Week 5 Flashcards
all of the available asset allocation approaches that can be employed to assist the asset allocation decision
A
Mean-variance analysis
B
Liability-driven investing (e.g. DB funds)
C
Benchmark-related
D
Fundamental risk approach
E
Two-stage approach
F
Scenario analysis
G
Dynamic strategies
H
Fill the buckets
Is the amount of “liability” in a DB fund totally determined by the portfolio manager or the board?
liability is not a choice. can be determined by some extent e.g. close DB fund to future new employees
the liability in a DB fund is an
actuarial estimate of the present value of future retirement benefits payable to members.
Is the “liability” driven by discount rate applied to projected benefits?
valuation of projected liabiiities rely on numerator (salary growth, longevity of employees)
denominator the discount rate
Why is the “liability” viewed as a negative asset (holding this asset results in paying out cash flows).
negative cash flows in the future
distinguish between DB fund managers and active equity managers?
db funds have their own characteristics/projected liabilites to meet, no benchmark performance
active australian equity managers given ASX 200 and ASX 100 benchmark as performance target
should all DB funds choose the minimum risk portfolio?
NO, minimum risk portfolio in DB funds is the portfolio or asset allocation that will provide perfect match between the assets and projected liabiltes
each db funds has its own board to go through negotaition process with sponsoring entity. opinion of representative from union of employees. use best match of assets and liabilites as a STARTING POINT then come up with asset allocation process
The asset allocation of DB funds is the outcome that
that balances the objectives of all stakeholders, i.e. sponsoring entity, members, government, portfolio manager, etc.
Mean-variance optimization can be applied to a DB fund asset alloction analysis if
the projected liability can be characterized and included as a negative asset in its total portfolio. This analysis helps to understand how the liability contributes to the total portfoio risk and return (its covariance with all the other assets in the portfolio).
helps portfolio manager to understand the projected liability to the total portfolio risk and return.
Fundamental risk approach may improve the risk-return tradeoff of portfolios by
switching to assets of similar expected return and lower standard deviations
apply on top of quantitiative asset allocation output to improve economic exposure
Fundamental risk approach (mostly qualitative) may be applied in
addition to a quantitative asset allocation approach, eg. mean-variance optimization, to improve the diversification of the protfolio marginally.
List methods of forecasting the ER of a group of assets
- implied view method
- black-litterman approach that combines market equilibrium and investors expectation
- Bayesian technique, for instance, James Stein estimator
Confidence interval around per-annum ER
usually narrows with investment horizon
wealth is
accumulation of return over multiple periods.
confidence interval around wealth
may increase or decrease with investment horizon given long term view and returns are not serially correlated
depends how ER returns are positive or negative.
variance is a
linear function of time only if returns and independently and individually distributed.
risk as measured by a shortfall constraint
depends on the mean and variance of means
shortfall constraint = probability of loss
method most likely to be an error maximiser/ generate an error maximiser/generate errors because of the errors in the inputs i.e. STD and ER
i.e. generate portfolios than remain largely a reflection of any errors or inconsistencies in the inputs
mean-variance optimisation based on historical inputs with asset weighting constraints imposed e.g. 20%
higher risk of errors in input. these will fit into mean-variance optimsisation –> mean variance optimisation = error maximiser
which of the following optimisation methods is most likely to generate portfolios than remain largely a reflection of any errors or inconsistencies in the inputs?
what are the inputs
STD and ER in mean variance optimisation model.
mean-variance optimisation with an additional constraint in benchmark risk i.e. tracking error versus the peer benchmark
why does this not make the mean-variance optimisatoin an error maximiser
even though you are using historical inputs, tracking error in place, more likely to generate something meaningful.
In instances where the expected returns do not seem reasonable, how might you respond in order to establish a more reasonable basis for analysis? (Implied views method)
option 6
Use another return modeling approach
In instances where the expected returns do not seem reasonable, how might you respond in order to establish a more reasonable basis for analysis? (Implied views method)
option 5
Adjust inputs towards something considered to be more reasonable
(Note: This probably needs to be done within a parametric approach, so that E[R]s and covariances (or standard deviation and correlation) are all adjusted towards their “underlying” levels, e.g. push up both E[R] and beta on DP. Under the non-parametric, data-based approach, only the mean and hence E[R] can be readily adjusted.)
In instances where the expected returns do not seem reasonable, how might you respond in order to establish a more reasonable basis for analysis? (Implied views method)
option 4
Possibly change the reference portfolio. (Note: This may be problematic. The reference portfolio has probably been selected for a specific reason, such as representing the peer group, etc. Also you should ideally use the reference portfolio relative to which assets are priced in the market, in the spirit of the CAPM. However, the identity of this portfolio is quite unclear
In instances where the expected returns do not seem reasonable, how might you respond in order to establish a more reasonable basis for analysis?
option 2
Try a different estimation interval (e.g. yearly data) or time periods, and see if estimates improve
In instances where the expected returns do not seem reasonable, how might you respond in order to establish a more reasonable basis for analysis?
option 1
Perhaps do nothing: the implied views approach may still provide a reasonable basis for your analysis, even if not perfect. Ask if any errors may make a significant difference to the outcomes
Data-based (non-parametric) analysis
Diversifying into commodities
but
− Increase in Sharpe ratio does NOT eventuate without the +0.33% adjustment to E[R] (try for yourself to confirm)
− Hence the benefit of adding commodities can depend on investor preferences, objectives and expectations. For instance, funding source may depend on whether investor prefers higher returns or lower risk
Data-based (non-parametric) analysis
Diversifying into commodities
appears
− Portfolio risk and return are both decreased if funded from all assets or equities, but reverse happens if funded from FI.
− Sharpe ratio increase when funded by all assets, equities or FI. It seems that the switching strategy does improve the risk-return trade-off for investor’s portfolio.
Data-based (non-parametric) analysis
Switch -10% from AE into WE (+6% unhedged, +4% hedged).
Equity switch On portfolio
Portfolio returns and Sharpe ratio both rise notably when return on WE is increased by 0.50%. Thus such a switch may be worthwhile if one had a more positive view of WE
This hints that the results from such analysis can be quite sensitive to (questionable) E[R] estimates.
Data-based (non-parametric) analysis
Switch -10% from AE into WE (+6% unhedged, +4% hedged).
Equity switch On baseline return inputs
On baseline return inputs, moving towards a more global equity portfolio reduces both return and risk on baseline inputs, but Sharpe ratio decreases. Hence limited benefit. (Note: Benchmark portfolio is “optimal” by construction under implied views, thus any change of weights amongst the existing assets will decrease the Sharpe ratio.)
Parametric analysis of adjustments to the baseline portfolio and general discussion
The parametric approach permits evaluation of
The parametric approach permits evaluation of assets for which a full data history does not exist, providing you can form estimates for expected returns and covariance
Parametric analysis of adjustments to the baseline portfolio and general discussion
Introduce a 10% weighting to emerging markets (EM). Fund the investment from all equities as follows: -5% AE, -3% WE, unh, -2% WE, h. (After the analysis is complete, reverse the switch so weights are back to the baseline).
• Introduce a 10% weighting to index-linked bonds (ILB). Fund the investment from fixed interest as follows: -5% AFI, -5% WFI.
What benefits arise from adding these two new assets to the portfolio?
Benefit 3
Adding ILBs, switching from FI: Expected return, risk and the Sharpe ratio all decrease, albeit marginally. This is a switch where related FI assets are replaced, hence diversification benefits are limited and portfolio remains concentrated. Hence no substantial benefit.
Parametric analysis of adjustments to the baseline portfolio and general discussion
Introduce a 10% weighting to emerging markets (EM). Fund the investment from all equities as follows: -5% AE, -3% WE, unh, -2% WE, h. (After the analysis is complete, reverse the switch so weights are back to the baseline).
• Introduce a 10% weighting to index-linked bonds (ILB). Fund the investment from fixed interest as follows: -5% AFI, -5% WFI.
What benefits arise from adding these two new assets to the portfolio?
Benefit 2
Adding EMs, switching from other equities: Expected return, risk and the Sharpe ratio all increase. Hence this seems like a good move, providing the additional risk is acceptable.
Parametric analysis of adjustments to the baseline portfolio and general discussion
Introduce a 10% weighting to emerging markets (EM). Fund the investment from all equities as follows: -5% AE, -3% WE, unh, -2% WE, h. (After the analysis is complete, reverse the switch so weights are back to the baseline).
• Introduce a 10% weighting to index-linked bonds (ILB). Fund the investment from fixed interest as follows: -5% AFI, -5% WFI.
What benefits arise from adding these two new assets to the portfolio?
Benefit 1
Potential diversification benefits: Adding new assets offers the potential for a more efficient portfolio, with a higher Sharpe ratio. This can work because the benchmark portfolio does not hold all available assets, hence may be sub-optimal. In other words, adding new assets may generate a higher efficient frontier.
To what extent might the following investments deliver ‘alpha’ versus ‘beta’, or something else?
opportunistic direct property fund that engages in property acquisition and development.
Combination of both alpha and beta. There is property beta, and exposure to fundamental factors such as the economy.
There is also an element of returns attributable to the management process, although they do not fully adhere to the traditional view of alpha as skillbased.
Some returns also arise from adding economic value to the underlying assets themselves.
To what extent might the following investments deliver ‘alpha’ versus ‘beta’, or something else?
Macro hedge fund that takes market-timing positions based on macroeconomic views.
Seeks alpha by timing beta. Hence will carry beta exposures, although which ones and in what quantum will vary continually.
Probably a hybrid of alpha and beta, and there is no clear demarcation between the two. Hence does not fit into the alpha/beta taxonomy very well.
To what extent might the following investments deliver ‘alpha’ versus ‘beta’, or something else?
Long-short hedge fund where each $1 of capital is invested in cash, but is used to support up to +$5 in long and -$5 in short equity positions.
‘Equity long-short’ hedge fund – Should be pure alpha, providing market exposure neutralized by longs and shorts. But beta exposure could creep in, if portfolio is not purged of all market exposure.
To what extent might the following investments deliver ‘alpha’ versus ‘beta’, or something else?
Enhanced passive equity fund, that is based around replicating a market index (e.g. S&P 500, S&P/ASX 300), but deviates occasionally from index weight when there is profit to be made. For instance, they may try to exploit temporary mispricing due to pressures stemming from large orders by other players (kind of a market-making or liquidity provision role); arbitrage between different classes of securities in the same company; or take advantage of IPOs (initial public offerings).
Both. Mainly beta, with a modest amount of alpha included (‘alpha-lite’)
beta and alpha
beta is exposure to the global market portfolio.
And, any positive expected return from exposure to a risk uncorrelated with this portfolio is alph
what is exotic beta
an exposure to a risk factor that is both uncorrelated with global markets and has a positive expected return – such as commodities –
The excess return from an exotic beta is alpha, and therefore, exotic betas should be included as a source of alpha in a portfolio.
benefit of exotic beta (source of alpha)
being relatively passive strategies, lower Transaction costs, liquidity requirements and management fees should be minimal, and capacity should be quite large
Since the returns are uncorrelated with those of the market, a modest exposure to an exotic beta should have minimal impact on the overall risk of most investors’ portfolios.
how to create a more efficient portfolio
Combining traditional beta with alpha from active management and relatively passive exposures to exotic betas
1) Beta: Basic Market Exposureexposure to developed equity markets can be obtained today by passively holding an index portfolio, traditional beta generates little cost in terms of fees, transaction costs or taxes. So, it makes sense for investors to include some beta as a return source in their portfolios. However, it should be complemented, and diversified, with other beta exposures and with active management strategies.
exposure to developed equity markets can be obtained today by passively holding an index portfolio, traditional beta generates little cost in terms of fees, transaction costs or taxes.
therefore investors include some beta as a return source in their portfolios. However, it should be complemented, and diversified, with other beta exposures and with active management strategies.
As we said earlier, exotic beta as a source of return shouldn’t persist because it is not an equilibrium phenomenon.
example
commodities are uncorrelated with equities and positive excess returns from commodities have been available for many decades, it’s likely that this premium will decline over time.
This will happen as commodity prices are bid up to equilibrium levels by investors trying to capture this exotic beta premium
Why does exotic beta exist?
risk premium for volatility exposure to individual assets s the primary source of the return in exotic betas
demand for liquidity
existence of returns from exotic beta is that the global market returns have fat tails on the downside, and investors are getting paid a premium to accept the risk of a market crash, which is concentrated in certain exotic betas
potential sources of exotic beta
commodities and catastrophe insurance
selling volatility in various markets, taking exposure to corporate default risk, investing in corporate mergers and acquisitions, and tilting toward stocks with characteristics such as value or small capitalization.
Increasingly, institutional portfolios are being built by considering active
(alpha) returns separately from broad market (beta) returns
The use of derivative securities to hedge and replicate market risk means that value added through active management need not be tied to the asset class in which the active management takes place
an institution that believes it has access to a fund manager who can produce alpha in some less prominent asset category
alpha with or without any commitment to the asset class itself.
Index fund
(e.g., the well-known S&P 500 fund provided by Vanguard), which provide beta exposure and require the investor to put up actual cash,
The portfolio return is divided into three parts:
the riskless return,
the risk premium from passive beta exposure,
and the alpha return from either (1) active management of individual securities or (2) tactical timing of beta exposures.
Beta Risk
Source of return
Skill required
Confidence in earning the expected return
Cost
Allocation of return among investors
Shape of the return distribution
Alpha Risk
Alpha should not be thought of as the return from active management, but rather as a
a return source that is not associated with any common risk factor
Hedge fund betas are
The common risk exposures shared by hedge fund managers pursuing similar strategies.
a meaningful component of their returns may be due to more common risk factors
Captures the insights behind a group of hedge fund strategies
- Reflects the same types of risk borne by hedge fund managers
- Earns a risk premium as compensation for this risk; if that risk premium is large, we may think of it as an inefficiency
Capturing hedge fund betas requires
significant skill, both in defining what is included in the strategies and in implementing them with the necessary techniques.
• Investing in hedge fund beta will allow many investors to
tap into a new, uncorrelated return source in an efficient and cost-effective manner
Colloquially, alpha has come to mean
“the excess returns from active managemen
alpha component of portfolio return
alpha, the portion of returns that cannot be attributed to these various risk factors
Beta component of portfolio return
One component is beta, the portion of returns that can be attributed to one or more systematic risk factors.
the most common risk factors (“betas”) were traditional investments, like equity and bond markets.
More recently, investors have broadened their portfolio analysis to include “exotic” betas, such as emerging market equities, high-yield debt, commodities and real estate.
What assets fall into the category of “exotic” betas
More recently, investors have diversified their portfolios across a wider range of asset classes than traditional developedmarket stocks and bonds.
Many of these new investments – commodities, real estate, emerging market equities and debt – fall into the category of “exotic” betas, or investments whose returns can be explained by exposure to less traditional risk factors
Like traditional betas, these tend to be associated with long-term exposure to one or more markets.
History of alpha and beta,
some active managers continued to beat the market’s return, generating alpha. investors began to realize that many managers were doing similar things to beat the market.
For example, some managers overweighted smaller-capitalization stocks, while others overweighted stocks that traded at low price-toearnings or low price-to-book ratios. Both of these groups tended to outperform the broad stock market indices over time
hedge fund beta
Convertible bond arbitrage
Convertible bonds has a common risk factor
beta of the strategy – the fundamental risk that these managers share – lies in the performance of convertible bonds relative to the hedging strategies managers use. The hedge fund beta for convertible bonds is created by holding a broad pool of convertible bonds and hedging out the stock, interest rate and credit exposures.
Defining the rules used to construct a beta involves three decisions:
- Inclusion – which securities are included (portfolio constituents) 2. Sizing – how much of each security to hold (portfolio construction) 3. Rebalancing – how to adjust these holdings over time (changes to #1 and #2)
hedge fund beta 3.
Rebalancing incurs transaction costs, which means more frequent rebalancing may reduce long-term returns.
hedge fund betas are inherently dynamic strategies, so portfolios must be assessed constantly and rebalanced regularly in order to preserve the integrity of each strategy
that only adjusts positions once a quarter would be dangerous.
Defining the rules used to construct a beta involves three decisions:
- Inclusion – which securities are included (portfolio constituents) 2. Sizing – how much of each security to hold (portfolio construction) 3. Rebalancing – how to adjust these holdings over time (changes to #1 and #2)
hedge fund beta 2.
Most hedge fund strategies involve offsetting long and short positions, which means there is no clear way to calibrate size.
Defining the rules used to construct a beta involves three decisions:
- Inclusion – which securities are included (portfolio constituents)
- Sizing – how much of each security to hold (portfolio construction)
- Rebalancing – how to adjust these holdings over time (changes to #1 and #2)
creating real-world hedge fund betas
requires skill (leverage, shorting, derivatives and the ability to trade frequently and with minimal market impact) in determining which strategies to include in a portfolio; d
efining the positions that comprise each strategy;
and then implementing (and rebalancing) those positions over time.
Alpha has zero correlation
with stocks and bonds
Investors Want Returns That Are:
- Positive over the long-term
- Uncorrelated to their existing portfolio exposures
Three Potential Sources for these Returns:
Investors Want Returns That Are:
- Positive over the long-term
- Uncorrelated to their existing portfolio exposures
As investors broaden their investment search from alpha to other new, non-correlated return sources, we expect they will seek to get additional exposure to hedge fund betas. We believe many portfolios have little exposure to these strategies. The easiest and most efficient way to gain exposure may be through
h direct investment in hedge fund betas. Today, hedge fund beta strategies are in their infancy, with only a handful of vehicles offered. But, we believe they have the potential to be a powerful contributor to portfolio returns
Creating hedge fund betas, as noted above, requires skill in
both definition (rules for inclusion, sizing and rebalancing of securities) and implementation (trading, financing, risk management).
Given the challenges of direct investment in hedge fund beta, the capacity constraints and the level of skill involved, these strategies should
command greater fees than traditional stock and bond market betas.
Hedge fund beta
capacity
hedge fund betas, which seek to exploit anomalies in global markets, inherently have limited capacity. If too much money seeks to exploit an anomaly, the anomaly will disappear and the expected returns from exploiting it will fall.
Conversely, when capital moves out of a strategy, the expected return rises.
The fact that hedge fund betas can get more or less crowded over time suggests that investors should consider a rebalancing policy to adjust their exposures.
Some asset allocation methods
Benchmark-relative
Using tracking error as a constraint to restrain allocation in mean-variance optimization.
How management of tracking error risk can imrove the utility of private investors and some mutual funds managers.
Some asset allocation methods
- Fundamental risk approach
- Step 1: Identify the common, fundamental risks to which the overall portfolio is most exposed
key risk factors
•Macroeconomic
–Economy; economic growth
–Income-share shifts
–Inflation
- Illiquidity
- Structural / systemic e.g. financial crisis, political, demographic
- Home bias
Some asset allocation methods
- Fundamental risk approach
- Step 1: Identify the common, fundamental risks to which the overall portfolio is most exposed
property
substantial exposure to Australia property market and also underlying that substantial risk exposure to Australian economic growth.
Some asset allocation methods
- Fundamental risk approach
- Step 2: Consider how the portfolio could be modified to reduce risk exposure without sacrificing too much E[r]
how to diversify?
Diversifying total portfolio into more asset classes so you have better risk return trade off
Some asset allocation methods
•Fundamental risk approach
When you run regression of total portfolio return and use index of equity and bond, find that much of the total portfolio return variation Is explained by
by the equity market movement over 90%.
Leading indicator of future market growth.
Some asset allocation methods
•Fundamental risk approach
Australian investor will hold Australian asset in ASX 200 or gov bonds in Australia. What do you have exposure to
Have 100% exposure to Australian economic growth. That Is the underlying risk factor.
Some asset allocation methods
•Fundamental risk approach
Economic diversification
- Step 1: Identify the common, fundamental risks to which the overall portfolio is most exposed i.e. affects the portfolio risk and return.
- Step 2: Consider how the portfolio could be modified to reduce risk exposure without sacrificing too much E[r]
Some asset allocation methods
Benchmark-relative
Using tracking error as a constraint to restrain allocation in mean-variance optimization.
How management of tracking error risk can imrove the utility of private investors and some mutual funds managers.
Fundamental risk approach is applied after
after quantitiative analysis e.g. mean variance optimization.
Have output e.g. diversified portfolio.
Look at possibilities of improving diversifcation of portfolio marginally
Portfolio modifications to attain more efficient portfolios
Using leverage
switch from A to C; if leverage is available, switch from C to D.
Portfolio modifications to attain more efficient portfolios
swapping assets of different exposure to a risk factor, but similar ER
e.g. office building or shopping centre. too much exposure to property market. I would like to diversify economic risk of total portfolio B by swapping asset to infrastructure project (similar ER as Office building but lower risk)
Infrastuture projects financed by gov, private entities,. Expected risk of infrastrucure project is less sensitive to economic development in economy
Other asset allocation methods
‘Fill the buckets’
It is a
It includes
It is a mental framework of asset allocation to present to investor given their circumstances and requirements about what investment opportunities are available
It includes the investment opportunity universe, instead of the traditional equity/bond/cash classifications. The framework allows broad market exposure and the opportunities to exploit market inefficiencies.
Other asset allocation methods
‘Fill the buckets’
there is no
No precise asset returns assumptions or percentage allocations are made because each investor has a unique circumstance.
You havea complete set of investment opportutnies for investor to choose from.
Does not produce any asset allocation
Two stage approach
Stage 1
At this stage you have great confidence in
confidence in data you have or great confidence or forecasting for that asset return.
Going to run optimization including the assets you can safely and confidently forecast the expected return, covariandce and std. e.g austrlian equity, Australia bond, international equity
Safe to run mean variance optimization.
Two stage approach
Stage 1
At this stage you have great confidence in
confidence in data you have or great confidence or forecasting for that asset return.
Going to run optimization including the assets you can safely and confidently forecast the expected return, covariandce and std. e.g austrlian equity, Australia bond, international equity
Safe to run mean variance optimization.
Two stage approach
Stage 2,
examine a list of things you want to test with your total portfolio,
introducing leverage, trying sensitivity or scenario analysis of forecastin different asset expected return, , std, covariance. Then you do asset allocation so you can havea greater chance of achieving the client’s objective
Two stage approach
Stage 2
what if labour gov comes into power- imputation credits
any excess imputation credits would no longer be paid as a cash refund if they have tax liability
Under the original system, imputation credits could be used to reduce an individual’s tax liability.
In 2001, the dividend imputation system was amended to allow any excess imputation credits i.e. those in excess of any tax liability, to be paid as a cash refund. This meant that those people with a tax rate lower than the company tax rate, generally 30%, would receive a cash refund
Two stage approach
Stage 2
run sensitivity analysis and scenario analysis.
example
If your investment horizon is for the next 5 years, in Australia will coincidence with another cycle of election. If your investment horizon is 3-5 years will allow for conditional modelling.
What if labour or liberal gov comes into power.
Two stage approach
Stage 2
you finetune
You finetune your analysis process given you have good understanding of how economy is going to evolve. And clearly defined investment horizon
Two stage approach
Stage 2
If you believe infrastructure
what do you do
Run a baseline portofolio baseline analysis of standard mean variance optimization then try to introduce new asset e.g. infrastructure in australia especially unlisted infrastrastructure.
Then impose your own expected return. How much excess this infrastructure project is going to offer on top of gov bond investment is the risk. How you may characterise covariance of infrastructure project on top of other assets in the portfolio
Two stage approach
Stage 2
Rely on?
–Rely on good judgment: supportable investment beliefs, logic, experience, simulations and sensitivity analysis
Two stage approach
Stage 2
investing in infrastrucutre look at
Look at funding from government; projected cash flow from project. Analyse robustly
Then decide how much you want to allocate in the asset by switching some funds in existing portfolio to this new asset
Two stage approach
Stage 2
Adjustments in stage 2 are expected to
example
to improve the chances of achieving the portfolio’s investment objectives. subjective approach
Example: over or under-weighting to various sub-components of broad assets classes, like over-weighting small cap stocks in global equity market.
Or include illiquid assets such as unlisted properties, PE and infrastructure.
Two stage approach
Stage 1
Why do we not use the output for asset allocation?
Whole class given same expected return, work on the same sample period and adjust return the same way, you ened up with same asset allocation
Two stage approach
Stage 2
what do you assume
–Optimization is unsafe
Two stage approach
Stage 1
what happens at the first stage
standard mean variance optimization
Resulting AA will meet plan risk-return objectives
Two stage approach
Stage 1
what do you assume
–Use equal expected returns for major equity markets
- assume all of the equity assets on average at equilibrium level they will have same level of expected return.
- E.g. assume Australian equity, international equity will have same levl of e® of 8% and same of std.
- that is their long term expectation and conditional modelling technique.
Two stage approach
First stage what do you not include
how do you include it?
First stage didn’t include assets that is difficult to forecast. Commodities are very volatile
If you want to include this asset, it wil be analysed in the second stage.
Two stage approach
Setting the stage
•collect inputs
Goals and preferences: objectives, risk tolerance
Circumstances: liabilities, asset classes, access, constraints
Capital markets: interest rate, asset returns, inflation, economic outlook
Investment horizon is 10_ years. Within 10 years have room to impose own
own conditional assumptions. E.g. Now they have concentrated exposure to propert market. you may start conditional modelling on how you will forecast performance of property market relative to other assts.
Two stage approach overcomes
the problem of hypersensitivity and model problem of standard mean variation optimization.
Dynamic strategies: Lifetime asset allocation
Recognises
Recognises that investment oportutnies changes, risk preference, circumstances change In different stages of their life
Dynamic strategies: Lifetime asset allocation
human capital when you retire
When they retire the value of human capital is obsolete. Your skills, knowledge not as updated. Ability to generate future cash flow is very limited.
Dynamic strategies: Lifetime asset allocation
For most investors human capital is
bond-like.
due to this substantial holding in bond-like assets, young people should diversify their financial assets towards equity market
Dynamic strategies: Lifetime asset allocation
in early stages of life what do you have
High human capital in early stages of life lead to wealth accumulation, clients need more allocation in growth assets, eg equity.
Dynamic strategies: Lifetime asset allocation
conditional asset allocation, allocation changes over time
Provides changes in portfolio adapting to changes in their life stage from growth to defensive
Scenario analysis
output
•Generating scenario output: provide rich information of return distribution, risk and diversification
Scenario analysis
analysis of potential scenarios in the future: economic growth, inflation, investor sentiment
Beta
Returns you may generate from passive market exposure
e.g. holding an asx 200 index or holding gov index.
Beta and alpha
fee
beta - cheap Vanguard Australian equity funds, they charge 20-30 basis points of management fee.
Beta and alpha
Generation
beta - just want to generate passive index return, you may choose to invest with market index e.g. Australian equity index provided by vanguard, colonial first state; passive product will provide you close match to return of a passive market index.
alpha - difficult to achieve; skill
Beta and alpha
availability
beta - widely available
alpha - rare alpha is supposed to be ‘zero sum game’, if you beat the market someone else must be losing.
Beta can be replicated and/or hedged using
using vehicles such as index futures, ETFs, swaps, etc
1.Risk modeling
beta
Alpha and beta framework will help us understand the risk of the portfolio coming from alpha or beta exposure
–Beta as common sources of variation (alpha is idiosyncratic)
–Beta exposures should be identified and managed
Interested in asst allocation of hedge funds and understand how they can generate ths outperformance in several years. One way you can do is
using alpha and beta. E.g. understand secrete of hegdge funds run the portfolio return of hedge funds against several beta exposures. S*p 500 index, some gov bond or corporate bond index so you have some ideas how return variations of hedge funds can be explained by passive index or beta exposure
used by a lot of portfolio managers esp when they want to find out secret of hedge funds or private equity funds
Alpha & Beta - Issues
50 years ago, funds managers hedge fund managers were adveritisng aggressively their skills in investing in small cap companies
. If you look at total returns of the funds, most of return variation is explained by
variation is explained by beta exposure and size effect. Not by selection of security, the small company and not by the skills of managers.
Alpha & Beta - Issues
•Beta masquerading as alpha
For actively managed funds, you believe you are buying market exposure (beta) and manager skills (alpha), for instance, a small cap fund.
It’s beating the market, but it’s the size factor (like the factor of Fama-French three factor model) that’s is generating the excess returns. It’s another form of market exposure, instead of skills.
exotic beta
transitory excess returns tied to a specific market-based exposure
exotic beta
example
Small cap company investment in some emerging markets can be classified as exotic beta exposure they have positive expected returns or even higher than broad market index.
exotic beta
Possible exotic beta sources:
high yield bonds, catastrophe bonds, commodities, emerging market equity, emerging market bond, global real estate, global small cap
exotic beta
Exotic beta exposure comes from transitory temporary market miscpricing of certain assets. E.g. commodities which his what we observed at the end of 1990s and early 2000s. They provide positive expected returns but low correlation with equity index or world equity market
‘Exotic beta’
The market is coming back
back to its equilibrium level. Past 1-2 decades, this correlation has increased with global equity market
Franking credits have been a particularly active feature for most
listed companies
If its proposed labor reforms are successfully legislated,
taxpayers will no longer be able to obtain cash refunds for excess credits if they exceed tax liabilities
more and more investors will move away from their home bias and begin looking offshore for higher returns
labour policy for franking credits
Financial impact on older investors and smfs
older independent investors will be most exposed – as they are most likely to receive franking credits in the form of cash refunds, which then contribute to their income stream
SMSF Association, provides the example that around 70 per cent of taxpayers who rely on shares as their preferred savings vehicle over the age of 75 receive franking credits, with an average annual value of $6,300.
The SMSF Association estimates that it will cut around $5,000 of income from the median SMSF in retirement phase earning around $50,000 per year in pension income with a 40 per cent allocation in Australian shares.
Franked dividends
refund
have a franking credit attached to them which represents the amount of tax the company has already paid. Franking credits are also known as imputation credits.
The refund applies when your total imputation credits that are attached to your franked dividends paid exceeds your basic income tax liability for the year.
A cash amount can be refunded to you reflecting the amount of excess imputation credits, after applying them and any other tax offsets to which you are entitled to
our dividend franking system is unique and often results in a
in a boost in the overall yield from Australian company shares, particularly for those on a low tax rate.
