1
Q
A
2
Q
Pensions | Funded status
A
status of PV pension assets - PV pension liabilities
• only DB plan
3
Q
Pensions | Plan surplus
A
- plan assets - plan liabilities
- > 0, then overfunded;
- only DB plan
4
Q
Pensions | Fully funded
A
plan assets and plan liabilities are roughly equal
• only DB plan
5
Q
Pensions | Accumulated benefit obligation (ABO)
A
PV of pension liabilities to date
• includes
◎ remaining pension benefits to currently retired
◎ retirement benefits earned to date by active employees based on their current salaries and years of service
• does NOT include
◎ effect of future salary increases or service on benefits
◎ effects of future service
• measure of liabilities for a terminated plan
• only DB plan
6
Q
Pensions | Projected benefit obligation (PBO)
A
PV of pension liabilities to date
• includes
◎ remaining pension benefits to currently retired
◎ retirement benefits earned to date by active employees based on their current salaries and years of service
◎ effect of future salary increases or service on benefits ALREADY earned
• does NOT include
◎ effects of future service
• measure of liabilities for a terminated plan
• only DB plan
7
Q
Pensions | Total future liability
A
- PBO + effects of FUTURE service by current employees
- not an accounting term
- only DB plan
8
Q
Pensions | Retired lives
A
of retirees
9
Q
Pensions | Active lives
A
of active employees
10
Q
Pensions | Sponsor company
A
the company the employee works for and that is providing the pension
11
Q
Pensions | Defined benefit plan
A
- employer promises to pay employeed during retirement an amount based on criteria such as salary, yrs of service
- employer bears investment risk
- generally not portable
- includes cash balance plan (individual accts >> portable)
12
Q
Pensions | Defined contribution plan
A
- employer contributes to an employee retirement acct
- employee (not employer) bears investment risk
- portable
- includes profit sharing plans (contribution based on company profits)
13
Q
Pensions | Pension risk tolerance
A
- relative to other institutions: somewhat above average to conservative
- plan surplus: greater surplus >> greater risk tolerance (negative surplus >> desire for more risk to fill gap - not allowed!)
- financial status and profitability: lower debt-equity ratio, greater profits >> greater risk tolerance
- sponsor, pension common risk: more correlated value >> lower risk tolerance
- plan features: greater liquidity needs (early retire), shorter time horizon >> lower risk tolerance
- workforce characteristics: younger, low retiree/active >> more risk tolerance
14
Q
Pensions | three methods of measuring risk
A
- asset/liability managment (ALM): stand dev of PLAN SURPLUS
- stand dev of assets (old way, but common)
- shortfall risk: prob of asset value or return falling below a level needed to meet funded status
◎ different def of funded can be used (eg fully funded, total future liability)
15
Q
Pensions | DB return objective (via IPS)
A
- cover pension liabilities
- acturial rate
- customers are the employees
- capital gains when low retiree/worker ratio; income and duration matching when high retiree/worker ratio
16
Q
Pensions | DB return objective from sponsor’s view
A
- reduce pension contributions
- reduce pension expenses (these appear on income statement)
- but must not lose sight of main objective: covering employee retirement
17
Q
Pensions | DB constraints: liquidity
A
affected by:
- # of retired lives
- sponsor contributions
- plan features (eg early retire, lump sum)
18
Q
Pensions | DB constraints: time horizon
A
- termination date, if the plan is terminating
- plan participants characteristics
◎ sometimes divided between active (retire age) and retired (life expectancy)
19
Q
Pensions | DB constraints: taxes
A
• most are tax exempt (state this on exam)
20
Q
Pensions | DB constraints: legal and regulatory factors
A
- In US, ERISA regulates DB plans
- pension plan trustee is fiduciary and must act in interests of plan participants
21
Q
Pensions | DB constraints: unique
A
• sometimes small size of plan impedes ability to manage
22
Q
Pensions | 2 risk management factors
A
- sponsor operating returns and pension returns should be uncorrelated
◎ no investing in company stock or same industry - coordinating pension investments/assets with liabilities (ALM)
◎ matching asset and liability durations using fixed income
23
Q
Foundations vs Endowments
A
• largely the same
• investment management the same
• legal distinction in the US
• founation: grant-making and funded by gifts; endowment: long-term fund owned by a non-profit
• both are
◎ not for profit
◎ serve a social purpose
◎ perpetual
24
Q
Foundation types
A
- Independent
- Company sponsored
- Operating
- Community
25
Foundation | Independent
* private or family
* grants to charities, educational, institutions, social orgs
* source: individual, family, or group
* annual spending: 5% of assets, not counting exp
26
Foundation | Company sponsored
* tied to sponsor
* grants to charities, ed, institutions; can further corp goals
* source: corp sponsor
* 5% of assets, not counting exp
27
Foundation | Operating
* sole purpose is funding an org
* source: individual, family or group
* spend 85% of div, int income; also 3.3% of assets
28
Foundation | Community
* publicaly sponsored
* fund social, ed, religious
* source: general public, large donors
* spending: none
29
Pension | DC: sponsor vs participant directed
like it sounds: sponsor or participant directs investments
30
Pension | cash balance plan
• DB plan w/account balance for each participant
• each period:
◎ credit for work (age, salary, etc)
◎ investment credit based on benchmark rate
◎ employer bears investment risk
31
Pension | ESOP
* employee stock ownership program
* DC
* allows employees to buy company stock, sometimes discounted
* before or after tax dollars
32
Foundations | Risk
* medium to high
* more aggressive than pensions
33
Foundation | Return
* If perpetual, preservation of purchasing power
* calc: payout + inf + exp; either add or compound
* total return
34
Foundation | Constraints: Time horizon
* perpetual, unless mandated to spend down to zero
* so long time horizon \>\> more risk
35
Foundation | Constraints: Liquidity
* min spending req = 'spending rate'
* many countries specify min spendin rate; US is 5%
* smoothing rule: smooth out distribution
* may hold portion of distribution in reserve
36
Foundation | Constraints: Tax considerations
* not taxable entities; not a major concern • US taxes private foundations at 1%
* unrelated income taxed at reg corp rate
37
Foundation | Constraints: Legal and regulatory
* Uniform Management Institutional Funds Act (UMIFA) adopted my most US states
* mostly tax exempt status issues
* few regulations
38
Endowments | Spending rules
• do not have min spending rate
• 3 types:
◎ simple: spending = S(begin mkt val); S = spending rate
◎ rolling 3 yr avg: spending = S\*(avg mkt val last 3 yrs)
◎ geometric: spending = R\*(last yr spending)\*(1 + inf) + (1 - R)\*S\*(begin mkt val)
39
Endowments | Risk
* medium to high
* time horizon is infinite \>\> more risk
* one qualification to high risk is more essential payout \>\> less risk
40
Endowments | Return
* preserve purchasing power
* total return
* 'inflation' rate should mirror the rate of the costs the endowment must cover (eg. health care costs)
41
Endowment | Constraints: Time horizon
perpetual
42
Endowment | Constraints: Liquidity reqs
usually low reqs; only current spending and emergencies
43
Endowment | Constraints: Tax
tax exempt (other than unrelated business income tax UBIT)
44
Endowment | Constraints: Legal
* Uniform Management Institutional Funds Act (UMIFA) adopted my most US states
* mostly tax exempt status issues
* few regulations
45
Endowment | Constraints: Unique
Often have unique restrictions based on their mandate
46
Two types of insurance company ownership
1. stock company owned by shareholders
2. mutuals (owned by policy holders)
• many mutuals have demutualized into stock companies
47
3 types of life insurance
1. whole life or ordinary life
2. variable life, universal life, variable universal life
3. term life
48
Life insurance | whole life or ordinary life
* fixed payoff at death
* cash value if policyholder terminates policy (or can be borrowed)
* cash builds up at 'crediting rate'
* disintermediation is when rates are high and policyholders withdraw funds \>\> requires liquidity
49
Life insurance | term life
year to year \>\> short duration assets to fund short duration liability (is this effectively true???)
50
Life insurance | Variable life, universal life or variable universal life
life whole life, but crediting rate tied to benchmark \>\> fewer withdrawls during high interest rates
51
Life insurance | Risk
• govts view as quasi-trusts; NAIC dictates asset valuation reserve (AVR) \>\> risk based capital \>\> more capital, less leverage
• overall conservative
1. valuation risk (ALM): asset and liability duration must be similar
2. reinvestment risk: ALM helps with this
3. cash flow volatility: bad
4. credit risk \>\> diversification
52
Life insurance | Return
* reqs are by 'line of business' (segment by lines of business)
* conservative, fixed income
* total return theoretically good, but not practical
53
LIfe Insurance | Constraints: Liquidity
Two issues:
1. disintermediation: when rates go up
◎ poor ALM makes problem worse if assets have longer duration
2. asset marketability
• more use of derivatives
54
Life insurance | Time horizon
* 20-40 years
* getting shorter due to volatile mkts
* segmentation and duration matching by line of business is norm
55
Life insurance | Tax
* taxable entities
* often actuarial assumed rate is tax free
* laws are fluid in the industry lately
* after-tax return is metric
56
Insurance constraints: Legal (HINT)
```
#1often answer is 'complex and extensive, should seek expert legal advice'
• heavily regulated at the state level
```
57
Life insurance | Legal
Regs often address:
1. eligible investments by asset class and max % holdings (often min interest coverage ratio on corp bonds)
2. In US, prudent investor rule; replaces eligible investments rule with portfolio risk/return
3. valuation methods
• heavily regulated at the state level
58
Life insurance | Unique
* concentration of product offerings
* company size
* level of surplus
59
List of Non-life insurance companies
1. health
2. property and casualty
3. surety
60
Treatment of non-life insurance companies on exam
treat like life insurance except where differences are mentioned
61
life and non-life insurance differences
1. liability duration is shorter (often 1 yr)
2. often long tail to policy resolution (eg. litigation)
3. non-life often has inflation risk (eg. replacement value of property)
4. life insurance is predictable payout, unpredictable timing; non-life is unpredictable in both amount and timing
5. non-life has underwriting or profitability cycle: 3-5 yrs; competition \>\> unprofitable, losing policies
6. non-life can be concentrated geographically or by event
62
What is critical to all insurance company investing
ALM (asset liability managment)
63
Non-life insurance | Risk
* quasi-fiduciary req
* payouts and timing are volatile (katrina, sandy)
* inflation (eg. replacement cost)
* cash flow req are volatile \>\> low risk tolerance
* (common stock-to-surplus was varied over decades)
64
Non-life insurance | Return (general)
* operated as two separate companies: insurance and investment
* policy premiums were not related to returns \>\> too low premiums
* partially improved
65
Life and non-life insurance Return differences
1. competition \>\> too low premiums (underwriting cycle)
2. profitability: investment return dictates profitability and offset poor premium pricing; ALM
3. growth of surplus \>\> high return, risky assets
4. seek after-tax, total return
5.less reg \>\> varied return across different companies
• buys taxable bonds when in loss period, buys tax-free when in profit period
66
Non-life insurance | Constraints: Liquidity req
High (critical aspect) \>\> money market assets, laddered portfolio of govt bonds, ALM
67
Non-life insurance | Constraints: Time horizon
Short because of short liability duration
68
Non-life insurance | Constraints: Tax
* taxable entities
* after-tax return is metric
69
Non-life insurance | Constraints: Legal
* Less reg and investment oversight than for life
* asset valuation reserve (AVR) is not req, but risk based capital is req
70
Non-life insurance | Constraints: Unique
no universal reqs
71
Banks | Objectives and Constraints
Defined by fact that portfolio is a residual use of funds
◎ bank borrows (liability) and loans (asset)
◎ borrowed - loaned = portfolio (unused borrowings)
• portfolio is lower return/lower risk than loan portfolio
• easier to adjust portfolio than borrowed and loaned funds
72
Banks | Risk
* below average
* use ALM
* Portfolio is used to keep overall asset duration similar to liability duration
* Portfolio is also used to manage credit risk and diversification of overall assets \>\> often very liquid to offset illiquid loans
73
Banks | Risk metrics
1. VAR
2. Leveraged Adjusted Duration Gap (LADG): duration of assets less leveraged duration of libilities
◎ form of ALM
◎ LADG = Dass - (L/A)Dliab, D = duration, L/A = leverage
◎ theo predicts equity change in value given int rate change (if +, rates up \>\> equity down; if -, move together; if 0 no effect on cap)
74
Banks | Return
Overall, goal is to earn positive interest rate spread: return on assets \> rate on liabilities (cost of funds)
75
Banks | Constraints: Liquidity
* high liquidity req
* function of withdrawls, loan demand and reg
76
Banks | Time horizon
Short and function of liability duration
77
Banks | Taxes
* taxable entities
* after-tax return is metric
78
Banks | Legal
* highly regulated
* risk-based capital reg \>\> RBC reserves against assets (risk up, reserve up) \>\> high liq portfolio
* reserve reqs
79
Banks | Unique
no universal constraints
80
8 types of institutions
Generalizable IPS:
1. pension funds
2. foundations
3. endowments
4. insurance companies
5. banks
Ungeneralizable IPS (intermediaries - invest other peoples' funds):
1. investment companies
2. hedge funds
3. commodity pools
81
Institutional asset management and ALM
* maximization of surplus (A - L) at each risk level
* ALM is preferred framework for portfolio evaluation when defined liabilities
* surplus and surplus volatility is key metrics
* asset and liability duration should be similar
* durations can be gamed to profit from int rate changes
* ALM best for DB plans, insurance companies and banks
82
Insurance companies: fixed income and surplus
* Fixed income needed to match liabilities is conservative
* Surplus is aggressive
83
Endowment | Contstraints: liquidity
* similar to foundation
* may hold portion of distribution in reserve
84
Prudent Investor Rule and Prudent EXPERT Rule with institutional asset managment
• Prudent Investor:
1. Foundations and endowments
2. Insurance
• Prudent Expert:
1. DB Plan
• Prudent expert is tougher than Prudent Investor
85
Duration matching
long term \>\> capital gains strategy; short term \>\> income strategy
86
Exam note: pension asset management
remember to:
1. match duration
2. diversify
87
Pension | 3 types of asset allocation
1. asset only: pick most efficient portfolio
2. liability-relative: pick assets that mirror the liability risk
3. duration management: better than asset-only, worse than liability-relative
• risk free definition
◎ asset only: cash return
◎ liability-relative: highly correlated to liability performance
88
Pension | asset allocation: duration management
* ok for short term duration pensions (eg. bankruptcy)
* better than asset-only, worse than liability-relative
89
Pension | asset allocation: benchmark
asset mix that mirrors liability performance and minimizes surplus volatility
90
Pension | market liability exposure
• active and inactive participants
• active:
◎ obligations from past service
◎ obligations from future service
• inflation exposure
◎ fixed, no inf exposure (nominal bonds)
◎ indexed, yes infl exposure (real rate, eg. TIPS)
◎ mixed
• accrued benefits: obligations to inactive + active obligations from previous service
91
Pension | future wage liablity + accrued benefits equals what?
* FASB: projected benefit obligation
* IASB: defined benefit obligation
92
Pension | future wage liability
• PV of expected future benefits based on wage growth
• 2 segments:
◎ inf
◎ real growth
• inf liability offset with real rate bonds; real growth liability offset with equities
93
Pension | 2 types of inactives
1. retirees: receiving payments
2. deferred's: not receiving payments yet, but owed money
94
Pension | liability noise
• non-mkt exposure
• 2 segments:
◎ demographic uncertainty
◎ model uncertainty
• demo uncertainty decreases as participants increase
• model uncertainty: active (many) \> deferred (longevity + timing) \> retired (longevity risk)
• hard to hedge
95
Pension | included in liability benchmark exposure
1. accrued benefits
2. active future wage
96
Pension | Market liability exposure segments
1. accrued benefits
2. active future wage growth
3. active future service rendered
4. active future participants
97
Pension | Asset-only vs liability-relative performance
* asset only is 60-70% equities + short, medium nominal bonds
* liability-relative is lower risk: derivatives, long bonds, TIPS, equities
* asset-only outperforms liability-relative
* liablity-relative may require contributions for future service rendered and future participants (not included in model or funding)
98
Pension | market risk for liabilities
1. interest rate
2. inflation
3. economic growth
99
WACC | asset beta
weighted avg of debt and equity beta
• used with CAPM to calc WACC
• debt beta can be assumed to be zero
• either operating assets or total assets (operating + pension); total is preferred
100
WACC | total asset beta
weighted avg of operating and pension asset betas
• = weight of equity in cap structure \* equity beta (BUT WEIGHT CAN CHANGE IF PENSION LIABILITIES INCLUDED)
101
WACC | computation
either avg weighted cost of debt + equity OR calced with asset beta used in CAPM
102
Pension | bigger danger: funding shortfall or ALM issue
ALM:
◎ balance sheets don't show asset/liability risk
◎ top 20% of US companies had large pension investments in equities (bad)
103
WACC computation
• WACC =
◎ We\*Ke + Wd\*Kd\*(1 - t)
◎ Rf + B\*(Rm - Rf), B = op asset beta (systemic risk of op assets)
104
Pension | equity beta
* found by regressing company's stock return on mkt return
* is risk of company's pension assets
105
Pension | pension asset beta
• Ba,p = Ws,p \* Bs,p
Ba,p=pension asset beta
Ws,p = weight of equities in pension assets
Bs,p = equity beta
106
Pension | 3 betas
total, operating, pension
107
WACC | effect on WACC of adding pension assets, liabilities
lowers WACC because pension liability (no equity) dilutes equity \>\> reducing weight
108
WACC | given total asset beta, pension asset beta and pension and op asset weights calc op asset beta and WACC
* op asset beta = (Ba,t - Wa,p \* Ba,p) / Wa,o
* WACC = Rf + Ba,o & MRP
* if Ba,t is initially calced without pension \>\> overestimation of Ba,t and Ba,o and WACC \>\> reject profitable projects
109
Pension | effects of increasing plans equity allocation or equity beta
\>\> increased plan risk \>\> increased:
◎ company equity beta
◎ total asset beta
◎ operating asset beta
◎ WACC
110
Pension | maintaining company's equity beta as plan equity rises
must increase proportion of equity in cap structure (issue shares, buy back debt)
111
Pension | asset/liability mismatch
* different risks OR
* same risks, but affected differently
112
WACC should be measured with or without pension assets/liabilities
without: only on operating asset beta, BUT AFTER recalcing asset operating beta with pension asset/liabilities!
113
Capital Market Expectations (CME)
* CME + ISP \>\> SAA (strategic asset allocation)
* also help detect ST asset mispricing (tactical asset allocation)
* Expectations of return, correlation and standard deviation of each asset class
* CME re classes of assets = macro expectations (top down)
* CME re specific assets = micro expectations (bottom up)
114
CME | beta vs alpha research
* beta = CME research
* alpha = excess returns of specific stratagies in specific asset classes
115
CME | 7 Step Process
1. Needed CMEs based on tax status, allowable asset classes, time horizon
2. assess historical performance, factors, make forecast
3. pick appropriate valuation model
4. Collect data (factors)
5. Inputs
6. Forecast CME
7. monitor performance, refine model
116
CME | 7 Data considerations in model (not 9 data problems)
1. calculation methodologies
2. data collection techniques
3. data def
4. error rates
5. investability and correction for free float
6. turnover in index components
7. potential biases
117
CME | 9 Data problems (not 7 data considerations)
1. econ data limitations
2. data measurement error and bias
3. historical estimate limitations
4. using ex post risk and returns
5. non-repeating data patterns
6. not accounting for conditioning information
7. misinterpretation of correlations
8. psychological traps
9. model and input uncertainty
118
CME | data problems: limits on econ data
1. time lag between collection and distribution
2. revisions
3. data and methodology change over time
119
CME | data problems: data measurement errors and bias
1. transcription errors (espeically if biased)
2. survivorship bias
3. appraisal (smoothed) data \>\> corr and stan dev are biased lower
120
CME | data problems: limitations of historical estimates
* past does not necessarily predict future
* regime change, non-stationarity \>\> diff statistical properties period to period
* leads to difficulty in picking best time period
121
CME | data problems: ex post data to determine ex ante
* only looking at bet outcomes rather than factors (risks) in the original bet
* incorrectly exclude possibilities (eg. risks) that didn't materialize but were issues
122
CME | data problems: over-fitting, spurious patters
• over-fitting data (data mining) or finding spurious patterns
• prevention:
◎ ask if economic (theoretical) explanation
◎ out-of-sample testing
◎ look for bias susceptibility
123
CME | data problems: conditioning information
* related to regime change
* if diff regimes can be identified, use correct data and inputs for that regime
* exp: if gdp is 4% in expansion and 1% in contraction, determine which period is coming and use appropriate value
124
CME | data problems: misinterpret correlation
* correlation vs causality
* does economic (theoreitical) explanation justify causality (also possible no causality, but both effects from third varaible) #alt method to corr is multiple regression
125
CME | data problems: 6 psychological traps
1. anchoring
2. status quo
3. confirming evidence
4. overconfidence
5. prudence
6. recallibility
126
CME | data problem: psychological trap: anchoring
put too much weight on earliest data; new data is given too little weight
127
CME | data problem: psychological trap: status quo
too much weight on historical data
128
CME | data problem: psychological trap: confirming
* look for data to back up beliefs
* prevention: seek counter opinions
129
CME | data problem: psychological trap: overconfidence
* ignore past mistakes and overestimate likelyhood of being right
* prevention: increase range of forecasts
130
CME | data problem: psychological trap: prudence
* overly conservative
* desire to avoid regret
* prevention: same as overconfidence, increase range of forecasts
131
CME | data problem: psychological trap: recallibility
letting extreme events in the past overly influence forecasts
132
CME | data problems: model and input uncertainty
• first principles uncertainty
◎ correct model?
◎ correct inputs?
133
CME | CME from 4 statistical tools
1. projecting historical data
2. shrinkage estimators
3. time series analysis
4. multifactor models
134
CME | statistical tool: projecting historical data
forecasting mean, stan dev, corr based on past mean, stan dev, corr
• use arithmetic or geometric mean (usually preferred)
135
CME | statistical tool: shrinkage estimator
using weights in historical data to reduce effect of outliers and more generally change influence of certain data
136
CME | statistical tool: time series analysis
forecast model based on past values of the estimate (eg. volatility)
137
CME | statistical tool: multi-factor models
forecast returns and covariances
• see var and covar equations
138
CME | 4 methds to derive CME
1. statistical tools
2. discounted cash flow model
3. risk premium model
4. financial equilibrium model
139
CME | CME from discounted cash flow model
* intrinsic value = PV of future cash flows
* exp: Gordon growth model (constant growth model) used for equity
* DCF also used with bonds
140
CME | Grinold Kroner expected return model
```
R = D1/P0 - Schange + i + g + P/Echange
R = exp return on stock
D1/P0 = current yield
Schange = % change in shares outstanding
i = exp inflation
g = real growth rate
P/Echange = % change in P/E (repricing term)
```
141
CME | 3 components of Grinold Kroner model
• R = sum of 3 components
1. exp income return = D1/P0 - Schange
2. exp nominal earnings growth = i + g
3. exp repricing return = P/Echange
142
CME | stock repurchase yield
exp % stock repurchased
• new issuance is negative \>\> subtract from current stock yield (D1/P0)
143
CME | CME from risk premium model
* build-up approach
* bond return = real risk free rate + inf + default risk prem + liq risk prem + maturity risk prem + tax prem
* equity return = bond + risk premium
144
CME | CME from financial equilibrium model
* assumes supply, demand in equilibrium \>\> efficient mkts \>\> models correctly price assets
* exp: ICAPM and Singer,Terhaar model
145
CME | ICAPM
Ri = Rf + Bint(Rm - Rf)
Bint = systemic risk of asset i returns to int'l mkts (CAPM, B is to domestic mkts)
• Bint (or B) = cov(i,m) / var(m) = p(im) sd(i) / sd(m)
146
CME | ICAPM: risk premium for asset
RPi = p(i,m) \* sd(i) \* (Rm - Rf) / sd(m) = p(i,m) \* sd(i) \* mkt sharpe ratio
147
CME | covariance between two variables that are functions of a one variable factor model
cov(i,j) = Bi \* Bj \* var(m), B is the coefficient to the independent variable in f(x) = i or j, m is the independent var (factor)
148
CME | cov(i,j), where i,j are dep var in a two factor model
cov(i,j) = B(i,1) \* B(j,1) \* var(x1) + B(i,2) \* B(j,2) \* var(x2) + (B(i,1) \* B(j,1) + B(i,2) \* B(j,2))\*cov(x1,x2)
149
CME | ERP
equity risk premium
• = corr(i,m) \* sd(i) \* mkt sharpe ratio
• if completely segmented, then corr = 1
150
CME | finding return based off of ERP and intergrated/segmented aspect
1. find ERP fully integrated
2. find ERP fully segmented (corr = 1)
3. use integration degree as weight to find ERP
4. Ri = ERP + risk free
5. calc cov(i,j) = BiBjVar(m)
151
CME | CME from surveys
* ask the experts \>\> CME
* if same people each time \>\> panel method
152
CME | CME adjusted by judgement
adjusting forecasts based on experience and judgement
153
CME | economic analysis: 2 components
1. cyclical
2. trend-growth
154
CME | cyclical analysis: 2 components
1. inventory cycle (2 - 4 yrs)
2. business cycle (9 - 11 yrs)
155
CME | economic analysis: metrics
1. real GDP
2. output gap
3. recession (2 consecutive quarters of decreasing GDP)
156
CME | economic analysis: inventory cycle
* 2 - 4 yrs
* metric: inventory / sales
* less variable due to JIT inventory
157
CME | economic analysis: business cycle
• 9 - 11 yrs
• 5 stages
◎ initial recovery
◎ early upswing
◎ late upswing
◎ slowdown
◎ recession
158
CME | business cycle: initial recovery
1. duration: few months
2. bus confidence rising
3. fiscal + monetary govt stim
4. falling inf
5. large output gap
6. falling int rates
7. bond ylds bottoming
8. rising equity prices
9. riskier assets do well
159
CME | business cycles: early upswing
1. duration: few yrs
2. growth w/ low inf
3. bus confidence rising
4. inventories rising
5. ST rates rising
6. output gap closing
7. rising bond ylds
8. stock mkt rising
160
CME | business cycles: late upswing
1. bus confidence high
2. employ high
3. output gap zero
4. inf rising
5. monetary tightening
6. ST rates rising
7. bond ylds rising
8. stock mkt rising, more vol
161
CME | business cycles: slowdown
1. duration: few months
2. bus confidence decreasing
3. inf rising
4. inv falling
5. ST rates peak
6. bond ylds peak, falling
7. yld curve may invert
8. stock mkt falling
162
CME | business cycles: recession
1. duration: 6-12 months
2. large decline in inv
3. bus confidence falls
4. profits fall
5. UE and bankruptcy increasing
6. ST rates fall
7. bond ylds fall
8. stock mkt rises in later part in anticipation
163
CME | Inflation effects on businesses
* inflation is fine: 0 - 3%
* highly levered firms are always impacted the most by the inf and rates
* defl bad \>\> sign of slow growth
164
CME | Inflation effects on cash
* cash is fine in high inflation because the return can float with rates
* defl bad due to 0 rates
165
CME | Inflation effects on equity
* inflation 0 -3% fine: equities are hedge
* above 3% \>\> concern fed will restrict econ growth
* defl bad \>\> sign of low growth
166
CME | Inflation effects on real assets
• inflation fine: real assets are hedge unless levered
167
CME | Consumer spending vs business spending
* consumer: 2/3, largely constant over business cycle, though seasonal over year
* business: 1/3, more volatile over business cycle
168
CME | fed rate levels
both the direction rates are moving as well as the absolutel level are important
169
CME | Fed neutral interest rate
real growth rate + inf rate
170
CME | Taylor rule
* Est of fed interest rate target
* Rtarget = Rneutral + 0.5 \* (GDPexp - GDP trend) + 0.5 \* (i exp - i target)
171
CME | affecting growth with fiscal policy
* only active govt policy to change deficit affects growth
* absolute level of deficit and natural changes in deficit do not (eg. reduction due to higher revenues during expansion)
172
CME | fiscal and monetary effects on yield curve
1. both stimulative \>\> steep yld curve and growth
2. both restrictive \>\> inverted yld curve and contraction
3. fiscal stim, monetary tight \>\> flat yld curve
4. fiscal tight, monetary stim \>\> slight upward slope of yld curve
173
CME | 2 components of economic growth
1. cyclical (ST)
2. trend (LT)
174
CME | economic growth: 2 trend components
1. change in employment levels
◎ population growth
◎ labor force participation
2. changes in productivity
◎ spending on new capital inputs
◎ total factor productivity growth (technology)
• sum all components to get exp growth rate
175
CME | govt policies that enhance growth
1. provide infrastructure
2. responsible fiscal policy
3. transparent, consistent, broad-based, limited tax policy
4. promote competitive markets
176
CME | economic growth: exogenous shocks
* unanticipated shocks • eg: bank crisis, foreigh crisis (oil shock)
* one country's shock affecting another country: contagion
177
CME | economics: macroeconomic links and interest rate differentials
• links: trade, exchange rates (pegged vs floating)
• interest rate differentials between countries can indicate diff in growth, monetary and fical policy
◎ theoretically all countries should have same real rate
178
CME | 6 factors of emerging economies
1. responsible fiscal and monetary policy
2. expected growth
◎ 4+% 3. reasonable currency valuation and current account deficit
◎ current acct deficit \< 4% gdp 4. reasonable leverage
◎ foreign debt \< 50% gdp
◎ debt \< 200% current acct receipts 5. foreigh exchange reserves relative to ST debt 6. efficient govt (structural reform)
179
CME | 3 methods of economic forecasting
1. econometrics
2. economic indicators
3. checklist
180
CME | economic forecasting: econometrics
• econ theory \>\> model
• pros:
◎ can be reused
◎ can accurately model economy
◎ quantitative forecasts
• cons:
◎ difficult, time consuming to create
◎ may not work in diff time periods
◎ better at expansions than recessions
◎ scrutiny of output to verify validity
181
CME | economic forecasting: economic indicators
• types: lagging, coincident, leading (preferred)
• pros:
◎ available from 3rd parties
◎ easy to understand
◎ adaptable to diff purposes
◎ validated by academic research
• cons:
◎ econ relationships change over time
◎ false signals from leading indicators
• one method is majority signals change coming
182
CME | economic forecasting: checklist method
• checklist of questions about economy
• pros:
◎ simple
◎ allows change over time
• cons:
◎ subjective
◎ time intensive
◎ may not model complex systems
183
CME | top down asset management process
1. generate CME
2. assign returns to asset classes
184
CME | list of 7 asset classes
1. cash:
2. credit risk free bonds: 2-4% real yld
3. credit risky bonds
4. emerging mkt govt bonds
5. inflation indexed bonds: yld falls during high inf as people buy them
6. common stock
7. emerging mkt stocks: corr w/developed countries
8. real estate
185
CME | forecasting exchange rates: 4 methods
1. relative PPP
◎ diff in inf \>\> exchange rate change
◎ true in LT
2. relative economic strength
◎ strong economy attracts investors \>\> appreciation
3. capital flows: eg. flows into equity, FDI \>\> appreciation
4. savings and investment (not common)
◎ if country has current acct deficit, must keep currency strong
186
EMC | Inflation effects on bonds
Does poorly, prices decline; Does well during deflation as prices rise
187
EMC | 2 international links
1. trade
2. capital flows (debt, equity, FDI)
188
EMC | exam notes:
for stock valuation, know: H-model, Fed model, Yardeni model, Tobin's q, equity q
189
Equity Valuation | Cobb-Douglas equation
• estimates country's real economic output
• Y = TFP \* K^a \* L^b
Y = real output
TFP = total factor productivity (aka A)
K = capital stock
L = labor input
a = output elasticity of capital stock
b = 1 - a = elasticity of labor
190
Equity Valuation | Cobb-Douglas equation: % change variation
%chg Y = %chg A + a \* %chg K + (1 - a) \* %chg L
• if TFP is constant (const returns to scale), then %chg A = 0 \>\> if K and A change by same amount, then Y changes by that % too
191
Equity Valuation | Cobb-Douglas equation: reasons TFP changes
1. technology
2. restrictions on labor or capital flows
3. trade restrictions
4. laws
5. division of labor
6. depleting/discovering natural resourcs
192
Equity Valuation | Cobb-Douglas equation: Solow residual
%chg TFP = %chg Y - a \* %chg K - (1 - a) \* %chg L
• portion of change in output related to change in total factor productivity
193
Equity Valuation | Pro of investing in a developing country with low corr to developed countries
* pro is diversification
* this can lead to lower required return by global investors
194
Equity Valuation | H-model
Po = Do / R - Gl \* (1 + Gl + N / 2 \* (Gs - Gl))
• div discount model with initial super growth
195
Equity Valuation | H-model: input relationships to output
* yrs to normal growth UP \>\> P UP
* either growth rate UP \>\> P UP
* required return UP \>\> P DOWN
196
Equity Valuation | top down vs bottom up
* top down: macroecon \>\> economy \>\> asset class \>\> sector \>\> individual firm
* bottom up: the opposite
* which to use depends on analysts investment strategy
197
Equity Valuation | why top down and bottom up can have different EPS results
* top down weakness: model is poor due to regime change, poor input variables (specfication problem), etc
* bottom up weakness: firms are too optimistic on the way down in a business cyclee and too pesimistic on the way up
198
Equity Valuation | 3 Relative value models for stocks vs bonds
1. Fed model
2. Yardeni model
3. 10-yr moving average PE model
199
Equity Valuation | Relative value: Fed model
• Fed ratio = S&P earnings yld / 10 yr Treasury yld
S&P yld: total op earnings / index value
• some say it should equal 1; in practice, is great than 1 and analysts look for significant changes away from LT average
200
Equity Valuation | Relative value: Fed model weaknesses
1. Ignores equity risk premium
2. Ignores SP earnings growth
3. compares real variable (index) to nominal variable (T yld)
201
Equity Valuation | Relative value: Yardeni model
• Yardeni 'fair' earnings yld for mkt = Yb - d(LTEG)
Yb = yld on A-rated corp bonds
d = weight for earnings growth (historically: 0.10)
LTEG = 5 yr consensus growth forecast
• estimates equilibrium earnings yld
• based off of constant growth div discount model (CGM) \>\> total earnings not just divs
202
Equity Valuation | Relative value: Yardeni model vs realized mkt yld
* if E1/P0 \> Yardeni \>\> mkt undervalued
* if E1/P0 \< Yardeni \>\> mkt overvalued
* can also be used as a ratio: mkt / Yardeni
203
Equity Valuation | Relative value: Yardeni weaknesses
1. uses corp bond yld as proxy for equity risk premium; this is a default risk, not a equity risk metric
2. relies on estimate of value investors place on earnings growth (d); could be wrong
3. relies on consensus estimate of growth (LTEG); could be wrong
4. assumes d and LTEG are constant; might not be
204
Equity Valuation | Relative value: 10 Yr Moving Average P/E
* Pnow/10 yr MA(E)
* compare the current 10 yr MA P/E to it's historical value
* uses real, inf adj figures for both P and E's
205
Equity Valuation | Relative value: 10 Yr Moving Average P/E: comments
1. considers inf effects
2. captures business cycle
3. backward looking (negative)
4. does not capture accounting rule changes
5. not good for ST analysis because extreme P/E can persist for a while
206
Equity Valuation | Asset-based value: Tobin's q and equit q
• Tobin's q = mkt val of debt + equity / asset replacement cost
• equity q = mkt val equity / net asset replacement cost
• if \> 1 \>\> overvalued; \< 1 \>\> undervalued
• weaknesses
◎ estimating replacement cost
◎ discrepancies persist
• mean-reverting (makes it easy to use)
207
BRICs | 6 largest economies in 2050
1. China
2. US
3. India
4. Japan
5. Brazil
6. Russia
208
BRICs | currency strength
• relative to their PPP, BRIC currencies are weak due to low income levels, high inflation and prices
209
BRICs | ingredients for a successful macroeconomic environment
1. stable inflation
2. fiscal policy
3. stable currency
4. good govt
210
BRICs | ingredients for a successful economy
1. macreconomic stability
2. instiutional efficiency
3. open trade
4. worker education
211
BRICs | important institutions in the economy
1. financial
2. markets
3. legal
4. govt
5. health
6. education
212
Asset Allocation | What is it?
* SAA is investor's desired exposure to systemic risk
* SAA = Capital Market Expectations + IPS
* asset weights are 'targets'
* portfolio is 'policy portfolio' or 'target portfolio' or 'benchmark'
* specific weights with each asset give desired systemic risk exposure
213
Asset Allocation | Tactical asset allocation
* managers attempt to generate alpha (excess return)
* deviates from SAA
* taking advantage of ST opportunities in the market
* TAA creates additional risk
* big focus: possible high cost of TAA due to transaction cost and illiquidity of alternative investments
214
Asset Allocation | SAA vs TAA
* SAA is LT allocation to different assets towards the goals and limitations of the IPS
* TAA is ST alpha
* SAA is systemic risk
* TAA is specific risk
* SAA accounts for almost the entire risk and return of the portfolio
215
Asset Allocation | ALM SAA vs Asset-only SAA
* ALM SAA models liabilities and allocates assets in relation to those liabilities
* Asset-only SAA disregards liabilites and maximizes return in relation to a specified level of risk
* ALM can be applied to any investor (eg. individiual)
* seems like ALM is superior
216
Asset Allocation | Dynamic vs Static Asset Allocation
* Dynamic looks at the investment outcomes of one time period on following time periods
* Static assesses each time period independently (often just a single period)
* Dynamic is superior (often used with ALM SAA)
217
Asset Allocation | effects of loss aversion
loss \>\> desire to make back the loss \>\> taking on too much risk
218
Asset Allocation | effects of mental accounting
* investor segments his needs and creates an independent investment strategy for each need
* investor does not look at portfolio in the aggregate \>\> does not access correlations or overall risk / return and diversification
219
Asset Allocation | effects of regret and fear of regret
• regret \>\> not taking a loss \>\> bigger loss / inefficient investment strategy
• fear of regret
◎ \>\> not taking action / too conservative \>\> inefficient investment strategy
◎ holding both winners and losers too long
220
Asset Allocation | rates: addition vs compound
• use compound when
◎ asked for
◎ multi-period
◎ path dependent
• otherwise use addition
221
Asset Allocation | Utility Adjusted Return
• adjusts return based on investor's risk aversion and portfolio variance
• U = R - .005 \* A \* var(portfolio)
U = utility adjusted return on specific portfolio
R = expected return
A = investor's risk aversion score
var(portfolio) = portfolio variance
• if using decimals for return, then use .05
222
Asset Allocation | 3 downside risks
1. shortfall
2. semivariance
3. target semivariance
4. Roy's Safety-First Measure
223
Asset Allocation | Roy's safety first measure
* RSF = (Rp - Rmar) / std dev p
* downside risk measure
* finds num of std devs the exp return is from the min acceptable return
224
Asset Allocation | Defining (specifying) asset classes
* class includes similar assets by description, system risk and other statistics
* classes are not highly correlated \>\> diversification
* distinct (no single investment fit two classes)
* aggregate of classes should encompass all investments \>\> increases return at all risk levels
* in aggregate contain many liquid assets
225
Asset Allocation | 6 common asset classes
1. domestic equity
2. domestic fixed income
3. global equity
4. global fixed income
5. cash & equivalents
6. alternative investments (real estate, PE, hedge funds, etc)
226
Asset Allocation | Deciding to add an investment to a portfolio
If Si \> Sp \* corr(i,p), Then yes, add it. Otherwise, no.
Si = new investment sharpe
Sp = existing portfolio sharpe
227
Asset Allocation | Asset allocation process
1. capital market expectation (CME)
2. effects on each asset class
3. allocate across classes that best meet IPS
4. monitor
5. revise
228
Asset management | general 3 step process throughout all management
1. action
2. monitor/evaluate
3. revise
229
Asset Allocation | 6 allocation methods
1. mean-variance optimization (MVO)
2. resampled efficient frontier
3. Black-Littman
4. Monte Carlo
5. ALM
6. experience-based
230
Asset Allocation | mean variance: constrained vs unconstrained
unconstrained allows short selling to create efficient portfolios; constrained does not
231
Asset Allocation | Black's mean variance theorem
any min-variance portfolio can be described as the weighted average of two other min-variance portfolios
232
Asset Allocation | MVO is how many periods
1
233
Asset Allocation | Efficient frontier ` CAL and CML
* CAL is the line defined by a risk free asset and an efficient frontier (EF) risky portfolio
* CML is the CAL with the market portfolio (everyone should hold it if everyone had same assessments)
234
Asset Allocation | Problem with CML
* often a risk free asset does not effectively exist (known return, std dev and corr = 0)
* Borrowing/lending the risk free asset is often effectively non-optimal with obligations \*borrowing) and fees (both)
235
Asset Allocation | exam note:
unless risk free or CML is specified, assume world of portfolios are those on the efficient frontier (EF)
236
Asset Allocation | Resampled Efficient Frontier (REF)
* EF is recreated using monte carlo, historical data and CME
* at each point on the frontier is the distribution from an average of multiple portfolios with the same expected return
* if the current portfolio is within a specificed confidence interval of the efficient portfolio (statistically equivalent), then no need to rebalance
237
Asset Allocation | advantages of REF vs EF
1. averaging process \>\> more stable frontier \>\> minor input changes \>\> minor effects on REF
2. portfolios more diversified
3. less rebalancing because existing portfolio likely to be statistically same as EF portfolio \>\> less turnover \>\> less cost
238
Asset Allocation | disadvantages of REF vs RF
1. lack of sound theoretical basis
2. same as MVO, historical data may not forecast future outcomes
239
Asset Allocation | Black-Litterman: unconstrained BL model (UBL)
1. manager picks global index as portfolio template
2. adjusts weights based on manager's expectations of asset classes
240
Asset Allocation | Black-Litterman: BL model (BL)
1. manager selects global index \>\> historical weights, std devs, corrs
2. reverse optimization / back solve / back out expected return (mkt consensus), market risk premium and cov of the assets (mkt consensus???)
3. adjusts returns and std dev based on manager's opinions
4. generate MVO (mean variance optimization) based on adjusted values
• no negative weights (short sales)
• more systematic/mathematical than UBL
• assumes financial mkts equilibrium
241
Asset Allocation | Black-Litterman: pros of BL model
1. mkt consensus exp return (only model that does not require estimates of exp return)
2. more diversification
3. less sensitive to input changes
242
Asset Allocation | ALM - risk graph
similar to CAL, but Y = expected surplus; X = st dev of surplus
243
Asset Allocation | ALM with other models
BL and monte carlo can both be used to help set ALM asset weights
244
Asset Allocation | how do I find the return, st dev and asset allocations of two combined portfolios
* R = W1 \* R1 + W2 \* R2
* SD = W1 \* SD1 + W2 \* SD2 (approx when corr = 1)
* portfolio 1 weight \* asset A weight in portfolio 1 + portfolio 2 weight \* asset A weight in portfolio 2 = new asset weight
245
Asset Allocation | ALM: MSVP
minimum surplus variance portfolio (min var and lowest surplus)
246
Asset Allocation | Exerience Based Technique (EBT)
* process of elimination using IPS
* 60/40 equity/bonds is mix for avg investor
247
Asset Allocation | Mean variance optimization (MVO): 6 strengths
1. optimization programs to find EF are inexpensive and commercially available
2. typically no negative weights
3. cash is included in risky assets
4. widely accepted
5. easy to adapt to Roy's
6. EF model can be simplified with corner portfolios
248
Asset Allocation | Mean variance optimization (MVO): 5 weaknesses
1. number and nature of required estimates
2. estimation bias in exp returns
3. static 1 period approach
4. output may be under diversified
5. ouput can be very sensitive to inputs
249
Asset Allocation | Resampled efficient frontier (REF): strengths
1. EF more stable (less impact from small input changes)
2. more diversified than traditional MVO
3. commerially available software
250
Asset Allocation | Resampled efficient frontier (REF) : weaknesses
1. no theoretical basis
2. inputs based on historical data
251
Asset Allocation | Black-Litterman: strength
1. Theo justifiable way to address input sensitivity & incorporate manager's views
2. more stable SAA
3. more diversification
4. unconstrained or constrained (better)
5. constrained quantifies and begins with mkt consensus returns, then let's manager adjust
6. commercially available
252
Asset Allocation | Black-Litterman: weaknesses
1. inputs based on historical data
2. complex
253
Asset Allocation | monte carlo simulation: strengths
1. stats tool to augment other approaches
2. incorporates path dependency
3. prob distribution can be used to answer liklihood to meet/miss returns
4. can be used to model liabilities and surplus
5. commercially available
254
Asset Allocation | monte carlo simulation: weaknesses
1. complex
2. false confidence due to complexity; only as good as assumptins, inputs
255
Asset Allocation | ALM: strengths
1. allocation of assets based on liabilities
2. surplus frontier; surplus vs risk
3. commercially available
4. otherwise similar to MVO
256
Asset Allocation | ALM: weaknesses
• same as MVO
1. number and nature of required estimates
2. estimation bias in exp returns
3. static 1 period approach
4. output may be under diversified
5. ouput can be very sensitive to inputs
257
Asset Allocation | experience based technique (EBT): strengths
1. uses decades of experience
2. easy to understand; consistent with more complex approaches
3. inexpensive
258
Asset Allocation | experience based technique (EBT): weaknesses
1. too simple for some investors
2. rules can be contradictory
259
Asset Allocation | Corner portfolios
* on the efficient frontier of MVO
* not clear how they are defined, but they are portfolios on the EF, which linear combination can be used to calculate other portfolios of a specific return or risk
260
my note:
don't forget to use compound calc on returns if 'compounding' or 'multiperiod' are mentioned
261
Asset Allocation | market portfolio on EF and sharpe ratio
the portfolio with the highest sharpe ratio ~ market portfolio
262
Asset Allocation | if a higher return than the mkt portfolio is required without borrowing
* pick a portfolio on the EF with the required return
* can use corner portfolios to approx the new portfolio return, std dev and asset allocations
263
Asset Allocation | differences between individuals and institutions
1. wealth accumulation is to meet goals like retirement and college (???)
2. structure of income and wealth accumulation
3. longevity risk
4. mortality risk
264
Asset Allocation | EXAMPLE of ndividual human and financial capital by age
• Example; none of the inputs are true in all cases, eg.
◎ HC = 100% bond
◎ retire at 60
◎ etc.
• HC is always 100% like a bond
• age 30: 10/90 FC/HC; FC: 100% eqty \>\> TC (total cap): 10/90 equity/bond
• age 50: 60/40 FC/HC; FC: 83.3 eqty / 16.6 bond \>\> TC: 50/50
• age 60: 100/0 FC/HC; FC: 50/50 \>\> TC: 50/50
265
Asset Allocation | reasons for international investment
1. reduced risk through low correlation
2. higher returns (if low corr and domestic is down, int'l might be up)
266
Asset Allocation | foreign asset risk
1. volatility of foreign asset value
2. volatility of foreign currency value
267
Asset Allocation | 5 correlation factors between countries
1. govt regulations
2. tech specialization
3. fiscal policy
4. monetary policy
5. culture & social differences
268
Asset Allocation | effect of int'l diversification on the efficient frontier (EF)
shifts curve up (same risk, higher return)
269
Asset Allocation | effect of adding int'l bonds to a int'l stock portfolio
• positive
• 3 factors:
◎ corr of global bond mkts
◎ corr of bonds to the stock portfolio
◎ if currency is hedged
270
Asset Allocation | Return on foreign asset equation
Rdom = Rlc + S + S \* Rlc
Rdom = return in investor currency(DC)
Rlc = return in local currency OF ASSET
S = %chg in FC(foreign currency)
• Local currency is NOT domestic currency!
271
Asset Allocation | risk of foreign asset (volatility of return)
VARdom = VARfa + VARfc + 2 \* SDfa \* SDfc \* Corr(fa, fc)
VARdom = var of domestic return
VARfa = var of foreign asset value
VARfc = var of foreign currency value
SD = standard deviation
Corr = correlation
• weights for both are 1, so can be dropped
272
Asset Allocation | Standard dev of domestic return will always be less/greater than
```
SD = stand dev
fa = foreign asset value
fc = foreign currency value
```
273
Asset Allocation | what is the contribution of currency risk
• =SDdom - SDfa
◎ SD = stand dev
◎ dom = domestic return
◎ fa = foreign asset value
274
Asset Allocation | currency risk not a major negative in foreign investment
1. combined risk of currency and foreign assets \< sum of currency risk + foreign assets risk
2. currency risk can be hedged
3. reduced thru diversification across multiple countries
• half the risk of foreigh stock risk (tho 2x bond risk)
• currency value mean reverts and dictated by fundamentals
275
Asset Allocation | argument against domestic-foreign asset diversification
• correlations have increased over time
• correlations among markets increase during volatile times when diversification is most important
• reason corr has increased:
◎ more trade
◎ capital mkt integration
◎ foreign corp are not multi-national and do not offer diversifcation
◎ capital mobility
276
Asset Allocation | convergence
as volatility increases, correlations increase (due to economic forces)
• empirical evidence is mixed; some crises have it, others do not
277
exam note: be able to argue both sides of 'corr increases when mkt volatility increases'
278
Asset Allocation | 7 reasons investors don't invest internationally
1. transaction costs
2. regs
3. taxes
4. currency risk
5. political risk
6. mkt efficiency
7. unfamiliarity
279
asset Allocation | barriers to int'l investment: transaction costs
* trading costs often higher outside US (eg. brokerage comm)
* stamp taxes
* price impact fees (on large block trades)
* custodial costs (multiple layers)
* record keeping and accounting costs
* management costs
* altogether: 10-12 basis pts
* alternative: ADR's for smaller investors (not great for large investors)
280
asset Allocation | barriers to int'l investment: regulations
* domestic regs limiting foreign investment (eg. pension fund regs)
* foreign regs limiting "foreign" investment in their companies (eg. many emerging mkts limit % owned of their companies)
281
Asset Allocation | barriers to int'l investment: taxes
• eg. foreign country withholding taxes on dividends for a period of months is nuisance
282
Asset Allocation | barriers to int'l investment: currency
* costs of accounting and trading (eg. converting)
* increased return volatility, tho this can be hedged
283
Asset Allocation | barriers to int'l investment: political risk
• eg.
◎ govt led currency devaluation
◎ nationalization
◎ special regs on foreign investors
284
Asset Allocation | barriers to int'l investment: market efficiency
* illiquidity of emerging mkts
* capital controls (eg. restricting withdrawl from country)
* lack of info
* integrity (insider trading)
285
Asset Allocation | barriers to int'l investment: unfamiliarity
fear of the unknown \>\> belief that foreign investments are riskier
286
Asset Allocation | global vs international investing
* corps are less conglomerate (across industries) and more int'l (across countries) than in the past
* global diversification = country diversification + industry diversification
287
Asset Allocation | Emerging markets traits
• good investments due to high return (in part from lack of integration), and low corr to developed mkts
• higher return and volatility
• not normal dist; large left tail
• crises persist longer
• high corr with other emerging mkts during crises
• common issues:
◎ unstable govt and social order
◎ undeveloped infrastructure
◎ poor education
◎ corrupt govt
◎ currency and asset value often pos corr
288
Asset Allocation | Emerging markets: 7 investability issues
1. reg limits on amount of stocks foreigners can own in aggregate or in a company
2. low free float due to govt ownership \>\> illiquidity
3. restrictions on cap repatriation
4. discriminatory taxation on foreigners
5. restrictions on currency conversions
6. reg req authorized investor status
7. low liquidity
CFA
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