Building Blocks of Active Equity Portfolio Construction Active management is the pursuit of returns in excess of the benchmark, or active return, adjusted for costs for an appropriate l
Trang 1Reading 29 Active Equity Investing: Portfolio Construction
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Security analysis involves ranking relative attractiveness
of securities while portfolio construction involves
selecting the securities for investments and determine
the percentage of allocation to each one Managers
need to consider that their insights regarding returns/risks
may prove to be inaccurate or affected by unknown events
Predictions on return and risk are common to most active investment styles
2 Building Blocks of Active Equity Portfolio Construction
Active management is the pursuit of returns in excess of
the benchmark, or active return, (adjusted for costs) for
an appropriate level of risk
Active return is determined by difference in weights
between active portfolio and benchmark and expressed
mathematically as:
𝑅"= $ ∆𝑊'𝑅' (
')*
Where:
Ri = return of security i
∆𝑊' = active weight = the difference between portfolio
weights WPi and the benchmark weights WBi
Active returns are generated if:
• Gains generated overweighting securities
which outperform the benchmark are, on
average, > losses generated by
underweighting securities which outperform
the benchmark and
• Gains generated by underweighting
securities which underperform the
benchmark are, on average, > losses
generated by overweighting securities which
underperform the benchmark
2.1 Fundamentals of Portfolio Construction
Rewarded factors: Investment risks (such as market or
liquidity risks) for which the investors expect to be
compensated by a long-term return premium
Sources of active return is the same regardless of
whether the manager follows a
fundamental/discretionary approach,
quantitative/systematic approach, a bottom-up or
top-down approach, or a style such as value or growth at
reasonable price Proportion of returns sourced from
exposure to rewarded factors, alpha and luck with vary
among managers and portfolio management
approaches
Ex post active returns can be decomposed as follows:
RA =Σ(βpk − βbk) ´ Fk + (α + ε) Where:
βpk = the sensitivity of the portfolio (p) to each rewarded factor (k)
βbk = the sensitivity of the benchmark to each rewarded factor
Fk = the return of each rewarded factor (α + ε) = return which cannot be unexplained by exposure to rewarded factors The volatility of the components depends on how the manager sizes individual positions
Alpha or a is the portfolio’s active return attributable to a
manager’s skills (security selection and factor timing) and strategies e is the idiosyncratic return resulting from
a random shock or noise or luck (bad/good) It is difficult
to isolate these two sources of return
Factor methodology has become popular in generating active returns with the growth in hedge funds and disappointing performance of many active managers
2.2 Building Blocks Used in Portfolio Construction
2.2.1) First Building Block: Overweight or Underweight Rewarded Factors
Rewarded factors include market, size, value and momentum Most individual securities have a beta > or <
1 to the market factor and non-zero exposure to other factors
Managers can add value by over and above the market portfolio by choosing exposures to rewarded risks which differ from those of the market
Most managers use narrower market proxies as a benchmark Indices which do not include all publicly traded securities have a market beta which differs from
1 Managers willing to create an exposure to rewarded risk, must establish the exposure relative to his or her benchmark to achieve an expected excess return
Trang 2Important points:
• A size factor of – 1 indicates a large-cap tilt
• A capitalization-weighted large-cap index
has no sensitivity to the value and
momentum factors
• A mid-cap fund/portfolio has a positive
exposure to the size factor
A portfolio manager can use factors analyze portfolio
performance regardless of whether factors are being
targeted or she focuses on securities which are believed
to be attractively priced Portion of the return not
explained by factors includes:
• Unique skills and strategies of the manager,
• An incomplete factor model that ignores
relevant factors, or
• Exposure to idiosyncratic risks which either
contributed positively or negatively to
performance
2.2.2) Second Building Block: Alpha Skills
Second building bock and manager’s alpha comprises
of two components
1) Skillful timing of exposures to rewarded factors
2) Unrewarded factors or other asset classes (such
as cash)
Any alpha generated by active managers must be high
enough to cover the fees associated with active
management
Exposure to rewarded factors has become accessible
via rules-based indexes Successfully timing this exposure
is a source of alpha The following example of provides
an illustration:
Example: Managers believe their skill partly originates
from when rewarded factor returns are less than or
greater than their average returns (factor timings):
• Managers with a market beta < 1 (> 1)
should outperform the market when market
return is negative (positive)
• Exposure to the market factor can be
adjusted and returns timed by investing in
securities with a market beta which is > or <
1
There is no consensus on the ability to generate alpha
from factor timing Alpha can also be generated by
timing exposure to unrewarded factors such as regional
exposure, sector exposure, the price of commodities, or
security selection
Thematic exposures do not represent rewarded factors
but represent a manager’s use of his or her skills to time exposures in the anticipation of reward
§ Example: While oil is not a rewarded factor, a manager who has a specific view on oil prices and correctly anticipated future oil prices, may alter his exposure to the energy sector in the hope of earning a reward
There is little evidence of an ability to consistently time rewarded factors
2.2.3) Third Building Block: Sizing Positions
Position sizing concerns balancing manager’s confidence in alpha and factor insights while mitigating idiosyncratic risks While position sizing affects alpha and factor insights, its greatest influence is on idiosyncratic risk
A manager can achieve exposure to a factor or set of factors with greater success if concentrated portfolios are used Level of idiosyncratic risk and the potential impact of luck on performance is greater in a concentrated portfolio vs a portfolio comprising many securities
Note: In concentrated portfolios, volatility of active returns attributable to idiosyncratic risks is greater There are greater deviations between realized portfolio returns and expected returns
A manager’s belief regarding skills level will determine degree of portfolio concentration:
§ Factor-oriented managers:
o Set up and balance exposure to rewarded factors
o Targets specific exposure to factors and maintains a diversified portfolio
to minimize idiosyncratic risk
§ Stock-picker:
o Believes he is skilled at forecasting security-specific performance
o Expresses his forward-looking views using a concentrated portfolio, assuming a high level of idiosyncratic risk
2.2.4) Integrating the Building Blocks: Breadth of Expertise
Sources of a manager’s active returns include:
§ Exposure to rewarded risks
§ Timing of exposures to rewarded factors
§ Position sizing and its implications for idiosyncratic risk
A manager’s success in combining these three sources is
a function of a manager’s breadth of expertise Broader
Trang 3expertise may increase the likelihood of generating
consistent, positive active returns
Fundamental law of active management: Confidence in
a manager’s ability to outperform his benchmark
increases when that performance is attributed to a
larger sample of independent (or uncorrelated)
decisions
Example of independent decision: Overweighting two
stocks whose returns are not driven by common factors
Managers must distinguish between the effective
number of independent active decisions from the
nominal number of active decisions when constructing
portfolios
Expected active portfolio return, E(RA) = 𝐼𝐶√𝐵𝑅𝜎01𝑇𝐶
Where:
IC – Expected information coefficient of the manager – extent to which the manager’s forecasted active returns correspond to the manager’s realized active returns
BR – Breadth – the number of truly independent decisions made annually
TC – Transfer coefficient – or the ability to translate portfolio insights into investment decisions without constraints (a truly unconstrained portfolio would have a transfer coefficient of 1)
𝜎01= the manager’s active risk
3 Approaches to Portfolio Construction
Portfolio construction is heavily influenced by a
manager’s ability to add value using the building blocks:
• Factor exposures
• Timing
• Position sizing
• Breadth or depth
The portfolio construction process should reflect
manager’s beliefs with respect to the nature of skills in
the following areas:
• Systematic or discretionary
• Bottom-up or top-down
both are discussed in the sections below
Each approach:
• can vary in the extent it is benchmark aware
versus benchmark agnostic
• is implemented within a framework which
specifies acceptable levels of active risk
and active share (how similar a portfolio is to
its benchmark) relative to a benchmark
3.1 The Implementation Process: The Choice of Portfolio Management Approaches
3.1.1) Systematic vs Discretionary
The manager’s beliefs regarding the three building
blocks of portfolio construction need to be examined in
a systematic and discretionary investment process
More likely designed to extract return premiums from balanced
exposures to known, rewarded factors
Search for active returns
by building greater understanding of:
o firm’s governance
o firm’s business model
o the competitive landscape
o through development of better factor proxies
o through successful timing strategies (few factor-based systematic strategies have integrated this approach)
Incorporate research-based rules across a broad universe of securities
o Strategies incorporate management judgement to the extent of strategy design and learning process associated with strategy implementation
Integrate management judgment often on a small subset of securities
Managers may additionally consider:
o financial metrics and
o nonfinancial variables
Reduce exposure to idiosyncratic risk & use broadly diversified portfolios to achieve desired factor exposure and minimize security-specific risk
Rely on more concentrated portfolios reflecting depth of manager’s insight on the company and its
competitive landscape
Practice: Example 1, CFA Curriculum, Volume 4, Reading 29
Trang 4Systematic Strategies Discretionary Strategies
More adaptable to a
formal portfolio
optimization process
o Parameters of the
optimization must
be carefully
considered by the
manager
Managers use a less formal approach to portfolio construction
3.1.2.) Bottom-Up vs Top-Down
Top-down approach: seeks to understand overall
geo-political, economic, financial, social, and public policy
environment and project how the expected
environment will affect (in the order illustrated below):
Bottom-up approach: Develops an understanding of the
environment by evaluating the risk and return of
individual securities The aggregate of risk & return
expectations imply expectations for overall economic
and market environment
Rely on returns from
factors
o Emphasize
macro factors
Rely on returns from factors
o Emphasize security-specific factors
Investment process
emphasizes on
factoring timing-
managers
opportunistically shift
the portfolio to capture
rewarded and
unrewarded factors
o May embrace
same security
characteristics
sought by
bottom-up
managers
o May raise cash
opportunistically
when overall
view of the
market is
unfavorable
Embrace styles as Value, Growth at Reasonable Price, Momentum and Quality
o Strategies are built around
documented rewarded factors
Managers likely to run
portfolios
concentrated with
macro factors
Runs diversified or Runs diversified or
concentrated portfolios
o Top-down sector rotator can run concentrated portfolios
o Top-down risk allocators can run diversified portfolios
concentrated portfolios
o Bottom-up stock picker can run concentrated portfolios
o Bottom-up value manager can run diversified portfolios
3.1.3) A Summary of the Different Approaches
• Exposure to rewarded factors is achieved using a bottom-up or top-down approach
• Top-down managers emphasize macro factors while bottom-up managers emphasize security-specific factors
• Top-down managers following a discretionary approach are more likely to implement factor timing
• Systematic managers are unlikely to run concentrated portfolio while discretionary managers can have concentrated or diversified portfolios, depending on their strategy and portfolio management style
• Systematic top-down managers principally emphasize macro factors, factor timing and have diversified portfolios Few managers belong to this category
Trang 53.1.4) Active Share and Active Risk
The two measures of benchmark-relative risk used to
evaluate a manager’s success include active share and
active risk Managers can increase their active share
without necessarily increasing active risk (and
vice-versa)
Calculating active share:
• Active share is easier to calculate than
active risk
• Measures the extent to which the number
and sizing positions in a manager’s portfolio
differ from the benchmark
• Active share = *3∑C 5𝑊𝑒𝑖𝑔ℎ𝑡;<=>?<@'<,'−
')*
𝑊𝑒𝑖𝑔ℎ𝑡DECFGHI=J,'5
where n = total number of securities in
portfolio and benchmark
• The two sources of active share are:
o Including securities in the portfolio
not in the benchmark
o Holding securities in the portfolio
which are in the benchmark but at different weights
• If two portfolios are managed against the
same benchmark but one has fewer
securities (is more concentrated), this
portfolio will have a higher active share
• Managers have full control of their active
share
• Active share is not affected by efficiency of
diversification
Calculating active risk:
• Active risk is a complicated calculation
• Like active return, active risk depends on
difference between security weights held in
the portfolio and benchmark
• Two measures of active risk:
o Realized active risk: actual, historical
standard deviation between portfolio return and benchmark return
o Predicted active risk: relies on
forward-looking estimates of variances and correlations
• Variance-covariance matrix is important in
the calculation of active risk
• Active risk is affected by degree of cross
correlation but active share is not
• Active risk depends on correlation and
covariances which are beyond the control
of the manager
• Active risk formula: 𝜎01=
K𝜎3L∑L𝛽;J− 𝛽DJN × 𝐹JN + 𝜎E3
Where:
𝜎3L∑L𝛽;J− 𝛽DJN × 𝐹JN is the variance
attributable to factor exposure
𝜎E3is the variance attributable to idiosyncratic risk
A relationship between active share, active risk, and factor exposure can be observed for an unconstrained investor
• High net exposure to a risk factor will lead to
a high level of active risk regardless of level
of idiosyncratic risk
• If the factor exposure is fully neutralized, active risk is entirely attributed to active share
• Active risk attributed to active share will be smaller if number of securities is large or average idiosyncratic risk is small
• Level of active risk will rise with an increase in factor and idiosyncratic volatility
Note:
• Active risk increases when a portfolio becomes more uncorrelated with its benchmark
• A closet indexer advertises itself as being actively managed but is substantially similar
to an index fund in its exposures
A manager can increase his degree of control over the level of active share and/or active risk by decreasing security concentration
A fund with an active share of 0.25 would be considered more expensive relative to a fund with an active share of 0.75 if both charge the same fees
3.2 The Implementation Process: The Objectives and Constraints
A common objective function in portfolio management
is to maximize risk-adjusted return
• If risk is being measured by predicted active risk, then the objective function involves maximizing the information ratio
• If risk is being measured by predicted portfolio volatility, then the objective function involves maximizing the Sharpe ratio
Typical constraints include limits on:
• Geographic
• Sector
• Industry
Practice: Example 2, CFA Curriculum, Volume 4, Reading 29
Trang 6• Single-security exposures
• Transaction costs
• Minimum market capitalization for a security
or entire portfolio
Other constraints may be specified in terms of a
maximum price-to-book ratio
Constraints may be specified relative to the benchmark
or without regard to it
Objectives and constraints of systematic managers are
explicitly specified while those of discretionary managers
are less explicitly specified
Objectives and constraints can be stated in absolute
terms or relative to a benchmark
Some optimization approaches specify their objectives in
terms of risk metrics such as portfolio volatility, downside
risk, maximum diversification and drawdowns These
approaches do not integrate an explicit expected return
component but implicitly create an exposure to risk
factors
Note: Any objective function which focuses on
minimizing/managing risk will select low-beta or value
securities
Objective functions which creates an exposure to
rewarded factors:
𝑀𝐴𝑋 $1
3𝑆𝑖𝑧𝑒'+ (
')*
1
3𝑉𝑎𝑙𝑢𝑒'+1
3𝑀𝑜𝑚𝑒𝑛𝑡𝑢𝑚'
Where Sizei, Valuei, Momentumi are standardized proxy
measures of Size, Value and Momentum for security i
The optimization process of discretionary managers
often relies on an implicit return-to-risk objective and
seeks to maximize exposure to securities with specific characteristics
When an explicit objective function is not used, heuristic methodologies can be considered to determine security weighting in a portfolio Examples include:
• Identify securities with desired characteristics and weigh them relative to their scoring on these characteristics
• Identify securities with desired characteristics and weigh them per their ranking or risk on these characteristics
A formal optimization process allocates risk more efficiently compared to alternative methodologies The constraints and objective function will be reflective of a manager’s philosophy and style For example,
• Stock pickers will have fewer constraints on security weights compared to multi factor managers seeking to minimize idiosyncratic risks
• A sector rotation manager will have more permissive constraints with respect to sector concentration compared to value
managers
Risk budgeting: The process of allocation portfolio risk
among its constituents An effective risk management
process requires the portfolio manager to do the
following:
• Determine which risk measure is appropriate
for the manager’s strategy
• Understand how each aspect of the strategy
contributes to its overall risk
o Understand what drives a portfolio’s
risk and ensuring the portfolio has the right kind of specific risks
• Determine the appropriate level of risk
budget
• Properly (& efficiently) allocate risk among
individual positions/factors
4.1 Absolute vs Relative Measures of Risk
The choice between absolute and relative risk is driven
by the mandate of the manager and investor goals For example, if the mandate is to outperform a benchmark index, the manager will focus on active risk
Managers who feel that benchmark-relative constraints inhibit their portfolio’s ability to realize its full potential can rely on:
• absolute risk measures – Portfolio risk must remain at or below predefined risk threshold and the manager can freely construct the portfolio without considering benchmark characteristics
Practice: Example 3 & 4, CFA Curriculum, Volume 4, Reading 29
Trang 7• relative risk measure – measures with wide
bands around target implies a
benchmark-relative approach with freedom to diverge
from benchmark characteristics
A manager’s chosen risks should be related to his
perceived skills
4.1.1) Causes and Sources of Absolute Risks
Total portfolio risk rises when a (n):
• new security which has a higher covariance
(due to higher variance or higher correlation)
than most of the existing securities is added
to a portfolio and
• existing security is replaced by another which
has a higher covariance with the portfolio
The above fundamental principles also work in reverse
Total portfolio variance (Vp) = ∑ ∑C 𝑥'𝑥a𝐶'a
')*
C ')*
Contribution of each asset to total portfolio variance
(CVi) = ∑C 𝑥'
a)* 𝑥a𝐶'a= 𝑥'𝐶';
where:
xj = the asset’s weight in the portfolio
Cij = the covariance of returns between asset i and asset
j
Cip = the covariance of returns between asset i and the
portfolio
Note: Assets in a portfolio can represent sectors,
countries, or pools of assets representing risk factors
(Value versus Growth, Small versus Large)
Example: An asset comprises three assets – A, B and C
The contribution of asset A to total portfolio variance is
determined as follows:
Weight of Asset A ´ Weight of Asset A ´ Covariance of
Asset A with Asset A
+ Weight of Asset A ´ Weight of Asset B ´ Covariance of
Asset B with Asset A
+ Weight of Asset A ´ Weight of Asset C ´ Covariance of
Asset C with Asset A
= Asset A’s contribution to total portfolio variance
A manager should aim to minimize risks attributed to
sources which are not related to his perceived skills
Therefore, absolute portfolio variance comprises: 1)
variance attributed to factor exposures (and related to
manager’s skills) and 2) variance unexplained and is
expressed as:
𝐴𝑏𝑠𝑜𝑙𝑢𝑡𝑒 𝑝𝑜𝑟𝑡𝑓𝑜𝑙𝑖𝑜 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒 = 𝑉j
= 𝑉𝑎𝑟 k$L𝛽';× 𝐹'N
J
')*
l + 𝑉𝑎𝑟L𝜀;N
If the manager’s portfolio is the market portfolio, variance of portfolio would be explained by a beta of 1
to the market factor and idiosyncratic risks would be diversified As one moves away from the market portfolio, portfolio variance is explained by other factors exposures and other risks unexplained by factors
4.1.2) Causes and Sources of Relative/Active Risk
Relative risk is important for managers concerned about their performance relative to a benchmark A measure
of relative risk is variance of portfolio’s active returns (AVp):
𝐴𝑉;= $ $(𝑥'− 𝑏')L𝑥a− 𝑏aN𝑅𝐶'a
C
a)*
C
')*
where:
xi = the asset’s weight in the portfolio
bi = the benchmark weight in asset i
RCij = the covariance of relative returns between asset i and asset j
𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛 𝑜𝑓 𝑒𝑎𝑐ℎ 𝑎𝑠𝑠𝑒𝑡 𝑡𝑜 𝑝𝑜𝑟𝑡𝑓𝑜𝑙𝑖𝑜 𝑎𝑐𝑡𝑖𝑣𝑒 𝑟𝑒𝑡𝑢𝑟𝑛 = 𝐶𝐴𝑉'= (𝑥'− 𝑏')L𝑥a− 𝑏aN𝑅𝐶'a
where RCij = the covariance of relative returns between asset i and j
Note:
• Depending on the composition of the benchmark, a lower risk asset could increase active risk while a higher risk asset might reduce it
• When allocating among countries, sectors, securities, and other factors the following principles hold:
o Introducing a low volatility asset to a benchmark within a portfolio benchmarked against a high volatility index will increase active risk
o Introducing a high volatility asset may reduce active risk if the asset has a high covariance with the benchmark
4.2 Determining the Appropriate Level of Risk
Examples of risk targets for different mandates:
• Market neutral hedge fund targets an
Trang 8absolute risk of 10%
• Long-only equity manager targets an active
risk of < 2% (a closet indexer)
• Long-only equity manager targets an active
risk of 6-10% (benchmark agnostic)
• Benchmark-agnostic manager targets an
absolute risk equal to 85% of index risk
The appropriate level of absolute or relative risk is a
function of manager’s:
• investment style and
• his/her conviction in the ability to add value
Three scenarios which give insight into practical risk limits:
Scenario 1: Implementation constraints:
These constraints degrade a portfolio’s information ratio
if active risk increases beyond a certain level
Example:
Consider two managers with the same information ratio
but different levels of active risk Manager can tolerate
higher risk and so increases active risk to match that of
Manager B
• In the absence of constraints and costs,
manager can increase risk by scaling up
active weights which proportionally
increases active returns Information ratio is
unchanged
• In the presence of constraints and costs,
leveraging the active risk will not
proportionally increase returns
o If short-selling is prohibited, he may
be unable to increase underweights
o If leverage is prohibited, he may be
unable to increase overweights
o If some securities have poor liquidity,
leveraging these position may be imprudent and impact trading costs
o If policy restricts maximum position
sizes, manager may not be able to scale up active risk
Scenario 2: Limited diversification opportunities:
Portfolios with high absolute risk targets face limited
diversification opportunities which may lead to a
decrease in Sharpe ratio
Markowitz efficient frontier demonstrates a concave
relationship between return and risk Expected returns
increase with risk but at a declining rate
Scenario 3: Leverage and its implications for risk:
There is a level of leverage beyond which volatility reduces expected compounded returns
Expected geometric return = expected arithmetic return when there is no leverage:
Rg = Ra – s2/2 where:
Rg = expected compounded/geometric asset return
Ra = expected arithmetic/periodic return
s = expected volatility The inclusion of the cost of funding will decrease active returns and result in a faster decline of the Sharpe ratio
In this case, volatility will remain proportional to the cost
of funding
If realized volatility is greater than expected, the combined impact of volatility and leverage on compounded return would be greater
Note: The Sharpe and information ratios do not always decrease following a rise in active risk, absolute risk or leverage A reasonable increase in the latter three measures may lead to an increase in expected compounded return
4.3 Allocating the Risk Budget
A manager can determine the contribution of each factor to the portfolio’s variance or active variance by understanding position sizing and covariance
The decomposition of the sources of realized risk will help determine whether the risk budget has been used effectively
A fund’s strategy and style will dictate much of the structure of its risk budget
When evaluating an investment manager, the asset owner needs to understand the drivers of active risk that can lead to differences in realized returns over time
Practice: Example 5, CFA Curriculum, Volume 4, Reading 29
Trang 9Reading 29 Active Equity Investing: Portfolio Construction
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5 Additional Risk Measures Used in Portfolio Construction and Monitoring
5.1 Heuristic Constraints
Risk constraints imposed during the portfolio construction
process may be formal or heuristic
Heuristic constraints are controls imposed on portfolio
composition through some exogenous classification
structure These constraints are based on experience or
practice and can be used to limit:
• exposure concentrations by sector, security,
industry or geography;
• net exposures to risk factors, such as beta,
size, value and momentum;
• net exposures to currencies;
• degree of leverage;
• degree of illiquidity;
• turnover/trading-related costs;
• exposures to reputational and environmental
risks; and
• other attributes related to an investor’s core
concerns
Risk heuristics can be used to limit unknown or
unexpected risks, a major managerial concern such as:
• A single position is limited to the lesser of:
o Five times the weight of the security
in the benchmark or
o 2%
• The portfolio must have a weighted average
capitalization < 75% of the index
• The portfolio may not size positions such that
it exceeds two times the average daily
trading volume of the past three months
• The portfolio’s carbon footprint must be
restricted
The above constraints can limit active manager’s ability
to exploit their insights into expected returns but may
also safeguard against overconfidence
Managers who manage portfolio risk using a bottom-up
process rely on heuristic characteristics to express their
risk objectives The portfolio construction process ensures
that this heuristic risk is achieved
Continuous monitoring is necessary to determine
whether an evolution of market prices causes heuristic
risk to be breached Managers will impose constraints on
heuristic characteristics of the portfolio even if formal
statistical measures of risk are used For example:
constraints on allocations to securities and sectors or for
international mandates Managers will low-volatility
mandates will also impose such constraints to limit
idiosyncratic risk
Formal risk measures are statistical in nature and related
to the portfolio returns distribution
Formal risk measures include:
• Volatility
• Active risk
• Skewness etc
A key difference between formal and heuristic risk measures: managers are required to estimate/predict risk For portfolio construction, forward-looking view of risk and active risk required and if realized risk varies from expected risk, actual portfolio performance can differ significantly from expectations
Different ways of using formal risk constraints:
In systematic strategies: formal risk constraints may be applied as part of the portfolio optimization process
In discretionary strategies: used as part of a feedback mechanism to determine whether portfolio will remain within predefined risk tolerance limits following the proposed change
All risk measures (formal or heuristic) can be expressed in absolute or relative terms In many cases, a portfolio imposes both formal and heuristic portfolio constraints
5.3 The Risks of Being Wrong
The consequences of being wrong about risk expectations is more severe when a strategy is leveraged
Example: A hedge fund owned a two times levered portfolio of highly rated mortgage-related securities The prices of these securities declined sharply following concerns related to the economy and market liquidity even though the securities were not materially exposed
to subprime mortgages The presence of leverage and price declines forced managers to sell their positions before price recovery
Effective risk management requires managers to consider the fact that unexpected volatility could negatively affect an investment strategy Spikes in volatility can be sector specific Risk constraints may be tightened in more volatile periods to protect against excessive variability
Trang 10Statistical risk measures used in portfolio construction
depend on management style
Example: Long/short managers with a neutral market
exposure and exposure to other risk factors target
volatility within a pre-defined range
For portfolios comprising limited number of securities,
formal risk measures will be less appropriate because
estimation errors in parameters will be greater
Measures of portfolio risk must be relevant to the nature
and objective of the portfolio mandate
Formal risk measures are not often outlined in the
investment policy statement even if managers are using
these measures This is because it may be difficult to measure and forecast such risk measures as volatility and value at risk Such risk measures are usually expressed as
a soft target by managers
If restrictions imposed by an active manager are too tightly anchored to the benchmark index, the resulting portfolio may too closely resemble benchmark
performance
Practice: Example 6, CFA Curriculum, Volume 4, Reading 29