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2021 CFA Level III > Asset Allocation 12-14 > Flashcards

Asset Allocation 12-14 Flashcards

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1
Q

government focuses on clarifying mission, creating a plan, and reviewing progress toward achieving long-and -short-term objectives.

A

the election of plan

achieve the agreed on goals and objectives

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2
Q

3 levels with governance hierarchy

A

covering investment committee
investment staff
3rd pary resources

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3
Q

effective governance models perform:

A
  1. articulate the long and short term objectives of the investment program
  2. allocate decision, rights and responsibilities among the fundamental units
  3. specify process for developing and approving investment policy statement
  4. specify processes for developing and approving the strategic asset allocation
  5. establish a reporting framework to monitor the program’s progress toward the agreed-on goals and objectives
  6. periodically undertake a governance audit
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4
Q

reporting framework

A

clear & concise, accurately answering questions

address performance evaluation, compliance with inv. guidelines

progress toward achieving the stated goals and objectives

benchmark

management reporting

governance reporting -address strength and weakness in a program execution

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5
Q

governance audit

A

to ensure that the established policies, procedures, and governance structure are effective

performed by 3rd independent party

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6
Q

effective investment governance ensures

A

durability/survivability of the investment program

weak to avoid decision-reversal risk

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7
Q

economic balance sheet

A

financial A/L
+ extended portfolio A/L

Financial asset
equity
FI

human capital
pv of trues earnings, inheritances, futures intellectual property

liability
ST borrwowing 
mortgage debt 
pv of future consumption
pv of prospective payout for foundations
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8
Q

asset only
grow asset
high return/volatility

A

focus on asset side of b/s, exp(r), risk, correlations

*target an overall required return

MVO mean variance optimization is the most familiar and deeply standard asset-only approach

maximize sharpe ratio for acceptable level of volatility

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9
Q

liability-relative/liability driven investing LDI

funding liability

A

objective of funding liabilities
provide money to pay liability when due

modell legal/quasi-liability
fund ability and invest excess asset and growth
penalty for not meeting liability (banks, DB, insurers)

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10
Q

goal-based /GBI

support needs

A

AA for sub-portfolio
each of which is aligned to specified goals
aspirational objective

model goals with specified required probability of success - individual investors

drawback: sub-portfolio add complexity
goals maybe ambiguous/may change overtime

mental accounting
bottom-up strategic AA

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11
Q

strategic asset allocation - Quant approach Utility theory

effect achieving IPS

A

optimal asset allocation

expected to provide the highest utility to the investor at the investors investment time horizon

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12
Q

power utility function

A

underlies mean-variance optimization

risk aversion does not depend on level of wealth

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13
Q

optimal asset allocation w* =

A

(U-rf)/(variance)*1/degree of risk aversion

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14
Q

Sharpe ratio

A

higher the greater its contribution to the sharpe ratio of the overall portfolio holding.

however this condition is not usually true. Diversification potential in a portfolio may differ. Portlio risk may decrease through favorable correlation characteristics of the strategies.

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15
Q

global market value weighted portfolio

on the line tangent to efficient frontier

A
  1. sum all investable asset hold by investors, reflects the balancing of supply and demand across world markets
  2. in financial theory, it minimizes diversification risk, which in principle is uncompensated
  3. makes the most efficient use of the risk budget
  4. serve as a starting point and ensure investor articulates a clear justification for moving away from global capitalization market weights

2 phases:

  1. allocate asset in proportion to global portfolio of stocks, bond, real asset
  2. disaggregate each of these broad asset classes in region, country, security weights using capitalization weights
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16
Q

implementation hurdle

A
  1. estimating the size of each asset class on a global basis is an imprecise exercise given the uneven availability of info on non-publicly traded assets
  2. the practicality of investing proportionately in residential real asset, much of which is held in individual homeowners’ hands has been questioned
  3. private commercial real estate and global private equity assets are not easily carved into pieces of a size that is accessible to most investors
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17
Q

liability relative

A

portfolio value match the liability with a buffer

FI primarily because int rates are a major financial driver of both liability and bond value.
Bond can be important in hedging liabilities but equities can be relevant for liability hedging too.

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18
Q

underfunded pension due to liability increase

A
  • optimal AA in general is sensitive to changes in the fund status of the plan
  • increase fund statues by decrease surplus risk overtime
  • as FS change, proportion of liability hedging asset and return seeking asset and duration of liability hedged change

sensitive to int. rate, duration, inflation, credit risk

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19
Q

tactical asset allocation TAA
active
ST

approaches:
1. discretional TAA
discretional relies in a qualitative interpretation of political, economic and financial market condition
2. Systematic TAA
systematic relies on quantitative signals to capture documented return anomalies that maybe inconsistent with market efficiency (value, momentum)

A

involves deliberate ST deviations from the strategic asset allocations by taking ST economic/financial market conditions that appear more favorable to certain asset classes

-investment return in short term is predictable

  • ST tilt away from the strategic asset mix
  • responsive to price momentum, perceived asset class valuation, stage of business cycle

Drawback:

  • may incur additional cost higher trading cost and taxes
  • TAA increases the concentration of risk relative to the policy portfolio

generating alpha through TAA decisions is dependent on successful market or factor timing rather than security selection

Evaluation (3 ways) between TAA and SAA

  1. sharpe ratio
  2. information ratio
  3. scatter plots
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20
Q

Dynamic asset allocation DAA

multi-period

A

deviation that are motivated by long-term valuation signals or even views

Barriers: monitory and trading cost (tax CGT)
should evaluate cost-benefit lens

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21
Q

GDP-weighted global bond index involves both active/passive choices

A

passive presented by the overall selection of the universe of global bonds

active choice is represented by the weighting scheme, which is to use the GDP rather than capital market weights. Tilting away from FI to real economy

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22
Q

Risk budgeting

A

variance, std of return, concern for tail risk, be quantified by VAR or drawdown, absolute/relative term

Active risk budgeting addresses the question of how much benchmark related risk an investor is willing to take in seeking to outperform a benchmark.

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23
Q

rebalancing

A

discipline of adjusting portfolio weights to more closely align with the strategic asset allocation

never rebalance implies rising risk/return
countercyclical
contrarian 逆势的 investment approach
align strategic asset allocation

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24
Q

percent-range rebalancing setting rebalancing thresholds or trigger points

A

target weight 50%
trigger point 45, 55%
range 10%

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25
Q

strategic consideration for rebalancing

using derivatives as a rebalancing tool to lower costs

A 
widen: 
正比：
transaction cost
correlation
momentum facto
tax consequences 
liquidity 
risk tolratce 
Narrow corridor:
high volatility
mean reversion
less correlation 
risk averse investor
  • higher transaction costs imply wider rebalancing ranges
  • more risk-averse investors will have tighter rebalancing ranges
  • less correlated assets also have tighter rebalancing ranges
  • beliefs in momentum factor widen rebalancing ranges
  • mean reversion encourages tighter ranges
  • tax discourage rebalancing and encourage asymmetric and wider rebalancing ranges
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26
Q

mean-variance optimization MVO markowitz
most concentrated

Um=E(Rm) - 0.005(risk aversion coefficient)* Variance m

coefficient = 4 moderate risk averse investor

A

maximize the expected return for an expected level of risk

provide a framework to determine how much to allocate to each asset class to create optimal asset mix

inputs: return, risk (std), pair-wise correlation

A single portfolio with specific asset class weights at each level of return describes traditional mean variance optimization.

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27
Q

reverse optimization

solve output high sensitivity of input of MVO

input determined by market cap weights, cov, and risk aversion coefficient.

more diversified

A

result in a much more diversified allocation since it uses global market portfolio as baseline.

COV - Reverse MVO - E(r)

start with optimal portfolio o weight from the global market and drive E(r)

run a traditional MVO based on E(r)

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28
Q

Criticism of MVO

inputs are historical data

A
  1. output sensitivity to input (garbage-in-garbage-out)
  2. concentrated allocation
  3. focus of skewness and kurtosis is ignored

indirectly incorporate skewness kurtosis or both into the utility function and use an asymmetric definition or risk such as conditional value at risk instead of variance

  1. highly granular and narrowly defined asset classes
    solve: redefine the asset class more broadly and follow rules for well specified asset classes.
  2. MVO is a single-period framework that does not take account of costs and taxes
  3. MVO does not model liability and goals (single period approach)
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29
Q

Resampled MVO

Solves input sensitivity and high concentration

Monte carlo similation

A

Monte carlo similation used to generate thousands of random variations of the inputs around the initial estimates, resulting thousands of simulated efficient frontiers.

Mont carlo simulation solves single period framework with all possible outcomes.

The resampled efficient frontier is an average of all the simulated frontiers

used to create an efficient frontier at each return level and run thousands of times resulting in an efficient frontier that is the result of an averaging process. The efficient frontier becomes a blur rather than a single sharp curve. At each level of return, the most efficient of the simulated efficient portfolios is at the center of the distribution.

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30
Q

risk aversion coefficient = 0

risk neutral investor

A

optimal AA is 100% invested in EM.

Exp Utility = Exp(r)

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31
Q

To achieve better-diversified efficient frontier:

A 
reverse optimization
black-litterman model
concentrated asset class weight
32
Q 
Solve input sensitivity: 
Address MVO's sensitivity to small differences in expected return estimates by archiving expected returns to those implied by the asset class weights of a proxy for the global market portfolios
A

reverse optimization

black-litterman model

33
Q

highest prob of exceeding 4% return

A

calculate sharpe ratio
= E(r)-target / std

E(r) = E(r) - 0.005*risk aversion coefficient * variance
the higher, the higher problem exceeding the threshold

34
Q

Non-nominal optimization

solves skewness and kurtosis, mean and variance only of MVO

A

Traditional MVO ignores non-normal distribution

use 1. mean-semi variance optimization

  1. mean-conditional var optimization
  2. mean-variance-skewness optimization
  3. mean-variance-skewness-kurtosis
35
Q

Monte carlo simulation solves single period framework with all possible outcomes.
Advantages relative to MVO:

A
  1. It has a multi-period framework
  2. Incorporate cost of rebalancing
  3. solves path-dependent issue by adjusts for change in cash flows
  4. incorporates statistics outside the normal distribution, skewness and excess kurtosis
36
Q

Intepret and critique an AA in relation to an investor’s economic B/S

A

investor with stable jobs with consistent capital
model CF with
human capital as an inflation-linked bond.

investor with less certain and more volatile future wage:
model human capital
as a mix of inflation-linked bond, equity and corp. bonds

including human capital & residential RE along with traditional investment vehicles increase investors capacity to bear risk.

37
Q

Liquidity in Asset Allocation

Less liquid asset classes
such as direct real estate, infrastructure, and private equity
- cannot be readily diversified to eliminate idiosyncratic risk, so representing overall asset class performance is problematic. 
-  far fewer indexes that attempt to represent aggregate performance for these less liquid asset classes than indexes of traditional highly liquid asset classes. 
- Finally, the risk and return characteristics associated with actual investment vehicles are typically significantly different from the characteristics of the asset classes themselves.
A
  1. it’s more challenging to make capital market assumption due to the lack of accurate index for less liquid assets
  2. even if there are accurate index, there are no low-cost passive investment vehicles to track them.

practical options:

  1. exclude less liquid asset classes from the MVO and consider RE funds as potential when fulfilling the target strategic AA.
  2. include them in MVO and model the inputs to represent the specific risk characteristics
  3. include then in MVO and model the inputs to represent the highly diversified characteristics associated with the true asset classes.
38
Q

3 aspects of risk budgets:

A
  1. identifies the total amount of risk and allocates the risk to a portfolio’s constituent parts
  2. an option risk budget allocates risk efficiently
  3. the process of finding the optimal risk budget is risk budgeting
39
Q

absolute/relative risk budget

A

The goal of risk budgeting is to maximize return per unit of risk.
A risk budget identifies the total amount of risk and attributes risk to its constituent parts.

An optimum risk budget allocates risk efficiently.

40
Q

absolute contribution to total risk (ACTR)

A

measure how much it contributes to portfolio return volatility for an asset class i

ACTRi = wi * MCTR = wi * beta * std

41
Q

optimal asset allocation

excess return /MCTR = Sharpe ratio = (E(r)-rf)/MCTRi

A

is optimal AA from a risk budgeting perspective

when the ratio of excess return to MCTR is the same for all assets and is equal to sharpe ratio of the portfolio.

42
Q

Fama French
factor based AA
solves non diversified risk of MVO

A

factors are typically observed based on market premiums and anomalies

the factor represents what is referred to as a zero(dollar) investment or self-financing investment.

factors generally have low correlations with the market and with one another
typically similar to the fundamental/structural factors used in multi-factor models

43
Q

developing liability-relative AA

A

plan surplus = MV(A) - PV(L)

funding ratio = MV(A)/PV(L) =1 fully funded and surplus =0

44
Q

3 approaches to liability relative asset allocation

1. surplus optimization

A

an extension of MVO that manages the portfolio surplus against the surplus volatility.

Um = E(Rs,m) - 0.005 * risk aversion coefficient * Variance (Rs,M)

Rsm =Surplus return = change in asset - change in liability / initial asset value

minimize risk of underlying by insurance companies and overfunded pension
most appropriate for conservative investors

increasing allocation to the hedging portfolio as the funding ratio and the surplus increase.

  • links asset and pv of liability through a correlation coefficient.
  • 1 step
  • simplicity
  • linear correlation
  • all level of risk
  • any funding ratio
  • single period
45
Q

allocation to corp bond declines with increase in plan surplus return can be explained by

A

positive correlation of bond prices with the pv of liability.

the hedging asset is employed to a greater degree at the low end of the surplus efficient frontier.

46
Q

3 approaches to liability relative asset allocation

A
  1. Surplus optimization
  2. two portfolio approach
  3. integrated asset-liability approach (ALM)
47
Q

forming hedging portfolio

A

asset and liability must be drive by the same factor
pv of future CF =mv of asset
date of valuation of asset = date of that for liabilities

48
Q

discount rate assumption
higher discount lead to higher funding ratio
require lower contribution from sponsors

A 
limitation:
1. funding ratio <1 
mv(c)/pv(l)<1 basis form is not applied 
2. loses due to the nature disasters cannot be hedged 
buy insurance
49
Q

3 approaches to liability relative asset allocation
3. integrated asset-liability approach (ALM)
DFA dynamic financial analysis

A

jointly optimizes assets and liabilities, typically against future changes in multiple factors.

potential to improve the institutions overall return

  • increase complexity
  • linear-non-linear
  • all level of risk
  • any funding ratio
  • multi-period
50
Q

goal based approach

E(R) with specific prob. success over the required time-horizon

A

size of inv = pr(future goal) / (1+ E(r)^n

51
Q

critique heuristic and other approach to AA

‘120 - YOUR AGE’

A

% allocation to equity = 120 - age

52
Q

critique heuristic and other approach to AA

60/40 stock/bond heuristic

A

60% equities vs. 40% bonds

53
Q

critique heuristic and other approach to AA

yale/endowment model

A

allocate larger amounts to alternative investment asset class

54
Q

critique heuristic and other approach to AA
risk parity 1/n
wi * cov(ri, rp) = 1/n * variance p

A

each asset class contribute the same amount to the total portfolio risk

weigit = 1/n
overweight less risky asset
underweight more risky asset

55
Q

asset size constraints - small assets

A

disadvantage subject to small asset:

  • minimum requirement for some investment is not met
  • lower governance capacity-sophistication and manpower resources
  • higher internal management fees
  • too small to diversify across asset classes
56
Q

tax consideration
interest income taxed at a higher rate than dividends/capi gains

taxable assets have existing unrealized capital gains/losses which come with embedded tax liabilities.

A

r at = r pt(1-t)
rat = pa rat (1-td) + pa rpt (1-tcg)

std at= std pt(1-t)

57
Q

3 potential ways current market value may be adj. to reflect the a/l:

A
  1. subtract the value of the embedded CGT from the current market value of the asset as if it were to be sold today
  2. assume the asset is to be sold in the future and discount the tax liability to its pv using the asset after-tax return as a discount rate
  3. assume asset is to be sold in the future and discount the tax liability to its pv using the after-rate rf rate.
58
Q

taxes and portfolio rebalancing

Rat = Rpt/(1-t)

A

occur less frequently in the taxable portfolio due to reduction in volatility

59
Q

reduce impact of taxation:

tax loss harvesting

A

trading to realized a capital loss to offset current/future realized capital gain, thereby reducing the taxes owned by the investor

60
Q

reduce impact of taxation:

Strategic asset allocation

A

place less tax-efficient assets in accounts with more favorable tax treatment, such as retirement savings account.

61
Q

tax deferred account
TDA
asset appreciate tax free but are taxes upon distribution

A

AF TDA = Vat = Vpt(1-t)

62
Q

TEA

tax exempt assets

A

not subject to taxes

63
Q

changes in investment objective/constraints from:

A 
asset size
business condition
investor's personal circumstances 
interest rate
cash flow 
regulation
time horizon
liquidity needs
economic environment and capital market expectation
change in committee members/trustees
64
Q

Strategic asset allocation SAA

A

LT investment policy targets fr asset class weight

65
Q

The Norway model

A

passively invests in publicly traded securities subject to environmental, social, and governance concerns.

66
Q

5 criteria in effectively specify asset classes

A
  1. asset within an asset class should be relatively homogenous
  2. asset classes should be mutually exclusive
  3. asset class should be diversifying
  4. asset classes selected for investment should have the capacity to absorb a meaningful proportion of an investor’s portfolio.
67
Q

impact of short sale on efficient frontier and asset allocation

A
  • short sale constraint allows only positive asset weights, this may shift the efficient frontier downward and to the right, shifting the theoretical maximum possible return for a given level of risk downward
  • in practice the constraint is not an issue because few investors would allow a “permanent” strategic allocation to short position.
68
Q

Grinold-Kroner model for Equity market return

A

Expected repricing return = change in P/E ratio = 0.5%

Expected income return =  dividend yield − increase in shares outstanding = 3.5% − ( −1.0%) = 4.5%

Expected nominal earnings growth =  real earnings growth + inflation = 2.1% + 1.9% = 4.0%

69
Q

r=(1+s)(1+i)(1+c)

A

s spending
i inflation
c cost of earning

70
Q

Heuristics approach

A

refers to rules that provide a reasonable but not necessarily optimal solution, Some investors may skip the various optimization techniques and simply adopt an asset allocation mix (such as the “120 minus your age” rule or a 60/40 stock/bond mix).

71
Q

Shortfall risk

A

is a liability-relative approach focused on the risk of having insufficient assets to pay obligations when due.

72
Q

corridor width

- frequency of rebalancing from strategic asset allocation

A

narrow when rebalance often

increase in volatility
higher volatility makes large divergences from the strategic asset allocation more likely

wider when rebalance rarely

increase in transaction cost
higher risk tolerance
higher correlation
-when asset classes move in sync, further divergence from target weights is less likely

low volatility

73
Q

the two portfolio model

a hedging portfolio + return seeking portfolio (mvo)

A

it allows the fund to create an asset portfolio that hedges its liabilities, while separately creating a portfolio that manages the remaining assets using mean-variance optimization (MVO) under a return-seeking approach.

  • 2 steps
  • linear/nonlinear
  • conservative level risk
  • positive funding ratio
  • single period
74
Q

Improvement to monte carlo simulations

A
  1. refine historical base asset class expectations for expected future economic conditions
  2. model the assets owned rather than generic asset classes.
75
Q

Advantage of resample efficient frontier

A
  1. likely to be more stable, leading to less frequent turnover and lower transaction cost.
  2. allocation likely includes more asset classes from increased diversification, consistent with her reduced risk tolerance
76
Q

advantage of black-litterman

A

adds in investors view of expected return

with constrain as strategic allocation to short is highly unusual.

77
Q

Corner portfolio

A

MVO is required to find the corner portfolio

it’s must be on the efficient portfolio

shortcut to interpolate points along the efficient frontier

2021 CFA Level III (12 decks)

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