Consumption and Investment Choices


Consumer Utility

Normative financial economics concerns optimal decisions made by individuals, firms and/or institutions. In an important sense, much of the subject matter of investments deals with optimal choices of investment and consumption.

Thus far we assumed that the investor/consumer makes optimal choices from among alternative combinations of present and contingent future consumption opportunities. Initially, we suggested that the individual picks the combination that he or she likes best. This hardly offers much help. Imagine an Analyst saying to a client: "do what's best".

Our second characterization of investor behavior utilized the concept of indifference curves or, more generally, indifference surfaces. The conclusion was somewhat more elegant, although hardly more useful: pick the combination from the opportunity line (or plane or hyperplane) on the highest (best) indifference surface.

At this point, we have provided little help for the Analyst seeking to offer direction to individuals or institutions seeking advice on either the optimal amount to be invested or the particular investments that should be undertaken.

As we will see, an Analyst can provide useful advice concerning such decisions. Individuals may differ in preferences, circumstances, constraints and predictions. A rather rich body of analytic methods can be invoked to help take such differences into account. Such techniques provide a core set of normative methods for investment management.

Here we will deal with three aspects that may lead informed individuals to adopt different strategies: differences in preferences, differences in wealth and differences in predictions. We leave for later the analysis of differences in constraints, other circumstances, and so on.

A formal construct that helps to highlight the differences among utility-based, wealth-based and prediction-based investment decisions uses the concept of consumer utility and the assumption that the goal of the consumer is to maximize the expected value of such utility. In this scheme, (1) consumer utility summarizes an individual's preferences, (2) possible combinations of consumption are related to wealth, and (3) the probabilities utilized to compute expected utility can be considered predictions. In principle, one can thus determine the extent to which investment decisions differ due to differences in predictions as opposed to differences in preferences or differences in wealth. In practice, such a neat taxonomy is difficult to attain. Nonetheless, every investment decision should be scrutinized in an attempt to determine (as best possible) the role that each such type of difference plays.

Consumer Utility Functions

Consider an individual trying to select a combination of apples today, apples in the future if the weather is good, and apples in the future if the weather is bad. We represent a consumption plan as a vector c in which the elements are the levels of consumption in every time and state; in this case: [consumption now, consumption later if the weather is good, consumption later if the weather is bad].

Consider a particular consumption plan, for example, [80,100,50]. Note that the consumer will, in fact, attain one of two of the mutually exclusive sets of consumption:

   if the weather is good:
       Now:      80        
       Future:  100
   if the weather is bad
       Now:      80
       Future:   50

It is generally assumed that consumer utility functions are such that all types of consumption are goods (i.e., more is preferred to less, other things equal). It is generally also assumed that in such functions, marginal utility (the added utility from one added unit) decreases as the number of units increases (i.e. there are decreasing returns to scale in consumption).

In some cases the utility associated with a given amount of future consumption will differ, depending on the state of the world in which the consumption takes place; for example, 5 apples might give more satisfaction on a rainy day than on a sunny one. In such cases, we say that the consumer has state-dependent utility.

The utility associated with additional consumption in one time period may depend on the amounts consumed in prior time periods. Consumers may fall into habits so that both the absolute amount of consumption and any change from previous levels may be of importance.

In many cases Analysts will take neither of these possible complications into account. Instead, they assume that utility is separable and additive -- that is, that there is a utility associated with each time period and state of the world and that the total utility is simply the sum of these sources of utility. Moreover, they assume that the utility associated with each time and state is of a particularly simple form.

Vector c, which represents a consumption plan, includes entries for at least two time periods; in our case: now and later. Let tp be a vector of the same length with coefficients indicating the consumer/investor's time preference. For example:

        now       future         future
              (good weather)  (bad weather)
         1.0        0.95          0.95

This indicates that a given amount of consumption in the future provides 0.95 times as much utility as the same amount of consumption now. If there were a third time period, the entries for that period in vector tp would typically be smaller than those for the second time period, and so on. One possibility would be to make the entries for the second period some constant d, those for the third period d^2, those for the fourth period d^3, etc.. This would allow the investor's time preference to be summarized with one number (d). In any event, all entries in vector tp that refer to a given time period will be the same.

Regarding utility itself, Analysts often make another restrictive assumption. They assume that the utility associated with a given time and state can be written as:


where ts is the time and state, tp(ts) is the time preference parameter for the associated time, c(ts) is the consumption planned for the time and state, and u(c(ts)) is the utility associated with that consumption, not taking into account the time at which it is received. This rules out, for example, the possibility that an Investor may have one attitude concerning risk in period 2 and a different attitude concerning risk in period 3.

Only one task remains -- to specify the utility function u(). Possible forms are discussed in subsequent sections. Suffice it to say that at the very least, utility should increase with consumption, but at a decreasing rate. Equivalently, the marginal utility (change in utility per unit change in consumption) should decrease as consumption increases.

The Expected Utility Maxim

We have associated an amount of consumer utility with each possible level of consumption. However, in fact some of the levels will not be realized. To take this into account, we multiply each utility level by the probability that the consumption in question will be attained. The sum of all such values is the expected utility of the consumption plan. We assume that the consumer's objective is to select from among all feasible plans, the one that provides the maximum expected utility. The latter is known as the expected utility maxim principle.

Let prob be a vector of the same length as c with probabilities assigned to each time and state by the Investor (consumer) and/or the Analyst. In this vector, the sum of all entries for a given time period will equal one. For example:

        now       future         future
              (good weather)  (bad weather)
         1.0        0.50          0.50

If there were entries for a third period, the sum of those entries would also be 1.0, and so on.

We are now in a position to write a formula for the expected utility eu of a consumption plan c. It is:

    eu = sum (prob.*tp.*u(c));

Given a vector of atomic security prices p, the optimal consumption/investment problem can then be stated as:

    Select:         c
    to Maximize:    eu
    Subject to:     p*c <= W 

where W is the consumer/investor's wealth.

The decision variables are the levels of planned consumption. The optimization problem is to select values for these variables that maximize the objective function without violating the inequality constraint. It can be solved either through a "search procedure" or, in some cases, by directly finding the values that satisfy a set of conditions that must obtain when the optimum solution for such a problem is found. Microsoft's Excel spreadsheet includes a solver procedure that employs an intelligent search method to solve problems of this sort. MATLAB's optimization toolbox also provides functions that can be used for the purpose.

Risk Tolerance

Given the expected utility maxim, we can see more directly the relationship between the curvature of the utility function and an Investor's tolerance for risk. To do so, we utilize a simple function of the following form:

    u(c)  = c.^k

where k is a positive constant between 0 and 1.  The greater the value of k, the less curved will be the function; if k were to equal 1.0, the curve would become a straight line.

Consider an investment that offers a probability of 0.50 that consumption will equal 80 apples (Good) and a probability of 0.50 that it will equal 20 apples (Bad). The table below shows the utility associated with each outcome for an investor with k=0.375. The expected utility -- the probability-weighted average of these two utility values -- is shown as well.

  k = 0.375

             Consumption    Utility
    Good         80          5.172
    Bad          20          3.075
          Expected Utility   4.124

      Certainty Equivalent  43.73

The expected utility maxim assumes that an investor will be indifferent between two investments if they offer the same expected utility.  But the expected utility of a certain investment will equal its utility. The certainty-equivalent for a risky investment can be defined as an amount to be received with certainty that the investor would just be willing to accept instead of the risky investment.  Here, we seek the value of c for which:

   c.^k = 4.124

The answer, also shown in the table above,  is 43.73 apples.  Thus although the investment offers an expected consumption of 50 apples (0.50*20 + 0.50*80), this investor considers it only as desirable as 43.73 apples for certain.

Now consider the investor with a utility function for which k=0.500. The corresponding calculations are shown in the table below. She considers the investment as desirable as 45.00 apples for certain. In a sense she "likes it better" than the first investor. If one had to pay 44 apples to obtain the investment, the first investor would pass the opportunity by, while the second one would seize it with pleasure.

   k = 0.500

             Consumption    Utility
    Good         80          8.944
    Bad          20          4.472
          Expected Utility   6.708

      Certainty Equivalent  45.00

The greater the value of k in a utility function of the type we have posited, the greater will be the certainty equivalent for a given risky investment.  Hence we can say that the greater the value of k, the greater the investor's tolerance for risk and the smaller his or her aversion to risk.  More generally, the smaller the curvature of the utility function, the greater is an investor's tolerance for risk.

Maximizing Expected Consumer Utility

Given our simplifying assumptions,  the expected utility of a consumption plan will depend on the consumer's time-preference,  risk tolerance, and assessment of the probabilities of the alternative states of the world.  In our example, there are only two such states.  Since the probability of bad weather will equal one minus the probability of good weather, we may focus on three parameters: two reflecting a consumer's preferences (time preference and risk tolerance), and one reflecting his or her predictions.

Given a set of prices p and a level of wealth W, a consumer/investor will choose a consumption plan c that maximizes expected utility, taking into account his or her time preference, risk tolerance and probability assessments. Note that the latter three aspects are not directly observable, while the former are, at least in principle. Investors with the same wealth facing the same set of prices can and often will differ in their choices of planned consumption. In general, those with greater preference for present as opposed to future consumption will consume more in the present and save less. Those with greater risk tolerance will take greater risk in their investment portfolio. And, other things equal, those who attach higher (lower) probabilities to certain events will invest more (less) in securities that pay off when those events take place.

To illustrate, we consider an investor with the following expected utility function:

   eu = cn^k  + prg*d*(cg^k)  + (1-prg)*d*(cb^k)

Here, the arguments of the function, cn, cg and cb,  are consumption now, consumption in the future if the weather is good, and consumption in the future if the weather is bad, respectively.  The three parameters of the function are k (a measure of risk tolerance), d (a measure of time preference), and prg (the estimated probability of good weather).  As in earlier examples, we assume that the prices are [1.00 0.285 and 0.665] for the three types of consumption (cn, cg and cb, respectively).

Investors whose preferences can be described with this type of utility function will react to increases in wealth by adjusting their plans proportionately. Thus, compared with an Investor with a wealth of 100, an investor with a wealth of 200 will consume twice as many apples today, and select a consumption plan involving twice as many apples if the weather is good and twice as many apples if the weather is bad. The savings rate and portfolio composition will be the same for any two investors that have (1) the same risk tolerance (more precisely, the same value of k) and (2) the same time-preference (more precisely, the same value of d), and (3) the same probability assessment (more precisely, the same value of prg) . Such invariance with respect to wealth is not a generally observed relationship, indicating that this form of an expected utility function does not capture the preferences of all investors. However, for now allows us to avoid issues associated with the effects of differences in wealth.

Consider an Investor with a wealth of 100 for whom k=0.375, d=0.96, and prg=0.50. Her optimal consumption plan c in units will be [48.76 112.27 28.94]. The values of the components (p.*c) will be:

      Now       Good Weather      Bad Weather
     48.76          32.00            19.24

She will spend 48.76% of her wealth on present consumption and invest 51.24%.  Her investment portfolio will consist of claims on apples if the weather is good with a value of 32.00 and claims on apples if the weather is bad with a value of 19.24.  Thus the proportion of the portfolio's value invested in good weather apples is 32.00/51.24, or 62.45%.

This example might seem extreme, since the investor spends only 48.76% of her wealth and invests the remaining 51.24% -- a seemingly extremely high savings rate. However, recall that we are dealing here with total wealth, including the present value of future income. It is important to recognize that an individual's wealth prior to retirement includes the value of his or her human capital. It should be included, along with financial and physical capital, when considering total wealth and when making plans for savings and risk-taking. Among other things, this suggests that younger investors (for whom human capital is likely to represent a majority of wealth) may choose to invest their physical and financial capital rather differently than older investors (for whom human capital may represent a minority of wealth). It also suggests that the nature of one's human capital should be taken into account when determining the appropriate investment of the non-human capital that is not consumed.

The next table shows the relationship between k and the decisions of interest. Each row portrays the optimal choice for a different investor. The first three columns indicate the parameters used in the analysis. The final columns show the values of, respectively, the amount consumed in the present, the amount planned to be consumed if the weather is good and the amount planned to be consumed if the weather is bad. The eighth row contains the results obtained earlier. The other rows show results for Investors that are alike with regard to time-preference and prediction but differ in risk tolerance.

     prg         k         d    consumed    good       bad
    0.5000    0.2000    0.9600   50.2676   27.4901   22.2422
    0.5000    0.2250    0.9600   50.1184   27.9926   21.8890
    0.5000    0.2500    0.9600   49.9600   28.5286   21.5114
    0.5000    0.2750    0.9600   49.7729   29.1149   21.1121
    0.5000    0.3000    0.9600   49.4887   29.7447   20.7666
    0.5000    0.3250    0.9600   49.3278   30.4329   20.2394
    0.5000    0.3500    0.9600   49.0605   31.1812   19.7583
    0.5000    0.3750    0.9600   48.7561   31.9981   19.2458
    0.5000    0.4000    0.9600   48.4089   32.8932   18.6978
    0.5000    0.4250    0.9600   48.0107   33.8783   18.1109
    0.5000    0.4500    0.9600   47.5525   34.9661   17.4814
    0.5000    0.4750    0.9600   47.0219   36.1728   16.8053
    0.5000    0.5000    0.9600   46.4062   37.5155   16.0783
    0.5000    0.5250    0.9600   45.6875   39.0175   15.2951
    0.5000    0.5500    0.9600   44.8436   40.7054   14.4510
    0.5000    0.5750    0.9600   43.8488   42.6102   13.5410
    0.5000    0.6000    0.9600   42.6711   44.7683   12.5606

As the table shows, investors with greater tolerance for risk will invest a greater proportion of their portfolios in the good pure security. Recall that it has a larger expected return but greater underperformance in bad times. Thus investors whose utility decreases at a slower rate (higher k) with decreases in wealth are more willing to take the risk of doing badly in bad times. Note that such investors also devote a slightly smaller portion of wealth to present consumption, and hence a larger portion of wealth to investment, since future prospects are somewhat more attractive to them than to those who are more concerned with the risk such investments entail.

The next table provides the same type of analysis for a group of investors who differ in time-preference but are, in other respects, like our original investor.

     prg         k         d    consumed    good       bad
    0.5000    0.3750    0.9000   51.3375   30.3861   18.2765
    0.5000    0.3750    0.9100   50.8964   30.6614   18.4422
    0.5000    0.3750    0.9200   50.4588   30.9350   18.6062
    0.5000    0.3750    0.9300   50.0265   31.2052   18.7684
    0.5000    0.3750    0.9400   49.5981   31.4720   18.9299
    0.5000    0.3750    0.9500   49.1757   31.7361   19.0883
    0.5000    0.3750    0.9600   48.7561   31.9981   19.2458
    0.5000    0.3750    0.9700   48.3429   32.2557   19.4014
    0.5000    0.3750    0.9800   47.9336   32.5117   19.5547
    0.5000    0.3750    0.9900   47.5279   32.7655   19.7066

As the table shows, investors with greater preference for future consumption will consume less and invest more. While the absolute values of the claims for consumption in the good and bad states of the world are affected, their relative values are not. Investors with this type of utility function will change only their savings rate when their time-preference changes. The composition of their portfolios will not be affected.

The final table completes the analysis by showing a group of investors with different assessments of the probabilities associated with the alternative future states of the world, but who are like our investor in other respects.

     prg         k         d    consumed    good       bad
    0.4000    0.3750    0.9600   50.3109   23.1037   26.5854
    0.4200    0.3750    0.9600   50.0734   24.8632   25.0634
    0.4400    0.3750    0.9600   49.7994   26.6357   23.5648
    0.4600    0.3750    0.9600   49.4864   28.4204   22.0932
    0.4800    0.3750    0.9600   49.1391   30.2092   20.6517
    0.5000    0.3750    0.9600   48.7561   31.9981   19.2458
    0.5200    0.3750    0.9600   48.3435   33.7809   17.8756
    0.5400    0.3750    0.9600   47.8998   35.5540   16.5462
    0.5600    0.3750    0.9600   47.4280   37.3134   15.2586
    0.5800    0.3750    0.9600   46.9306   39.0545   14.0150
    0.6000    0.3750    0.9600   46.4086   40.7727   12.8187

Note the dramatic effects of differences in predictions. Optimists, who assign a higher probability to good weather, will invest considerably larger portions of their portfolios in good weather apples (securities with higher expected returns and possibilities for greater underperformance). They invest more of their wealth as well. Differences in opinions really do make horse races (as has been said).

Representative Investors

Recall that an Investor who assigned a probability of 0.50 to good weather, and had a utility function with k=0.375 and d = 0.96 and wealth of 100 would choose a consumption plan (in units) of [48.76  112.27 28.94].  Now, assume that in the aggregate social product, the proportions of the three types of consumption are precisely the same.  If so, our candidate can be considered a representative Investor.   Why so? Because a society with aggregate consumption of [48.76*z  112.27*z 28.94*z] (where z is a positive constant) and prices [1.00 0.285 0.665] could be populated entirely by a set of identical investors, each of whom had this specific utility function.   The existence of such preferences and predictions on the part of every investor would be consistent with the attributes of equilibrium that would be observed in such a society.  Since preferences and predictions cannot generally be observed by the outside analyst (financial or other), it is helpful to determine at least some possible attributes for such elements from observed magnitudes.

By construction, a representative investor will find it optimal to (1) save at the societal savings rate, and (2) hold the market portfolio. Hence, any investor who assigns the same probabilities to states of the world , has the same risk tolerance, the same impatience and (in the general case) the same wealth as a representative investor should also save at the societal savings rate and hold the market portfolio. The concept of a representative investor thus provides a useful benchmark against which one can compare oneself. Other things equal, if an Investor makes different probability assessments from the representative investor, it will be optimal to "tilt" holdings towards securities that pay more in states that the Investor feels are more likely than does the representative Investor. Other things equal, if an Investor has greater (less) tolerance for risk than the representative Investor, he or she should hold a portfolio with a higher (lower) expected return than the market portfolio. Other things equal, if an investor is more (less) patient, he or she should save more (less) than is typical in the society.

This type of comparison is complicated by the fact that the representative Investor may not be unique. For example, the world we have described could instead be populated by some other set of representative investors. In one sense, this does not matter. Any one of the possible set of representative investors can be used as a benchmark with which one can compare oneself. However, most analyses of optimal consumption and investment decisions go farther, as we will see.

Market Efficiency

We say that a securities market is efficient relative to a given set of information if the prices of securities are the same as they would be if all participants had that information and processed it appropriately.  Note that this definition does not require the holdings to be the same as they would be if all the participants had the information and processed it appropriately.  Consider the situation in which Investor A is overly optimistic about the prospects for a firm., while Investor B is overly pessimistic.  Under these conditions, the price of the firm's stock might be precisely the same as it would be if A and B had each made informed predictions.  If so, we would say that the market was efficient because the average of Investor's opinions was, in a rather broad sense, correct.  Note, however, that under the posited conditions, Investor A would hold "too much" of the security, and investor B "too little", relative to the amounts they would hold (and should have held) had they obtained the same information and processed it appropriately.

Key to the notion of market efficiency is that of what we will call fully-informed probabilities. Such probabilities would be assessed by a sophisticated Analyst with access to a defined set of information. In effect, such probabilities "take the information into account" in an efficient manner.

Using this construct, we can say that a market is efficient relative to a given set of information if security prices are the same as they would be if every Investor utilized fully-informed probabilities. Under these conditions, it makes sense to concentrate on a representative Investor who uses fully-informed probabilities. The risk tolerance of such an Investor is likely to be roughly (or exactly) equal to a wealth-weighted average of the risk tolerances of the Investors in the society (the latter is sometimes termed the societal risk tolerance). Similarly, the impatience of this representative Investor is likely to be roughly (or exactly) equal to a wealth-weighted average of the degrees of impatience of the consumer/investors in the society (sometimes termed the societal degree of impatience).

Betting and Tailoring

There are three possible reasons why Investors X and Y may wish to hold different portfolios. Two relate to preferences and one to predictions.

First, Investors' attitudes toward risk and return may differ. An outside expert cannot argue that such differences (if fully informed) are "wrong", any more than an outside expert can tell a consumer whether he or she should prefer beer to wine. If Investors understand the characteristics of alternative investment vehicles and agree on their prospects and probabilities, differences in holdings can be said to be utility-based or consistent with market efficiency. Adjusting portfolio holdings (and/or consumption/investment decisions) to suit differences in utility can be considered tailoring.

The second reason for differences in holdings is associated with differences in levels of wealth. Wealthier individuals generally invest a greater absolute amount of money. Some may invest a greater percentage of their wealth, others a smaller percentage, and yet others the same percentage. Some wealthier individuals choose investment portfolios that are riskier, others portfolios with the same risk, and yet others portfolios with less risk. Differences in holdings that arise due to differences in Investor wealth are, like differences due to underlying preferences, consistent with efficient markets. Implementing strategies designed to accommodate such differences can thus also be considered tailoring.

The third reason is different. Investors (or their financial advisors) may disagree about the probabilities of alternative future states of the world. (Here we assume that all agree about the possible states of the world and the payments associated with various securities in each of the states; in this setting, the only disagreements about the future relate to the probabilities associated with alternative states.) Such disagreements can arise when investors utilize disparate sets of information and/or process a given set of information differently (although at a more profound level, the latter can be considered a variant of the former).

Despite this, the wealth-weighted average probabilities assessed by investors may be equivalent to fully-informed probabilities, since the probabilities assessed by those with greater amounts invested (and hence greater incentive to gather information and process it well) are weighted more heavily in computing the averages. This notion underlies the often-made assumption that consensus probabilities are equal to fully-informed probabilities.

Loosely speaking, we can term an investor's probability assessments to be deviant if they differ from those of the consensus of investors. If security prices do not reflect efficient-market probabilities, at least some investors whose holdings are based on deviant predictions may profit from such differences. On the other hand, if markets are efficient, differences in holdings based on deviant predictions will generally prove undesirable in the long run, leading only to added transactions costs and lack of appropriate diversification. In either event, adjusting portfolio holdings (and/or the consumption/investment decision) to suit differences from consensus estimates of the likelihoods of alternative scenarios can be considered prediction-based, and inconsistent with market efficiency. In the vernacular, such choices can simply be termed betting.

Active and Passive Management

Those who concentrate on tailoring holdings to suit an investor's preferences and/or circumstances generally employ investment approaches that the investment industry classifies under the heading passive management.  Those who bet on differences in predictions generally employ approaches classified under the heading active management.  Tailoring decisions tend to be designed to implement a strategy that requires only small changes over time.  Such decisions typically involve small and relatively infrequent changes, and hence can be considered  "passive".  

Bets, however, are likely to change rather dramatically, as new information is revealed and investors react differently to such information. Investors making decisions based on differential predictions are likely to generate a significant number of trades, and are thus appropriately termed "active".