
| |
| | location = [[Stanford, California]]
| |
| | issn = 1095-5054
| |
| | ref = harv
| |
| }}
| |
| | |
| * {{cite journal
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| | last = Menger
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| | first = Karl
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| | authorlink = Karl Menger
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| |date=August 1934
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| | title = Das Unsicherheitsmoment in der Wertlehre Betrachtungen im Anschluß an das sogenannte Petersburger Spiel
| |
| | journal=[[Zeitschrift für Nationalökonomie]]
| |
| | issn = 0931-8658
| |
| | volume = 5
| |
| | issue = 4
| |
| | pages = 459–485
| |
| | doi = 10.1007/BF01311578
| |
| | id = (Paper) (Online)
| |
| | ref = harv
| |
| }}
| |
| | |
| *{{cite web
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| | url = http://arxiv.org/pdf/1110.1578v1.pdf
| |
| | last = Peters
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| | first = Ole
| |
| |date=October 2011b
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| | title = Menger 1934 revisited
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| | journal=Journal of Economic Literature
| |
| | ref = harv
| |
| }}
| |
| | |
| *{{cite journal
| |
| | last = Peters
| |
| | first = Ole
| |
| | year = 2011a
| |
| | title = The time resolution of the St Petersburg paradox
| |
| | url = http://rsta.royalsocietypublishing.org/content/369/1956/4913.full.pdf
| |
| | journal = [[Philosophical Transactions of the Royal Society]]
| |
| | volume = 369
| |
| | pages = 4913–4931
| |
| | doi = 10.1098/rsta.2011.0065
| |
| | ref = harv
| |
| }}
| |
| | |
| * {{cite journal
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| | last=Pianca
| |
| | first=Paolo
| |
| | title=The St. Petersburg Paradox: Historical Exposition, an Application to Growth Stocks and Some Simulation Approaches
| |
| | journal=Quaderni Di Didattica, Department of Applied Mathematics, University of Venice
| |
| |date=September 2007
| |
| | volume=24
| |
| | pages=1–15
| |
| | url=http://www.dma.unive.it/quaderni/QD24-2007.pdf
| |
| | ref = harv
| |
| }}
| |
| | |
| * {{cite journal
| |
| | last1 = Rieger
| |
| | first1 = Marc Oliver
| |
| | last2 = Wang
| |
| | first2 = Mei
| |
| |date=August 2006
| |
| | title = Cumulative prospect theory and the St. Petersburg paradox
| |
| | journal=[[Economic Theory (journal)|Economic Theory]]
| |
| | issn = 0938-2259
| |
| | volume = 28
| |
| | issue = 3
| |
| | pages = 665–679
| |
| | doi = 10.1007/s00199-005-0641-6
| |
| | id = (Paper) (Online)
| |
| | ref = harv
| |
| }} ([http://www.sfb504.uni-mannheim.de/publications/dp04-28.pdf Publicly accessible, older version.])
| |
| | |
| * {{cite journal
| |
| | last = Samuelson
| |
| | first = Paul
| |
| |date=January 1960
| |
| | title = The St. Petersburg Paradox as a Divergent Double Limit
| |
| | journal=[[International Economic Review]]
| |
| | volume = 1
| |
| | issue = 1
| |
| | pages = 31–37
| |
| | doi = 10.2307/2525406
| |
| | ref = harv
| |
| | jstor = 2525406
| |
| | publisher=Blackwell Publishing
| |
| }}
| |
| | |
| * {{cite journal
| |
| | last = Samuelson
| |
| | first = Paul
| |
| | authorlink = Paul Samuelson
| |
| |date=March 1977
| |
| | title = St. Petersburg Paradoxes: Defanged, Dissected, and Historically Described
| |
| | journal= [[Journal of Economic Literature]]
| |
| | volume = 15
| |
| | issue = 1
| |
| | pages = 24–55
| |
| | ref = harv
| |
| | jstor = 2722712
| |
| | publisher= American Economic Association
| |
| }}
| |
| | |
| * {{cite book
| |
| |last= Todhunter
| |
| |first= Isaac
| |
| |authorlink= Isaac Todhunter
| |
| |title= A history of the mathematical theory of probabilities
| |
| |year= 1865
| |
| |publisher=[[Macmillan & Co]]
| |
| | ref = harv
| |
| }}
| |
| | |
| * {{cite journal
| |
| |last1=Tversky
| |
| |first1=Amos
| |
| |last2=Kahneman
| |
| |title=Advances in prospect theory: Cumulative representation of uncertainty
| |
| |journal=[[Journal of Risk and Uncertainty]]
| |
| |year=1992
| |
| |volume=5
| |
| |pages=297–323
| |
| | ref = harv
| |
| }}
| |
| | |
| ===Bibliography===
| |
| *{{cite journal
| |
| | last = Aumann
| |
| | first = Robert J.
| |
| | authorlink = Robert Aumann
| |
| |date=April 1977
| |
| | title = The St. Petersburg paradox: A discussion of some recent comments
| |
| | journal=[[Journal of Economic Theory]]
| |
| | volume = 14
| |
| | issue = 2
| |
| | pages = 443–445
| |
| | doi = 10.1016/0022-0531(77)90143-0
| |
| }}
| |
| *{{cite journal
| |
| | last = Durand
| |
| | first = David
| |
| |date=September 1957
| |
| | title = Growth Stocks and the Petersburg Paradox
| |
| | journal=[[The Journal of Finance]]
| |
| | volume = 12
| |
| | issue = 3
| |
| | pages = 348–363
| |
| | doi = 10.2307/2976852
| |
| | jstor = 2976852
| |
| | publisher=American Finance Association
| |
| }}
| |
| *{{cite web
| |
| | url = http://cepa.newschool.edu/het/essays/uncert/bernoulhyp.htm
| |
| | title = Bernoulli and the St. Petersburg Paradox
| |
| | work=The History of Economic Thought
| |
| | publisher=[[The New School for Social Research]], New York
| |
| | accessdate = 2006-05-30
| |
| }}
| |
| | |
| *{{cite book |title=Taking Chances |last=Haigh |first=John |year=1999 |publisher=Oxford University Press |location=Oxford,UK |isbn=0198526636 |pages=330 }}(Chapter 4)
| |
| | |
| ==External links==
| |
| * [http://www.mathematik.com/Petersburg/Petersburg.html Online simulation of the St. Petersburg lottery]
| |
| | |
| [[Category:Economics paradoxes]]
| |
| [[Category:Behavioral finance]]
| |
| [[Category:Mathematical economics]]
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| [[Category:Probability theory paradoxes]]
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| [[Category:Decision theory paradoxes]]
| |