FINM7008/2003 (Applied) Investments
Week 12
Revision
Xiaoting Wei
RSFAS, Australian National University
For this lecture, we will review the concepts covered
throughout the semester.
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We commenced the course by recognising
that an investment involves an entity:
▪ Directly or indirectly placing wealth in real or
financial assets that are expected to generate returns
in the future;
▪ Assuming a certain level of risk, or probability that
the investment will yield a lower than expected return;
and,
▪ Foregoing consumption of the invested wealth today
with the hope of generating further funds for future
consumption.
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Segmentation of Financial Markets
▪ Money market
▪ Capital market
How securities are trades?
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▪ Primary market vs. secondary market
▪ Privately held v.s. publicly traded companies
As investors are primarily concerned with risk
and return, it is important to understand how to
calculate each measure.
▪ Norminal interest rate vs. real interest rate
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▪ Holding period return (HPR)
▪ Geometric mean vs. Arithmatic mean
▪ Risk and risk premium
▪ Measures of return
▪ Expected return and standard deviation
▪ Sharpe Ratio
Recalling the assumption that investors prefer more
wealth to less but are also risk averse, we discussed
how portfolio managers aim to achieve the best
tradeoff between risk and return. Doing this involves:
▪ Deciding what fraction of money to invest in the risky
versus riskless assets, or making the capital allocation
decision. This step represents the first part of the asset
allocation decision; and,
▪ Thereafter, deciding which particular securities to invest
in within each asset class, or making the security
selection decision.
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We saw how the capital allocation decision can be broken down
into two distinct stages, namely:
▪ Identifying the risk-return tradeoff involved in choosing between risky
and riskless assets; and,
▪ Deciding the optimal mix of risky and riskless assets given risk aversion.
In doing this, we derived the Capital Allocation Line, (“CAL”),
which plots the complete portfolio characteristics for a given
weighting of risky assets. Thereafter, we graphically depicted
how an investor uses indifference curve analysis to select the
optimal portfolio in which to invest.
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Next, we:
▪ Asked what happens when the risky asset is actually a
portfolio comprised of multiple assets and the weights in
these assets have the potential to change?;
▪ Discussed how investors can identify the optimal risky
portfolio in both the simple situation where there are only
two risky assets as well as when multiple risky assets exist;
▪ Saw that, once the optimal risky portfolio has been
constructed, the individual investor’s degree of risk
aversion will determine the optimal proportion of the
complete portfolio to invest in the risky assets.
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Next, we examined the implications of portfolio theory
for the equilibrium structure of expected returns on
risky assets. More specifically, we first reviewed the
Sharpe-Lintner CAPM and its assumptions and, in doing
so, also discussed how:
▪ Researchers have sought to extend the model so as to make it
applicable to the real world by relaxing its assumptions. By
way of example, relaxing the assumption of unlimited
borrowing and lending at the risk free rate lead to the
development of the Zero-Beta CAPM; and,
▪ It is implemented in practice using index models.
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We then saw how we can combine the no-arbitrage argument
with the concept of factor models to derive a multifactor asset
pricing model known as the APT. More specifically, we:
▪ Derived a single-factor APT and showed that it implied an SML
equivalent to the CAPM;
▪ Extended the model to a multi-factor setting so as to account for the
existence of more than one risk; and,
▪ Discussed work that offers some insight into what risk factors should
be included in a multi-factor asset pricing model, namely that of Chen,
Roll and Ross and Fama and French.
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While some argue the CAPM cannot be truly tested unless the
composition of the true market portfolio is known and reflected
in all tests, others use a market proxy to test the model. The
results of these tests were mixed. Specifically:
▪ Early empirical evidence was inconsistent with the CAPM; but,
▪ More recent testing has provided greater support for the model.
In considering empirical evidence in relating to both the CAPM
and APT, it is also important to note that many of their
implications have been accepted in practice.
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Next we discussed whether the markets in which investors make
decisions are informationally efficient. More specifically, we:
▪ Were introduced to the three versions of the EMH;
▪ Considered evidence relating to the profitability of
momentum strategies, the ability of publicly available
information to predict positive abnormal risk-adjusted
returns and the occurrence of information leakages in the
lead up to the release of public information; and,
▪ Discussed how the evidence noted in the previous point at
least casts some doubt on the weak, semi-strong and
strong form versions of the EMH hypotheses respectively.
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Thereafter, we discussed how evidence on market inefficiency
has led to the emergence of the behavioural finance literature.
More specifically, the literature argues that:
▪ A lack of profitable strategies within the market does not
necessarily imply prices are correct; and,
▪ Prices are not reliable signals as to how investors should
allocate capital; however,
▪ The impact of investor irrationality on asset pricing is still
being debated; and,
▪ Therefore, it is too soon to know whether asset pricing
models incorporating behavioural components will gain
ongoing acceptance.
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For the following two lectures, we focused on fixed-
interest securities. More specifically, we:
▪ Reviewed and extended the bond pricing approach first
introduced in your prior studies; and,
▪ Discussed the term structure of interest rates, which is a
collection of theories that seek to explain the relationship
between time to maturity and yield to maturity. Theories
we discussed include the Expectations Hypothesis and
Liquidity Preference Theory.
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We then considered the numerous strategies that are available
to managers of bond portfolios, stratifying those discussed into
active and passive management approaches. In discussing bond
management strategies, we also considered how:
▪ Duration can be used as a measure of the sensitivity of bond prices to
changes in interest rates;
▪ A convexity adjustment can be made to duration measures to improve
their accuracy;
▪ Duration-matching can be used as a tool to immunise bond portfolios
from interest rate risk; and,
▪ Duration can be employed in other aspects of bond management.
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We then returned our discussions to portfolio
management in general, considering the:
▪ Various approaches available to measure portfolio
performance;
▪ Importance of adjusting performance measures to
take into account the risk associated with the
investment under consideration;
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▪ Range of risk-adjusted measures available when
assessing performance and the appropriateness of
each. Some of the measures we covered include
Sharpe’s measure, Treynor’s measure, Jensen’s
measure or the portfolio’s alpha and the
information or appraisal ratio; and,
▪ Techniques that are used to attribute portfolio
performance to certain parts of the investment
decision making process.
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Next, we introduced hedge funds. In particular,
we:
▪ Distinguished hedge funds from mutual funds;
▪ Discussed some of the strategies which hedge funds may
employ;
▪ Illustrated how to hedge a positive alpha portfolio from
market risk, via portable alpha and pure play; and
▪ Discussed some of the issues which may arise with
performance measurement and hedge fund fee structure.
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