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Chapter 37 Portfolio management and measurement.

WHAT IS IT?

Previous chapters presented tools and techniques to evaluate specific types of investments such as common stocks, corporate bonds, and government bonds. Next up is the overall investment planning process. This process begins with analyzing an investor's objectives and constraints and ends with evaluating the results of investment decisions. This chapter shows how to develop an investment policy statement to guide the investment process. It also presents return measures useful for evaluating portfolio performance and choosing appropriate asset allocations (the proportion of different asset classes in an investor's portfolio). The final section demonstrates the importance of allocating assets appropriately to meet a client's objectives and constraints. The next chapter presents more advanced topics in asset allocation using modern portfolio theory.

THE INVESTMENT PROCESS

Planning for investments is related to the overall financial planning process. The general steps in the financial planning process are adapted here for the investment planning process:

1. Establishing client-advisor relationships.

2. Gathering client data and determining objectives and expectations.

3. Analyzing the client's financial status, current investments, and special needs.

4. Developing and presenting the Investment Policy Statement.

5. Implementing the investment policy.

6. Monitoring the portfolio.

Note that the first four steps in the process involve gaining an understanding of the client and developing an appropriate investment policy to assist the client in meeting his objectives. The actual decision as to what investments to purchase comes much later. A planner must know the client before implementing an investment strategy.

Client Lifecycle Analysis

While each client is unique, there are common themes that impact the creation of an investment policy. One of these themes is that people's needs and resources change over time, and an investment policy must first identify these needs and then reflect these changes.

For example, consider Mary. A 25-year old beginning her career, she has no savings and barely earns enough to pay the bills. At this stage, she is probably mostly concerned with setting aside an emergency fund and reducing risks such as the possibility of disability.

When Mary is 35, she is married with children, and earning more. Her husband also works, and they have more disposable income. They can afford to save some of this income for their future needs, which are college for the children and their own retirement.

At 65, Mary and her husband retire and their earned income levels decline dramatically. At this point, they rely on their investments, including retirement plans, to maintain their newfound leisure. Eventually, they will probably want any of their wealth that remains at the time of their death to be passed to their children or charities.

This scenario is familiar to everyone, and is often called the investor life cycle. The investor life cycle is considered to run through three phases: (1)

1. Accumulation phase

2. Consolidation phase

3. Spending phase

During the accumulation phase, the client is accumulating assets: saving and investing for the future. As this is the earliest stage during which investing will occur, there is typically a long time horizon. Clients in this phase are often able to accept more risk since they have time to accumulate wealth. They may therefore prefer a higher risk and return policy, although they have a low level of net worth to be invested. In other cases, clients in the accumulation phase may have more pressing needs. If the client is saving to purchase a home or to build an emergency fund, their time horizon is shorter and risk tolerance may be low despite their long life expectancy.

The consolidation phase occurs when the client's income outpaces expenses and wealth accumulates more rapidly. The client has greater wealth to invest and still has a relatively long time horizon. However, the time horizon shortens over this period to arrive at the spending phase. During this phase, the client typically can tolerate moderate to higher risk in order to achieve higher returns.

The spending phase is when earned income (such as wages) ends and investment income is needed from accumulated retirement and non-retirement funds to meet living expenses. The client typically has a desire for lower risk and higher investment income during this period. Since life expectancies can be long, the time horizon is shorter, but not necessarily short, during this phase.

Client Risk Tolerance

A client's willingness to accept investment risk is a function of a number of factors. While most individuals have some degree of risk aversion, some individuals are more tolerant of risk than others. This can be a function of their willingness to undertake risk (for example, based on past experiences) or their ability to take risk (for example, alternative sources of income and/or wealth such as a potential inheritance). A client's time horizon is also relevant. Generally, the longer the investment time horizon, the greater the ability to incur risk.

A useful framework for considering risk tolerance is the economic concept of utility. Utility is the satisfaction that an individual gets from consuming goods and services and, in terms of wealth, the satisfaction conferred by a given level of wealth. Consider Figure 37.1, which shows one possible relationship between wealth and utility. This utility function indicates that as investor wealth increases, the investor's utility increases. Further, there is a linear relationship so that starting at any point such as A, an increase in wealth of $X will increase utility by the same amount as a decrease in wealth of $X will decrease utility. An investor with such a utility function is said to be risk-neutral; neither avoiding nor seeking risk.

[FIGURE 37.1 OMITTED]

Another possible utility function is presented in Figure 37.2. This function shows a convex utility curve, where utility increases at a faster rate as wealth increases. An investor with wealth at point B would be risk seeking, since he would gain more utility for an $X increase in wealth than he would lose utility for an $X decrease in wealth.

[FIGURE 37.2 OMITTED]

Lastly, Figure 37.3 shows a concave utility function, where utility increases at a slower rate as wealth increases. An investor with wealth at point C will be risk-averse, because as wealth decreases by $X the investor's utility decreases by more than it increases when wealth increases by $X.

[FIGURE 37.3 OMITTED]

For most goods and services, economists assume diminishing marginal utility--the more a person has of a good, the less satisfaction he gets from each additional unit. If investors have diminishing marginal utility for wealth, they would exhibit the risk-averse utility function presented in Figure 37.3.

One problem with utility is that it cannot be measured, so it is not easy to assess an individual's risk preferences. Additionally, research on the behavior of individuals indicates that these utility functions do not capture the subtlety of human utility functions. In their well-known work on Prospect Theory, Kahneman and Tversky found that investors do not exhibit the same behavior for gains and losses. Kahneman and Tversky performed experiments where individuals were faced with choices such as:
   Choice A: Participate in a gamble where there
   is a 50% chance of winning $1,000 and a 50%
   chance of winning nothing.

   Choice B: Receive $450 with certainty.


They found that individuals exhibit risk aversion behavior when faced with choices involving a sure gain (they tended to take Choice B), but when faced with choices involving a sure loss or a possibility of a loss they exhibit risk seeking behavior. They conclude that individuals' utility functions appear to be concave for gains and convex for losses.

While investor's risk tolerance cannot be measured precisely, questionnaires have been developed which provide a good starting point to understanding a client's risk tolerance relative to other investors. Professor William Droms has been a leader in developing risk tolerance questionnaires with his Global Portfolio Allocation Scoring System (PASS), which is designed to categorize investors into risk tolerance categories. Recently Droms and Stauss presented a modified version of his scoring system that considers the interaction of risk tolerance and time horizon. Figure 37.4 presents the questionnaire proposed by Droms and Strauss. The minimum score on this questionnaire is 6 and the maximum 30. Clients with a higher score and longer time horizon will have a higher tolerance for and ability to take risk.

Droms and Stauss stress that the risk tolerance questionnaire is only a starting point in understanding the client in order to develop an appropriate investment policy statement.

THE INVESTMENT POLICY STATEMENT

A client's Investment Policy Statement should be developed in accordance with the client's objectives and constraints. Objectives include the desired return and level of risk that the client is willing and able to take. Constraints are limitations that must be considered in the investment process, such as liquidity, time horizon, taxes, and legal or regulatory restrictions. Lastly, constraints can include unique client circumstances and other self-imposed client preferences.

Determining the objectives for risk and return must be done simultaneously due to their interrelatedness. Generally, the higher the risk, the higher the return investors require. A starting point is to determine the return necessary to meet the investor's objectives. For example, if the investor wants to accumulate $1,000,000 over the next 20 years and can deposit $20,000 at the end of each year, an 8.8% return is necessary (see Chapter 32, "Time-Value Concepts").

The next issue is whether that return can be achieved at a risk level appropriate for the investor. Risk is often measured as the standard deviation of returns (a measure of total risk). However, individual investors may perceive potential losses to be more important than potential gains. Standard deviation includes both upside and downside deviations.

Consider the historical return data for 1976 through 2005 provided in Figure 37.5. The data exhibit the expected positive relationship of risk and returns. The funds with the highest return had the highest risk measured based on both standard deviation and proportion of years with a loss. Treasury bills represent a risk-free rate of return. The consumer price index represents a level of inflation.

The investor's desired rate of return should be obtainable and consistent with risk tolerance. Financial advisers often present long term historic risk and return data, such as that from www.ibbotson.com or www.globalfinanciadata.com, to clients to demonstrate potential returns and risk. Historic returns do not necessarily predict future returns, but they do provide guidance as to what is possible. If an investor desires a long-term compound return of 15% with a standard deviation of 5% and no negative returns, this is not likely achievable given the historical data. The return exceeds that exhibited by any of the asset classes in the past and the risk is certainly much lower than could likely be achieved for that level of return.

Historical index returns are not achievable since they do not include fees and expenses. Use of index fund return data does consider some fees and expenses. Care must also be taken when using nominal historic returns. Some historical periods had high returns, but high inflation. If current or expected inflation differ at the time the investment policy is being developed, consideration should be given to using real (inflation-adjusted) returns.

The ability to achieve a desired return is also a function of certain constraints. The liquidity constraint is the client's desire to maintain a certain level of liquid assets (such as cash). The time horizon constraint relates to the timing of expected withdrawals. A long time horizon generally allows the investor to accept more risk. If the investor has particular needs (or desires) for cash at particular dates (such as for a second home purchase), this must be factored into the investment policy. Since taxes can have a significant impact on net investment returns, any tax constraints should be considered. If the account is tax-deferred, there is more investment flexibility (except that municipal bonds would not be appropriate). If the account is taxable, tax favored investment returns such as long-term gains and dividends should be considered. Any legal or regulatory constraints should be examined. For example, if the client has a trust, the trust document must be examined. Further, the need to adhere to state law "prudent man/prudent investor" provisions must be considered. Some clients have unique circumstances or preferences that can lead to constraints on the investment policy. For example, the investor may wish to avoid tobacco or military-industrial stocks or may prefer mutual funds to individual securities.

Once the client's objectives and constraints are determined, they should be put in writing as an Investment Policy Statement to guide asset allocation and security selection for the client's accounts.

Return Measures for Portfolio Evaluation

Previous chapters have shown a variety of return measures such as holding-period returns and internal rates of return. Which of these is appropriate when evaluating portfolio performance? Further, should the performance be compared to the risk-free rate or some other benchmark such as a market index?

Let's look at a hypothetical example. Assume an investor deposits $100,000 in a professionally managed account. One year later, the account has grown in value to $120,000 and the investor withdraws $30,000 (remaining value $90,000). At the end of the second year, the account value is $99,000. No other additions or withdrawals were made. During the same two years, the risk-free rate remained constant at 6% and a relevant benchmark earned 18% the first year and 12% the second.

The investor's return could be measured as the holding-period return over the two years:

[R.sub.H] = [MV.sub.E] - [MV.sub.0] + D/[MV.sub.0]

Where [R.sub.H] is the holding-period return

[MV.sub.E] is the market value of the account at the end

[MV.sub.0] is the market value at the beginning and

D is the net distributions during the time period (contributions minus withdrawals)

For this investor the holding-period return is:

RH = [MV.sub.E] - [MV.sub.0] + D/[MV.sub.0] = 99,000 - 100,000 + 30,000/100,000

= 0.29 or 29%

This return measure informs the investor that they have earned 29% over the holding period, but since the holding period is two years, it is not that useful in comparing to benchmarks or prior periods. Return measures are usually expressed on an annual basis.

The holding-period return could be computed for each year individually. The holding period return for year one is:

[R.sub.H] = [MV.sub.E] - [MV.sub.0] + D/[MV.sub.0] = 90,000 - 100,000 + 30,000/100,000

= 0.20 or 20%

The holding-period return in year two is:

[R.sub.H] = [MV.sub.E] - [MV.sub.0] + D/[MV.sub.0] = 99,000 - 90,000/90,000

= 0.10 or 10%

So the investor earned 20% in the first year and 10% in the second. These annual returns can be compared to the benchmark since there were no withdrawals or deposits during the year, only at the beginning or end of the year. Year one returns of 20% beat the benchmark by 2% and returns in year two trailed the benchmark by the same 2%. Note that, had there been interim withdrawals or deposits, holding-period returns for sub-periods would need to be calculated.

Having beaten the index one year and trailed it the next by a similar amount, how should the manager's performance be evaluated? The simple average of the holding period returns is 15% for both the manager and the benchmark. However, the simple average does not adequately capture the performance during the two-year period.

To measure the geometric average performance of the account over the period, the internal rate of return for the portfolio can be computed over the two-year time period. Using a financial calculator with the following inputs:
Cash Flow Time Zero          (100,000)
Cash Flow Time One                       30,000
Cash Flow Time Two (Value)    99,000


Solving for the internal rate of return yields 15.62%. (See Chapter 33, "Measuring Investment Risk.") The internal rate of return is also known as a dollar-weighted return. The investor earned more than the simple average of 15% in this instance due to the timing of the withdrawal. By withdrawing funds after the 20% return and before the lower 10% return, the investor earned a higher average return. Note, however, that since the dollar-weighted return is an internal rate of return, it implicitly assumes that cash flows are re-invested at the same rate.

While the dollar-weighted return may measure the return to the investor, it does not measure the performance of the portfolio manager. The decision to withdraw funds was made by the investor and should not be included in the manager's evaluation.

Instead, a time-weighted return is used. The time-weighted return is measured as:

[R.sub.p] = [[(1 + [R.sub.1])(1 + [R.sub.2])(1 + [R.sub.3]) ... (1 + [R.sub.N])].sup.1/N] - 1

It measures the geometric return, excluding the impact of contributions and withdrawals, over the period. As such, it is an appropriate measure of the portfolio manager's performance. For this example, the time-weighted return would be:

[R.sub.p] = [[(1 + [R.sub.1])(1 + [R.sub.2])(1 + [R.sub.3]) ... (1 + [R.sub.N])].sup.1/N] - 1

= [(1.20)(1.10)]1/2 - 1 = 14.89%

In this case, the portfolio manager's performance was an average annual return of 14.89% over the two years. This is slightly less than the simple average and quite a bit less than the dollar-weighted average that included the impact of the investor's withdrawal. It can also be compared to the benchmark index by calculating the time-weighted benchmark return of [(1.18)(1.12)]1/21=14.96. Doing so, it is discovered that although the magnitudes of the outperformance in year 1 and underperformance in year 2 were equal, the manager's annual returns over the entire period fell slightly behind those of the benchmark. Fortunately, the difference turned out to be minimal.

Risk-Adjusted Performance Measures

The return earned is only one component of portfolio performance. Another important component is the amount of risk taken to achieve the return. Portfolio performance can and should (assuming risk-averse investors) be evaluated on a risk-adjusted basis. In risk-adjusted measures, return is compared to the portfolio's riskiness. Ahigh return relative to risk is desirable. In this section, four types of risk-adjusted returns are examined: the Sharpe ratio, the Treynor ratio, the information ratio, and Jensen's alpha.

The Sharpe ratio measures the excess return of a portfolio relative to risk and is computed as:

Sharpe Ratio = [R.sub.p] - [R.sub.f]/[O.sub.p]

The numerator represents a portfolio's excess return over the risk-free rate. The denominator measures the portfolio's risk as the standard deviation of portfolio returns (total risk).2 If the Sharpe Ratio is negative, the portfolio's return was lower than the risk-free rate. The higher the Sharpe Ratio, the better the performance.

For this example, the following is used: a risk-free rate of 6%, the portfolio's time-weighted return of 14.89% annually and standard deviation of 7.07%, and the benchmark return and standard deviation of 14.96% and 4.24%, respectively. (3) Plugging in these numbers gives the portfolio a Sharpe ratio of 1.26 [(14.89 - 6.00) / 7.07]. By comparison, the benchmark index has a Sharpe ratio of 2.11 [(14.96 - 6.00) / 4.24]. The benchmark's much higher Sharpe ratio indicates that it was much less risky than the portfolio given their similar returns. (4)

The Treynor ratio also measures the excess return relative to risk but measures risk as Beta:

Treynor Ratio = [R.sub.p] - [R.sub.f]/[[beta].sub.p]

As with the Sharpe ratio, a positive number indicates greater returns than the risk-free rate and a higher ratio is preferred. If it is assumed the portfolio had a Beta of 1.2, a Treynor ratio is derived of 7.41 [(14.89 - 6.00) / 1.2]. Typically, the portfolio Beta is measured against the benchmark, so the benchmark should have a Beta of 1.0 and a resulting Treynor ratio of 8.96 [(14.96 - 6.00) / 1.00]. This measure also shows the manager produced worse risk-adjusted returns than the benchmark. Note, however, that if the Beta of a portfolio differs significantly from that of the benchmark it could signal that the chosen benchmark is inappropriate because it does not reflect the manager's style (or that the manager is inappropriate because he doesn't follow the investment guidelines).

Using the risk-free rate as the hurdle rate for determining the excess return may not be a high enough hurdle for some. An alternative is to calculate an information ratio, which measures excess return relative to the benchmark portfolio:

Information Ratio = [R.sub.p] - [R.sub.B]/[[sigma].sub.Excess]

The risk measure is the standard deviation of the excess return. For this portfolio, excess return is -0.07% [14.89 - 14.96]. The standard deviation of excess return is 2.83%, yielding an information ratio of -0.02. The negative information ratio is another sign that this manager has not performed well.

Jensen's alpha is another risk-adjusted performance measure. However, it is measured quite differently:

[alpha] = [R.sub.p] - [[R.sub.f] + [[beta].sub.p] ([R.sub.m] - [R.sub.f])]

Alpha is measured as the portfolio's return in excess of that predicted by the capital asset pricing model (see Chapter 36, "Asset Pricing Models"). An alpha of zero indicates that the portfolio earned its expected rate of return given its risk (measured as Beta). A positive alpha indicates that the portfolio manager has added value. Given this example, alpha equals -1.86 [14.89 - {6.00 + 1.2 x (14.96 - 6.00)}]. The negative alpha indicates this portfolio manager has not performed as well as predicted by the capital asset pricing model.

Note that for risk-adjusted measures using Beta, a diversified portfolio is assumed. Standard deviation measures total risk and does not assume a diversified portfolio. The Sharpe and Treynor ratios will provide similar rankings for well diversified portfolios.

Selecting an Appropriate Benchmark

It has been described how to measure portfolio results compared to a benchmark. An equally important consideration is which benchmark to use. The most frequently cited benchmark is the S&P 500 index, but this may not be appropriate for every investor as it consists only of large-cap U.S. stocks, which may not be similar to the investor's portfolio.

Appropriate benchmark selection should follow naturally from the investment planning process. Once the client's preferences, constraints, risk tolerance, and return requirements are established and a mix of assets is selected to accomplish these goals, a benchmark should be chosen that reflects the same goals. For example, if the client's asset allocation is 50% large-cap stocks and 50% intermediate-term bonds, the benchmark should have a similar construction. A single benchmark that contains the same proportions of each asset would be acceptable, as would a combination of two separate single-asset class benchmarks. In some cases, the choice may depend on whether the investor has chosen separate equity and fixed income managers or whether a single investment manager is responsible for the entire account. Complex allocations may even require construction of a custom benchmark.

While the terms "benchmark" and "index" are often substituted for each other, an appropriate benchmark could be a published index, a custom composite of assets or indexes, or a peer group of similar funds or managers. Regardless of which type of benchmark is chosen, the CFA Institute and other global investment bodies generally agree that it should meet the following criteria:

1. Representative of the asset class or mandate--An investor in small-cap stocks should not choose a manager who invests in S&P 500 names, nor should they compare their small-cap manager to that index.

2. The benchmark should be investible--This means that the investor should be able to invest in the benchmark as an alternative to hiring an active manager. There is no sense in comparing performance to a benchmark that could not be reasonably matched (such as a market-weighted portfolio of all the real estate in the world.)

3. Should be constructed in a disciplined and objective manner - Some managers believe the benchmark should be easy to beat so their performance looks better. The investor may prefer a tougher standard. The benchmark should have neither bias.

4. Formulated from publicly available information.

5. Acceptable by the manager as the neutral position--The manager should be comfortable with comparisons to the benchmark.

6. Consistent with the investor's status regarding taxes, time horizon, etc.

In short, the benchmark should reflect both the client's needs and the manager's style. Otherwise, either the manager or the benchmark was not selected well.

Risk-Adjusted Measures and Investment Policy

Risk-adjusted measures can be useful in setting investment policy for a client and in explaining the importance of asset allocation to the client. Based on the historical data presented earlier, the return versus risk data provided in Figure 37.6 can be computed. Sharpe ratios were computed using average returns relative to Treasury bills and the standard deviation of returns for the asset class. Notice that although large stocks have a high level of risk, they have the highest risk-adjusted return. Government bonds have the next highest risk-adjusted return.

To demonstrate the importance of diversification among asset classes, five portfolios are formed as presented in Figure 37.7 and the same measures computed. The equity portion of the portfolio consists of large stocks.

The fixed income portion of the portfolio consists of equal weights of government bonds and Treasury bills. By creating portfolios with asset classes that are not perfectly correlated, the overall risk has been reduced and the risk-adjusted returns are higher than could be obtained with any single asset class.

This example is based on a simple portfolio formation that did not consider the correlations of the asset classes or the appropriateness of the individual asset classes. The next chapter examines asset allocation and portfolio construction using advanced techniques including Modern Portfolio Theory and Monte Carlo simulation.

WHERE CAN I FIND OUT MORE ABOUT IT?

1. AIMR Benchmarks and Performance Attribution Subcommittee Report (Charlottesville, VA: CFA Institute, August 1998), www.cfainstitute.org.

2. John L. Maginn and Donald L. Tuttle, Managing Investment Portfolios: A Dynamic Process, 2nd Edition (Charlottesville, VA: CFA Institute, 1990).

3. William G. Droms and Steven N. Stauss, "Assessing Risk Tolerance for Asset Allocation," Journal of Financial Planning, March 2003.

4. Daniel Kahneman and Amos Tversky, "Prospect Theory: An Analysis of Decision Under Risk," Econometrica, March 1997, Vol. 47, No. 2.

QUESTIONS AND ANSWERS

Question--Would an investor be likely to prefer a manager who generates an alpha of 2.0% and has a portfolio Beta of 1.0 or one who generates an alpha of 1.0% and has a portfolio Beta of 2.0?

Answer--The risk-averse investor should prefer the manager who generates higher alpha, as that manager is earning returns in excess of those expected given the level of risk taken on. However, it would be desirable to have additional information about the level of returns and the composition of the portfolio.

Question--Jose's small-cap investment manager has produced returns that lag the benchmark S&P 500 index. What should Jose do?

Answer--The S&P 500 index is an inappropriate benchmark for a small-cap portfolio. Jose must first decide whether he wants to invest in small cap stocks or large cap stocks. In the case of the former, he should compare his manager to a different index, such as the Russell 2000. In the latter case, he should hire a manager who follows a large cap strategy.

Question--A consultant wants to evaluate the performance of a large-cap investment manager and has collected the risk and return information below. Calculate and evaluate the manager's Sharpe Ratio, Treynor Ratio, Information Ratio, and Alpha.
Manager's 10-year annualized return     11.7%

S&P 500 10-year annualized return        9.0%

Risk-free rate                           5.0%

Manger's 10-year standard deviation     21.3%
of returns

S&P 500 10-year standard deviation      16.2%
of returns

Manger's Beta (relative to S&P 500)     1.2

Standard deviation of manager's         2.0%
excess returns


Answer--The ratios are calculated as follows:

Sharpe Ratio = (11.7 - 5.0) / 21.3 = 0.31

Treynor Ratio = (11.7 - 5.0) / 1.2 = 5.6

Information Ratio = (11.7 - 9.0) / 2.0 = 1.35

Alpha = 11.7 - (5.0 + 1.2 x [9.0 - 5.0]) = 1.9%

The Sharpe and Treynor Ratios can only be evaluated with respect to those earned by other managers.

The Information Ratio is positive, which indicates that the manager outperformed the benchmark. It is also greater than one, which suggests the additional risk taken was less than the incremental return generated.

The 1.9% Alpha shows that the manager beat the benchmark performance, relative to the additional risk the manager took, by 1.9% annually. This is a good performance.

CHAPTER ENDNOTES

(1.) More than three phases are possible. In Maginn and Tuttle (see "Where Can I Find Out More About It?" above), a gifting phase is included. A pre-accumulation phase when income is less than or equal to expenses can also be imagined. We focus on what we consider to be the three main phases for purposes of investment policy.

(2.) The denominator can also be measured as the standard deviation of the excess return rather than the standard deviation of the portfolio return.

(3.) Obviously, the two years of data are insufficient to generate statistically meaningful measures for return and standard deviation, but it is assumed that the two years were typical of those generated over a longer period for purposes of this illustration.

(4.) There is no standard level of Sharpe or Treynor ratios that are good versus bad. The level of the ratio is dependent upon the time period and data source used. They should be evaluated relative to similar ratios computed for the same time period and in a similar manner.
Figure 37.4

                                     Strongly
                                       Agree       Agree      Neutral

Earning a high long-term total
return that will allow my capital        5           4           3
to grow faster than the inflation
rate is one of my most important
objectives.

I would like an investment that
provides me with an opportunity          5           4           3
to defer taxation of capital
gains to future years.

I do not require a high level of         5           4           3
current income from my
investments.

I am willing to tolerate some
sharp down swings in the return          5           4           3
on my investments in order to
seek a potentially higher return
than would normally be expected
from more stable investments.

I am willing to risk a short term        5           4           3
loss in return for a potentially
higher long-term rate of return.

I am financially able to accept a        5           4           3
low level of liquidity in my
investment portfolio.

Over what period of time to you       Short-      Inter-       Long-
expect to remain invested in this     term (3     mediate      term
portfolio?                             years      term (4     (over 7
                                     or less)      to 7       years)
                                                  years)

                                                 Strongly
                                      Disgree     Disgree

Earning a high long-term total
return that will allow my capital        2           1
to grow faster than the inflation
rate is one of my most important
objectives.

I would like an investment that
provides me with an opportunity          2           1
to defer taxation of capital
gains to future years.

I do not require a high level of         2           1
current income from my
investments.

I am willing to tolerate some
sharp down swings in the return          2           1
on my investments in order to
seek a potentially higher return
than would normally be expected
from more stable investments.

I am willing to risk a short term        2           1
loss in return for a potentially
higher long-term rate of return.

I am financially able to accept a        2           1
low level of liquidity in my
investment portfolio.

Over what period of time to you
expect to remain invested in this
portfolio?

Global Portfolio Allocation Scoring System (PASS) chart used
with permission of Dr. William G. Droms, CFA.

Figure 37.5

Asset Class                    Average      Standard     Proportion
                                Return     Deviation      of years
                                                        with a loss

Large Stocks (S&P 500)          13.84%       15.40%        20.00%
Government Bonds (10 year)      9.56%        11.62%        16.67%
Treasury Bills (3 month)        6.22%        3.15%         0.00%
Consumer Price Index            4.35%        2.29%         0.00%

Source: Based on data obtained from Global Financial Data, Los
Angeles, CA www.globalfindata.com.

Figure 37.6

Asset Class                    Average       Sharpe      Proportion
                                Return       Ratio        of years
                                                        with a loss

Large Stocks (S&P 500)         13.84%         0.49         20.00%
Government Bonds (10 year)      9.56%         0.29         16.67%
Treasury Bills (3 month)        6.22%         0.00          0.00%
Consumer Price Index            4.35%        -0.63          0.00%

Figure 37.7

Asset Class          Average     Sharpe      Proportion
                     Return       Ratio       of years
                                            with a loss

90% Equity
10% Fixed Income     13.24%       0.50         20.00%

75% Equity
25% Fixed Income     12.35%       0.51         20.00%

50% Equity
50% Fixed Income     10.86%       0.51         13.33%

25% Equity
75% Fixed Income      9.38%       0.46          3.33%

10% Equity
90% Fixed Income      8.48%       0.36          3.33%
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Title Annotation:Techniques of Investment Planning
Publication:Tools & Techniques of Investment Planning, 2nd ed.
Date:Jan 1, 2006
Words:5554
Previous Article:Chapter 36 Asset pricing models.
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