CFA 2018 exam level 3 level 3 wiley study guide vol 3

Reading 13: Managing Institutional Investor Portfolios 103Non-Life Insurance Companies Property and Casualty Wiley Study Guide for 2018 Level III CFA Exam Volume 3: Economic Analysis, As

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Wiley Study Guide for 2018 Level III CFA Exam

Volume 1: Ethical and Professional Standards & Behavioral Finance

Study Session 1: Code of Ethics and Standards of Professional Conduct

Lesson 7: Standard VII: Responsibilities as a CFA Institute Member or CFA Candidate 107

Study Session 2: Ethical and Professional Standards in Practice

Lesson 1: Ethical and Professional Standards in Practice, Part 1: The Consultant 119

Lesson 2: Ethical and Professional Standards in Practice, Part 2: Pearl Investment

Study Session 3: Behavioral Finance

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Reading 7: Behavioral Finance and Investment Processes 165

Wiley Study Guide for 2018 Level III CFA Exam Volume 2: Private Wealth Management & Institutional Investors Study Session 4: Private Wealth Management (1)

Study Session 5: Private Wealth Management (2)

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Reading 13: Managing Institutional Investor Portfolios 103

Non-Life Insurance Companies (Property and Casualty)

Wiley Study Guide for 2018 Level III CFA Exam

Volume 3: Economic Analysis, Asset Allocation, Equity & Fixed Income Portfolio Management

Study Session 7: Applications of Economic Analysis to Portfolio Management

Lesson 2: Tools for Formulating Capital Market Expectations, Part 1: Formal Tools 8

Lesson 3: Tools for Formulating Capital Market Expectations, Part 2: Survey and

Lesson 5: Economic Analysis, Part 2: Economic Growth Trends, Exogenous Shocks, and

Lesson 7: Economic Analysis, Part 4: Asset Class Returns and Foreign Exchange Forecasting 33

Lesson 1: Estimating a Justified P/E Ratio and Top-Down and Bottom-Up Forecasting 39

Study Session 8: Asset Allocation and Related Decisions in Portfolio Management (1)

Lesson 5: Goal-Based Asset Allocation, Heuristics, Other Approaches to Asset Allocation,

Study Session 9: Asset Allocation and Related Decisions in Portfolio Management (2)

Lesson 3: Altering or Deviating from the Policy Portfolio 85

Lesson 1: Distinguishing between a Benchmark and a Market Index and

Study Session 10: Fixed-Income Portfolio Management (1)

Study Session 11: Fixed-Income Portfolio Management (2)

Lesson 3: Formulating a Portfolio Postioning Strategy for a Given Market View 161

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Reading 25: Equity Portfolio Management 197

Lesson 6: Identifying, Selecting, and Contracting with Equity Portfolio Managers 222

Wiley Study Guide for 2018 Level III CFA Exam

Volume 4: Alternative Investments, Risk Management, & Derivatives

Study Session 13: Alternative Investments for Portfolio Management

Study Session 14: Risk Management

Study Session 15: Risk Management Applications of Derivatives

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Wiley Study Guide for 2018 Level III CFA Exam Volume 5: Trading, Monitoring and Rebalancing, Performance Evaluation,

& Global Investment Performance Standards Study Session 16: Trading, Monitoring, and Rebalancing

Lesson 4: Trade Execution Decisions and Tactics and Serving the Client's Interests 17

Study Session 17: Performance Evaluation

Study Session 18: Global Investment Performance Standards

Lesson 7: Real Estate, Private Equity, and Wrap Fee/Separately Managed Accounts 96

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Time to complete: 2 to 3 hours

Reading summary: This is one of the longest readings in the entire CFA Curriculum at

Level III, so plan your time accordingly The focus of the first portion of the reading is

on formal tools to determine long-term expectations, mainly for returns Then, short- and

long-term economic growth forecasting and analysis are explored The reading then

examines how various asset classes perform at different stages of the business and inflation

cycles

LESSON 1: ORGANIZING THE TASK: FRAMEWORK AND CHALLENGES

LOS I4a: Discuss the role of, and a framework for, capital market

expectations in the portfolio management process Vol 3, pp 6-13

LEARNING OBJECTIVES

The portfolio management process begins with understanding the client’s objectives and

constraints, which are documented in the investment policy statement (IPS) This client-

specific information is then combined with the portfolio manager’s expectations about the

long-term performance of asset classes to establish a unique strategic asset allocation But

how do managers form their capital market expectations? That is the question addressed by

this reading

After studying this material, the candidate should be able to:

1 Explain how capital market expectations fit within the portfolio management

process;

2 Describe analytical tools and models used to develop capital market expectations;

3 Discuss the implications of the business cycle and economic policy for capital

market expectations;

4 Explain how macroeconomic variables like inflation, interest rates, and exchange

rates are forecast and how they influence capital market expectations

A SYSTEMATIC APPROACH

The strategic asset allocation represents the base case, or normal state, partitioning of a

portfolio among the various asset classes available in the investment universe Each asset

class (e.g., stocks, bonds, real estate, etc.) has unique risk and return characteristics that

respond to changing economic conditions So in order to ascertain which asset classes

belong in a particular investor’s portfolio and in what proportion, the manager must have

some idea of what the prevailing economic environment might look like and how asset

classes might react under those conditions These insights are collectively referred to as the

manager’s capital market expectations

Given the vast amount of data available to asset managers, developing capital market expectations is best implemented using a systematic approach In a general framework, the manager must address each of the following functions:

• Data collection, analysis, and interpretation of output

• Deriving conclusions that lead to forecasts of expected returns, risk, and correlations

• Monitoring, evaluating performance, and adjusting the process to improve future performance

The process of setting capital market expectations is usually considered beta research,

which emphasizes systematic risk of broad asset classes (e.g., equities, fixed income, and real estate) The research takes a macroeconomic perspective that uses the same inputs (e.g., interest rates, inflation, GDP growth, etc.) to develop expectations that are used to

design a strategic asset allocation Alpha research is an investment-specific approach

that seeks to earn excess risk-adjusted returns, which is more closely related to security selection

Steps in Formulating Capital Market Expectations

Step 1: Specify the final objectives o f the process and the relevant time period The purpose

of this step is to limit the scope of the research With so much information available, the manager cannot consider everything under the sun For example, if the client’s IPS limits acceptable asset classes to only domestic stocks and bonds, there is no need to research emerging-market real estate or commodity futures Managers often complete this step by drafting a set of questions to be answered, which helps to focus their efforts

Step 2: Review past performance and conditions While the past is not necessarily

indicative of the future, it is a logical place to start, with the understanding that relation that held in the past are susceptible to change

Step 3: Define methods and models Establishing the methodology early in the process will

help determine what data is required

Step 4: Collect data When considering data sources, the manager must evaluate their

timeliness, accuracy, and reliability

Step 5: Apply analytical techniques, models, and judgment to interpret results Particular

attention should be paid to the assumptions underlying models, the consistency with which data is used, and any conflicts that might challenge the plausibility of output

Step 6: Draw conclusions Here the manager determines and documents his or her

expectations that will be used in establishing the portfolio’s strategic asset allocation

Step 7: Evaluate results and adjust Actual results are compared to previous expectations

to assess the level of accuracy that the expectations-setting process is delivering Good forecasts are:

• Unbiased, objective, and well researched;

• Efficient, minimizing the magnitude of forecast errors; and

• Internally consistent

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Vol 3, pp 13-23

Forecasting Challenges

Faulty analysis may create a portfolio that is inappropriate for the client The analysis

might be compromised by unrealistic assumptions, unreliable data, or analyst biases

Data Limitations

Economic data is notorious for problems related to timeliness (released with a lag), so

you’re always looking backward to make forward-looking projections It can also be error-

prone, requiring revision of previously released data Finally, changes in the way the data

is collected or compiled can make past reporting incompatible with future releases

Errors and Biases

Simple mistakes during the data gathering and compiling process can show up as

transcription errors Elements that drop out of data sets over time, as a result of mergers

or bankruptcies for instance, make comparing indexes difficult across periods difficult

and can give an overly optimistic impression This phenomenon is called survivorship

bias Finally, valuation of illiquid assets is often done using appraisals Because they are

somewhat subjective and are usually performed at wider intervals, rather than continuous

pricing found in high-volume trading, appraisals tend to underestimate volatility and

distort correlations between asset returns

Historical Data

While historical data might be a good starting point in developing a forecast, simply

extrapolating the past into the future is a naive approach The relation between variables

that held in the past are often subject to the conditions that prevailed at the time, such

as central bank policies and available technology These underlying conditions are often

referred to as regimes Regime changes create inconsistencies in the way variables interact

from one period to another This creates a non-stationarity problem where the mean,

variance, and correlations of variables are unstable over time

Analysts can also run into the problem of not having a long enough history of data to

work with If this is the case, simply looking at time series drawn at greater frequency to

increase the number of observations is not usually an effective solution

Ex Post Risk versus Ex Ante Measures

Ex post risk is backward-looking and may underestimate the perceived ex ante risk In

other words, backward-looking risk metrics will not reflect possible events that were a

concern at the time but did not ultimately come to pass Those concerns would be reflected

only in forward-looking (ex ante) risk metrics.

Analysts’ BiasesAnalytical biases lead to the finding of relations that don’t really exist So-called spurious correlations are often the result of data-mining or time-period bias.

D ata-m ining bias occurs when a data set is analyzed over and over again until some statistically significant relation is found Analysts should always have some underlying economic rationale for including a variable in a model so as to avoid including spurious correlations that lead to faulty forecasts

Time-period bias occurs when the analyst shifts time horizons in order to find the best fit with the conclusions he or she is seeking The relation between variables might be significant for a particular time interval, but they do not hold outside that period Testing models with out-of-sample data is a good way to avoid this bias

Ignoring Conditioning InformationConditioning is adjusting our expectations when there are new facts that are relevant to forecasting the future Measurements of risk and return are often based on historical data However, an analyst should also consider the current and expected market environment Forecasts should be based on conditional information and not simply unconditional averages of the past

Correlation Is Not CausationJust because two variables are correlated does not necessarily mean that one causes the other to occur Correlation can indicate one of three possibilities: A predicts B, B predicts

A, or C predicts A and B Looking solely at the correlation between A and B could be very misleading Therefore, it is important to have a theoretical justification for the expected relation between variables

It is also possible to reach a false negative conclusion by blindly relying on correlations Recall that correlation measures the linear relation between two variables However, it is possible that they are related to one another in a nonlinear way Their linear correlation may be insignificant, but the relation between the two variables might still have predictive power

was written many

years before the

BF readings If

you are tested on

these specific six

biases, the question

will relate to an

economist instead

of an individual

investor.

Psychological traps are common mental biases that jeopardize the accuracy of forecasts

A nchoringoccurs when initial findings dominate the rest of the analysis Analysts must keep an open mind and allow the entirety of the research to lead to their conclusions

Status quo bias projects the recent past into the future Regret avoidance might drive this bias as analysts are loath to look foolish by predicting a major departure from what has prevailed in the past Rigorous analysis can provide confidence to pursue an objective forecast even if it seems out of the ordinary

The confirm ing evidence trapis the tendency to emphasize information that supports one’s initial hypothesis and discount evidence to the contrary Maintaining self-awareness, investigating contradictory evidence, and designating a person to play the devil’s advocate are approaches to combating this form of bias

range of possible outcomes as a means to avoid this trap.

Prudence trap is the temptation to moderate conclusions so as to appear more

conventional than the research itself indicates Unorthodox forecasts that are far outside

consensus opinion can prove brilliant if they turn out to be accurate but humiliating if

they fail to materialize Analysts can defend against this bias with rigorous research and

allowing for a wider range of possible outcomes

Recallability bias occurs when the research is heavily influenced by events that have left

a lasting impression on the analyst, particularly catastrophic or dramatic events such as a

market crash Grounding conclusions on objective data rather than on personal emotion

minimizes the distortion and addresses this trap

Example 1-1

Amy Cobourg is the fund manager of a small emerging market fund that invests in both

large-cap and mid-cap stocks Cobourg has seen large gains in her personal portfolio

from investments in Poland and is keen to take advantage of her knowledge of the region

Currently, 25 percent of the portfolio is invested in the mining industry in Poland, which

saw great returns the previous year due to a global boom in commodity prices Cobourg

is forecasting an average 12 percent (±10 bps) return on investment for commodity

stocks for the coming year

Cobourg recently read an article from a highly regarded mining industry analyst who

specializes in Polish companies The article suggests doubt and concern for the three

largest businesses in the sector due to the author’s forecast of economic recession and

lower prices Cobourg’s supervisor, John Curran, disagrees with the report and says

that the three companies are in a good position to handle a downturn, which he believes

will profit by a reduction in the supply of gold from South Africa due to a miner’s strike

there

Cobourg revises her forecast to an expected return of 11 percent, only slightly lower

than her existing 12 percent expectation, believing that Poland will gain extra market

share at South Africa’s expense

for each trap identified

Solution:

Overconfidence—Overestimating own knowledge of Polish stocks based on her own

portfolio Possibly used too narrow of range (±10 bps) for her forecast

Anchoring trap— Cobourg only slightly revised expectations to 11% from 12% despite

the negative outlook in the article

Confirming evidence trap—Ignores the negative outlook in the article but agrees with

the effect of potential profit from Poland’s gain in market share at South Africa’s

expense

©

Model RiskFinancial and economic models are abstract representations of markets They try to uncover the factors that influence the behavior of the variable being forecast However,

as abstract representations, they are incomplete, providing only estimates of dependent variables

A model used to forecast economic variables or asset returns has two sources of error First

is the accuracy of the model inputs Data is often imperfect, or model inputs themselves must be estimated from other models The second source of error is the model itself To the extent that the abstract representation departs from reality, the model’s forecast will also deviate from the dependent variables’ actual value

LESSON 2: TOOLS FOR FORMULATING CAPITAL MARKET EXPECTATIONS, PART 1: FORMAL TOOLS

LOS 14c: Demonstrate the application of formal tools for setting capital market expectations, including statistical tools, discounted cash flow models, the risk premium approach, and financial equilibrium models

Vol 3, pp 23^40 ANALYTICAL METHODS AND TOOLS

Financial theory and practice provide a variety of tools and techniques for analysis and forecasting asset returns Like more menial tasks, the analyst must select the right tool for the right job In this section, we consider formal tools, which include statistical models, discounted cash flow models, and other quantitative techniques We also consider survey and consensus approaches

Quantitative Tools: Statistical Methods

Recall that there are two types of statistics: descriptive and inferential Descriptive statistics seek to organize and present data in meaningful ways Inferential statistics attempt to estimate or predict the characteristics of a population by looking at smaller samples

Historical Averages and EstimatorsThe simplest forecast looks solely at past data An analyst can compute the average return and variance of a sampled time series over a specific period If the distribution of the data

is stable, the sample statistics might be good estimates of their future values There are, however, different methods of computing an average In finance, the most commonly used methods are the arithmetic average, which is best for an estimate at a single point in time, and the geometric average, which is best for averaging compound returns over time

Shrinkage EstimationShrinkage estimation is the weighted average of two estimates of a parameter based on the relative confidence the analyst has in using two methods For example, an analyst might use sample historical data to estimate a covariance matrix and an alternative method such

as a factor model to estimate a second covariance matrix, called a target covariance matrix

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model and historical estimates are 0.80 and 0.20, respectively The shrinkage estimate of

the covariance would be 0.80(24) + 0.20(40) = 27.2

In all cases, a shrinkage estimate using any target covariance matrix is a more efficient (or

at least not less efficient) estimate than the historical average

Example 2-1

Richard Ayoade is using a shrinkage estimator approach to estimating covariances

between Mexican and Colombian equities He estimates that the covariance between

Mexican and Colombian equities is 76 using historical data He also estimates the

covariance as 64 using a factor model approach

Colombian equities if the analyst has 80 percent confidence in the factor model

approach

historical average alone

Solutions:

A 0.20(76) + 0.80(64) = 66.4

B The shrinkage estimator approach will lead to an increase in the efficiency of

the covariance estimates versus the historical estimate

We can also determine a shrinkage estimate for mean returns by taking a weighted average

of historical mean return and some other target estimate, like the average mean of a group

of assets For example, given five assets with sample mean returns of 7 percent, 11 percent,

13 percent, 15 percent, and 19 percent, respectively, and a weight of 70 percent on the

sample mean, we would calculate the grand mean return as 13 percent and the shrinkage

estimate of the first asset’s return as 0.3(9%) + 0.7(13%) = 11.2%.

Time-Series Analysis

Time-series estimators are based on regression using lagged variables, which are past

values of the dependent variable For example, a model used to determine the short-term

volatility in a variety of asset markets was developed at JPMorgan The model shows that

the variance (a 2) in time t is dependent upon its value in the preceding period t — 1 and the

square of a random error term ef

a? = p a ^ + (1 - p)e2

The larger the coefficient term, P, the greater influence the past variance (c^r_1) has on the

forecasted variance (of ) This variance “memory” from one period to the next is called

volatility clustering

®

Multifactor Regression Models

Multifactor models provide asset return forecasts (R,) based on risk factors (Fk) that are

thought to drive returns The risk factors represent the required return for assuming that

particular source of risk The factor sensitivities (bik) are the regression coefficients that

measure the degree to which the return is affected by a particular risk factor, or the asset’s exposure to that risk

Multifactor models are also well suited for estimating covariances between asset class returns

Quantitative Methods: Discounted Cash Flow Models

Discounted cash flow (DCF) models are based on the fundamental premise that the value

of any asset is the present value of its future cash flows

DCF models estimate the intrinsic value of an asset The expected return on the asset is embedded in the relation between the asset’s intrinsic value and its current market price However, an expected return based on this intrinsic valuation approach is realized only when the market price converges to the intrinsic value, which can take a long time to happen For that reason, intrinsic value approaches are generally regarded as useful in setting long-term, strategic expectations as opposed to short-term, tactical expectations.Dividend Discount Model (DDM)

The Gordon (constant) growth dividend discount model is a widely recognized DCF

model for estimating a stock’s intrinsic value The current price (P q) is determined by the

next dividend [D\ = Dq(1 + g)], discounted at the required return on common equity (re) adjusted for the estimated growth rate of dividends (g), which are assumed to grow at the

same rate as earnings

A ^ Do<X + g)

r e ~ 8 re - g

The expected return of the stock, E(R), is the required return on equity Rearranging the

preceding equation to solve for the required return provides an estimate of the expected return on common stock

E(R) = D q <1 + 8)

Po

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dividend yield represents income, while the growth rate represents the capital gains yield,

g, which might be assumed to be the growth rate in nominal gross domestic product (GDP)

for a broadly defined equities asset class

Grinold-Kroner Model

In many countries, particularly in the United States, firms have preferred to return excess

cash to shareholders in the form of share repurchases rather than dividend distributions

Grinold and Kroner (2002) adapted the traditional DDM to account for this form of

distribution as well as expected changes in relative value that investors attach to earnings

via the price-earnings (P/E) multiple

D

P - % AS + INFL + gr + % APE

We can read the model as: “The expected return on equity, E(R), is approximately equal

to the dividend yield (D/P) less the expected percent change in the number of shares

outstanding (%AS) plus the rate of inflation (INFL) plus the real expected earnings growth

rate (gr) plus the percent change in the price-earnings multiple (%APE).”

Notice that a share repurchase would result in a negative change in the shares outstanding

Subtracting a negative number results in a positive impact on the expected return

The model can also be used to decompose historical returns The three sources of the asset

return are:

1 An expected income return: D/P - %AS

2 An expected nominal earnings growth return: INFL + gr

3 An expected repricing return: %APE

Example 2-2

Fred Schepisi holds a $200 million equity portfolio He is considering adding to the

portfolio based on an assessment of the risk and return prospects facing the economy

in Thailand Information pertaining to the Thai economy and capital markets has been

collected as shown:

• Expected dividend yield of 1.75 percent on equities;

• Expected repurchase yield of 1.33 percent on equities;

• Expected long-term inflation rate of 6.66 percent per year;

• Expected long-term corporate real earnings growth rate of 2.33 percent

per year; and

• Expected P/E multiple expansion of 0.50 percent per year

The expected rate of return on Thai equities using the Grinold-Kroner model is:

E(R)

/v

If the stock market’s earnings yield (E/P) is lower than the 10-year Treasury bond yield, stocks are overvalued, and investors would shift their money into the less risky T-bonds.

The Build-Up Approach

The risk premium approach (build-up approach) starts with the nominal risk-free rate and adds premiums for the various priced risk factors for which investors require to be compensated for assuming

j E(R^) = Rj7 + RPy + RP2 + ••• + RR/c

where E(Rt) is the asset’s expected return, RF denotes the nominal risk-free rate

of interest, and RP represents the risk premiums.

Fixed-Income Premiums

To determine the expected return for a bond, E(Rb), the analyst begins with the real

risk-free rate of interest and adds the relevant premiums for priced risk factors

E{Rb) - rrF + RPlNFL + RP 'Default + RR Liquidity + RR Maturity + R ^T ax

The risk premiums compensate the bond investor for: deferring consumption (rrF), the loss of purchasing power (RPINFL), difficulty in exiting the investment (RPLiquidity)’ putting capital at risk for longer periods of time (RPMaturity)’ and the tax disadvantage of some types of bonds versus others (RPTax).

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Because equity investors have a lower priority claim on a firm’s cash flows than debt

holders, the equity risk premium (ERP) compensates the equity investors for additional risk

of loss to their investment Therefore, the equity risk premium is the excess return over the

nominal risk-free rate (RF), which is usually estimated by the 10-year U.S Treasury yield.

E(RS) = R f + ERP - YTM10_year Treasury + ERP

While the yield on the 10-year Treasury is readily available, the value of the equity risk

premium is a hotly debated topic among academics and practitioners

LESSON 3: TOOLS FOR FORMULATING CAPITAL MARKET EXPECTATIONS,

PART 2: SURVEY AND PANEL METHODS AND JUDGMENT

LOS 14c: Demonstrate the application of formal tools for setting capital

market expectations, including statistical tools, discounted cash flow

models, the risk premium approach, and financial equilibrium models

Vol 3, pp 40-48

Equilibrium Models

Equilibrium models are based on the principles of modern portfolio theory and mean-

variance optimization techniques They define the risk-return relation when the supply and

demand for assets are equal

The International Capital Asset Pricing Model

The International CAPM (ICAPM) approach assumes the same form as the regular CAPM

model you are likely very familiar with The ICAPM relies on the return for the theoretical

global market portfolio (RM).

E(Ri) = RF + M E (R M) - R F]

The equation implies that an asset class risk premium = E(Rt) - RF ] is a function of

the world market risk premium [RP m = E{RM) - RF ] with the global investable market

(GIM) serving as a proxy for the world market Given that the beta term is equal to the

covariance of the asset class with the GIM divided by the variance of the GIM, the asset

class risk premium can be estimated by:

0 i°iWPi1M

V ° M J

©

The terms in the preceding equation can be rearranged to show that the asset class risk

premium is equal to the GIM’s Sharpe ratio [(/?M - RF) / o M = RPM / o M ] multiplied by

the standard deviation of the asset class’s return and its correlation with the GIM’s return

The ICAPM estimates the expected return for an asset class as the risk-free rate plus an asset risk premium, which is the asset class beta times the GIM risk premium This version

is a simple, one-factor model with very rigid, and not very realistic, assumptions For instance, it assumes perfect markets that are fully integrated and efficient

Example 3-1

A portfolio manager is working on developing his capital market expectations He manages a balanced fund consisting of stocks and bonds The manager believes that the ICAPM will produce the best estimate of the expected returns for these two asset classes He collected the following information for each

For the two asset classes in question, RPst0Cks = 0.30(12.0%)(0.75) = 2.7% and

RPbonds = 0.30(5.0%)(0.65) = 0.975% Adding these risk premiums to the risk-free rate

produces the manager’s estimate of the expected returns

E(Ri) = RF +RPi E(Rslocks) = 3.2%+ 2.7% = 5.9%

E {R-bonds) = 3.2% + 0.975% = 4.2%

Singer-Terhaar ApproachThe Singer-Terhaar approach adds a level of sophistication to the simple ICAPM approach

by incorporating market imperfections into the analysis The two imperfections we will consider are market segmentation and illiquidity Singer-Terhaar recognizes that the

standard ICAPM risk premium should be adjusted for market segmentation (RPl ) and

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Market integration versus segmentation refers to the ability of capital to freely flow

from one market to another In a fully integrated market, the flow of capital between

countries and/or asset classes is unimpeded by excessive costs, government interventions,

or investor biases Fully segmented markets are completely isolated from one another

so that no capital flows between them at all The extent to which markets are integrated

is best thought of as a continuum with every country showing at least some degree of

segmentation

To reestimate an asset class’s risk premium in light of its degree of market segmentation, we

first recognize that the standard ICAPM risk premium assumes a fully integrated, frictionless

market Taken to the opposite extreme, a fully segmented market restricts the reference global

investable market (RM) to the local market so that the correlation between its returns and the

asset class’s returns is 1.0, which is effectively the correlation of the local market with itself

To determine the market segmentation-adjusted risk premium (RPt ), the analyst must

compute two risk premiums, the fully integrated premium, which is the ICAPM risk

premium (RPj), using the correlation coefficient between the asset class and the GIM

(p;- M), and the fully segmented risk premium, which assumes that the asset class and the

market portfolio are perfectly positively correlated

A shrinkage estimate is used to combine the two extreme scenarios into a single risk

premium Recall that a shrinkage estimate is a weighted average where the weights sum to

1.0 The analyst may subjectively assign weights, but empirical research shows that most

developed markets are 65 to 85 percent integrated (35 to 15 percent segmented)

An example might help to illustrate the process of estimating the market segmentation-

adjusted risk premium Assume we are given the following information about two asset

classes, stocks and bonds

The Sharpe ratio for the GIM is 0.30 and the markets are 70 percent integrated with the

world market

To compute the market segmentation-adjusted risk premium (RP( ), we first use the

ICAPM to estimate what it would be under a perfectly integrated scenario

On the exam,

make sure that

you provide the

examiners with the

measure they want

you to provide For

example, if you are

asked to provide

the risk premium

of the asset class

and you provide

the expected return,

then you would

only receive partial

credit for a morning

If, however, you are asked to estimate the illiquidity premium, only one method is described in the curriculum It employs a multiperiod Sharpe ratio (MPSR), which is a measure of risk-adjusted return A rational investor would only choose an alternative asset

if its MPSR is at least as large as the market portfolio’s MPSR over the liquidity horizon

So, if the alternative asset’s MPSR (RP/o,) computed using ICAPM is less than the market

portfolio’s (RP m /G m ), we can derive the return that would make them equal The difference

between this derived return and the ICAPM return is the liquidity premium

Again, an example might help to illustrate the process of estimating the illiquidity risk premium Assume we are given the following information about the global investable market (GIM) and two asset classes, common stocks and collectibles

Asset Class Standard Deviation Correlation with GIM[

to account for illiquidity To compute the illiquidity risk premium, we first compute the

ICAPM risk premium for the collectibles asset class (RPC).

Finally, subtract the ICAPM risk premium from the risk premium derived from the MPSR

to estimate the liquidity premium

RPuquidity = 5.7% - 2.0% = 3.7%

Example 3-2

An analyst is using the Singer-Terhaar approach to estimate the expected returns for

domestic stocks, bonds, and private equity

Asset Class

Standard Deviation

Correlation with GIM

Degree of Integration

Illiquidity Premium

The expected return on the GIM is 8.0 percent and the risk-free rate is 3.5 percent

i Domestic stocks

ii Private equity

i The Singer-Terhaar approach starts with the ICAPM and adjusts the riskpremium for the level of market segmentation and adds an illiquidity premium when appropriate

£(/?, ) = R f + RP* + RPt liquidity

Since stocks are very liquid, the illiquidity risk premium is zero, dropping out of the equation The market segmentation-adjusted risk premium is the weighted average of the ICAPM (fully integrated) version and the fully segmented (perfect positive correlation), where the weights are the degree of integration and its complement (degree of segmentation)

E(Rp) = RF + RP* + RPliquidity = 3.5% + 7.6% + 2.4% = 13.5%

© 2018 Wiley

setting capital market expectations Vol 3, pp 48-50

Consensus Opinion Methods

Capital market expectations can also be determined by surveying the opinion of experts

When the same group of experts is queried over a series of surveys, the approach is called

a panel method This is effectively a consensus opinion approach that relies on the work of

others

The Role of Judgment

Quantitative models provide an objective rationale for forecasts However, experience and

judgment are critical complements to analysis Remember that models are completely

dependent upon the quality of inputs Garbage in garbage out

LESSON 4: ECONOMIC ANALYSIS, PART 1: INTRODUCTION

AND BUSINESS CYCLE ANALYSIS

LOS 14e: Discuss the inventory and business cycles, the impact of consumer

and business spending, and monetary and fiscal policy on the business

cycle Vol 3, pp 50-54

MACROECONOMICS

Asset returns (expected and actual) are closely related to economic activity Accelerating

economic activity drives revenues higher, which in turn drive profits higher, which increase

cash flows available to the asset owners and increases the value of assets that represent

claims on those cash flows Declining economic activity has the reverse effect

This relation is consistent with asset-pricing theory, which predicts higher risk premiums

for assets that are strongly, positively correlated with the ups and downs of economic

activity and low risk premiums for assets with payoffs that are weakly, or negatively,

correlated with the economy

The Business Cycle

The economy follows a general upward, long-term trend through time but not in a straight

line The business cycle describes the recurring ebb and flow of economic activity along its

long-term trend line Economists often refer to a short-term inventory cycle, lasting two to

four years, and a longer, nine- to eleven-year business cycle

Although economic cycles reflect recurring and measurable variations in economic

activity that can be clearly seen in retrospect, anticipating those movements with effective

forecasts is a significant challenge The key metrics for monitoring economic activity and

the business cycle include real GDP, the output gap, and whether or not the economy is in

recession

Gross domestic product (GDP) is the standard measure of economic output representing

the value of all finished goods and services produced in a particular country during

the year regardless of who owns the assets that produced them As measured from an

expenditures approach, GDP is the sum of consumption (C), investment (7), government

spending (G), and net exports ( X - M).

GDP = C + I + G + ( X - M )

The change in total output is a function of change in quantity demanded and change in

pricing GDP can change as a result of changes in prices (P) or a change in the quantity

of goods and services actually produced ( 0 , where nominal GDP = PQ Since we’re

interested in economic output as a measure of well-being, we’ll focus on real GDP, which

is nominal GDP adjusted to reflect a constant price level

Output gap: Potential GDP measures the level of output that could be achieved if the

economy operates at its most efficient level Potential GDP gradually increases as the country’s capacity to produce increases The path of this gradual rise in capacity is shown

as the long-term trend line in Exhibit 4-1

Exhibit 4-1: The Business Cycle

An easy way to

remember the

output gap is that a

positive output gap

long-on equipment), current real GDP rises above potential GDP and inflatilong-onary pressures build Once the economy slows and real GDP falls below potential GDP (idle workers, mothballed facilities and equipment), the rate of unemployment increases

Recession: An economic contraction follows a peak in the business cycle It can merely

represent movement back toward the long-term growth rate However, if real GDP declines

in two successive quarters, the contraction is officially deemed a recession

The following discusses the inventory cycle and the business cycle in more detail

© 2 0 1 8 W iley

In the most basic model of a company, a product is manufactured and then sold to

customers The managers of the company try to ensure that enough product inventory is

available to fill customer orders, but not so much that excessive storage costs are incurred

or that too much capital is tied up in unsold merchandise However, manufacturing takes

time, so some inventory must be kept on hand, although carefully managed

The inventory cycle measures the fluctuations in inventories, which come about because

of managements’ activities in balancing inventory levels based on their near-term

expectations about demand (economic activity) If inventories begin to build, managers

might slow down production in anticipation of an economic contraction If inventories

begin to fall, they might increase production in order to meet rising demand

In the positive phase of the inventory cycle, business confidence is high, production is

increasing, employment is expanding, and GDP grows This continues up to an inflection

point when businesses view their inventories as too high, which might occur when sales

suddenly disappoint or real GDP growth slows Restrictive monetary policy and higher

input prices may also provoke production cuts to reduce inventories The inventory cycle

then enters the contraction phase with waning confidence, slowing production, rising

unemployment, and slow or declining GDP growth

LOS 14f: Discuss the impact that the phases of the business cycle have on

short-term/ long-term capital market returns Vol 3, pp 52-54

Phases of the Business Cycle

Here we’ll take a closer look at the phases of the business cycle and the typical reactions

they elicit in the capital markets (see Exhibit 4-2 and Table 4-1)

Exhibit 4-2: Phases of the Business Cycle

©

1 Initial Recovery

The initial recovery phase is short, lasting a few months, in which the economy is only beginning to emerge from a slowdown or recession Businesses become more optimistic, although consumers have not yet shown much confidence Governments continue their pursuit of stimulative policies in the form of lower interest rates or a budgetary deficit in this phase Although the output gap is still strongly negative, an upswing in the inventory cycle is likely driving the recovery, while inflation remains low

Impact on assets: Government bond yields are likely bottoming as the inflation rate is

low, pushing bond prices higher Stocks might rise sharply as fears of a recession subside Cyclical and riskier assets perform well in anticipation of a forthcoming expansion

2 Early Upswing

Once the recovery takes hold, confidence is strong and momentum grows This is the sweet spot of solid economic growth with no signs of serious inflation Lower unemployment gives consumers confidence to borrow and spend Businesses rebuild inventories and increase investment in light of strong sales and higher capacity utilization Higher output lowers unit costs, increasing factory efficiency and profits The output gap generally closes slowly, drawing out the expansion at least a year or more

Impact on assets: Short-term interest rates eventually begin to rise as the central bank

withdraws the stimulus put in place during the previous contraction, while long-term rates remain relatively stable Stocks continue to rise in this phase as long as growth does not overheat the economy and create a significant rise in the rate of inflation

3 Late Upswing

The output gap has closed and the economy begins overheating Confidence is still high, unemployment is low, and inflation starts to rise with wage increases and labor shortages

Impact on assets: Interest rates rise as a result of restrictive monetary policy as central

banks rein in inflation by engineering slower growth (hoping for a soft landing) Bond yields rise as a result of higher expected inflation Although stock prices might continue to rise, investors become nervous, creating increased volatility

4 Slowdown

Higher interest rates bite into the economy, slowing growth significantly At this point, the economy is vulnerable to negative shocks that could easily tip it into recession Business confidence begins to waver as production is cut in response to rising inventory levels and contributing to the slowdown Inflation may continue to rise in the short term

Impact on assets: Short-term interest rates likely peak, resulting in an inverted yield curve

as long-term rates fall at the first sign of contraction Stock prices likely fall as confidence wanes, although interest-rate-sensitive equities like financials and utilities may outperform

5 Recession

In a recession, defined as two successive quarterly declines in GDP, business and consumer confidence falls as businesses sharply reduce inventory and investment Consumers reduce spending on big-ticket items Central banks try to stimulate with expansionary monetary policy Profits and inflation fall as bankruptcies and unemployment rise

Impact on assets: Both short-term interest rates and bond yields fall Stocks usually begin

to rise in the later stages of a recession in anticipation of a recovery

© 2 0 1 8 W iley

Phase Economy

Fiscal and Monetary Policy Confidence Capital Markets

1 Initial recovery Inflation still declining Stimulatory fiscal

policies

Confidence starts to rebound

Short-term rates low or declining; bond yields bottoming; stock prices strongly rising

2 Early upswing Healthy economic

growth; inflation remains low

Increasingconfidence

Short-term rates moving up; bond yields stable to up slightly; stock prices trending upward

3 Late upswing Inflation gradually

picks up

Policy becomes restrictive

Boommentality

Short-term rates rising; bond yields rising; stocks topping out, often volatile

4 Slowdown Inflation continues to

accelerate; inventory correction begins

Confidencedrops

Short-term interest rates peaking; bond yields topping out and start-ing to decline; stocks declining

5 Recession Production declines;

inflation peaks

Confidenceweak

Short-term rates declining; bond yields dropping; stocks bottoming and then starting to rise

LOS 14g: Explain the relationship of inflation to the business cycle and the

implications of inflation for cash, bonds, equity, and real estate returns.

Vol 3, pp 55-59

The Price Level

Inflation is a persistent increase in the general price level, whereas deflation is a fall in the

general price level A consumer price index, which is based on a representative basket of

goods and services that are periodically priced relative to a base year and aggregated, or a

GDP deflator, an inflation index used to adjust or deflate the nominal series for inflation,

are used to discern the overall trend

Both inflation and deflation can be destructive influences on the economy Inflation erodes

the purchasing power of cash and increases risk premiums for assets Deflation degrades

investments purchased with debt and encourages the deferral of purchases based on the

expectation of lower prices in the future, thus suppressing aggregate demand and retarding

economic growth

For investors, inflation expectations are built into required returns If, however, actual

inflation differs from expected inflation, it can have consequences for investment returns

When actual inflation is greater than expected [INFL > E(INFL)], short-term debt and real

estate benefit, while stocks and bonds suffer

Expected inflation exceeding actual inflation [INFL < E(INFL)] tends to be good for bonds

but bad for other asset classes

The responsibility of maintaining stable prices rests with the world’s central banks Some

countries also expect their central banks to promote the long-run growth of the economy

In order to be effective, there are three general principles that underlie the structure of central banks.

1 A central bank should be independent of political influence

2 A central bank should set an inflation target to provide policy discipline and to signal markets of its policy intentions

3 A central bank should use countercyclical monetary policies, implemented primarily through short-term interest rates, to prevent real GDP from deviating too far from potential GDP (or for too long)

Predicting the Business CycleDeveloping capital market expectations might be as simple as determining the economy’s current position in the business cycle and extrapolating its path Unfortunately, the business cycle is notoriously difficult to predict because its length and amplitude vary, making turning points particularly difficult to anticipate Determining which circumstances and catalysts might signal shifts from one stage to the next is never clear in real time but often obvious in retrospect Finally, geopolitics play a significant role as exogenous shocks that are particularly difficult to anticipate

LOS 14f: Discuss the impact that the phases of the business cycle have on short-term/ long-term capital market returns Vol 3, pp 59-63

Factors That Influence the Business CycleSince the business cycle is defined by changes in output (real GDP), we look to the demand function from our economics studies to help us identify the factors that influence it

GDP = C + I + G + ( X - M )

Consumer Demand

The sources of data on consumer spending are retail sales and consumer consumption data, which can be erratic and affected by weather and holidays The most important factor affecting consumption is consumer income after tax, which depends on wages, inflation, tax, and employment growth Employment growth is closely watched because data is usually available on a timely basis

Business Demand and Investment

Business investment and inventories reveal recent business activity, and both can be volatile Business investment falls during recessions and rises during expansions Data for inventory requires caution Rising inventories can be both a positive and a negative signal Rising inventory can imply confidence in expected future sales if it is in the early stage

of the inventory cycle, but it can also imply that sales are lower than expected, which is a bearish sign

called to action in order to mitigate the impact of economic crises.

The most commonly used tool for implementing central bank policy is the manipulation

of short-term interest rates By lowering rates, the central bank encourages borrowing

and investment Lower interest rates signify monetary easing intended to stimulate the

economy and reduce unemployment Raising interest rates, tight money, has the opposite

effect with the intention of curbing inflation

Because interest rate movements have such dramatic effects on asset prices, predicting

what the central bank will do, so-called Fed watching, is a widely employed tactic among

investors Unfortunately, central banks tend to be a bit tight-lipped about their next move

One reason for their somewhat secretive behavior is the often conflicting information with

which they must make decisions At any given moment, the right course of action might

not be clear Under these circumstances, making bold, contradictory, or waffling statements

could easily send financial markets into wild gyrations Central banks prize stability, not

volatility

LOS 14h: Demonstrate the use of the Taylor rule to predict central bank

behavior Vol 3, pp 63-64

One approach to predicting central bank policy movements is called the Taylor rule

(after Stanford economist John Taylor) This model sets the optimal level of short-term

interest rates based on the stable-state, or neutral, short-term rate that is consistent with

the long-term (trend) growth rate of the economy plus a weighted average of the expected

deviations of GDP growth from trend and inflation from the target rate

Reading this equation, the short-term policy interest rate (usually the federal funds rate in

the United States) should be set to the stable-state rate that is consistent with the long-term

growth rate of the economy If the growth rate in real GDP is expected to fall short of trend

(usually around 3.0%), reduce the policy rate If real GDP growth is expected to exceed the

trend rate, increase the policy rate Similarly, if inflation is expected to exceed the target

rate (usually around 2.0%), increase the rate Finally, if inflation is expected to fall short of

the target, reduce the rate

Example 4-1

Denis Villeneuve is asked to estimate what the policy interest rate level should be based

on targets for inflation and overall economic growth rates assuming the following

information:

• 1.75 percent is the neutral value of the short-term interest rate

• 1.25 percent is the inflation target

• 1.5 percent is the GDP trend rate of growth.

• 2 percent is the inflation forecast

• 0.5 percent is the forecast for GDP growth

prices and full employment using the Taylor rule

Solution:

Using the Taylor rule:

Optimal ~ ^ N e u tr a l [0 -5 X { G D P g p orecast G D P g T r e n d ) ^ F orecast ^ T a r g e t)]

The central bank implements monetary policy mainly through open market operations that adjust money supply There is a relation between the growth in money supply and the growth in nominal GDP (inflation plus real growth) Inflationary pressures may build if the money supply grows faster than nominal GDP

Should the economy languish too long in recession, the central bank may stimulate growth

by reducing interest rates However, should rates go to zero, the central bank must rely on other means to lower long-term interest rates One approach is called quantitative easing

in which the central bank purchases assets (government bonds, sovereign debt, mortgage- backed securities, etc.), driving up prices and lowering yields

Fiscal Policy

Fiscal policy is defined by government taxing and spending decisions that influence the growth rate of the economy It is not necessarily the aggregate deficit or surplus that affects the economy, but the intentional changes that seek to manipulate aggregate demand that constitute fiscal policy In other words, forecasting the business cycle’s response to fiscal policy focuses on the deliberate changes in fiscal policy as opposed to the natural fluctuations in tax revenues as economic activity ebbs and flows Certain automatic stabilizers, such as unemployment benefits, that serve to moderate the business cycle are not considered fiscal policy unless benefits are extended or increased as part of a deliberate stimulus program