Discussion Papers In Economics
And Business

The Comparative Statics on Asset Prices
Based on Bull and Bear Market Measure
Masamitsu Ohnishi
Yusuke Osaki

Discussion Paper 04-10

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANThe Comparative Statics on Asset Prices
Based on Bull and Bear Market Measure
Masamitsu Ohnishi
Yusuke Osaki

Discussion Paper 04-10

May 2004

この研究は「大学院経済学研究科・経済学部記念事業」
基金より援助を受けた、記して感謝する。

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANThe Comparative Statics on Asset Prices
Based on Bull and Bear Market Measure∗
Masamitsu Ohnishi † and Yusuke Osaki ‡Abstract– For single–period complete financial asset markets with representative investors,
we introduce a bull market measure for uncertain state occurrence and its associated ordering between representative investors in markets based on their marginal rate of substitution
between equilibrium consumption allocations among possible states. These concepts combine
and generalize the likelihood–ratio–dominance relation between probability prospects of state
occurrence and the Arrow–Pratt ordering of risk aversion in expected utility settings. By analyzing the comparative statics for bull market effects on equilibrium asset prices, we derivesome monotone properties of the risk–free rate and discounted prices of dividend–monotone
assets.
Keywords– Bull and Bear Market Measure, Comparative Statics, Equilibrium Asset Price,
Dividend–Monotone Asset, Total Positivity of Order 2
JEL Classification– D81, G12∗
An earlier version of this paper was presented at the 2002 annual meetings of the Japanese Association of Mathematical Sciences and the Japanese Finance Association. The authors would like to thank
Marc Bremer, Kazuhiko Ōhashi, Katsushige Sawaki and two anonymous referees for their comments andsuggestions. Of course, all remaining errors are our responsibility.
†
Graduate School of Economics, Osaka University, 1–7 Machikaneyama–machi, Toyonaka, Osaka 560–
0043, Japan, and Daiwa Securities Chair, Graduate School of Economics, Kyoto University, Yoshida–honmachi, Sakyo–ku, Kyoto 606–8501, Japan. E–mail: ohnishi@econ.osaka-u.ac.jp‡
Graduate School of Economics, Osaka University, 1–7 Machikaneyama–machi, Toyonaka, Osaka 560–
0043, Japan. E–mail: osakiyusuke@srv.econ.osaka-u.ac.jp

1. Introduction
A great number of studies on the comparative statics for economic behaviors in uncertain economic environments have been done under expected utility settings. The mostcommon problems are portfolio selections discussed in financial economics and the effectsof stochastic dominance shifts on probability prospects of asset returns or shifts in risk
aversion of investors on optimal portfolios, see e.g. Gollier [4].
One of the reasons why expected utility settings have been widely used for analysis
of decision making under uncertainty is their easy tractability due to the decomposability of expected utilities into probability prospects (probability distributions) of risks andattitudes toward risks (von Neumann and Morgenstern (vN–M) or Bernoulli utility functions, [19]). However, there are many critical discussions regarding the validity of expectedutility settings, see e.g. Machina [12, 13].
When we adopt the expected utility settings for modeling of decision making under
uncertain economic environments, comparative static analysis for the effects of changes
in probability prospects and/or attitudes toward risks become of great interests. There
have been many studies on these respective subjects since the publication of the seminal
papers by Rothschild and Stiglitz [17, 18] for the former and Arrow [1] and Pratt [16]for the latter. However, only few papers are devoted to comparative static studies in theframeworks of non–expected utilities.
In this paper, under non–expected utility settings, we analyze comparative statics for
single–period complete financial asset markets with representative investors. We introduce
a bull market measure for uncertain state occurrence and its associated ordering between
representative investors in markets based on their marginal rate of substitution between
equilibrium consumption allocations among possible states by using the TP2 (Totally
Positive of Order 2) concept4) . This concept can be combined and generalized with thelikelihood–ratio–dominance (LRD) relation between probability prospects of state occurrence (Milgrom [14]) and the Arrow–Pratt ordering of risk aversion (Arrow [1] and Pratt[16]) in expected utility settings. Therefore, our results are extensions of the previous
results obtained by Milgrom [14] and Ohnishi [15]. Milgrom [14] examined the effects of
LRD shifts in the probability prospect of the representative investor on the risky asset in afinancial market with one risk–free and one risky assets, that is, a market where the 1–fundseparation theorem holds. Ohnishi [15] derived some monotone properties for the effectsof the LRD shifts in probability prospect or changes in the Arrow–Pratt risk aversion of
the representative investor in a complete financial market with multiple assets.
This paper is organized as follows. In Section 2, we consider a single period asset
market model with the representative investor, and examine equilibrium asset prices inthis market. In Section 3, we introduce a bull and bear market measure and its associatedordering by using the TP2 concept. In Section 4, we analyze the comparative statics forthe bull market effects on equilibrium asset prices, and show that dividend–monotone
asset prices have some monotone properties.

2. Asset Market
Consider a standard single–period asset market model described as follows, see e.g. Duffie[3] and LeRoy and Werner [11]. This model has two dates indexed by t = 0, 1. The
uncertainty is revealed at t = 1 and is classified into one of S states, indexed by s =1, . . . , S. In the asset market, there are I investors indexed by i = 1, · · · , I. Each investor
i is characterized by his/her own utility function V i : RS+ → R and an initial endowment
ei = (ei1 , . . . , eiS )> ∈ RS+ . The utility function V i exhibits investor i’s preference %i
4)TP2 is frequently called Log–Supermodularity in the theory of economics of uncertainty (see, e.g.,
Athey [2] and Gollier [4]). As for the details of the theory of Total Positivity (TP), see Karlin [7], and for
its economic and financial applications, see Jewitt [5, 6], Kijima and Ohnishi [8, 9, 10].

1

concerning a consumption allocation ci = (ci1 , . . . , ciS )> ∈ RS+ for t = 1 which is planned at
t = 0. We assume that the utility function V i is strictly increasing and strictly concave5) .
Notice that we generally consider non–expected utility functions, some comments on a
reduction to the cases of expected utilities are considered in Section 3.2.
The asset market trades N assets indexed by n = 1, · · · , N , and they are characterized
by an S × N dividend matrix D = (dsn ; s = 1, · · · , S, n = 1, · · · , N ), where dsn is theamount of the dividend which asset n pays in state s at t = 1. We assume that theasset market is frictionless and competitive. Further, we assume that the asset market iscomplete. That is, the rank of the dividend matrix equals the number of states: rank(D) =S. We also assume that the asset market does not admit any arbitrage opportunities. Thatis, there are no portfolios h = (h1 , . . . , hN )> ∈ RN satisfying either of the following two
conditions:hq, hi ≤ 0;

Dh ≥ 0 and Dh 6= 0

(1)

orhq, hi < 0;Dh ≥ 0,(2)

where q = (q1 , . . . , qN )> ∈ RN++ are asset prices. In the theory of asset pricing, it is widely
known that if the asset market does not admit arbitrage opportunities and is complete,then there exists a unique price system, Arrow–Debreu securities or state securities. The
Arrow–Debreu security s (= 1, . . . , S) or state s security pays one unit of dividend whenstate s occurs at t = 1 and nothing elsewhere. We call the prices of the Arrow–Debreu
securities, state prices and denote them as ψ = (ψ1 , . . . , ψS )> ∈ RS++ .
In the asset market, every investor i will maximize his/her utility from a consumption
allocation ci = (ci1 , . . . , ciS )> for t = 1 which is planned at t = 0 by purchasing a portfolio
hi = (hi1 , . . . , hiN )> . Then, the utility maximization problem of agent i is represented asfollows:
Maximize
ci ,hiV i (ci )(3)subject to

ei + Dhi = ci ,(4)ihq, h i = 0.

(5)

We can rewrite the above problem by state prices as follows:
Maximizeci
subject toV i (ci )(6)hψ, ci i = hψ, ei i.

(7)

The constraints of the above optimization problems are equalities because the utility
function V i is assumed to be strictly increasing.
Next, we define the representative investor in the asset market. The representative
investor has the utility function U defined as follows:
¯ I
)
( I
¯X
X
¯
ci = c , c ∈ RS+(8)
U (c) := supλi V i (ci )¯¯
c1 ,··· ,cI i=1
i=1
where λi ≥ 0, i = 1, · · · , I; is investor i’s weight. At this time, it is widely known that the
representative investor’s utility function is strictly increasing and strictly concave when5)

In this paper, the terms “increasing” and “decreasing” are used in the weak sense, that is, “increasing”
means “nondecreasing” and “decreasing” means “nonincreasing”.

2every investor P
i’s utility function V i is strictly increasing and strictly concave. Thus,
the constraint Ii=1 ci = c is an equality. We denote the aggregated endowment: e =PIii=1 e . Then the representative investor is characterized by his/her utility function
U : RS+ → R and the initial endowment e ∈ RS+ . In the equilibrium, we consider theutility maximization problem of the representative investor in the asset market as follows:
Maximizecsubject to

U (c)

(9)

hψ, ci = hψ, ei.

(10)Under this set–up, the representative investor’s consumption allocation is equal to theaggregated endowment: c = e, in the equilibrium of asset market. Then, by the firstorder conditions for optimality of the optimization problem (9), (10), state prices ψs ,s = 1, . . . , S in the equilibrium are represented as follows:ψs = PS∂s U (e)s=1 es ∂s U (e),s = 1, . . . , S,(11)c ∈ RS+

(12)

where
∂s U (c) :=

∂U
(c),
∂cs

is the marginal utility function from consumption cs in state s (= 1, . . . , S) at t = 1.
The equilibrium price q of an arbitrary asset or asset portfolio whose dividend in states (= 1, . . . , S) at t = 1 is ds , is represented as follows:q=SX

ds ψ s .

(13)

s=1

The equilibrium price qf of the risk–free asset and the risk–free rate Rf are evaluatedas follows:
S
X

PS∂s U (e);qf =ψs = PSs=1
s=1 es ∂s U (e)s=1PSes ∂s U (e)11
Rf == Ps=1.
= PS
Sqf
s=1 ψss=1 ∂s U (e)(14)

If we defineψsβs := PS∂s U (e)= Rf ψs = PS
,
ψ
∂
U
(e)
s
s
s=1
s=1

s = 1, . . . , S,

(15)then we can consider β = (β1 , . . . , βS )> as a probability vector (or a probability massPS
function) since βs ≥ 0, s = 1, . . . , S; ands=1 βs = 1. In the arbitrage pricing theory,>
β = (β1 , · · · , βS ) is called the risk neutral probability measure or equivalent martingale
measure. By rewriting eq. (13), we obtained the risk neutral evaluation formula for theequilibrium price of an arbitrary asset whose value in state s (= 1, · · · , S) is ds , as follows:
S

S

s=1

s=1

X
1 X
βs ds = qf
βs ds .
q=
Rf

3

(16)

3. Bull and Bear Market
3.1 Definition
In the previous section, we see that an asset market is characterized by a representative
investor j. So we call an asset market with a representative investor j (= 1, 2), as market
j, where representative investor j is characterized by his/her utility function U j : RS+ → RP
and an aggregated endowment e = Ii=1 ei . In this and following sections, without any
loss of generality, we assume that an aggregated endowment is monotone increasing in thestate number:e1 ≤ . . . ≤ eS .

(17)

Now we characterize different attitude to the asset market to introduce the desirability
to states. We reinterpret the marginal utility in state s: ∂s U (e) to be the measure of thedesirability to state s. We call the marginal utility in state s to be reinterpreted, bulland bear market measure. Note that the consumption allocation c of the representative
investor with strictly increasing utility function is equal to the aggregated endowment
e. Note also that the aggregated endowment is assumed to be monotone increasing inthe state numbers: e1 ≤ . . . ≤ eS . We now introduce an ordering relation between asset
markets. We say that the asset market is more bullish (or more bearish), if the more bullish(more bearish) asset market prefer the state with higher (lower) consumption allocation
than the less bullish (less bearish) asset market. To get more precise expression, we use
the common economic concept of marginal rate of substitution of consumption allocation
to state m for consumption allocation to state l, which is defined as the ratio of their
marginal utilities:
MRSml (e) :=∂m U (e),∂l U (e)1 ≤ l ≤ m ≤ S; e ∈ RS+ .

(18)

Note that el ≤ em for 1 ≤ l ≤ m ≤ S by the assumption on the aggregated endowment.
Then eq. (18) expresses the amount of lower consumption allocation that the investor
must be given to compensate him/her for one unit marginal reduction in higher consumption allocation m. That is, eq. (18) is the relative evaluation of an additional consumption
allocation with higher consumption state m measured by that at state l with lower consumption. In this preparation, we define that for two markets 1 and 2, market 2 is morebullish than market 1 if the following inequality holds:
MRS1ml (e) :=∂m U 2 (e)∂m U 1 (e)≤=: MRS2ml (e),∂l U 1 (e)∂l U 2 (e)1 ≤ l ≤ m ≤ S; e ∈ RS+ .

(19)

Hence, eq. (19) tells us relative evaluations in more bullish markets at the higher state m
are higher than those in less bullish markets. We redefine the ordering of bull market, eq.
(19) by the use of TP2 (Totally Positive of Order 2) concept.
Definition 3.1. Market 2 is said to be more bullish (less bearish) than market 1 (ormarket 1 is said to be more bearish (less bullish) than market 2) at aggregated endowmente (∈ RS+ ) if and only if the function ∂s U j (e) is TP2 with respect to s = 1, · · · , S andj = 1, 2, that is,¯¯¯∂l U 1 (e) ∂m U 1 (e)¯¯¯(20)¯∂l U 2 (e) ∂m U 2 (e)¯ ≥ 0, 1 ≤ l ≤ m ≤ S.

4

3.2 The Case of Expected Utility
Until now, we consider U : RS+ → R to be a non–expected utility function. In this subsection, we assume, for a special case, U : RS+ → R has an expected utility representation:
U (c) =SX

πs u(cs ), c ∈ RS+ ,

(21)

s=1

where π = (π1 , . . . , πS )> is a probability vector consisting of a probability prospect πsPthat state s occurs at t = 1 with πs ≥ 0, s = 1, . . . , S, Ss=1 πs = 1, and u : R+ → R isa von Neumann–Morgenstern (vN–M) (or Bernoulli) utility function. We further assume
that an investor is risk–averse: u0 > 0, u00 ≤ 0. Since a utility function U : RS+ → R withan expected utility representation is linear in probability, we can decompose it into twoparts: a probability prospect π and an attitude toward risk represented by a vN–M utility
function u. The effects of the former are investigated with the application of the theoryof stochastic dominances, one of which is the likelihood–ratio–dominance (LRD). For thelatter, Arrow [1] and Pratt [16] consider that the attitude toward risk is represented by
the degree of concavity of vN–M utility function. This is called the Arrow–Pratt Absolute
Risk Aversion (ARA). As discussed later, since effects of shifts in probability prospect
π and changes in attitude toward risk on decision making, work in the same (opposite)
direction, these concepts could be considered dual in the sense of TP2 (see Gollier [4]).
The observation motivates our introduction of new bull and bear market concepts
We introduce the definition and properties of stochastic dominances used in this andfollowing sections:Definition 3.2 (Stochastic Dominances). Let αj = (α1j , . . . , αSj ), j = 1, 2 be two
probability vectors (or probability mass functions) on {1, . . . , S}.
(1) α2 dominates α1 in the sense of likelihood–ratio–dominance (LRD) if αsj is TP2(Totally Positive of Order 2) with respect to s = 1, . . . , S and j = 1, 2, that is,
¯ 1
¯
1 ¯
¯ α αm¯ l¯(22)¯ α2 α2 ¯ ≥ 0, 1 ≤ l ≤ m ≤ S.
ml
In this case, we write this as α1 ≤LRD α2 .
(2) α2 dominates α1 in the sense of First order Stochastic Dominance (FSD) if
S
X

αs1 ≥

S
X

αs2 ,

k = 1, . . . , S.

(23)

s=k

s=k

In this case, we write this as α1 ≤FSD α2 .
The following theorem is well known in the theory of stochastic dominances. For details
see, e.g., Kijima and Ohnishi [8].
Theorem 3.1. Let αj = (α1j , . . . , αSj ), j = 1, 2 be two probability vectors (or probability
mass functions) on {1, . . . , S}. We have the followings:(1) α1 ≤LRD α2 implies α1 ≤FSD α2 .
(2) α1 ≤FSD α2 holds if and only if, for any S–dimensional vector f = (f1 , . . . , fS ) withincreasing components (f1 ≤ . . . ≤ fS ), we haveSX

αs1 fs ≤

s=1

S
X
s=1

5

αs2 fs .

(24)

Next, introduce the definition and properties of Arrow–Pratt ordering of risk aversion.
Define the Absolute Risk Aversion (ARA) of u in the Arrow–Pratt sense byA(x; u) := −u00 (x)(≥ 0).
u0 (x)(25)

Definition 3.3. Let uj (uj 0 > 0, uj 00 ≤ 0), j = 1, 2 be twice differentiable vN–M utility
functions of two risk averters, defined on a common open interval of the real line R. If it
holds that
A(x; u1 ) = −u100 (x)u200 (x)≥−= A(x; u2 ),
u10 (x)u20 (x)∀x,(26)

then u1 is said to be more risk averse than u2 (u2 is said to be more risk tolerant thanu1 ) in the sense of APRA (Arrow–Pratt Risk Aversion) and in this case, we write this as
u1 ≥APRA u2 .
In previous works (e.g., Jewitt [5, 6], Kijima and Ohnishi [9]), the ordering of ARA in
the Arrow–Pratt sense is characterized by the TP2 concept: u1 ≥APRA u2 if and only if:¯ 10¯¯ u (x) u10 (y) ¯¯¯(27)¯ u20 (x) u20 (y) ¯ ≥ 0, x ≤ y,that is, uj 0 (x) is TP2 with respect to j = 1, 2 and x.
In the case of expected utility, marginal utility in state s is represented by∂s U (c) = πs u0 (cs ),s = 1, . . . , S; c ∈ RS+ ,(28)

therefore the condition of Definition 3.1 is reduced to the followings: πsj uj 0 (es ) is TP2 withrespect to s = 1, · · · , S and j = 1, 2, i.e.,¯ 1 10¯
1 u10 (e )¯¯π u (el ) πm
m
1 10
2 20
1 10
2 20
l
¯
¯
¯π 2 u20 (el ) π 2 u20 (em )¯ = πl u (el )πm u (em ) − πm u (em )πl u (el ) ≥ 0, 1 ≤ l ≤ m ≤ S.(29)mlEach of the conditions π 1 ≤LRD π 2 and u1 ≥APRA u2 is generalized to¯ 1 10¯
1 u10 (e )¯¯π u (el ) πm
m ¯
1 10
2 20
1 10
2 20
l
¯
πl u (el )πm u (em ) − πm u (em )πl u (el ) = ¯ 2 20
1 ≤ l ≤ m ≤ S.(30)
2 u20 (e )¯ ≥ 0,
πl u (el ) πmm
In other words, eq. (30) suggests a set of sufficient condition of Definition 3.2:
Proposition 3.1. Suppose that two probability prospects π j , j = 1, 2 and two vN–M
utility functions uj : R+ → R satisfy the following two conditions:(SD) In the sense of LRD, π 2 dominates π 1 , i.e., π 1 ≤LRD π 2 ;(RA) In the sense of APRA, market 1 is more risk averse than market 2, i.e., u1 ≥APRA u2 .
Then the conditions of Definition 3.1. are satisfied.

64. Comparative Statics
In this section, we examine some comparative statics on equilibrium prices of three
types of assets or asset portfolios as follows:
Definition 4.1.
(RF) Assets and/or portfolios that pay one unit of consumption as a dividend in all states.
That is, the asset whose dividend ds in state s is 1 in every state s (= 1, · · · , S), i.e.,d1 = · · · = dS = 1. We call this type of assets risk–free assets;(MI) Assets and/or portfolios that pay dividends which are monotonic increasing in states,i.e., d1 ≤ · · · ≤ dS . We call this type of assets MI (Monotone Increasing) assets;(MD) Assets and/or portfolios that pay dividends which are monotonic decreasing in states,i.e., d1 ≥ · · · ≥ dS . We call this type of assets MD (Monotone Decreasing) assets.
By eq. (14) in Section 2, the equilibrium price qf of the risk–free asset and the risk–freerate Rf are evaluated asSXPS∂s U (e)qf =;ψs = PSs=1
s=1 es ∂s U (e)s=1PSes ∂s U (e)
1
1
Rf =
= PS
= Ps=1.
S
qf
s=1 ψss=1 ∂s U (e)(31)

In the remaining of this subsection, we consider two markets, market 1 and 2 forcomparative static analysis and assume that market 2 is more bullish than market 1(market 1 is more bearish than market 2). In this set–up, we obtain the following theorem:
Theorem 4.1. Suppose two markets and assume that one market is more bullish thanthe other market. Then, the risk–free rate in a more bullish market is higher than thatin a less bullish market. Or equivalently, the equilibrium price of the risk–free asset ina more bullish market is lower than that in a less bullish market. That is, the following
relations hold:Rf1 ≤ Rf2

qf1 ≥ qf2 .

and

(32)

Proof. Define∂s U j (e)αsj := PS,js=1 ∂s U (e)j = 1, 2.

(33)

Then, we can rewrite the risk–free rates by using αsj , s = 1, · · · , S as:
Rfj =

S
X

αsj es ,j = 1, 2.

(34)

s=1

Notice that αj = (α1j , · · · , αSj )> , j = 1, 2 are considered as probability vectors (or probaPSjbility mass functions), since αsj ≥ 0, s = 1, · · · , S;
s=1 αs = 1.
Now we show that
αs2
is monotone increasing in s.
αs1
By definition of αsj , s = 1, · · · , S, j = 1, 2, we have
PS
1
2
αs2
s=1 ∂s U (e) ∂s U (e)
·
.
=
P
S
2
αs1
∂s U 1 (e)s=1 ∂s U (e)
7

(35)

(36)

Since, by Definition 3.1,∂l U 2 (e)∂m U 2 (e)≤,∂l U 1 (e)∂m U 1 (e)1 ≤ l ≤ m ≤ S,(37)

the second factor of the right hand side in eq. (36) is monotone increasing in s so that thelikelihood ratio αs2 /αs1 is monotone increasing in s. Since αj , j = 1, 2 can be considered
as probability vectors (or probability mass functions), α2 dominates α1 in the sense of
LRD, i.e., α1 ≤LRD α2 . In the previous section, we know that the stochastic order of
LRD implies the stochastic order of FSD. We assume that e1 ≤ . . . ≤ eS so that we obtain
Rf1 =

S
X

αs1 es ≤SX

αs2 es = Rf2 ,

s=1

s=1

qf1 =

1
1
≥ 2 = qf2 .
1
Rf
Rf

(38)

or equivalently,(39)

Theorem 4.2. Let us consider the risk–free asset as a numèrare. The relative price ofan MI (MD) asset in a more bullish (more bearish) market is higher than that in a lessbullish (less bearish) market. That is, the following inequalities hold:
2
1
qMI
qMI
≤
qf1
qf2

while

1
2
qMD
qMD
≥
,
qf1
qf2

(40)

j
j
where qMI
and qMDare prices of an MI asset and MD asset, respectively.

Proof. We defineψsβs := PS∂s U (e)= Rf ψs = PS,
s=1 ψss=1 ∂s U (e)s = 1, · · · , S,

(41)

then we can consider β = (β1 , · · · , βS )> as a probability vector (a probability mass function) sinceβs ≥ 0, s = 1, · · · , S;S
Xβs = 1.

(42)s=1

By eq. (16) of Section 2, an equilibrium relative price of an asset whose value in state s(= 1, · · · , S) is ds , can be evaluated as
S

S

s=1

s=1

X
X
q
ds ψs =
βs ds .
= Rf q = Rf
qf

(43)

We can prove the theorem in a similar way to the proof of Theorem 4.1.
Here, MI (MD) assets are characterized below. MI (MD) assets have the property that
more high dividends are realized when higher (lower) consumption allocations are realized.
In other words, MI (MD) assets pay higher dividends in economic boom (slowdown).
Finally, we give an economic interpretation of the result of Theorem 4.2. Definition 3.1
can be rewritten as;
MRS1ml (e) ≤ MRS2ml (e) and MRS1lm (e) ≥ MRS2lm (e),81 ≤ l ≤ m ≤ S; e ∈ RS+ , (44)

where MRSml(lm) (e) is marginal rate of substitution of consumption allocation to statem(l) for consumption allocation to state l(m). In other words, eq. (44) tells us the relativeevaluation of an additional consumption allocation with higher (lower) consumption statem(l) measured by that at state l(m) with lower (higher) consumption of more bullish (morebearish) markets is higher than less bullish (less bearish) markets. From the assumption ofdividends of MI (MD) assets, the demand of MI (MD) assets in more bullish (more bearish)
markets is relatively higher than that in less bullish (less bearish) markets. Therefore theequilibrium price of MI (MD) assets in more bullish (more bearish) markets is higher thanthat in less bullish (less bearish) markets.

5. Concluding Remarks
For single–period complete financial asset markets with representative investors, we introduced a bull market measure for uncertain state occurrence and its associated ordering
between representative investors in markets based on their marginal rate of substitution
between equilibrium consumption allocations among possible states. By analyzing thecomparative statics for bull market effects on equilibrium asset prices, we derive somemonotone properties of the risk–free rate and discounted prices of dividend–monotone
assets. These results are extensions of the previous results based on the likelihood–ratio–
dominance relation between probability prospects of state occurrence and the Arrow–Prattordering of risk aversion under expected utility settings.

9

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Press, Princeton.
[4] Gollier, C. (2001) The Economics of Risk and Time, The MIT Press, Cambridge.
[5] Jewitt, I. (1987) Risk Aversion and the Choice between Risky Prospects: The Preservation of Comparative Statics Results, Review of Economic Studies, 54, 73–85.
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60–70.
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