1 Introduction
1.1 Motivation
The primary goal of this paper is to extend three wellknown theories of decisionmaking to allow for nonArchimedean (unbounded and/or discontinuous) preferences as defined in Definition 1.1 below. The theories that we extend are (i) coherent previsions of [Reference de Finetti11], (ii) lotteries and horse lotteries of [Reference Anscombe and Aumann1, Reference Von Neumann and Morgenstern41], and (iii) general acts of [Reference Savage35]. The objects that an agent compares differ amongst the three theories. In Section 3 below we show how to interpret each of the theories as a special case of the framework that we develop in this paper.
Definition 1.1. Let ${\mathcal {X}}$ be a set.

1. A binary relation $\precsim $ on ${\mathcal {X}}$ is a preorder if it is both reflexive and transitive. A preorder $\precsim $ is total if, for all $X,Y\in {\mathcal {X}}$ , $(X\precsim Y)\vee (Y\precsim X)$ .

2. A binary relation $\ll $ on ${\mathcal {X}}$ is a strict partial order if it is transitive and asymmetric ( $X\ll Y$ implies $\neg [Y\ll X]$ ).

3. If $\ll $ is a strict partial order on ${\mathcal {X}}$ we say that $\ll $ is Archimedean Footnote ^{1} if, for all $X,Y,Z\in {\mathcal {X}}$ ,
(1) $$ \begin{align} \left(\alpha X + [1\alpha]Y\ll Z\text{\ for all real}\ 0<\alpha\leq1\right)\text{\ implies\ }\neg(Z\ll Y). \end{align} $$ 
4. Let $\precsim $ be a preorder on ${\mathcal {X}}$ that expresses an agent’s preferences. Let $\ll $ be a strict partial order on $\mathcal {X}$ such that $X\ll Y$ implies $X\precsim Y$ . If $\ll $ is not Archimedean, we say that the agent’s preferences are nonArchimedean.
Archimedean preferences are continuous at $\alpha =0$ for mixtures of the form in the first clause of (1). Also, if X is worth infinitely less than Z which in turn is just a little bit less valuable than Y, then (1) can fail.
Example 1. Let $\Omega $ be an infinite set with a $\sigma $ field $\Sigma $ of measurable sets and a countably additive probability defined on it. Let $X_0$ be an unbounded realvalued function with infinite expected value, and let $\mathcal {X}$ be the linear span of $\{X_0\}$ and the set of bounded realvalued measurable functions defined on $\Omega $ . Each element of $\mathcal {X}$ has a unique representation as $X=aX_0+Y$ where a is a real number and Y is bounded. The expected value of each such X is $E(Y)$ if $a=0$ and $\mathrm { sign}(a)\infty $ if $a\ne 0$ . Define $X\ll Z$ to mean $E(X)<E(Z)$ . To see that $\ll $ is not Archimedean, let $X=X_0$ , $Y=2$ , and $Z=1$ in (1).
The need for nonArchimedean preferences arises in several ways. One way is when certain needs must be satisfied before others can be addressed as described by Rekola [Reference Rekola32]. Another is when some options are deemed infinitely more valuable than others. While modelling ecological preferences, Gelso and Peterson [Reference Gelso and Peterson17] say (p. 36) “someone who regards biodiversity protection as a moral duty cannot be compensated for the extinction of a species.” For preferences between random variables, larger is often preferred to smaller. It is common to express such preferences through expected utility maximization. When some random variables are unbounded (see Example 1 above) or when the domain space is uncountable (see Examples 4 and 5 below), certain “larger is better” preferences are inherently nonArchimedean.
All three Archimedean theories that we extend also assume that preferences are stateindependent, are expressed via total preorders, and satisfy a linearity assumption. We relax the stateindependence and totalpreorder assumptions and drop altogether the assumption that preferences are Archimedean. Allowing utility to be statedependent is particularly important in financial applications where different states of the world can entail different exchange rates between currencies as in [Reference Schervish, Seidenfeld and Kadane36] and/or different relative prices for commodities. We maintain a linearity assumption in order to achieve an expectedutility representation.
A popular way to model nonArchimedean preference is through a lexicography of Archimedean preferences. Let $A=\{\precsim _\alpha \}_{\alpha \in \aleph }$ be a wellordered set of total preorders that represent Archimedean preferences on a set $\mathcal {X}$ . The resulting lexicographic preference $\precsim _A$ is defined by (i) $X\sim _AY$ if $X\sim _\alpha Y$ for all $\alpha $ , and (ii) $X\prec _AY$ if $X\prec _\alpha Y$ for the first $\alpha $ such that $\neg (X\sim _\alpha Y)$ . A common example is to let each $\precsim _\alpha $ be a ranking by expected utility values $P_\alpha (U_\alpha (X))$ . Previously mentioned authors [Reference Gelso and Peterson17, Reference Rekola32] use lexicographies to model their nonArchimedean preferences. Also, Blume, Brandenburger, and Dekel [Reference Blume, Brandenburger and Dekel7] use lexicographies in game theory to allow conditioning on events that would otherwise have zero probability and Miranda and Van Camp [Reference Miranda, Van Camp, Augustin, Cozman and Wheeler25] use lexicographies to model sets of acceptable choices in a nonArchimedean setting. See also [Reference Blume, Brandenburger and Dekel6, Reference Hausner, Thrall, Coombs and Davis21, Reference Petri and Voorneveld31] for some theoretical considerations. Halpern [Reference Halpern20] contains an extensive comparison of the uses of lexicographic preferences and nonstandard numbers for representing preferences. In particular, Examples 3.3 and 4.8 of that paper show that there are cases of nonArchimedean preferences that cannot be modeled via lexicographies of standard expected utilities while showing that all lexicographic preferences can be represented by a nonstandard utility. See also [Reference Rizza33]. In this way, a nonstandard representation is a strict generalization of lexicographic preferences. In this paper we use nonstandardvalued functions to represent nonArchimedean preferences.
1.2 Standard versus nonstandard numbers
For the remainder of the paper, we refer to the familiar real numbers in the set ${\mathbb {R}}$ as standard numbers to distinguish them from the nonstandard numbers that we describe in Appendix A.1 and use liberally throughout the paper. We call a function numerical if it takes either standard or nonstandard values. In all cases, the calculations that are part of an agent’s expressions of preference involve only standard numbers. We use nonstandard numbers to represent an agent’s preferences after preferences are expressed and to infer a probability and utility to express that representation. Since we use multiple number systems, we need to be careful about what we mean by “linear” in various settings.
Definition 1.2. A space $\mathcal {W}$ of functions is a standardlinear space if $\alpha Y+\beta Z\in \mathcal {W}$ for all standard $\alpha ,\beta $ and all $Y,Z\in \mathcal {W}$ . A nonstandardvalued function U on a standardlinear space $\mathcal {W}$ is called a standardlinear function if $U(\alpha Y+\beta Z)=\alpha U(Y)+\beta U(Z)$ , for all $Y,Z\in \mathcal {W}$ and all standard $\alpha ,\beta $ . The standardlinear span of a set is the smallest standardlinear space containing the set.
Notice that $U(0)=0$ for every standardlinear function U. Definition 1.2 restricts the coefficients in linear combinations to be standard even though the values of U might be nonstandard. Readers desiring a more thorough understanding of nonstandards than we present in Appendix A could read one of the many treatments such as [Reference Nelson27, Reference Robinson34].
Other treatments of probability and/or decision theory that make use of nonstandard numbers include [Reference Benci, Horsten and Wenmackers4, Reference Duanmu and Roy13, Reference Pedersen29, Reference Wenmackers, Pettigrew and Weisberg42]. Section 3.2 of [Reference Pedersen29] has extensive references along with some details of some of the attempts to make use of nonstandardvalued probabilities. The same author, in [Reference Pedersen30], investigates representations of nonArchimedean coherent preference over unconditional realvalued gambles. Our representation incorporates coherent conditional preferences in Section 4. The approach of [Reference Benci, Horsten and Wenmackers4, Reference Benci, Horsten and Wenmackers5] is primarily to define probabilities that take infinitesimal values. For a probability P on a set $\Omega $ to be a “nonArchimedean probability,” in their terminology, they impose a condition that requires all singletons $\{\omega \}\in \Omega $ to have probabilities that are standard multiples of a common infinitesimal $\epsilon $ . That is, there is an infinitesimal $\epsilon $ such that for every $\omega \in \Omega $ , there is a standard $a_\omega>0$ such that $P(\{\omega \})=a_\omega \epsilon $ . This assumption places restrictions on the forms of nonArchimedean preferences that can be expressed. For example, one cannot have a probability on the integers in which every even integer has the same positive infinitesimal probability $\epsilon $ and every odd integer has the same positive infinitesimal probability $\delta $ , but $\delta /\epsilon $ is itself infinitesimal.
For those familiar with nonstandard models of the reals, all of our analysis is external rather than internal.Footnote ^{2} The main reason for an external analysis is that the nonstandards are nonArchimedean from an external perspective, but are Archimedean from an internal perspective. Furthermore, we want to insure that those aspects of the decision problem to which the agent must attend are all of a familiar nature, such as the concepts of “finite,” “countable,” “lottery,” “set,” “sum,” and “linear.” We use nonstandards solely to represent an agent’s preferences when those preferences satisfy the assumptions we state in Section 1.4. None of those assumptions requires understanding of nonstandard concepts.Footnote ^{3}
Narens [Reference Narens26] develops a nonArchimedean theory of measurement. The theory leads to measurements whose values lie in nonstandard models of the reals. Narens’ measurement systems have a number of features in common with probability and preference, so it is not surprising that nonstandard numbers are useful for representing nonArchimedean preference structures.
1.3 Some notation
Throughout this paper, $\Omega $ denotes a state space, $\mathcal {X}$ denotes a set of random quantities, which are functions from $\Omega $ to a set $\mathcal {O}$ of outcomes. Subsets of $\Omega $ are called events. When $\mathcal {X}$ is a set of random variables, the set $\mathcal {O}$ will be the standard numbers ${\mathbb {R}}$ . For other cases, both $\mathcal {X}$ and $\mathcal {O}$ will be more complicated sets that are constructed later. We will make much use of the following concepts:
Definition 1.3. Let $\precsim $ be a preorder and let $\ll $ be a strict partial order on the same set $\mathcal {X}$ , and let U be a numerical function defined on $\mathcal {X}$ .

1. We say that U represents $\precsim $ if, for all $X,Y\in \mathcal {X}$ ,
(2) $$ \begin{align} X\precsim Y\text{\ if and only if\ } U(X)\leq U(Y). \end{align} $$ 
2. We say that U agrees with $\precsim $ if, for all $X,Y\in \mathcal {X}$ ,
(3) $$ \begin{align} X\precsim Y\text{\ implies\ } U(X)\leq U(Y). \end{align} $$ 
3. We say that U agrees with $\ll $ if, for all $X,Y\in \mathcal {X}$ ,
(4) $$ \begin{align} X\ll Y\text{\ implies\ } U(X)< U(Y). \end{align} $$
The following results follow easily from Definition 1.3.
Proposition 1.4. Let U be a numerical function defined on a set $\mathcal {X}$ .

• U represents a unique preorder $\precsim $ on $\mathcal {X}$ , defined via (2) and $\precsim $ is total.

• U represents a preorder $\precsim $ if and only if $aU+b$ represents $\precsim $ for all positive a and all b.
1.4 Expressed preference
In our approach, preference amongst random quantities is expressed by willingness to trade.
Definition 1.5. Let X and Y be elements of a standardlinear space $\mathcal {X}$ . If an agent is willing to trade X to receive Y, we write $X\precsim Y$ . If both $X\precsim Y$ and $Y\precsim X$ , we say that the agent is indifferent between X and Y, which we express by $X\sim Y$ . If $(X\precsim Y)\wedge [\neg (Y\precsim X)]$ we write $X\prec Y$ .
We deliberately give no name to the relation $\prec $ for reasons that will become apparent in Example 2 below. The first assumption that we make merely avoids the two extremes in which the agent either is willing to make no trades or is willing to make all trades.
Assumption 1. For all $X\in \mathcal {X}$ , $X\precsim X$ , and there exist $X,Y\in \mathcal {X}$ such that $X\prec Y$ .
Our next assumption expresses the idea that willingness to trade depends only on the agent’s net change in fortune, which we state formally as follows.
Assumption 2. Suppose that $X,X',Y,Y'\in \mathcal {X}$ and $YX=Y'X'$ . The agent is willing to give X to get Y if and only if the agent is willing to give $X'$ to get $Y'$ .
Our next assumption is the trading analog to de Finetti’s assumption that an agent is willing to accept all finite sums of fair gambles.
Assumption 3. Suppose that $X_j\precsim Y_j$ for $j=1,2$ and $\alpha _1,\alpha _2$ are positive standard numbers. Then
Proposition 1.6 states some straightforward properties of the first three assumptions.
Proposition 1.6. Suppose that $\precsim $ satisfies Assumptions 1–3. Then $\precsim $ is a preorder, $\prec $ is a strict partial order, and $\sim $ is an equivalence relation.
A general preorder might not be total, and hence may leave some elements of $\mathcal {X}$ uncompared, i.e., neither $X\precsim Y$ nor $Y\precsim X$ .
Example 2 (Consensus).
Let $\aleph $ be a set, and let $\{\precsim _\alpha \}_{\alpha \in \aleph }$ be a collection, indexed by $\aleph $ , of total preorders on a standardlinear space $\mathcal {X}$ . Our agent might think of $\aleph $ as indexing a set of experts whose opinions the agent wants to adopt to the extent that they agree. Define the binary relation $\precsim $ on $\mathcal {X}$ by $X\precsim Y$ if, for all $\alpha \in \aleph $ , $X\precsim _\alpha Y$ . If each $\precsim _\alpha $ satisfies Assumptions 1–3, then so does $\precsim $ , which will also be a preorder, but not necessarily total. In general, for each $X,Y\in \mathcal {X}$ , $\aleph $ can be written as the union of three disjoint subsets:
If $\aleph _{Y\prec X}=\emptyset $ , then $X\precsim Y$ . In that case, if either of the other two sets is empty, there is unanimity about how the experts would trade X and Y. For example, if $\aleph _{X\sim Y}=\emptyset $ , the agent is willing to trade X to get Y and will refuse to trade Y to get X. If both are nonempty, the agent is willing to trade X to get Y but has expressed neither willingness nor refusal to trade Y to get X. For example the agent might want to look more closely at which experts lie in each of the sets $\aleph _{X\sim Y}$ and $\aleph _{X\prec Y}$ before deciding whether to trade Y to get X. If both $\aleph _{X\prec Y}$ and $\aleph _{Y\prec X}$ are nonempty, then X and Y are not compared by $\precsim $ .
As other authors have done, e.g., [Reference Giarlotta, Doumpos, Figueira, Greco and Zopounidis18, Reference Giarlotta and Greco19, Reference Nishimura and Ok28], we find it useful to allow an agent to distinguish preferences like the two cases in which $\aleph _{Y\prec X}=\emptyset $ but $\aleph _{X\prec Y}\ne \emptyset $ that appear in Example 2.
Definition 1.7. Let $\precsim $ satisfy Assumptions 1–3. For each case of $X\prec Y$ , the agent can express whether this is an unambiguous oneway preference, which we denote $X\ll Y$ or an ambiguous oneway preference, which we denote $X\vartriangleleft Y$ .
In Example 2, unambiguous oneway preference $X\ll Y$ corresponds to both $\aleph _{Y\prec X}$ and $\aleph _{X\sim Y}$ being empty, while $X\vartriangleleft Y$ corresponds to both $\aleph _{X\sim Y}$ and $\aleph _{X\prec Y}$ being nonempty while $\aleph _{Y\prec X}$ is empty. In order for an “unambiguous” oneway preference to mean what it sounds like, we impose the following assumption.
Assumption 4. The relations $\ll $ and $\vartriangleleft $ satisfy the following:

• $X\prec Y$ if and only if $(X\ll Y)\vee (X\vartriangleleft Y)$ ,

• $(X\ll Y)\wedge (Y\precsim Z)$ implies $X\ll Z$ , and

• $(X\precsim Y)\wedge (Y\ll Z)$ implies $X\ll Z$ .
If the second bullet in Assumption 4 were violated, the agent would be willing to trade Y to get Z and would be willing to contemplate trading Z to get X, which would violate the understanding of $X\ll Y$ as unambiguous willingness to trade only one way. A similar violation arises if the third bullet is violated. The first claim in Proposition 1.8 is a direct consequence of Theorem 3.4 of [Reference Giarlotta and Greco19], and the second claim is straightforward.
Proposition 1.8. If $\precsim $ satisfies Assumptions 1–4, then $\precsim $ is a consensus as in Example 2. If $\precsim $ satisfies Assumptions 1–3 choosing $\ll $ to be $\prec $ satisfies Assumption 4, as does choosing $\ll $ to be empty.
We alert the reader that, although $X\vartriangleleft Y$ expresses a willingness to consider trading Y for X, nothing in general can be inferred jointly from two or more such relations, as the next example illustrates.
Example 3. Let $\Omega =\{0,1\}$ and let $\mathcal {X}$ be the set of all standardvalued functions defined on $\Omega $ . Define $X\precsim Y$ as $X(\omega )\leq Y(\omega )$ for $\omega =0,1$ , and define $X\ll Y$ as $X(\omega )<Y(\omega )$ for $\omega =0,1$ . It is straightforward that Assumptions 1–4 hold. Let $X=0$ , $Z=1$ , and $Y=I_{\{0\}}(\omega )$ . Then $X\vartriangleleft Y$ and $Y\vartriangleleft Z$ . The agent would be willing to contemplate trading Y to get X or trading Z to get Y. But both trades together cannot be contemplated because that would imply a willingness to contemplate trading Z to get X where $X\ll Z$ . These same comparisions also illustrate that $\vartriangleleft $ is not transitive, whereas $\ll $ and $\prec $ are transitive.
We are now ready to formalize our model for trading.
Definition 1.9. Let $\Omega $ be a set, and for each $\omega \in \Omega $ let $\mathcal {O}_\omega $ be a standardlinear space. Let $\mathcal {O}_\Omega =\prod _{\omega \in \Omega }\mathcal {O}_\omega $ and $\mathcal {O}=\bigcup _{\omega \in \Omega }\mathcal {O}_\omega $ . Let $\mathcal {X}\subseteq \mathcal {O}_\Omega $ be a standardlinear space of functions with domain $\Omega $ .Footnote ^{4} Let $\precsim $ and $\ll $ be binary relations on $\mathcal {X}$ . If $\precsim $ and $\ll $ satisfy Assumptions 1–4, we call $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ a trading system. If $\precsim $ is a total preorder and $\ll $ is $\prec $ , then $\mathcal {T}$ is a total trading system. The sum of finitely many terms of the form $\alpha (YX)$ , where $X\sim Y$ and $\alpha $ is standard is called a fair trade. The sum of finitely many terms of the form $\alpha (YX)$ , where $X\precsim Y$ and $\alpha>0$ is standard is called an acceptable trade. Denote the set of acceptable trades as $\mathcal {V}_{\mathcal {T}}$ .
Proposition 1.10 states some straightforward properties of trading systems.
Proposition 1.10. Suppose that $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ is a trading system. The set $\mathcal {V}_{\mathcal {T}}$ of all acceptable trades is a convex cone, and it is the set of all trades V such that $0\precsim V$ . The set of all fair trades is a standardlinear space, and it is the equivalence class (under $\sim $ ) that contains the trade 0. Finally, $V\in \mathcal {V}_{\mathcal {T}}$ if and only if for all $X\in \mathcal {X}$ , $X\precsim X+V$ .
1.5 Dominance and coherence (part one)
Suppose that a (possibly nonstandardvalued) function U on $\mathcal {X}$ represents a total trading system $(\mathcal {X},\precsim ,\prec )$ . There is a necessary condition for $U(X)$ to be expressed as the expected value of the utility of $X(\omega )$ with respect to a probability over $\Omega $ . Loosely speaking, the condition is the following:
Let $X,Y\in \mathcal {X}$ . If for all $\omega $ , $Y(\omega )$ is at least as valuable as $X(\omega )$ when state $\omega $ occurs, then $U(X)\leq U(Y)$ .
In the theory of [Reference de Finetti11], where $\mathcal {X}$ is a linear space of standardvalued random variables, we can be more precise about the above condition. For each standard number x and each $\omega \in \Omega $ and each random variable X such that $X(\omega )=x$ , x is assumed to be the utility value to the agent, when the state $\omega $ occurs, of receiving the random variable X. The condition then becomes “ $X(\omega )\leq Y(\omega )$ for all $\omega $ implies $U(X)\leq U(Y)$ .”
In more general theories, where each $X(\omega )$ may be some nonnumerical object $x\in \mathcal {O}$ (the codomain of X) and the utility of each object in $\mathcal {O}$ might vary with $\omega $ , the utility to the agent of receiving $X(\omega )=x$ could depend on both $\omega $ and x. Later (Definition 4.3 in Section 4.1) we define what we mean by $X(\omega )\leq Y(\omega )$ and $X(\omega )<Y(\omega )$ when $\mathcal {O}\ne {\mathbb {R}}$ . Regardless of what are the objects in $\mathcal {O}$ , there are several ways in which $X\leq Y$ but $X\ne Y$ .
Definition 1.11. Let $X,Y\in \mathcal {X}$ .

• We say that Y weakly dominates X or X is weakly dominated by Y if $X(\omega )\leq Y(\omega )$ for all $\omega \in \Omega $ and there is $\omega \in \Omega $ such that $X(\omega )<Y(\omega )$ .

• We say that Y strictly dominates X or X is strictly dominated by Y if $X(\omega )<Y(\omega )$ for all $\omega \in \Omega $ .

• We say that Y uniformly dominates X or X is uniformly dominated by Y if there exists a standard $\epsilon>0$ such that $X(\omega )\leq Y(\omega )\epsilon $ for all $\omega \in \Omega $ .
It is trivial to see that weak dominance is an extension of strict dominance which, in turn, is an extension of uniform dominance. Many of our results do not depend on which version of dominance an agent chooses. For those results that depend on the form of dominance (primarily in Section 4), we are explicit about which form is needed. We use $X\prec _{_{ {\scriptsize \text{Dom}}}} Y$ to denote “Y dominates X” in whichever sense the agent chooses. In [Reference de Finetti11], dominance means uniform dominance. Our next assumption formalizes the idea that more is better.
Assumption 5. The agent chooses one of the senses of dominance. Suppose that $X,Y\in \mathcal {X}$ . If $X\leq Y$ , then $X\precsim Y$ . If $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ , then $X\ll Y$ .
Definition 1.12. A trading system $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ is called coherent if it satisfies Assumption 5.
When $\mathcal {O}={\mathbb {R}}$ , note that dominance is defined on all of ${\mathbb {R}}^\Omega $ , while Assumption 5 pertains only to elements of $\mathcal {X}$ . Some of our results apply only to coherent trading systems, and these contain clauses such as “If $\mathcal {T}$ is coherent ….” Other results apply more generally, and do not contain such clauses.
Example 4. The smallest coherent trading system on a linear space $\mathcal {X}$ of standardvalued random variables must include all cases of dominance (whichever form we choose) amongst the elements of $\mathcal {X}$ . Let $\Omega $ be an arbitrary set, and let $\mathcal {X}$ be the linear span of all constants and all indicators of singletons. Let $\prec _{_{{\scriptsize \text{Dom}}}}$ stand for any of the three forms of dominance. Each element of $\mathcal {X}$ is constant except for at most finitely many points. Hence strict and uniform dominance are the same if $\Omega $ is infinite in cardinality. Let $X\precsim Y$ if and only if either $X=Y$ or $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ . It is straightforward that $\precsim $ is a preorder, but not total. Note that, for all $X,Y\in \mathcal {X}$ and all standard $\alpha>0$ , $0\precsim \alpha (YX)$ if and only if $X\precsim Y$ . If $X_j\prec _{_{{\scriptsize \text{Dom}}}} Y_j$ for $j=1,2$ , then $\alpha _1X_1+\alpha _2X_2\prec _{_{{\scriptsize \text{Dom}}}}\alpha _1Y_1+\alpha _2Y_2$ , so Assumptions 1–3 are satisfied. Define $\ll $ to be $\prec _{_{{\scriptsize \text{Dom}}}}$ so that Assumptions 4 and 5 are satisfied. Then $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ is a coherent trading system. We will return to this example later (Example 5) to prove that its preferences are nonArchimedean when $\Omega $ is uncountable and $\prec _{_{{\scriptsize \text{Dom}}}}$ means weak dominance.
2 Representing and extending a trading system
2.1 Representations of total trading systems
In this section, we show how to represent a total trading system by a (possibly nonstandardvalued) numerical function.
Definition 2.1. Let $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ be a trading system. A numerical function U on $\mathcal {X}$ agrees with $\mathcal {T}$ if U agrees with $\precsim $ and with $\ll $ . (Recall Definition 1.3.) If $\mathcal {T}$ is a total trading system and U represents $\precsim $ then we say that U represents $\mathcal {T}$ .
The following result follows easily from Definition 2.1.
Proposition 2.2. A numerical function U represents a total preorder $\precsim $ if and only if
Next, we introduce a class of numerical functions that represent total trading systems.
Definition 2.3. A standardlinear function U (recall Definition 1.2) is called monotone if $X\leq Y$ implies $U(X)\leq U(Y)$ . A monotone standardlinear function U is said to respect dominance if $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ implies $U(X)<U(Y)$ .
Lemma 2.4. Let U be a standardlinear function defined on a standardlinear space $\mathcal {X}$ of functions defined on a state space $\Omega $ . Then U represents a total trading system $\mathcal {T}=(\mathcal {X},\precsim ,\prec )$ . Also $\mathcal {T}$ is coherent if and only if U is monotone and respects dominance.
Proof. Assume that U is a standardlinear function on a standardlinear space $\mathcal {X}$ . Define the total preorder $\precsim $ on $\mathcal {X}$ by (2). For the first claim, we need to verify Assumptions 1–4. Assumption 1 follows because a preorder is reflexive. For Assumption 2, suppose that $YX=Y'X'$ . Since U is standardlinear,
For Assumption 3, note that U being standardlinear implies that
for all standard $\alpha _1,\alpha _2$ and $X_1,X_2\in \mathcal {X}$ . For Assumption 4, note that $\ll $ is $\prec $ .
For the second claim, we need to prove that Assumption 5 holds if and only if U is monotone and respects dominance. For the “if” direction, assume that U is monotone and respects dominance. Since U is monotone, $X\leq Y$ implies $U(X)\leq U(Y)$ and $X\precsim Y$ . Since U respects dominance, $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ implies $U(X)<U(Y)$ and $X\prec Y$ , so Assumption 5 holds. For the “only if” direction, assume that Assumption 5 holds. To see that U is monotone, assume that $X\leq Y$ . The first requirement of Assumption 5 is that $X\precsim Y$ , which implies that $U(X)\leq U(Y)$ , and U is monotone. To see that U respects dominance, assume that $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ . The second requirement of Assumption 5 is that $X\prec Y$ , which implies that $U(X)<U(Y)$ , and U respects dominance.
2.2 Agreement, representation and extension
If $\precsim $ is a not a total preorder, then there can be no numerical function U such that (2) holds. The problem is the “if” direction of (2) rather than the “only if” direction. In other words, representation as defined in Definition 1.3 is not achievable for preorders that are not total. On the other hand, agreement with a preorder and with a strict partial order are possible.
When it comes to extension of a trading system, there are two modes of extension that are important to our analysis. One mode corresponds to adding more comparisons (amongst elements of a single set $\mathcal {X}$ ) to the preorder, bringing it closer to being total. The other mode corresponds to expanding the domain of definition of the preorder (from one set $\mathcal {X}$ to a larger set $\mathcal {X}'$ ). Along with the second mode of extension comes a corresponding concept of restricting the domain of definition.
Definition 2.5. Let $\mathcal {X}$ and $\mathcal {X}'$ be standardlinear spaces with $\mathcal {X}\subseteq \mathcal {X}'$ . Let $\rho $ be a binary relation on $\mathcal {X}$ , and let $\rho '$ be a binary relation on $\mathcal {X}'$ .

• If $\mathcal {X}=\mathcal {X}'$ and $X\rho \ Y$ implies $X\rho ' Y$ , we say that $\rho '$ is an extension $_1$ of $\rho $ .

• If $(X,Y\in \mathcal {X})\wedge (X\rho \ Y)$ implies $X\rho '\ Y$ , we say that $\rho '$ is an extension $_2$ of $\rho $ .

• If $\rho '$ is an extension $_2$ of $\rho $ , we say that $\rho $ is the restriction of $\rho '$ to $\mathcal {X}$ .

• Suppose that $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ and $\mathcal {T}'=(\mathcal {X},\precsim ',\ll ')$ are trading systems. If $\precsim '$ and $\ll '$ are extensions $_1$ of $\precsim $ and $\ll $ respectively, we call $\mathcal {T}'$ an extension $_1$ of $\mathcal {T}$ .

• Let $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ and $\mathcal {T}'=(\mathcal {X}',\precsim ',\ll ')$ be trading systems. If $\mathcal {X}\subseteq \mathcal {X}'$ and if $\precsim '$ and $\ll '$ are extensions $_2$ of $\precsim $ and $\ll $ respectively, we call $\mathcal {T}'$ an extension $_2$ of $\mathcal {T}$ .
To be clear, each binary relation and each trading system is both an extension $_1$ and an extension $_2$ of itself. The following result about extension $_2$ is key in our theorems on representation. Its proof appears in Appendix C.1.
Lemma 2.6. Let $\mathcal {X}$ and $\mathcal {X}'$ be standardlinear spaces of functions with domain $\Omega $ and such that $\mathcal {X}\subseteq \mathcal {X}'$ . Let $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ be a trading system. There exists a trading system $\mathcal {T}'=(\mathcal {X}',\precsim ',\ll ')$ that is an extension $_2$ of $\mathcal {T}$ . If it is not required that $\mathcal {T}'$ be coherent, $\mathcal {T}'$ can be chosen such that $\mathcal {V}_{\mathcal {T}'}=\mathcal {V}_{\mathcal {T}}$ . If $\mathcal {T}$ is coherent and it is required that $\mathcal {T}'$ be coherent, assume that $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ are defined on $\mathcal {X}'$ and are extensions $_2$ of $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ on $\mathcal {X}$ . Then a coherent $\mathcal {T}'$ can be chosen so that for every $V'\in \mathcal {V}_{\mathcal {T}'}$ there is $V\in \mathcal {V}_{\mathcal {T}}$ such that $V\leq V'$ .
Note that Lemma 2.6 above (as well as Lemma 2.7 and Theorem 2.9 below) have language about $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ on a larger space being extensions $_2$ of $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ on a smaller space. When $\mathcal {O}={\mathbb {R}}$ , this condition is met trivially. The language is included to allow us to use these same results in other cases after Section 4.1 where $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ are defined in terms of each specific trading system.
2.3 Finding agreeing functions
Our main representation Theorem 2.8 states that a trading system $\mathcal {T}$ has a standardlinear function U that agrees with it and an extension $_1$ to a total trading system that is represented by U. Results from [Reference Giarlotta, Doumpos, Figueira, Greco and Zopounidis18, Reference Giarlotta and Greco19, Reference Nishimura and Ok28] give the extension $_1$ for a general preorder, but without the representing function and without attention to the properties of a trading system. The following result has both Theorems 2.8 and 2.9 as special cases, and its proof appears in Appendix C.3.
Lemma 2.7. Assume the following structure:

• $\mathcal {Y}$ and $\mathcal {W}$ are standardlinear spaces of functions defined on $\Omega $ with $\mathcal {Y}$ a proper subset of $\mathcal {W}$ .

• $\mathcal {T}_{\mathcal {Y}}=(\mathcal {Y},\precsim _{\mathcal {Y}},\prec _{\mathcal {Y}})$ is a total trading system that is represented by the standardlinear function $U:\mathcal {Y}\rightarrow^{\ast}\hspace{2.5pt}{\mathbb{R}}$ , where $^{\ast }{\mathbb {R}}$ is a nonstandard model of the reals.

• $\mathcal {T}_{\mathcal {W}}=(\mathcal {W},\precsim _{\mathcal {W}},\ll _{\mathcal {W}})$ is the extension $_2$ of $\mathcal {T}_{\mathcal {Y}}$ obtained from Lemma 2.6.
Then U can be extended to a standardlinear function $U':\mathcal {W}\rightarrow ^{\ast}\hspace{2.5pt}{\mathbb{R}}'$ , where $^{\ast }{\mathbb {R}}'$ contains $^{\ast }{\mathbb {R}}$ and such that $U'$ represents a total trading system $\mathcal {T}'=(\mathcal {W},\precsim ',\prec ')$ that is an extension $_2$ of $\mathcal {T}_{\mathcal {Y}}$ . Also, if $\mathcal {T}_{\mathcal {Y}}$ is coherent and $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ are defined on $\mathcal {W}$ so as to be extensions $_2$ of $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ on $\mathcal {Y}$ , then $\mathcal {T}'$ can be chosen to be coherent.
Theorem 2.8. Let $\mathcal {T}$ be a trading system. There exists a standardlinear function U that agrees with $\mathcal {T}$ and total trading system $\mathcal {T}'$ that is an extension $_1$ of $\kern1pt\mathcal {T}$ such that U represents $\mathcal {T}'$ . If $\mathcal {T}$ is coherent, $\mathcal {T}'$ can be chosen to be coherent.
Proof. Apply Lemma 2.7 with $\mathcal {Y}=\{0\}$ (the trivial standardlinear space containing only the additive identity in $\mathcal {X}$ ), $0\precsim _{\mathcal {Y}}0$ , $\mathcal {W}=\mathcal {X}$ , $\mathcal {T}_{\mathcal {W}}=\mathcal {T}$ , $U(0)=0$ , and $^{\ast }{\mathbb {R}}={\mathbb {R}}$ . Let $\mathcal {T}'$ be the $\mathcal {T}'$ that results from Lemma 2.7, and let U be the corresponding $U'$ . These satisfy the conclusion of Theorem 2.8.
Example 5 (Continuation of Example 4).
Recall the smallest coherent trading system $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ from Example 4. This time, assume that $\prec _{_{{\scriptsize \text{Dom}}}}$ means weak dominance and that $\Omega $ is uncountable. Then $X\prec Y$ and $X\ll Y$ both mean that Y weakly dominates X. Here we show that $\precsim $ is nonArchimedean. Theorem 2.8 says that $\mathcal {T}$ can be extended $_1$ to a coherent total trading system $\mathcal {T}'=(\mathcal {X},\precsim ',\prec ')$ with a representing function U that agrees with $\mathcal {T}$ . Without loss of generality, assume that $U(0)=0$ and $U(1)=1$ . So $X\prec Y$ (i.e., $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ ) implies $U(X)<U(Y)$ . For every nonempty finite subset $E=\{\omega _1,\dots ,\omega _n\}$ of $\Omega $ , dominance and standardlinearity imply that
For each $\omega \in \Omega $ either $U(I_{\{\omega \}})$ is infinitesimal or it is greater than $1/n$ for some standard integer n. There can be no more than $n1$ values of $U(I_{\{\omega \}})>1/n$ or (6) would be violated for a finite set E containing n such $\omega $ points. Hence, all but at most countably many $\omega $ have $U(I_{\{\omega \}})$ infinitesimal. Let $\omega _1,\omega _2\in \Omega $ be such that $U(I_{\{\omega _j\}})$ is infinitesimal for $j=1,2$ . Let $X=1$ , $Y=I_{\{\omega _1,\omega _2\}}$ , and $Z=I_{\{\omega _1\}}$ . Then, $Z\prec _{_{{\scriptsize \text{Dom}}}} Y$ , $U(Z)>0$ , and $U(\alpha X+[1\alpha ]Y)<0$ if $0<\alpha \leq 1$ . It follows that
but $Z\prec _{_{{\scriptsize \text{Dom}}}} Y$ , which violates (1). Hence the preference is nonArchimedean. It also follows that for each coherent extension $_1 \mathcal {T}'$ , $\precsim '$ is also nonArchimedean. For example, we might want all $I_{\{\omega \}}$ to be indifferent to each other. In this case, we can construct a representing function U as follows. For each constant function $X\equiv c$ , $U(X)=c$ , and for each nonconstant function $X=h_0+\sum _{j=1}^nh_jI_{\{\omega _j\}}$ , $U(X)=h_0+\epsilon \sum _{j=1}^nh_j$ . Note that this U is standardlinear and monotone, and it respects weak dominance, so Lemma 2.4 says that it represents a coherent total trading system which extends $_1 \mathcal {T}$ .
Theorem 2 of [Reference Skala40] shows that every total preorder can be represented by a nonstandardvalued function, but the standardlinear property that we need is not proven in that paper.
2.4 Extending $_2$ a trading system
Let $\mathcal {T}=(\mathcal {X},\precsim ,\ll )$ be a (coherent) trading system. Theorem 2.8 says that there exists a standardlinear function U that agrees with $\mathcal {T}$ and such that U represents a (coherent) total trading system $\mathcal {T}'$ that is an extension $_1$ of $\mathcal {T}$ . Extension $_2$ of $\mathcal {T}'$ is also possible if $\mathcal {X}$ is a subspace of a larger standardlinear space, as stated in Theorem 2.9.
Theorem 2.9. Let $\mathcal {T}=(\mathcal {X},\precsim ,\prec )$ be a total trading system on a standardlinear space $\mathcal {X}$ with standardlinear representing function U. Let $\mathcal {X}'$ be a standardlinear space of functions that includes $\mathcal {X}$ as a proper subset. Then there is a total trading system $\mathcal {T}'=(\mathcal {X}',\precsim ',\prec ')$ that is an extension $_2$ of $\mathcal {T}$ and a standardlinear function $U'$ on $\mathcal {X}'$ that represents $\mathcal {T}'$ and extends U to $\mathcal {X}'$ . If $\mathcal {T}$ is coherent and $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ are defined on $\mathcal {X}'$ so that they are extensions $_2$ of $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ on $\mathcal {X}$ , then $\mathcal {T}'$ can be chosen to be coherent.
Proof. Apply Lemma 2.7 with $\mathcal {T}_{\mathcal {Y}}=\mathcal {T}$ , $\mathcal {W}=\mathcal {X}'$ , and U being the U in the statement of Theorem 2.9. The $\mathcal {T}'$ and $U'$ that result from Lemma 2.7 satisfy the conclusion of Theorem 2.9.
Example 6 (Continuation of Example 5).
The linear space $\mathcal {X}$ used in Example 5 is the set of all standardvalued functions on an uncountable set $\Omega $ that are constant except at possibly finitely many points. Because weak dominance is defined on the set of all functions from $\Omega $ to ${\mathbb {R}}$ , Theorem 2.9 says that we could extend $_2$ each of the nonArchimedean coherent total trading systems from Example 5 to nonArchimedean coherent total trading systems on larger linear spaces $\mathcal {X}'$ of standardvalued functions.
For example, suppose that $\Omega =[0,1]$ , the closed unit interval and that we have chosen $\mathcal {T}$ to make $U(I_{\{\omega \}})=\epsilon $ for all $\omega $ . It is possible to extend $_2\ \mathcal {T}$ to the set $\mathcal {X}'$ of all simple functions that are measurable with respect to the smallest field $\Sigma $ of subsets of $\Omega $ that contains all intervals (closed, open, halfopen, or degenerate). For example, the degenerate interval $[\omega ,\omega ]$ is the singleton $\{\omega \}$ . (We do not allow $[\omega ,\omega )$ to be called an interval.) The field $\Sigma $ consists of all unions of finitely many disjoint intervals. The simple functions that are measurable with respect to $\Sigma $ have the form
for finite n, standard numbers $h_1,\ldots ,h_n$ , and disjoint intervals $J_1,\ldots ,J_n$ . For a nondegenerate interval J define $U'(I_J)$ to be the length of J minus $\epsilon $ for each missing endpoint, and $U'(I_{\{\omega \}})=\epsilon $ . Although the given representation of functions in $\mathcal {X}$ is not unique, it is straightforward to show that, for X being the function in (7),
is well defined and extends the function U defined in Example 5. The function $U'$ is standardlinear and monotone, and it respects weak dominance. Hence, by Lemma 2.4, $U'$ represents a coherent total trading system which extends $_2\ \mathcal {T}$ because $U'$ extends U.
The following example is modified from [Reference Seidenfeld, Schervish and Kadane38]. It involves random variables with a familiar distribution in which externally infinite nonstandard numbers are needed to represent nonArchimedean preferences amongst them.
Example 7. Let $\mathbb {Z}^+$ stand for the set of positive integers, and let $\Omega =\mathbb {Z}^+\times \{1,2\}$ . Let P be the following probability on $\Omega $ : $P(\{(n,j)\})=2^{n1}$ for $n\in \mathbb {Z}^+$ and $j\in \{1,2\}$ , which is countablyadditive. Let $\mathcal {X}$ be the set of all bounded functions defined on $\Omega $ , each of which has a finite expected value $E(X)$ with respect to P. The function $E(X)$ represents a (weakly, strictly, and uniformly) coherent total trading system $\mathcal {T}=(\mathcal {X},\precsim ,\prec )$ .
Define the following three unbounded functions on $\Omega $ :
It follows that all three of these functions have the same distribution, namely, each of them takes the value $2^k$ with probability $2^{k}$ for $k=1,2,...$ . Each of them also has infinite expected value. Let $\mathcal {X}'$ be the linear span of $\mathcal {X}\bigcup \{X_1,X_2,W\}$ . All three forms of dominance are defined on $\mathcal {X}'$ and are extensions $_2$ of the same form of dominance on $\mathcal {X}$ . We can use Theorem 2.9 to extend $_2\ \mathcal {T}$ to a coherent total trading system $\mathcal {T}'=(\mathcal {X},\precsim ',\prec ')$ with representing function $U'$ . Since each of $X_1$ , $X_2$ , and W has infinite expected value under P, it is necessary that all three of $U'(X_1)$ , $U'(X_2)$ , and $U'(W)$ must be externally infinite nonstandard numbers. However, we show next that, despite having identical distributions, $X_1$ , $X_2$ , and W cannot be indifferent in a (weakly, strictly, or uniformly) coherent trading system.
First, note that
for all $\omega $ . Hence there is a uniform dominance relation that cannot be respected by a preference in which all three are indifferent. We could, for example, have $W\prec ' X_1\sim ' X_2$ by choosing an externally infinite x and setting $U'(X_1)=U'(X_2)=x$ and $U'(W)=x1/2$ . There are other possible choices for $U'(X_1)$ and $U'(X_2)$ , but they must satisfy $U'(X_1)+U'(X_2)=2U'(W)+1$ because of (8). Finally, $U'$ is well defined on all of $\mathcal {X}'$ which includes all linear combinations of $X_1$ , $X_2$ , and W with both positive and negative coefficients.Footnote ^{5}
There are many other examples of standardlinear spaces with proper supersets. One can easily imagine an agent determining a set of preferences over a small set $\mathcal {X}$ of objects and then being offered additional options in a set $\mathcal {X}'$ . Here is an example of a situation that might seem of a different nature, but which still fits the setup of Theorem 2.9. It is related to the concepts of awareness growth and reverse Bayesianism.Footnote ^{6}
Example 8 (Awareness growth).
Suppose that an agent has a total trading system $\mathcal {T}=(\mathcal {X},\precsim ,\prec )$ where each element of $\mathcal {X}$ is a function from $\Omega $ to a space $\mathcal {O}$ . At some point, the agent realizes that the “actual” state space is a different set $\Omega '$ . There are two common models for this realization.

Refinement: The agent learns that the elements of $\Omega $ are not atomic. That is, each element $\omega $ appears to be a subset of $\Omega '$ .

Expansion: The agent learns that $\Omega $ is merely a proper subset of the “actual” state space $\Omega '$ .
In either case, one recommendation (called reverse Bayesianism) is for the agent to preserve those preferences included in $\mathcal {T}$ when extending the preference relation to include any new objects that need to be considered. Theorem 2.9 can be applied in both the refinement and expansion cases to achieve that goal. Specifically, there is a onetoone mapping T between $\mathcal {X}$ and a set $\mathcal {X}^*=\{T(X):X\in \mathcal {X}\}$ of functions from $\Omega '$ to a standardlinear space $\mathcal {O}'$ such that $\mathcal {T}^*=(\mathcal {X}^*,\precsim ^*,\prec ^*)$ is a total trading system with $X\precsim Y$ if and only if $T(X)\precsim ^* T(Y)$ . If $\mathcal {T}$ is coherent and $\mathcal {O}={\mathbb {R}}$ , then $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ are defined on $\mathcal {X}'$ so as to be extensions $_2$ of $\leq $ and $\prec _{_{{\scriptsize \text{Dom}}}}$ on $\mathcal {X}$ .
In the refinement case, for each $\omega \in \Omega $ , there is a subset $C_\omega \subseteq \Omega '$ such that the distinct elements of $\mathcal {C}=\{C_\omega :\omega \in \Omega \}$ form a partition of $\Omega '$ . For each $X\in \mathcal {X}$ and $\omega '\in \Omega '$ , define $T(X)(\omega ')=X(\omega )$ where $\omega '\in C_\omega $ . Each such $T(X)$ is constant on each element of $\mathcal {C}$ . If $\mathcal {T}$ is coherent, then $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ in $\mathcal {T}$ if and only if $T(X)\prec _{_{{\scriptsize \text{Dom}}}} T(Y)$ in $\mathcal {T}^*$ for all three forms of dominance.
In the expansion case, the additional functions in $\mathcal {X}'$ are defined on the whole set $\Omega '$ and may take values that are not in the codomain $\mathcal {O}$ of the functions in $\mathcal {X}$ . Let $\mathcal {O}'$ be the codomain of the functions defined on $\Omega '$ that the agent wants be able to trade. For each $X\in \mathcal {X}$ and $\omega \in \Omega $ define
All such $T(X)$ are identical on the part of $\Omega '$ of which the agent recently became aware. If $\mathcal {T}$ is weakly coherent, $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ if and only if $T(X)\prec _{_{{\scriptsize \text{Dom}}}} T(Y)$ . There are no cases of $X\prec _{_{{\scriptsize \text{Dom}}}} Y$ in $\mathcal {T}^*$ for the other two forms of dominance, but if $\mathcal {T}$ is uniformly or strictly coherent, $\mathcal {T}^*$ is both uniformly and strictly coherent.
In both the refinement and expansion cases, the agent can determine what set $\mathcal {X}'$ (containing $\mathcal {X}^*$ ) of functions defined on $\Omega '$ are available for trading. Theorem 2.9 then allows extension $_2$ of $\mathcal {T}^*$ to a total trading system $\mathcal {T}'=(\mathcal {X}',\precsim ',\prec ')$ . If $\mathcal {T}$ is coherent, the extension $_2$ of $\mathcal {T}^*$ to $\mathcal {T}'$ can be done so that $\mathcal {T}'$ retains the same form of coherence.
3 Three decision theories
In this section, we show how the structure of Section 1 and the results of Section 2 extend three wellknown theories of decisionmaking.
3.1 Previsions for random variables
The first Archimedean theory to which our results apply is the theory of previsions of [Reference de Finetti11], which begins with an arbitrary set of standardvalued random variables. For each X in that set, an agent chooses a standard value $P(X)$ (called the prevision of X) such that the agent is willing to trade away either X or $P(X)$ in order to receive the other one. Specifically, the change in fortune $\alpha [XP(X)]$ is considered a fair gamble for all standard $\alpha $ . Although de Finetti’s theory deals only in fair trades (indifference), there is an implicit assumption that “more is better,” which is built into his notion of coherence (corresponding to uniform dominance in Definitions 1.11 and 1.12). In [Reference de Finetti11], the agent is willing to accept every finite sum of fair gambles. In particular, the agent is willing to accept
for all standard $\alpha $ . If $P(X)=P(Y)$ , the righthand side of (9) is $\alpha (XY)$ , and the agent is implicitly willing to trade X to get Y or to trade Y to get X. If $P(X)\ne P(Y)$ , there is an implicit strict preference in one direction, e.g., if $P(Y)>P(X)$ and $\alpha <0$ , the fair trade (9) is strictly smaller than $\vert \alpha \vert (YX)$ , so the agent is willing to trade X to get Y, but not the other way. In addition, willingness to accept all finite sums of fair trades implies that a coherent prevision P on an arbitrary set $\mathcal {Y}$ of random variables extends uniquely to a coherent prevision on the linear span $\mathcal {X}$ of $\mathcal {Y}$ . Define the total preorder $\precsim $ on $\mathcal {X}$ defined “ $X\precsim Y$ if and only if $P(X)\leq P(Y)$ .” It follows that $(\mathcal {X},\precsim ,\prec )$ is a total trading system that is represented by the linear function P. Our theory extends that of [Reference de Finetti11] by dropping the requirement that every element of $\mathcal {X}$ be indifferent to some standard constant.
A simple example of a random variable that is not indifferent to a standard constant arises with an “almostfair” coin. For an evenmoney bet (odds equal 1) the agent strictly prefers the bet that pays on heads over the bet that pays on tails. But, for every bet that is not at even money (i.e., odds are different from 1), the agent strictly prefers the side of the bet that pays the larger amount. Theorem 3.1 of [Reference Fishburn15] implies that there is no standardvalued prevision that ranks these bets in the order of the stated preferences. See also [Reference Debreu, Thrall, Coombs and Davis12]. But a nonstandardvalued function can represent such preferences. Random variables with infinite previsions (such as Example 7) are also cases in which fair prices are not available. The nonstandardvalued functions that represent these preferences are not fair prices, but they provide a numerical representation of preference in the manner of expected utility.
3.2 Horse lotteries
The second theory to which our results apply is that of [Reference Anscombe and Aumann1, Reference Von Neumann and Morgenstern41] for decisions about horse lotteries, which are functions from $\Omega $ to the set of simple lotteries over a set of prizes.
3.2.1 Horse lotteries in general
Definition 3.1. For each $\omega \in \Omega $ , let $\mathcal {P}_\omega $ be the set of prizes available in state $\omega $ . A simple lottery r is a probability on a finite subset $\mathcal {P}(r)\subseteq \mathcal {P}_\omega $ . Let $\mathcal {R}_\omega $ be the convex set of simple lotteries available in state $\omega $ .Footnote ^{7} For ease of notation, let $\mathcal {P}=\bigcup _{\omega \in \Omega }\mathcal {P}_\omega $ and $\mathcal {R}=\bigcup _{\omega \in \Omega }\mathcal {R}_\omega $ be, respectively, the sets of all prizes available in at least one state and all lotteries available in at least one state. Let $\mathcal {R}_\Omega =\prod _{\omega \in \Omega }\mathcal {R}_\omega $ , which is a subset of $\mathcal {R}^\Omega $ . A horse lottery is a function $h\in \mathcal {R}_\Omega $ , i.e., $h(\omega )\in \mathcal {R}_\omega $ for every $\omega \in \Omega $ . Let $\mathcal {H}$ stand for the set of horse lotteries under consideration, which we assume to be a convex subset of $\mathcal {R}_\Omega $ .Footnote ^{8}
In each application, the set $\mathcal {H}$ of horse lotteries can be different, but each such $\mathcal {H}$ must be a convex subset of $\mathcal {R}_\Omega $ . For $h_1,h_2\in \mathcal {R}_\Omega $ and $\alpha \in [0,1]$ , the meaning of ${h_3=\alpha h_1+(1\alpha )h_2}$ is that $h_3(\omega )=\alpha h_1(\omega )+(1\alpha )h_2(\omega )\in \mathcal {R}_\omega $ , because $\mathcal {R}_\omega $ is convex. A set $\mathcal {H}$ of horse lotteries is not a linear space. Next, we show how to create a linear space that is equivalent to $\mathcal {H}$ in an appropriate sense.
3.2.2 A linear space for horse lotteries
The set $\mathcal {H}$ of horse lotteries is a convex subset of $\mathcal {R}_\Omega $ , but is not a linear space. Hausner [Reference Hausner, Thrall, Coombs and Davis21] (Sections 2–4) assumes that $\precsim '$ is a total preorder that satisfies the following axiom, which is part of the theory of [Reference Anscombe and Aumann1, Reference Von Neumann and Morgenstern41]:
Independence Axiom: Let $\precsim '$ be a preorder on a convex set $\mathcal {H}$ of horse lotteries. For all $h_1,h_2,g\in \mathcal {H}$ and standard $0<\alpha <1$ , $h_1\precsim ' h_2$ if and only if $\alpha h_1+(1\alpha )g\precsim '\alpha h_2+(1\alpha )g$ .
Hausner [Reference Hausner, Thrall, Coombs and Davis21] shows how to create a standardlinear space $\mathcal {K}_0$ with a preorder $\precsim $ that satisfies our Assumptions 2 and 3 in Section 1.4 above. This is done as follows. For each $\omega \in \Omega $ , let $\mathcal {O}_\omega $ be the set of all simple signed measuresFootnote ^{9} on $\mathcal {P}_\omega $ that give measure 0 to the whole set $\mathcal {P}_\omega $ . Let $\mathcal {O}=\bigcup _{\omega \in \Omega }\mathcal {O}_\omega $ , and let $\mathcal {O}_\Omega =\prod _{\omega \in \Omega }\mathcal {O}_\omega $ . Then
is a standardlinear space. Define $\precsim $ on $\mathcal {K}_0$ as follows. For each $k_1,k_2\in \mathcal {K}_0$ , express $k_2k_1=\alpha (h_2h_1)$ with $\alpha>0$ and $h_1,h_2\in \mathcal {H}$ . Then say that $k_1\precsim k_2$ if $h_1\precsim 'h_2$ . Hausner [Reference Hausner, Thrall, Coombs and Davis21] (Section 4) shows that $\precsim $ is well defined and satisfies Assumptions 2 and 3. The theory of [Reference Anscombe and Aumann1, Reference Von Neumann and Morgenstern41] satisfies Assumption 4 vacuously since $\precsim $ is a total preorder. Dominance and coherence are not issues that arise in the theory of [Reference Anscombe and Aumann1, Reference Von Neumann and Morgenstern41] as horse lotteries are not numerically comparable without further assumptions.
The stateindependence assumption of [Reference Anscombe and Aumann1, Reference Von Neumann and Morgenstern41] implies that all $\mathcal {R}_\omega $ sets are the same. Our theory is general enough to include cases in which the $\mathcal {R}_\omega $ sets might all be the same or might be different. We also drop the Archimedean axiom and allow $\precsim '$ to not be total as do other authors such as [Reference Aumann2, Reference Baucells and Shapley3, Reference Dubra, Maccheroni and Ok14]. Our weaker stateindependence Assumption 7 is stated in Section 4.1.
3.2.3 Representing horse lotteries
For the remainder of this paper, when we refer to the horselottery case, we will assume that $\mathcal {X}$ is the standardlinear space $\mathcal {K}_0$ defined in Section 3.2.2. (The case in which $\mathcal {X}$ is a linear space of standardvalued random variables will be called the randomvariable case.) In the horselottery case, it would be easier on the intuition if each representing function of a trading system had $\mathcal {H}$ as its domain rather than $\mathcal {K}_0$ . This is easily arranged. Let $\mathcal {T}=(\mathcal {K}_0,\precsim ,\prec )$ be a total trading system in a horselottery case with standardlinear representing function U. Let $\mathcal {H}$ be the set of horse lotteries that corresponds to $\mathcal {K}_0$ as in Section 3.2.2. For each $k\in \mathcal {K}_0$ , we can write $k=\alpha (h_1h_2)$ with $\alpha>0$ standard. Then $0\precsim k$ is equivalent to $h_2\precsim 'h_1$ for a total preorder $\precsim '$ on $\mathcal {H}$ . Let $h_0\in \mathcal {H}$ be arbitrary, and define
It follows that $V(h_0)=0$ and
Also, V represents $\precsim '$ and satisfies
for all $h_1,h_2\in \mathcal {H}$ and all standard $\beta \in [0,1]$ .
3.3 Savagestyle acts
The third theory to which our results apply is that of Savage [Reference Savage35]. This theory makes some assumptions (including stateindependence) about preferences amongst acts (functions) from a state space $\Omega $ to a set F of consequences (prizes) and then proves an expectedutility representation for those preferences. Lemma 3.2 below starts with those same assumptions and shows that there is a set of lotteries over the acts with an implied willingness to trade that satisfies the assumptions that appear in Section 1.4 of this paper. We then weaken the original assumptions of Savage [Reference Savage35] and show how to use our results for the horselottery case to represent nonArchimedean and statedependent preferences over the acts of Savage [Reference Savage35]. Whenever we refer to “the horselottery case” in this paper, we implicitly include the theory of Savage in that case.
At this point, we can show how a nonArchimedean version of the theory of Savage [Reference Savage35] becomes a special case of trading systems in the horselottery case without any additional assumptions or choices by the agent. The proof of Lemma 3.2 is in Appendix C.4.
Lemma 3.2. Let $\mathcal {F}$ be a set of functions from $\Omega $ to F, and let $\precsim '$ be a total preorder on $\mathcal {F}$ that satisfies the seven postulates (P1–P7) of Savage [Reference Savage35]. Let $\mathcal {H}$ be the set of finite mixtures of elements of $\mathcal {F}$ . Then $\precsim '$ extends to a total preorder on $\mathcal {H}$ , and the $\mathcal {K}_0$ and $\precsim $ constructed from $\mathcal {H}$ and $\precsim '$ in Section 3.2.2 form a total trading system $(\mathcal {K}_0,\precsim ,\prec )$ that satisfies Assumptions 1–4.
Despite the fact that Savage worked hard to avoid making the assumption that his set of acts contained the mixtures that we assume, his postulates are sufficient to show that his preorder extends to a total trading system that satisfies our assumptions without any further choices needed from the agent. For the purposes of this paper, instead of assuming a subset of P1–P7 or some weakened versions of them, assume only that there is a set $\mathcal {F}$ of Savagestyle acts with a preorder (not necessarily total) $\precsim '$ . Then embed $\mathcal {F}$ into the convex set $\mathcal {H}$ of Lemma 3.2 which is a special case of a set of horse lotteries. We then proceed with the same analysis and assumptions as in Sections 3.2.2 and 1.4. In particular, we make Assumptions 1–4. By so doing, we implicitly weaken some of Savage’s postulates so as to allow nonArchimedean preferences, In addition, all of the extension and representation results in Section 2 above apply to the resulting trading system, as well as the results in Section 4 below. In the end, if the agent does not want to think about mixtures of Savagestyle acts, we show (in Section 4.7) how to restrict the results of Section 4 to the original Savagestyle acts.
4 Probability and expected utility
In this section, we explore the relationship between finitely additive expectation and the representing function of a total trading system. Throughout the section,