CFA 2018 level 3 schweser practice exam CFA 2018 level 3 question bank CFA 2018 CFA 2018 r14 capital market expectations IFT notes

Capital Market Expectations

IFT Notes

Capital Market Expectations
1. Introduction .............................................................................................................................................. 3
2. Organizing the Task: Framework and Challenges ..................................................................................... 3
2.1 A Framework for Developing Capital Market Expectations ................................................................ 3
2.2 Challenges in Forecasting.................................................................................................................... 4
3. Tools for Formulating Capital Market Expectations ................................................................................. 8
3.1 Formal Tools........................................................................................................................................ 8
3.2 Survey and Panel Methods ............................................................................................................... 15
3.3 Judgment........................................................................................................................................... 16
4. Economic Analysis ................................................................................................................................... 16
4.1 Business Cycle Analysis ..................................................................................................................... 16
4.2 Economic Growth Trends.................................................................................................................. 22
4.3 Exogenous Shocks ............................................................................................................................. 23
4.4 International Interactions ................................................................................................................. 23
4.5 Economic Forecasting ....................................................................................................................... 25
4.6 Using Economic Information in Forecasting Asset Class Returns ..................................................... 26
4.7 Information Sources for Economic Data and Forecasts .................................................................... 28
Summary..................................................................................................................................................... 29
Examples from the Curriculum ................................................................................................................... 39
Example 1. Capital Market Expectations Setting: Information Requirements (1) .................................. 39
Example 2. Capital Market Expectations Setting: Information Requirements (2) .................................. 40
Example 3. Historical Analysis ................................................................................................................. 41
Example 4. Incorporating Economic Analysis into Expected Return Estimates...................................... 41
Example 5. Inconsistency of Correlation Estimates: An Illustration ....................................................... 42
Example 6. A Change in Focus from GNP to GDP ................................................................................... 42
Example 7. Smoothed Data: The Case of Alternative Investments (1) ................................................... 42
Example 8. Smoothed Data: The Case of Alternative Investments (2) ................................................... 44

Example 9. Using Regression Analysis to Identify a Change in Regime .................................................. 44
Example 10. Causality Relationships ....................................................................................................... 45
Example 11. Traps in Forecasting ........................................................................................................... 45
Example 12. Adjusting a Historical Covariance ....................................................................................... 45
Example 13. The Grinold–Kroner Forecast of the US Equity Risk Premium ........................................... 46

IFT Notes for the Level III Exam

www.ift.world

Page 1


Capital Market Expectations

IFT Notes

Example 14. Forecasting the Return on Equities Using the Grinold–Kroner Model .............................. 47
Example 15. The Long-Term Real Risk-Free Rate.................................................................................... 47
Example 16. The Real Interest Rate and Inflation Premium in Equilibrium ........................................... 48
Example 17. The Risk Premium: Some Facts .......................................................................................... 48
Example 18. Justifying Capital Market Forecasts .................................................................................... 48
Example 19. Setting CME Using the Singer–Terhaar Approach .............................................................. 50
Example 20. Short-Term Consumer Spending in the United Kingdom ................................................... 53
Example 21. Judgment Applied to Correlation Estimation ..................................................................... 53
Example 22. The Yield Curve, Recessions, and Bond Maturity ............................................................... 54
Example 23. Inflation, Disinflation, and Deflation .................................................................................. 54
Example 24. An Inflation Forecast for Germany ..................................................................................... 55
Example 25. The 1980–1982, 2001, and 2008–09 US Recessions .......................................................... 56
Example 26. A Taylor Rule Calculation.................................................................................................... 57

Example 27. Monetary Policy in the Eurozone Compared with the United States in 2001 and 2010 ... 57
Example 28. Cycles and Trends: An Example .......................................................................................... 58
Example 29. Forecasting GDP Trend Growth.......................................................................................... 58
Example 30. An Analyst’s Forecasts ........................................................................................................ 59
Example 31. Central Bank Watching and Short-Term Interest Rate Expectations ................................. 60
Example 32. Economic Return Drivers: Energy and Transportation ....................................................... 60
Example 33. Researching US Equity Prospects for a Client .................................................................... 61
Example 34. Modifying Historical Capital Market Expectations ............................................................. 63
Example 35. A Currency Example ........................................................................................................... 65
Example 36. The USD/Euro Exchange Rate, 1999–2004 ........................................................................ 65
This document should be read in conjunction with the corresponding reading in the 2018 Level III CFA®
Program curriculum. Some of the graphs, charts, tables, examples, and figures are copyright
2017, CFA Institute. Reproduced and republished with permission from CFA Institute. All rights reserved.
Required disclaimer: CFA Institute does not endorse, promote, or warrant the accuracy or quality of the
products or services offered by IFT. CFA Institute, CFA®, and Chartered Financial Analyst® are
trademarks owned by CFA Institute.

IFT Notes for the Level III Exam

www.ift.world

Page 2


Capital Market Expectations

IFT Notes

1. Introduction
In this reading we will discuss capital market expectations i.e. the investor’s expectations about the risk

and return prospects of asset classes. Capital market expectations are a key input in creating a strategic
asset allocation. An important point to note here is that capital market expectations are macro
expectations. By contrast, expectations about individual assets are micro expectations. Macro
expectations help us in strategic asset allocation, whereas, micro expectations help us in security
selection and valuation. This reading focuses on macro expectations, we will discuss micro expectations
in a later reading.
The major sections in this reading are:
 Framework and challenges
 Tools for formulating capital market expectations
 Economic analysis

2. Organizing the Task: Framework and Challenges
2.1 A Framework for Developing Capital Market Expectations
This section addresses LO.a:
LO.a: Discuss the role of, and a framework for, capital market expectations in the portfolio
management process
As discussed, capital market expectations are used to determine an investor’s strategic asset allocation.
They are an important part of the portfolio management process.
To formulate capital market expectations, the following framework should be used:
Step 1: Specify the final set of expectations that are needed, including the time horizon to which they
apply. An analyst needs to understand the scope of the analysis, set boundaries and only focus only on
what is relevant. An investment policy statement can guide you in this task. The analyst should write
down the questions which need to be answered. Examples 1 and 2 in the curriculum contrast the
expectation settings for two managers. Manger 1’s information requirement relates to US equity and
fixed income markets only. By contrast, Manger 2’s information requirement relates not only to US and
non-US equity and fixed-income markets, but also to three alternative investment types.
Refer to Example 1 from the curriculum.
Refer to Example 2 from the curriculum.
Step 2: Research the historical record. Analyzing historical return data can be a useful starting point
when forecasting returns. However, beyond simply providing average returns over a certain time

horizon, historical data should be analyzed to determine the factors which drive returns. As noted in
Example 3, forecasters who make predictions without regard to past experience have no benchmarks to
distinguish between what is new about their expectations and what may be a continuation of past
experience. If your forecast contradicts the historical trend, you need to supply supporting analysis for

IFT Notes for the Level III Exam

www.ift.world

Page 3


Capital Market Expectations

IFT Notes

your forecast.
Refer to Example 3 from the curriculum.
Step 3: Specify the method(s) and/or model(s) that will be used and their information requirements.
Section 3 discusses several methods that can be used to set capital market expectations, some of which
may be more appropriate than others in different circumstances. You should consider the time horizon
when selecting appropriate model. For example, if the time horizon is long, a discounted cash flow
model can be used.
Step 4: Determine the best sources for information needs. Using relevant and accurate data is critical
to the process of setting capital market expectations. You need to consider the quality of data, the cost
involved and the frequency of data (for example, daily data, monthly data etc.) Exhibit 33 provides a list
of useful data sources.
Step 5: Interpret the current investment environment using the selected data and methods, applying
experience and judgment. For example, if you believe that the economy is headed towards a recession,
then you need to factor this in your expectations. You cannot say that the historically high returns on

equities will continue in the current investment environment.
Step 6: Provide the set of expectations that are needed, documenting conclusions. Having analyzed
and interpreted the data, in this step you actually document your expectations. You basically answer the
questions that were formulated in Step 1. A good forecast should be:
 Unbiased, objective and well researched
 Efficient i.e. you need to minimize forecast errors
 Internally consistent, you should not make contradicting predictions. For e.g. you cannot predict
that economy will go in a recession and equities will continue giving high returns.
Step 7: Monitor actual outcomes and compare them to expectations, providing feedback to improve
the expectations-setting process. This purpose of this step is to continually refine and improve the
forecasting process.
Refer to Example 4 from the curriculum.
Refer to Example 5 from the curriculum.

2.2 Challenges in Forecasting
This section addresses LO.b:
LO.b: Discuss challenges in developing capital market forecasts
Nine challenges encountered in developing capital market forecasts are:
2.2.1. Limitations of Economic Data
Three basic issues to consider for any economic data are:
 Timeliness: Making accurate forecasts requires access to timely data. For example, the US
Bureau of Labor Statistics releases monthly non-farm payroll data on the first Friday of the
following month. By contrast, data measures for smaller, less developed economies may take
IFT Notes for the Level III Exam

www.ift.world

Page 4

Capital Market Expectations




IFT Notes

months to collect, process, and disseminate. Older, stale data is less useful when developing
capital market expectations.
Accuracy: In addition to being timely, data must also be accurate. Data that requires significant
revisions after its initial publication is less reliable and therefore less useful for the purpose of
forecasting capital market expectations.
Definitions and calculation methods: Statistics agencies often make changes to their methods of
collecting and processing economic data. Analysts must be aware of the effect of the changes
and whether data produced using the new methods is consistent with data produced using the
old methods. For example, many years ago GNP was popularly used but in the last few decades
GDP has become the standard for measuring an economy.

Refer to Example 6 from the curriculum.
2.2.2. Data Measurement Errors and Biases
The three major issues are:
 Transcription errors: Transcription errors, which are “errors in gathering and recording data”,
can be as simple as data entry errors. For example, the number “52” may have been entered
when the correct number is 25. Ideally, data providers will have processes to reduce or
eliminate transcription errors.
 Survivorship bias: For example, if you are looking at the returns of a hedge fund index, then you
need to be aware of the fact that only hedge funds that performed well and survived have
reported their performance. Hedge funds that did not perform well and did not survive, have
not reported their performance. So survivorship bias causes:
o An upward bias for reported returns

o Overly-optimistic expectations of future returns
 Appraisal (smoothed) data: The prices of assets such as real estate, which do not trade in liquid
market, are based on periodic appraisals. If appraisals are done, for example, each month, the
daily prices may be interpolated. As shown in Example 7, the periodic snapshots from appraisals
smooth out the true volatility of returns. The consequences of smoothed data are:
o A reported standard deviation of returns that is below the true standard deviation
o A downward bias for reported correlations with other assets
Refer to Example 7 from the curriculum.
Refer to Example 8 from the curriculum.
2.2.3. The Limitations of Historical Estimates
Regime change: A key question when using historical data is determining the appropriate time period to
analyze. If we are certain that the same return drivers observed in historical data will continue to drive
future returns, we can include data going back as long as these return drivers are relevant (i.e., the data
is “stationary”). However, events such as regime changes often cause return drivers to change, which
results in nonstationary data. Effectively, the data predating a change is representative of one regime
and the data from the subsequent period represents a different regime. Extending the length of the
historical period being analyzed increases the risk of including data from multiple regimes. Only
historical data from a regime that is fully representative of current and expected market conditions
should be used.

IFT Notes for the Level III Exam

www.ift.world

Page 5


Capital Market Expectations

IFT Notes

To overcome the problem, and to identify if a regime change has occurred, we use regression analysis
with dummy variables.
Refer to Example 9 from the curriculum.
2.2.4. Ex Post Risk Can Be a Biased Measure of Ex Ante Risk
Ex ante risk is the risk that you are anticipating. In contrast, ex post risk is the risk that is based on the
data that you have seen in the past. Often, analysts are influenced by the historical value of risk while
making future estimates of risk.
2.2.5. Biases in Analysts’ Methods
Commonly observed biases are:
 Data mining bias: If an analyst takes the same set of data and keeps running computer
simulations till he finds some patterns. This pattern may not have an economic justification. This
is an example of data-mining bias. To overcome this problem, the best forecasting models limit
the variables used to those that have an “explicit economic rationale”.
 Time period bias: Analysts can demonstrate time-period bias by basing their forecasts on time
periods were things were a little different. For e.g. small cap stocks usually outperform large cap
stocks. But if you looked at data only from the 1975-1983 time period, you would conclude that
large cap stocks outperform small cap stocks.
2.2.6. The Failure to Account for Conditioning Information
Capital market expectations depend heavily on the assumptions analysts make regarding market
conditions. For example, Exhibit 7 (below) from Asset Allocation, Section 4.2.3 shows that correlations
between developed market and emerging market indexes tend to spike during periods of economic
crisis. A forecast of return correlations that is based on the assumption of normal market conditions is of
no relevance during periods of economic crisis.

IFT Notes for the Level III Exam

www.ift.world

Page 6

Capital Market Expectations

IFT Notes

2.2.7. Misinterpretation of Correlations
Correlation is not (necessarily) causation. As noted in the curriculum, there are at least three possible
explanations for a high correlation between variable A and variable B:
1. A predicts B
2. B predicts A
3. A third variable C predicts both A and B
After observing a high correlation between two variables, you need to correctly predict where that high
correlation is coming from.
Refer to Example 10 from the curriculum.
2.2.8. Psychological Traps
Biases that should be considered with respect to forecasting capital market expectations are discussed
below:
 Anchoring trap: This refers to the tendency of investors to focus on a specific purchase price or
price target. In the context of capital market expectations, an analyst may become anchored on
the first information he receives and fail to adequately incorporate new information that
suggests the first information is no longer accurate.
 Status quo trap: The status quo trap is the tendency to set capital market expectations based on
the assumption that current economic trends will continue. In Example 11, Philip Lasky expects
the recent market downturn to continue despite the fact that his portfolio has generated
positive risk-adjusted returns over the past three years.
Refer to Example 11 from the curriculum.
 Confirming evidence trap: The confirming evidence trap, is the tendency to give greater weight
to information that supports one’s preexisting beliefs. In Example 11, Philip Lasky has read
numerous estimates of the Canadian equity risk premium, but repeatedly refers to the most

pessimistic of those in his conversation with Cynthia Casey.
 Overconfidence trap: When setting capital market expectations, analysts often rely on models,
which can lead them to provide overly-precise forecasts and refuse to consider the possibility
that outcomes may fall outside a narrow range.
 Prudence trap: Analysts may moderate their capital market expectations in order to avoid
appearing extreme and out-of-line with the market consensus. In Example 11, Cynthia Casey
revises her initial estimate of economic growth downward after perceiving that many of her
clients consider this view to be overly-optimistic.
 Recallability trap: When setting capital market expectations, analysts can be unduly influenced
by memories of past events, which result in skewed forecasts. For example, a manager with
strong memories of failing to profit from a bull market may produce overly-optimistic forecasts.
2.2.9. Model Uncertainty
The uncertainty surrounding which model can be used to generate accurate forecasts is called model
uncertainty.
By contrast, an analyst may be certain about which model to use, but uncertain about the quality of the
input data. This second form of uncertainty is called input uncertainty.

IFT Notes for the Level III Exam

www.ift.world

Page 7


Capital Market Expectations

IFT Notes

3. Tools for Formulating Capital Market Expectations
In order to produce these estimates, an analyst can use:

 Formal research tools (see Section 3.1)
 Survey and panel methods (see Section 3.2)
 Judgment based on their past experiences (see Section 3.3)

3.1 Formal Tools
This section addresses LO.c:
LO.c: 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
Compared to the methods discussed in sections 3.2 and 3.3, formal research tools are empirically-based
methods designed to produce precise forecasts of variables such as the expected return for a given asset
class over a specific period. Formal quantitative tools are used extensively throughout the investment
sector, because they allow analysts to document the use of an objective forecasting process.
The tools discussed in this section are:
 Statistical methods (3.1.1)
 Discounted cash flow (DCF) models (3.1.2)
 Risk premium approach (3.1.3)
 Financial market equilibrium (3.1.4)
Note that Example 4 (in Section 2.1) provides a brief discussion of each of these tools.
3.1.1 Statistical Methods
When studying the statistical methods that can be used to develop capital market expectations, it is
helpful to remember the end product of this process. Exhibit 10 from Example 18 (Section 3.1.4) is
shown below as a reminder.

IFT Notes for the Level III Exam

www.ift.world

Page 8

Capital Market Expectations

IFT Notes

Historical Statistical Approach: Sample Estimators: The “simplest approach” to generate the returns,
standard deviations, and correlations that appear in Exhibit 10 would be to use their historical averages.
For example, as shown in Exhibit 3, the arithmetic mean annual return for US equities was 8.3 percent
with a standard deviation of 20.3 percent between 1900 and 2010. If the analyst believes that the
factors that drive US equity returns were constant during this period and are representative of current
and expected market conditions, she may use on these historical averages.
Shrinkage Estimators: Rather than relying exclusively on historical data, an analyst may use the
shrinkage estimation method, which produces a forecast that is a weighted average of historical data
and data generated using another forecasting method. In Example 12, Cynthia Casey gives a 0.3
weighting the covariance figure derived from historical data and a 0.7 weighting to the covariance figure
generated using a factor model approach.
Refer to Example 12 from the curriculum.
Time-Series Estimators: Time-series models estimate a variable’s future value based on its past (lagged)
values (and possibly lagged values of other variables). The relevant lagged values are plugged into a
regression formula, which produces a forecast of the dependent variable. For example, volatility in the
current period can be stated as the weighted average of the previous period volatility and a random
error term.
Multifactor Models: Multi-factor models use regression analysis of historical data to identify return
drivers, which are used as independent variables in a regression formula that produces a forecast of the
dependent variable. They are useful for the following reasons:
 Returns on all assets are related to a common set of return divers
 Filters out noise (when factors are well chosen)

IFT Notes for the Level III Exam

www.ift.world

Page 9


Capital Market Expectations


IFT Notes

Makes it easy to verify the consistency of the covariance matrix

Exhibit 4 assumes that the two factors Global Equity Factor and Global Bonds Factor drive the returns of
all assets. Given a standard deviation of 14% for equities and 4% for bonds and a correlation of 0.3
among the two factors, we can create the following factor covariance matrix.

Global Equity
Global Bonds

Factor Covariance Matrix
Global Equity
0.0196 (0.14 x 0.14 )
0.0017 (0.14 x 0.04 x 0.3)

Global Bonds
0.0017 (0.14 x 0.04 x 0.3)
0.0016 (0.04 x 0.04)

To derive the asset covariance market we need to know how a market responds to factor movements.
Refer to Exhibit 5 which shows the hypothetical statistics for five markets. The numbers are derived

through statistical methods such as regression of historical data.

Market A
Market B
Market C
Market D
Market E

Sensitivities
Global Equity (F1)
Global Bonds (F2)
1.10
0
1.05
0
0.9
0
0
1.03
0
0.99



Residual Risk (%)
10.0
8.0
7.0
1.2
0.9

In the above example, if Market A moves by 110 points in response to 100 point move of global equities,
then the factor sensitivity of Market A to Factor 1 (Global Equity) is 1.1
We can say that Market A is a pure equity market since the factor sensitivity to global bonds is 0.
The covariance between Markets A and B can be calculated using the following formula:

Mij=bi1bj1Var(F1)+bi2bj2Var(F2)+(bi1bj2+bi2bj1)Cov(F1,F2)
(For i=1 to 5, j = 1 to 5, and i≠j)
M12 = (1.1)(1.05)(0.0196) + (0)(0)(0.0016) + [(1.10)(0) + (0)(1.05)](0.0017) = 0.0226
3.1.2 Discounted Cash Flow Models
Discounted cash flow (DCF) models provide an expected return (or fair price) based on cash flows and
expected growth. Because they are forward-looking, DCF models are especially useful in the process of
setting long-term capital market expectations in stable, developed markets. They are much less
appropriate for short-term forecasts. DCF models can be applied to equity markets as well as fixedincome markets.
Equity Markets
Gordon Growth Model: The best-known DCF model is the Gordon (constant) growth model, which
appears below:

IFT Notes for the Level III Exam

www.ift.world

Page 10


Capital Market Expectations

IFT Notes

D0 = Dividend (current period)

D1 = Dividend (next period)
E(Re) = Expected return
P0 = Market value or price
g = Growth rate
A critical component of the Gordon growth model is the growth rate for corporate earnings and
dividends (g), which can be estimated using the nominal GDP growth rate for the overall economy.
However, market indexes are not perfectly representative of the overall economy and it may be
necessary to adjust the nominal GDP growth rate by adding (or subtracting) an estimate of excess
corporate growth. An index that is more representative of the overall economy will require a smaller
adjustment compared to a less representative index.
Grinold-Kroner model: Like the Gordon growth model, the Grinold-Kroner model (shown below) can also
be used to calculate the expected return for a market index.
𝐸(𝑅𝑒 ) ≈

𝐷1
− ∆𝑆 + 𝑖 + 𝑔 + ∆𝑃𝐸
𝑃

The components of the Grinold-Kroner model are:
 Income Return = D1/P – ΔS
 Nominal Earnings Growth Return = i + g
 Re-pricing Return = ΔPE
Important points to note are:
 Income return: D1/P is the same dividend yield that was used in the Gordon growth model.
However, because many companies have chosen to distribute cash to shareholders in the form
of share repurchases (as opposed to dividends), the Grinold-Kroner model includes ΔS, which is
called the repurchase yield and is expressed as the percentage change in the number of shares
outstanding, as an adjustment for share repurchases . An increase in the number of shares
outstanding is a negative repurchase yield and lowers the income return. By contrast, a
decrease in the number of shares outstanding means that investors are getting money and

results in a higher income return.
 Nominal earnings growth: This includes both estimated real long-term earnings growth (g) and a
long-term inflation forecast (i).
 Repricing return: This component of expected return is simply the expected percentage change
in price/earnings ratio (ΔPE).
Refer to Example 13 from the curriculum.
Refer to Example 14 from the curriculum.
Fixed-Income Markets
Discounting future cash flows is as “standard tool” for determining the value of fixed-income securities.

IFT Notes for the Level III Exam

www.ift.world

Page 11


Capital Market Expectations

IFT Notes

The rate at which future cash flows are discounted is referred to as the yield to maturity (YTM).
However, using a DCF model to valued fixed-income securities is based on the (often unrealistic)
assumption that cash flows received in the form of coupon payments can be reinvested at the YTM.
3.1.3 The Risk Premium Approach
Future cash flows that can be predicted with complete certainty can be discounted at the risk-free rate.
However, if cash flows are subject to risks such as the credit risk associated with corporate bonds,
investors will apply a higher discount rate and valuations will be lower. The risk premium approach
combines (or builds up) various risk premiums into a single discount rate that is used to value future
cash flows.

A General Expression
The single discount rate produced by the risk premium approach is referred to as the expected return
for an asset – that is to say, investors expect this return as compensation for the various sources of risk
that they will be exposed to. As shown in the exhibit below, risk premiums of 2.5 percent and 1.5
percent are added to the risk-free rate of 4.5 percent in order to arrive at an overall discount rate of 8.5
percent.

Building up to a discount rate
9.00%
8.00%
7.00%
6.00%
5.00%

[SERIES NAME]
[VALUE]
[SERIES NAME]
[VALUE]

Overall discount
rate [VALUE]

4.00%
3.00%
2.00%

[SERIES NAME]
[VALUE]

1.00%

0.00%

Fixed-Income Premiums
For fixed-income securities, the base discount rate is the nominal risk-free rate, which is the sum of the
real risk-free rate and a premium for expected inflation. In practice, the YTM on a government bond,
such as the 10-year US Treasury, is used as a proxy for the nominal risk-free rate.
For corporate bonds, investors will demand a default risk premium, which increases the discount rate.
Additional premiums may be applied to compensate for illiquidity, longer maturity, and even taxes.
Refer to Example 15 from the curriculum.
Refer to Example 16 from the curriculum.
Refer to Example 17 from the curriculum.

IFT Notes for the Level III Exam

www.ift.world

Page 12


Capital Market Expectations

IFT Notes

The Equity Risk Premium
Investors always have the option of simply investing in the risk-free asset. Therefore, risky assets must
offer higher expected returns as compensation for their higher level of risk. For equities, this systematic
risk is captured by the equity risk premium, which is the difference between expected returns for
equities and the risk-free rate. As shown in Exhibit 9, the average equity risk premium observed in 17
developed economies over the period of 1900 to 2010 was 5 percent.
Assuming a nominal risk-free rate of 4.5 percent (as represented by the YTM on a long-term government

bond) and an equity risk premium of 5 percent, the discount rate applied to equities would be 9.5
percent. This method of calculating an equity market discount rate is also known as the bond-yield-plusrisk-premium method.
3.1.4 Financial Market Equilibrium Models
Financial equilibrium models are used to value asset classes during period in which the supply and
demand are in balance (i.e., the market is at equilibrium). The most well-known financial market
equilibrium model is the international capital asset pricing model (ICAPM), which is the basis for the
Singer-Terhaar approach to forecasting capital market expectations.
The Singer-Terhaar model is used to calculate a risk premium for an asset class (e.g., Latin American real
estate or European equities) based on the sensitivity of its returns relative to those of the global
investable market (GIM), which is discussed further below. Formally, this is calculated using Equation 10:
𝑅𝑃𝑖 = 𝜎𝑖 𝜌𝑖,𝑀 (

𝑅𝑃𝑀
)
𝜎𝑀

where,
RPi is the risk premium for a given asset class i
σi is the standard deviation of returns for asset class i
ρi,M is the correlation between returns for asset class i and returns for the global investable market (GIM)
RPM is the risk premium for the GIM (expected returns above the risk-free rate)
σM is the standard deviation of returns for the GIM
Note that (RPM/ σM) is the GIM Sharpe ratio.
Global Investable Market (GIM):
The global investable market (GIM) is defined as “a practical proxy for the world market portfolio
consisting of traditional and alternative asset classes with sufficient capacity to absorb meaningful
investment.” The Singer-Terhaar model calculates the expected return for an asset class based on the
sensitivity of its returns with the GIM. For exam purposes, the key piece of information you will need is
the GIM Sharpe ratio, which is typically estimated at approximately 0.30. You may simply be given a GIM
Sharpe ratio of, for example, 0.32. Alternatively, you may be required to calculate this figure using the

GIM risk premium (the expected return for the GIM minus the investor’s domestic risk-free rate) and the

IFT Notes for the Level III Exam

www.ift.world

Page 13


Capital Market Expectations

IFT Notes

standard deviation of the GIM’s returns (σM).
Market Integration:
As mentioned, the Singer-Terhaar model is used to calculate a risk premium for an asset class. If all
investors from all markets could easily invest in the asset class, it be perfectly integrated. In the case of
perfect integration, the risk premium could be calculated using Equation 10. The curriculum gives the
example of Canadian equities, which have a standard deviation of 17% and a 0.70 correlation with the
GIM. Using a GIM Sharpe ratio of 0.28, the risk premium for Canadian equities is:
17% x 0.70 x 0.28 = 3.33%
However, asset classes are rarely (if ever) fully-integrated with the GIM. Therefore, the Singer-Terhaar
model produces a risk premium that is a weighted average of two numbers:
1. The risk premium assuming full integration with the GIM
2. The risk premium assuming no integration with (fully segmented from) the GIM
In both cases, the risk premium is calculated using Equation 10. When full integration with the GIM is
assumed, ρi,M is simply the correlation between the asset class and the GIM. In the curriculum’s example
of Canadian equities, ρi,M is 0.70 and, as shown above, generates a risk premium of 3.33%.
When full segmentation is assumed, ρi,M becomes 1.0 because the asset class is assumed to be perfectly
correlated with itself. Equation 10 is still used, but ρi,M can be dropped. However, it may be helpful to be

consistent and simply use a different number for ρi,M. In the curriculum’s example of Canadian equities,
the risk premium assuming full segmentation is:
17% x 1.0 x 0.28 = 4.76%
Note that the risk premium will always be higher when full segmentation is assumed because ρi,M will
always be less than 1.0 when full integration is assumed.
Illiquidity Premium
As mentioned in Section 3.1.3.2, investors may demand extra yield (i.e., a premium, which is added to
the discount rate) as compensation for holding an illiquid bond. With the Singer-Terhaar model, an
illiquidity premium (if given) is added.
Steps in Singer-Terhaar Model
Below is a demonstration of how to use the Singer-Terhaar model to calculate a risk premium and
expected return. The data are taken from Example 19.

IFT Notes for the Level III Exam

www.ift.world

Page 14


Capital Market Expectations

IFT Notes

Step 1: Calcultate the risk premium assuming full integration with GIM. Add
illiquidity premium (if given)

(11.5% x 0.5 x 0.28) + 0.30% = 1.91%
Step 2: Calculate the risk premium for the same asset assuming full segmentation
from GIM. Add illiquidity premium (if given)

(11.5 x 1.0 x 0.28) + 0.30% = 3.52%
Step 3: Calculate the weighted average of the risk premiums based on level of
integration with GIM.

(1.91% x 0.70) + (3.52% x 0.30) = 2.39%
Step 4: Calculate the expected return by adding the weighted risk premium and
the risk-free rate.

2.39% + 3.00 = 5.39%
Exam tips related to the Singer-Terhaar model:
 You should be able to do a basic Singer-Terhaar calculation in 5 minutes or less
 Be sure to note whether they are asking for the risk premium or the expected return (which is simply
the risk premium plus the risk-free rate).
 If given more than one risk-free rate, use the investor’s domestic risk-free rate.
Refer to Example 18 from the curriculum.
Refer to Example 19 from the curriculum.

3.2 Survey and Panel Methods
Sections 3.2 and 3.3 address LO.d:
LO.d: Explain the use of survey and panel methods and judgment in setting capital market
expectations
Surveys
Section 3.1 covered several methods that can be used to estimate the returns, standard deviations, and
correlations that are required to set capital market expectations. An alternative approach is to ask a
group of academics and/or professionals for their estimates. For example, Exhibit 12 shows the results
of surveys of over 200 financial economists who were asked to provide their estimate of the long-term
US equity risk premium. In Example 24 (Section 4.1.3), Hans Vermalen bases his forecast of German
inflation in part on a survey of manufacturers.
Panels

The panel of forecasting capital market expectations is simply the survey method, but the respondents
remain relatively unchanged over time.
Refer to Example 20 from the curriculum.

IFT Notes for the Level III Exam

www.ift.world

Page 15


Capital Market Expectations

IFT Notes

3.3 Judgment
An analyst may use formal statistical methods to generate a set of capital market expectations and then
make adjustments based personal experience and judgment. In Example 21, William Chew uses a
multifactor model to produce a correlation estimate of between 0.40 and 0.45, but adjusts this
correlation down to 0.30 based on his analysis of inflation forecasts. While judgments may not be
empirically precise, they are commonly used in practice. As noted in Section 4.5.1, even forecasters who
develop highly-specialized econometric models “use a great deal of personal judgment in arriving at
forecasts.”
Refer to Example 21 from the curriculum.

4. Economic Analysis
“History has shown that there is a direct yet fluid relationship between actual realized asset returns,
expectations for future asset returns, and economic activity.”
This is a long session which covers:
 Business cycle and inventory cycle

 Economic growth trends
 Exogenous shocks
 International interactions
 Economic forecasting
 Forecasting asset class returns
This section addresses LO.e:
LO.e: Discuss the inventory and business cycles, and the effects that consumer and business
spending, and monetary and fiscal policy have on the business cycle

4.1 Business Cycle Analysis
Business cycle analysis is an important component of capital market expectations because asset class
returns are significantly influenced by patters of overall economic activity. However, correctly predicting
future economic activity and returns is a challenge.
Gross Domestic Product (GDP)
Business cycle analysis focuses on fluctuations in the growth rate for an economy’s gross domestic
product (GDP). Formally, GDP is defined as “the total value of final goods and services produced in an
economy during a year.”
In any given year, GDP growth will be faster or slower depending on economic conditions. For example,
US GDP grew by 3.3 percent (in real terms) in 2005 and 1.8 percent in 2007. However, as will be
discussed in Section 4.2, a developed economy like America’s can be expected to grow at an average
annual rate of approximately 2.5 percent (in real terms) over the long run. This is referred to as the long-

IFT Notes for the Level III Exam

www.ift.world

Page 16


Capital Market Expectations

IFT Notes

term trend growth rate.
Output Gap
The output gap can be thought of as the difference between the current GDP growth rate and the longterm trend growth rate. When short-term GDP growth is below the long-term trend growth rate, the
output gap is positive and economic output is below-capacity. Conversely, when the economy is growing
faster than the long-term trend growth rate, the output gap is negative and inflationary pressures build.
Using the figures from above, the US economy was growing above the assumed long-term trend growth
rate of 2.5 percent in 2005 and below this rate in 2007.
Recession
The generally accepted definition of a recession is two consecutive quarters of negative economic
growth.
4.1.1 The Inventory Cycle
As overall economic growth fluctuates, manufacturers adjust their production levels based on expected
sales. When the economy is growing, companies are bullish about their future sales prospects and
production is increased. As the economy slows, companies lower their expectations of future sales and
reduce production.
Interpreting the inventory-to-sales ratio: As shown in Exhibit 14, a rising inventory-to-sales ratio is
typically associated with slower economic growth, as consumers spend less and inventories pile up. By
contrast, a declining inventory-to-sales ratio is typically associated with faster economic growth, as
consumer spending increases at a faster rate than production. However, caution is required when
interpreting inventory data. For example, a rising inventory-to-sales ratio may be a positive or negative
signal for economic growth depending on the stage of the business cycle. Additionally, while inventory
cycles of 2 to 4 years have been observed, the overall trend shown in Exhibit 14 is for declining
inventory-to-sales ratios as retailers, manufacturers, and suppliers have adopted “just in time” inventory
practices.
4.1.2 The Business Cycle
This section covers LO.f
LO.f discuss the effects that the phases of the business cycle have on short-term/long-term capital

market returns;
The five phases of a business cycle are:
 Initial recovery
 Early upswing
 Late upswing
 Slowdown
 Recession
Refer to Exhibit 15 which summarizes these phases.

IFT Notes for the Level III Exam

www.ift.world

Page 17


Capital Market Expectations

Phase

Economy

Fiscal and
Monetary
Policy

1. Initial
recovery

Inflation still

declining

Stimulatory
fiscal policies

2. Early
upswing

Healthy economic
growth; inflation
remains low

3. Late
upswing

Inflation gradually
picks up

4. Slowdown

5. Recession

IFT Notes

Confidence

Capital Markets

Confidence
starts to

rebound

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

Increasing
confidence

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

Boom mentality

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

Inflation continues to
accelerate; inventory
correction begins

Confidence
drops

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

Production declines;
inflation peaks

Confidence
weak

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

Policy becomes
restrictive

Refer to Example 22 from the curriculum.
4.1.3 Inflation and Deflation in the Business Cycle
This section addresses LO.g:
LO.g: Explain the relationship of inflation to the business cycle and the implications of inflation for
cash, bonds, equity, and real estate returns
Inflation tends to be highest in the late upswing phase of the economic cycle when short-term GDP
growth is above the trend rate and the economy is operating above-capacity and recedes as economic
growth is below the trend rate. Central banks strive to prevent inflation from increasing above an
acceptable level – indeed many central banks are mandated to keep inflation below a specific target
level. As shown in Exhibit 18, inflation has a neutral effect most asset classes when it is at or below an
expected level, which can be thought of as the economy being in an equilibrium state. The exception is
equities, which tend to outperform during periods of low inflation. By contrast, both bonds and equities
underperform when inflation rises above expectations.
Deflation is simply negative inflation, which means that overall prices are lower than they were in the
previous period. Deflation is considered to be a threat because it undermines debt-financed

investments. Note in Exhibit 18 that real estate, which is a highly-leveraged investment, suffers during
periods of deflation. More importantly, deflation reduces the ability of central banks to stimulate the
economy by lowering interest rates because their target interest rate cannot be set below zero.

IFT Notes for the Level III Exam

www.ift.world

Page 18


Capital Market Expectations

IFT Notes

When interest rates are very low and unemployment is high, central banks may engage in quantitative
easing (QE). QE is a form of monetary policy tool in which a central bank injects liquidity into the
financial system by purchasing high-quality fixed-income securities, mortgage-backed securities and
high-quality corporate bonds from banks and other financial institutions. As a result of QE, central bank
balance sheets and bank reserves increase while sovereign bond yields fall. Unlike conventional open
market operations, QE involves large-scale, ongoing purchases of securities which may result in quasipermanent increases in the level of bank reserves. In order to fund these purchases, a central bank
creates an equally large quantity of bank reserves in the form of central bank deposits.
Refer to Exhibit 18 which shows the effects of inflation/deflation on asset classes.
Real Estate/Other Real
Assets

Cash

Bonds

Equity

Inflation at or
below
expectations

Short-term
yields steady
or declining.
[Neutral]

Yield levels maintained;
market in
equilibrium. [Neutral]

Bullish while market in
equilibrium
state.[Positive]

Cash flow steady to
rising slightly. Returns
equate to long-term
average. Market in
general
equilibrium. [Neutral]

Inflation above
expectations

Bias toward

rising rates.
[Positive]

Bias toward higher yields
due to a higher inflation
premium. [Negative]

High inflation a
negative for financial
assets. Less negative
for
companies/industries
able to pass on inflated
costs. [Negative]

Asset values increasing;
increased cash flows
and higher expected
returns. [Positive]

Deflation

Bias toward
0% shortterm rates.
[Negative]

Purchasing power
increasing. Bias toward
steady to lower rates (may
be offset by increased risk of

potential defaults due to
falling asset
prices). [Positive]

Negative wealth effect
slows demand.
Especially affects assetintensive, commodityproducing (as opposed
to commodity-using),
and highly levered
companies. [Negative]

Cash flows steady to
falling. Asset prices face
downward
pressure. [Negative]

Refer to Example 23 from the curriculum.
Refer to Example 24 from the curriculum.
4.1.4 Market Expectations and the Business Cycle
If an investor can identify the current phase of the cycle and correctly predict when the next phase will
begin, he or she should be able to outperform the market. Furthermore, if a recession is being
predicted, it is useful to estimate the severity. For developed economies, recessions will be less severe
if:



The upswing was relatively short of mild
There was no asset bubble

IFT Notes for the Level III Exam

www.ift.world

Page 19


Capital Market Expectations



IFT Notes

Inflation is relatively low (so central bank can respond)
Global economic and political environments are stable

Refer to Example 25 from the curriculum.
4.1.5 Evaluating Factors that Affect the Business Cycle
To set capital market expectations, we need to focus on business cycle analysis on four areas:
1. Consumer spending: In most economies, this is the biggest component of GDP. It accounts for
nearly 60% to 70% of the GDP. To predict consumer spending we look at:
1. Store sales data, consumption data
2. Consumer income data after tax
3. Employment data
2. Business spending: This is a smaller share of the GDP, relative to consumer spending. However it
is considerably more volatile. To predict business spending we look at business investment and
inventories. US Example: Purchasing Managers Index (PMI). This is a measure of how much
businesses are purchasing.
3. Foreign trade: Foreign trade typically accounts for 10% to 15% of the GDP of most large
economies.
4. Government activity: Monetary and fiscal policy can impact the GDP. These are explained

below.
This section addresses LO.h:
LO.h: Demonstrate the use of the Taylor rule to predict central bank behavior
Monetary Policy: Central banks should use monetary policy (primarily interest rates) to control the
economy and prevent it from either overheating or suffering in a recession for too long.
As an analyst you should try to predict the central bank’s policy rate. This can be done using the Taylor
rule.

Roptimal = Rneutral + [0.5(GDPforecast − GDPtrend) + 0.5(Iforecast − Itrend)]
Where,
Roptimal
Rneutral
GDPgforecast
GDPgtrend
Iforecast
Itarget

= the target for the short-term interest rate
= the short-term interest rate that would be targeted if GDP growth were on trend and
inflation on target
= the GDP forecast growth rate
= the observed GDP trend growth rate
= the forecast inflation rate
= the target inflation rate

Short-term GDP growth rate above the trend rate and above-target expected inflation will result in a

IFT Notes for the Level III Exam

www.ift.world

Page 20


Capital Market Expectations

IFT Notes

target rate that is above the neutral rate.
What Happens When Interest Rates Are Zero or Negative?
Under “zero lower bound,” negative policy rates are not sustainable as the negative interest rates lead
to substantial deposit withdrawals and fall in banks reserves, resulting in upward pressure on interest
rates and downward pressure on economic growth due to credit contraction. However, as of the
beginning of 2017, negative policy rates have proven to be sustainable because unlike vault cash, bank
deposits and bank reserves provide an implicit yield or convenience value by facilitating trade in goods,
services, and financial instruments. As long as this convenience value is greater than the explicit cost of
holding those deposits, negative policy rates are sustainable. Nonetheless, the effectiveness of
expansionary monetary policy is dubious at low and negative interest rate levels because in a negative
interest rate environment, consumers, investors, businesses, and banks tend to have greater levels of
uncertainty and therefore, they may not act as desired by monetary policy makers.
Implications of Negative Interest Rates for Capital Market Expectation
It is difficult to incorporate negative interest rates into capital market expectations over finite horizons.
When short-term rates are negative, the long-run equilibrium short-term rate can be used as the
baseline rate for forming capital market expectations. This rate can be estimated using the neutral policy
rate (Rneutral) in the Taylor rule adjusted for a modest spread between policy rates and default-free rates.
Following are some key considerations when forming capital market expectations in a negative interest
rate environment:






Useful historical data (including instances of negative rates) may not be available or is less reliable;
as a result, quantitative models (statistical models, in particular) based on such historical data may
not provide accurate results;
Since historical averages may be less useful, forecasting models must account for differences
between the current environment and historical averages;
Simultaneous use of different monetary policy tools may distort market relationships, e.g. shape of
the yield curve or the performance of specific sectors;

Refer to Example 26 from the curriculum.
Refer to Example 27 from the curriculum.
This section addresses LO.i
LO.i: Interpret the shape of the yield curve as an economic predictor and discuss the relationship
between the yield curve and fiscal and monetary policy
Fiscal Policy: Fiscal policy refers to the government’s manipulation of tax revenue and spending in order
to influence the economy. In analyzing fiscal policy, an analyst should remember two points:
1.

Focus on changes in budget deficit rather than the absolute level. An increase in the budget deficit
(increase in government spending > increase in tax revenue) is referred to as an expansionary fiscal

IFT Notes for the Level III Exam

www.ift.world

Page 21


Capital Market Expectations

IFT Notes

policy. Governments typically engage in such a policy to get out of a recession.
2. Focus on changes in deficit due to deliberate changes in government fiscal policy. Recognize that
budget deficit changes even without deliberate changes in government fiscal policy. During
recessions the budget deficit will automatically widen because unemployment benefits (spending)
increase and tax revenue falls. On the other hand, when the economy grows the budget deficit
automatically decrease because unemployment benefits decrease and tax revenue increases.
Shape of the yield curve as an economic predictor: An upward sloping yield curve indicates that shortterm rates are low relative to long-term rates. This shape implies that economic activity will improve. It
has been observed that the yield curve tends to flatten (or even become inverted) prior to a recession.
The fiscal/monetary policy usually impacts the shape of the yield curve. Refer to Exhibit 20 which shows
the four possibilities.
Fiscal Policy

Monetary Policy

Loose

Tight

Loose

Yield curve steep

Yield curve moderately steep

Tight

Yield curve flat

Yield curve inverted

4.2 Economic Growth Trends
This section addresses LO.j:
LO.j: Identify and interpret the components of economic growth trends and demonstrate the
application of economic growth trend analysis to the formulation of capital market expectations
The components of economic growth trends are:
 Growth from labor inputs
o Labor force growth
o Labor force participation
 Growth from labor productivity
o Growth from capital inputs
o Total factor productivity (TFP) growth
Refer to Example 28 from the curriculum.
Investments also play a crucial role in GDP growth, because a high investment amount leads to more
capital. In fast-growing economies like Singapore and China, between 30 percent and 40 percent of GDP
is invested annually. Slower-growing countries in South America have typically been able to manage
capital investment rates of only 15 to 20 percent of GDP.
Economic growth is also influenced by government policies. Some of the pro-growth structural policies
are:
 Fiscal policy is sound
IFT Notes for the Level III Exam

www.ift.world

Page 22


Capital Market Expectations






IFT Notes

Public sector is minimally invasive on the private sector
Competition within the private sector is encouraged
Infrastructure and human capital development are supported
Tax policies are sound

Refer to Example 29 from the curriculum.

4.3 Exogenous Shocks
This section addresses LO.k:
LO.k: Explain how exogenous shocks may affect economic growth trends
Events such as natural disasters or political events that come from outside the economic system can be
difficult to predict, but their impact can be devastating. Because they are not expected, exogenous
shocks are not factored into current asset prices. An economy that experiences an exogenous shock
should eventually return to its long-term growth rate, but it may be several years before a full recovery.
Some examples of exogenous shocks are:
 Shifts in government policies: Most shifts in trends are likely to come from shifts in government
policies. For example, a major fiscal law that prevents the government from borrowing beyond
certain limits can be a very effective constraint on excessive spending.
 Oil Shocks: Disruptions in the oil supply caused by, for example, geopolitical crises in the Middle
East, can cause prices to spike. Because much economic activity depends on oil, higher prices
can have ripple effects throughout the economy, such as lower business investment and
consumer spending power, which can lead to higher inflation and job losses.
 Financial Crises: When asset bubbles burst, commercial banks who have made loans based on

inflated valuations, will sharply curtail lending, which can have a devastating effect for an entire
economy. In response, central banks are forced to intervene by lowering short-term interest
rates, but their scope for action is limited if a financial crisis occurs when interest rates are
already low.

4.4 International Interactions
This section addresses LO.l:
LO.l: Identify and interpret macroeconomic, interest rate, and exchange rate linkages between
economies
Dependence of a particular economy on international interaction depends on the size and degree of
specialization. Large countries with diverse economies, tend to be less influenced by developments
elsewhere than small countries.
Macroeconomic Linkages
A country’s economy is impacted by:
1. Changes in foreign demand for their exports. Take a country like India. An increase in foreign
demand of Indian exports will cause the economy to improve.

IFT Notes for the Level III Exam

www.ift.world

Page 23


Capital Market Expectations

IFT Notes

2. Changes in cross-border investments. Continuing with India, increases in foreign investments in
India will cause the economy to improve. A reduction in foreign investments will have a negative

impact on the Indian economy.
Interest Rate/Exchange Rate Linkages
Some countries directly peg their currencies at a fixed exchange rate with another currency (often the
US dollar). The advantages of a peg are:
 Businesses know that exchange rates won’t change dramatically
 Smaller economies can use currency pegs to control inflation
If Country X has pegged its exchange rate to the US dollar, the interest rates in Country X will depend on
market confidence in the peg. If confidence in the peg is high the interest rate in Country X will be
similar to the US dollar interest rate. If the peg is perceived to be unsustainable the interest rate
differential will increase. In other words, investors will demand a premium for holding Country X
currency.
For floating exchange rates, the:
 currency of the country with the higher real interest rate will appreciate, all else equal.
 currency of the country with the higher inflation rate will depreciate, all else equal.
Emerging Markets
This section addresses LO.m:
LO.m: Discuss the risks faced by investors in emerging-market securities and the country risk
analysis techniques used to evaluate emerging market economies
Emerging markets offer higher risk, higher return relative to developed markets.
Emerging economies depend on foreign debt to finance their capital investment. By contrast, developed
economies borrow from domestic sources.
Additionally, emerging economies are often characterized by dependence on specific commodities or a
manufacturing sector that is heavily concentrated in one industry.
Important factors to consider when investing in emerging markets are:
 Fiscal and monetary policy
o Deficit to GDP (2 – 4% is acceptable)
o Debt to GDP (70 – 80% is acceptable)
 Economic growth prospects
o Emerging economies should be growing faster than 4% annually (in real terms)
Because of their dependence on foreign debt and relatively undiversified economies, investors in

emerging markets should pay particular attention to the following factors:
 External accounts
o Current account deficit should be below 3 percent of GDP

IFT Notes for the Level III Exam

www.ift.world

Page 24


Capital Market Expectations





IFT Notes

o See Example 35
External debt
o Foreign debt should be below 50 percent of GDP
o Debt to current account receipts should be below 200 percent
Liquidity
o Foreign exchange reserves should be at least 200 percent of short-term debt
Political situation
o Will the government follow through on structural economic reforms?

4.5 Economic Forecasting
This section addresses LO.n:

LO.n: Compare the major approaches to economic forecasting
The major approaches to economic forecasting are:
4.5.1 Econometric Modeling
Econometric modeling generates capital market expectations by combining quantitative methods and
economic theory. Points to note are:
 Model complexity depends on a number of variables; bigger models (more variables) are not
always better
 Requires good data, which may not always be available
 Inputs are selected based on their ability to predict future economic growth
 Relationships between inputs may change over time
The advantages of this approach are:
 Good at simulating the effects of changes in specific variables
 Imposes a consistency constraint in making forecasts
 Forces the analyst to reassess prior views
 Good at forecasting economic upswings
The disadvantages of this approach are:
 Complex and time-consuming to create
 Requires careful analysis of output
 Historical relationships between variables change
 Better at predicting recoveries than recessions
4.5.2 Economic Indicators
Economic indicators are economic statistics that contain information on an economy’s recent past
activity or its current or future position in the business cycle. This is the simplest forecasting approach to
use because it requires following only a limited number of variables. Leading economic indicators are
best thought of as early signs of probable events to come.
Some of the commonly used leading indicators in the US are:
 Average weekly hours, manufacturing
IFT Notes for the Level III Exam

www.ift.world

Page 25