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The '''St. Petersburg paradox''' or '''St. Petersburg lottery'''<ref>{{cite book|title=Conceptual foundations of risk theory|author-link=Michael D. Weiss|first=Michael D.|last=Weiss|publisher=U.S. Dept. of Agriculture, Economic Research Service|url=https://books.google.com/books?id=v33W8lKfOo0C&pg=PA36|page=36|year=1987}}</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.

The paradox takes its name from its resolution by [[Daniel Bernoulli]], one-time resident of the [[Saint Petersburg|eponymous Russian city]], who published his arguments 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]],<ref>{{cite book|last1=Plous|first1=Scott|title=The psychology of decision-making|publisher=McGraw-Hill Education|isbn=978-0070504776|chapter=Chapter 7|date=1993-01-01}}</ref> who first stated it in a letter to [[Pierre Raymond de Montmort]] on September 9, 1713 {{harv|de Montmort|1713}}.<ref>{{cite book|last=Eves|first=Howard|title=An Introduction To The History of Mathematics|edition=6th|publisher=Brooks/Cole – Thomson Learning|date=1990|page=427}}</ref>

== The paradox ==
A casino offers a [[game of chance]] for a single player in which [[Coin flipping|a fair coin is tossed]] at each stage. The initial stake begins at 2 dollars and is doubled every time heads appears. The first time tails appears, the game ends and the player wins whatever is in the pot. Thus the player wins 2 dollars if tails appears on the first toss, 4 dollars if heads appears on the first toss and tails on the second, 8 dollars if heads appears on the first two tosses and tails on the third, and so on. Mathematically, the player wins 2<sup>''k''</sup> dollars, where ''k'' equals number of tosses (k must be a whole number and greater than zero). What would be a fair price to pay the casino for entering the game?

To answer this, one needs to consider what would be the average payout: with probability {{sfrac|1|2}}, the player wins 2 dollars; with probability {{sfrac|1|4}} the player wins 4 dollars; with probability {{sfrac|1|8}} the player wins 8 dollars, and so on. The [[expected value]] is thus

:<math>\begin{align}
  E &= \frac{1}{2}\cdot 2+\frac{1}{4}\cdot 4 + \frac{1}{8}\cdot 8 + \frac{1}{16}\cdot 16 + \cdots \\
    &= 1 + 1 + 1 + 1 + \cdots \\
    &= \infty \,.
\end{align}</math>

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 expected 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 Robert 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.

== Solutions ==
Several approaches have been proposed for solving the paradox.

=== Expected utility theory ===
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.

In Daniel Bernoulli's own words:
<blockquote>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.</blockquote>

A common utility model, suggested by Bernoulli himself, is the [[logarithm|logarithmic function]] ''U''(''w'')&nbsp;=&nbsp;ln(''w'') (known as ''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 the sign of whose expected net change from accepting the gamble is a good criterion for real people's behavior. For each possible event, the change in utility {{nowrap|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 incremental utility of the lottery now converges to a finite value:
:<math>\Delta E(U) = \sum_{k=1}^\infty\frac{1}{2^k}\left[\ln\left(w + 2^k - c\right) - \ln(w)\right] < \infty \,.</math>

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 change in expected utility). For example, with natural log utility, a [[millionaire]] ($1,000,000) should be willing to pay up to $20.88, a person with $1,000 should pay up to $10.95, a person with $2 should borrow $1.35 and pay up to $3.35.

Before Daniel Bernoulli published, in 1728, a mathematician from [[Republic and Canton of Geneva#History|Geneva]], [[Gabriel Cramer]], had already found parts of this idea (also motivated by the St. Petersburg Paradox) in stating that
<blockquote>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.</blockquote>

He demonstrated in a letter to Nicolas Bernoulli<ref>Xavier University Computer Science. [http://cerebro.xu.edu/math/Sources/NBernoulli/correspondence_petersburg_game.pdf correspondence_petersburg_game.pdf – Nicolas Bernoulli]</ref> 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.

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 even more rapidly increasing payoffs. For any unbounded utility function, one can find a lottery that allows for a variant of the St. Petersburg paradox, as was first pointed out by Menger {{harv|Menger|1934}}.

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}}.

=== Probability weighting ===
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]].

[[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 probability events 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 the [[utility]] function is lower than the power coefficient of the probability weighting function {{harv|Blavatskyy|2005}}. Intuitively, the utility function must not simply be concave, but it must be concave relative to the probability weighting function to avoid the St. Petersburg paradox.
One can argue that the formulas for the prospect theory are obtained in the region of less than $400 {{harv|Tversky|Kahneman|1992}}. This is not applicable for infinitely increasing sums in the St. Petersburg paradox.

=== 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, p. 284-5. --><!-- Keynes, John Maynard; A Treatise on Probability (1921), Pt IV Ch XXVI §9. --> Keynes, in particular, insisted that the ''relative risk''{{clarify|date=September 2018}} of an alternative could be sufficiently high to reject it even if its expectation were enormous.{{Citation needed|date=July 2019}}

=== Finite St. Petersburg lotteries ===
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 [[Logarithmic growth|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'' = floor(log<sub>2</sub>(''W'')) is the maximum number of times the casino can play before it no longer fully covers the next bet. The expected value ''E'' of the lottery then becomes:
:<math>\begin{align}
  E &= \sum_{k=1}^{L} \frac{1}{2^k} \cdot 2^k + \sum_{k=L+1}^\infty \frac{1}{2^k} \cdot W \\
    &= L + \frac{W}{2^L}\,.
\end{align}</math>

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):

{|class="wikitable" style="text-align:right;"
! Banker !! Bankroll !! Expected value of lottery !! Consecutive flips to win max. !! Attempts for 50% chance to win max. !! Play time (1 game/minute)
|- 
|align=left| Friendly game || $100 || $7.56 || 6 || 44 || 44 minutes
|- 
|align=left| Millionaire || $1,000,000 || $20.91 || 19 || 363,408 || 252 days
|- 
|align=left| Billionaire || $1,000,000,000 || $30.86 || 29 || 372,130,559 || 708 years
|- 
|align=left| [[Bill Gates]] (2015) || $79,200,000,000<ref>The estimated net worth of Bill Gates is from [[Forbes]].</ref> || $37.15 || 36 || 47,632,711,549 || 90,625 years
|- 
|align=left| [[List of countries by GDP (nominal)|U.S. GDP]] (2007) || $13.8 [[Trillion (short scale)|trillion]]<ref name="imf">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).</ref> || $44.57 || 43 || 6,096,987,078,286 || 11,600,052 years
|- 
|align=left| [[List of countries by GDP (nominal)|World GDP]] (2007) || $54.3 trillion<ref name="imf"/> || $46.54 || 45 || 24,387,948,313,146 || 46,400,206 years
|- 
|align=left| [[Googol]]aire || $10<sup>100</sup> || $333.14 || 332 || 1.340E+191 || 8.48E+180 × life of universe
|}

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.

The premise of infinite resources produces a variety of paradoxes in economics. In the [[Martingale (betting system)|martingale betting system]], a gambler betting on a tossed coin doubles his bet after every loss, so that an eventual win would cover all losses; this system fails with any finite bankroll. The [[gambler's ruin]] concept shows a persistent gambler will go broke, even if the game provides a positive [[expected value]], and [[Impossibility of a gambling system|no betting system]] can avoid this inevitability.

== Recent discussions ==
Although this paradox is three centuries old, new arguments are still being introduced.

=== Feller ===
A mathematically correct solution involving sampling was offered by [[William Feller]].<ref name=":0">{{Cite book|title=An Introduction to Probability Theory and its Applications Volume I.|last=Feller|first=William|year=|isbn=|location=|pages=}}</ref> In order to understand Feller's answer correctly, sufficient knowledge about probability theory and statistics is necessary, but it can be understood intuitively "to perform this game with a large number of people and calculate the expected value from the sample extraction". In this method, when the games of infinite number of times are possible, the expected value will be infinity, and in the case of finite, the expected value will be a much smaller value.

=== Samuelson ===
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:
<blockquote>"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}}</blockquote>

== Further discussions ==
=== Marginal utility and philosophical view ===
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}}.

=== Heuristic parameters and risks ===
Recently some authors suggested using heuristic parameters <ref>{{Cite journal|last=|first=|date=2016|title=Decision making and Saint Petersburg Paradox: focusing on heuristic parameters, considering the non-ergodic context and the gambling risks|url=https://ideas.repec.org/a/ite/iteeco/160406.html|format=PDF|journal=Rivista Italiana di Economia Demografia e Statistica|volume=70|issue=4|pages=147–158|via=}}</ref>  (e.g. assessing the possible gains without neglecting the risks of the Saint Petersburg lottery) because of  the highly stochastic context of this game {{harv|Cappiello|2016}}. The expected output should therefore be assessed in the limited period where we can likely make our choices and, besides the non-ergodic features {{harv|Peters|2011a}}, considering some inappropriate consequences we could attribute to the expected value {{harv|Feller|1968}}.

== See also ==
{{div col}}
* [[Ellsberg paradox]]
* [[Exponential growth]]
* [[Gambler's ruin]]
* [[Kelly criterion]]
* [[Martingale (betting system)]]
* [[Pascal's mugging]]
* [[Two envelopes problem]]
* [[Zeno's paradoxes]]
{{div col end}}

== Notes and references ==
;Citations
{{reflist|30em}}
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*{{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
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*{{cite book |title=Taking Chances |url=https://archive.org/details/takingchanceswin0000haig |url-access=registration |last=Haigh |first=John |year=1999 |publisher=Oxford University Press |location=Oxford, UK |isbn=978-0198526636 |pages=[https://archive.org/details/takingchanceswin0000haig/page/330 330] }}(Chapter 4)
*{{cite book |title=Large Sample Methods in Statistics. An Introduction with Applications |last=Sen |first=P.K. |year=1993 |publisher=Springer |location=New York |isbn=978-0412042218 |pages= |last2=Singer|first2=J.M.}}

==External links==
* [http://www.mathematik.com/Petersburg/Petersburg.html Online simulation of the St. Petersburg lottery]

{{Economic paradoxes}}

[[Category:Economics paradoxes]]
[[Category:Behavioral finance]]
[[Category:Mathematical economics]]
[[Category:Probability theory paradoxes]]
[[Category:Decision-making paradoxes]]
[[Category:Coin flipping]]