In finance, a portfolio is an appropriate mix or collection of investments held by an institution or an individual. Holding a portfolio is a part of an investment and risk-limiting strategy called diversification. By owning several assets, certain types of risk (in particular specific risk) can be reduced. The assets in the portfolio could include Bank accounts; stocks, bonds, options, warrants, gold certificates, real estate, futures contracts, production facilities, or any other item that is expected to retain its value. In building up an investment portfolio a financial institution will typically conduct its own investment analysis, whilst a private individual may make use of the services of a financial advisor or a financial institution which offers portfolio management services. Management Portfolio management involves deciding what assets to include in the portfolio, given the goals of the portfolio owner and changing economic conditions. Selection involves deciding what assets to purchase, how many to purchase, when to purchase them, and what assets to divest. These decisions always involve some sort of performance measurement, most typically expected return on the portfolio, and the risk associated with this return (i.e. the standard deviation of the return). Typically the expected return from portfolios of different asset bundles are compared. The unique goals and circumstances of the investor must also be considered. Some investors are more risk averse than others. Mutual funds have developed particular techniques to optimize their portfolio holdings. See fund management for details. [edit]Portfolio formation Many strategies have been developed to form a portfolio. equally-weighted portfolio capitalization-weighted portfolio price-weighted portfolio optimal portfolio (for which the Sharpe ratio is highest) [edit]Models
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In finance, a portfolio is an appropriate mix or collection of investments held by an institution or an
individual.
Holding a portfolio is a part of an investment and risk-limiting strategy called diversification. By owning
several assets, certain types of risk (in particular specific risk) can be reduced. The assets in the
portfolio could include Bank accounts; stocks, bonds, options, warrants, gold certificates, real
estate, futures contracts, production facilities, or any other item that is expected to retain its value.
In building up an investment portfolio a financial institution will typically conduct its own investment
analysis, whilst a private individual may make use of the services of a financial advisor or a financial
institution which offers portfolio management services.
Management
Portfolio management involves deciding what assets to include in the portfolio, given the goals of
the portfolio owner and changing economic conditions. Selection involves deciding what assets to
purchase, how many to purchase, when to purchase them, and what assets to divest. These
decisions always involve some sort of performance measurement, most typically expected return on
the portfolio, and the risk associated with this return (i.e. the standard deviation of the return).
Typically the expected return from portfolios of different asset bundles are compared.
The unique goals and circumstances of the investor must also be considered. Some investors are
more risk averse than others.
Mutual funds have developed particular techniques to optimize their portfolio holdings. See fund
management for details.
[edit]Portfolio formation
Many strategies have been developed to form a portfolio.
equally-weighted portfolio
capitalization-weighted portfolio
price-weighted portfolio
optimal portfolio (for which the Sharpe ratio is highest)
[edit]Models
Some of the financial models used in the process of Valuation, stock selection, and management of
portfolios include:
Maximizing return, given an acceptable level of risk
Modern portfolio theory—a model proposed by Harry Markowitz among others
There are many different methods for calculating portfolio returns. A traditional method has been
using quarterly or monthly money-weighted returns. A money-weighted return calculated over a period
such as a month or a quarter assumes that the rate of return over that period is constant. As portfolio
returns actually fluctuate daily, money-weighted returns may only provide an approximation to a
portfolio’s actual return. These errors happen because of cashflows during the measurement period.
The size of the errors depends on three variables: the size of the cashflows, the timing of the
cashflows within the measurement period, and the volatility of the portfolio[1].
A more accurate method for calculating portfolio returns is to use the true time-weighted method. This
entails revaluing the portfolio on every date where a cashflow takes place (perhaps even every day),
and then compounding together the daily returns.
[edit]Attribution
Performance Attribution explains the active performance (i.e. the benchmark-relative performance) of
a portfolio. For example, a particular portfolio might be benchmarked against the S&P 500 index. If the
benchmark return over some period was 5%, and the portfolio return was 8%, this would leave an
active return of 3% to be explained. This 3% active return represents the component of the portfolio's
return that was generated by the investment manager (rather than by the benchmark).
There are different models for performance attribution, corresponding to different investment
processes. For example, one simple model explains the active return in "bottom-up" terms, as the
result of stock selection only. On the other hand, sector attribution explains the active return in terms
of both sector bets (for example, an overweight position in Materials, and an underweight position in
Financials), and also stock selection within each sector (for example, choosing to hold more of the
portfolio in one bank than another).
An altogether different paradigm for performance attribution is based on using factor models, such as
the Fama-French three-factor model.
Portfolio manager
A ' team of analysts and researchers, and are ultimately responsible for establishing an
investment strategy, selecting appropriate investments and allocating each investment properly for
a fund- or asset-management vehicle.
Portfolio managers are presented with investment ideas from internal buy-side analysts and sell-side
analysts from investment banks. It is their job to sift through the relevant information and use their
judgment to buy and sell securities. Throughout each day, they read reports, talk to company
managers and monitor industry and economic trends looking for the right company and time to invest
the portfolio's capital.
Portfolio managers make decisions about investment mix and policy, matching investments to
objectives, asset allocation for individuals and institutions, and balancing risk against. performance.
Portfolio management is about strengths, weaknesses, opportunities and threats in the choice of debt
vs. equity, domestic vs. international, growth vs. safety, and other tradeoffs encountered in the
attempt to maximize return at a given appetite for risk.
In the case of mutual and exchange-traded funds (ETFs), there are two forms of portfolio
management: passive and active. Passive management simply tracks a market index, commonly
referred to as indexing or index investing. Active management involves a single manager, co-
managers, or a team of managers who attempt to beat the market return by actively managing a
fund's portfolio through investment decisions based on research and decisions on individual
holdings. Closed-end funds are generally actively managed.
That's what warren buffet says about investing in the market..."The basic ideas of investing are to look
at stocks as business, use the market's fluctuations to your advantage, and seek a margin of
safety"....
Portfolio ManagementThe act or practice of making investment decisions in order to make the largest possible return. Portfolio management takes two basic forms: active and passive. Active management involves using technical, fundamental, or some other analysis to make trades on a fairly regular basis. For example, one may sell stock A in order to buy stock B. Then, a few days or weeks later, one may sell stock B to buy bond C. Passive management, on the other hand, involves buying an index, an exchange-traded fund, or some other investment vehicle with securities the investor does not directly choose. For example, one may buy an exchange-traded fund that holds all the stocks on the S&P 500. See also: Asset management, Investment adviser.
Portfolio Management is used to select a portfolio of new product development projects to achieve th following goals:
Maximize the profitability or value of the portfolio Provide balance Support the strategy of the enterprise
Portfolio Management is the responsibility of the senior management team of an organization or business unit. This team, which might be called the Product Committee, meets regularly to manage the product pipeline and make decisions about the product portfolio. Often, this is the same group that conducts the stage-gate reviews in the organization.
A logical starting point is to create a product strategy - markets, customers, products, strategy approach, competitive emphasis, etc. The second step is to understand the budget or resources available to balance the portfolio against. Third, each project must be assessed for profitability (rewards), investment requirements (resources), risks, and other appropriate factors.
The weighting of the goals in making decisions about products varies from company. But organizations must balance these goals: risk vs. profitability, new products vs. improvements, strategy fit vs. reward, market vs. product line, long-term vs. short-term. Several types of techniques have been used to support the portfolio management process:
Heuristic models Scoring techniques Visual or mapping techniques
The earliest Portfolio Management techniques optimized projects' profitability or financial returns using heuristic or mathematical models. However, this approach paid little attention to balance or aligning the portfolio to the organization's strategy. Scoring techniques weight and score criteria to take into account investment requirements, profitability, risk and strategic alignment. The shortcoming with this approach can be an over emphasis on financial measures and an inability to optimize the mix of projects. Mapping techniques use graphical presentation to visualize a portfolio's balance. These are typically presented in the form of a two-dimensional graph that shows the trade-off's or balance between two factors such as risks vs. profitability, marketplace fit vs. product line coverage, financial return vs. probability of success, etc.
The chart shown above provides a graphical view of the project portfolio risk-reward balance. It is used to assure balance in the portfolio of projects - neither too risky or conservative and appropriate levels of reward for the risk involved. The horizontal axis is Net Present Value, the vertical axis is Probability of Success. The size of the bubble is proportional to the total revenue generated over the lifetime sales of the product.
While this visual presentation is useful, it can't prioritize projects. Therefore, some mix of these techniques is appropriate to support the Portfolio Management Process. This mix is often dependent upon the priority of the goals.
Our recommended approach is to start with the overall business plan that should define the planned level of R&:D investment, resources (e.g., headcount, etc.), and related sales expected from new products. With multiple business units, product lines or types of development, we recommend a strategic allocation process based on the business plan. This strategic allocation should apportion the planned R&D investment into business units, product lines, markets, geographic areas, etc. It may also breakdown the R&D investment into types of development, e.g., technology development, platform development, new products, and upgrades/enhancements/line extensions, etc.
Once this is done, then a portfolio listing can be developed including the relevant portfolio data. We favor use of the development productivity index (DPI) or scores from the scoring method. The development productivity index is calculated as follows: (Net Present Value x Probability of Success) / Development Cost Remaining. It factors the NPV by the probability of both technical and commercial success. By dividing this result by the development cost remaining, it places more weight on projects nearer completion and with lower uncommitted costs. The scoring method uses a set of criertia (potentially different for each stage of the project) as a basis for scoring or evaluating each project. An example of this scoring method is shown with the worksheet below.
Weighting factors can be set for each criteria. The evaluators on a Product Committee score projects (1 to 10, where 10 is best). The worksheet computes the average scores and applies the weighting factors to compute the overall score. The maximum weighted score for a project is 100.
This portfolio list can then be ranked by either the development priority index or the score. An example of the portfolio list is shown below and the second illustration shows the category summary for the scoring method.
Once the organization has its prioritized list of projects, it then needs to determine where the cutoff is based on the business plan and the planned level of investment of the resources avaialable. This subset of the high priority projects then needs to be further analyzed and checked. The first step is to check that the prioritized list reflects the planned breakdown of projects based on the strategic allocation of the business plan. Pie charts such as the one below can be used for this purpose.
Other factors can also be checked using bubble charts. For example, the risk-reward balance is commonly checked using the bubble chart shown earlier. A final check is to analyze product and technology roadmaps for project relationships. For example, if a lower priority platform project was omitted from the protfolio priority list, the subsequent higher priority projects that depend on that platform or platform technology would be impossible to execute unless that platform project were included in the portfolio priority list. An example of a roadmap is shown below.
This overall portfolio management process is shown in the following diagram.
Finally, this balanced portfolio that has been developed is checked against the business plan as shown below to see if the plan goals have been achieved - projects within the planned R&D investment and resource levels and sales that have met the goals.
With the significant investments required to develop new products and the risks involved, Portfolio Management is becoming an increasingly important tool to make strategic decisions about product development and the investment of company resources. In many companies, current year revenues are increasingly based on new products developed in the last one to three years. Therefore, these portfolio decisions are the basis of a company's profitability and even its continued existence over the next several years.
Portfolio Management may refer to:
Investment management , handled by a portfolio manager
IT portfolio management
Project management
Project portfolio management
Investment management is the professional management of various securities (shares, bonds and
other securities) and assets (e.g., real estate) in order to meet specified investment goals for the
benefit of the investors. Investors may be institutions (insurance companies, pension funds,
corporations etc.) or private investors (both directly via investment contracts and more commonly
via collective investment schemes e.g. mutual funds or exchange-traded funds).
The term asset management is often used to refer to the investment management of collective
investments, (not necessarily) while the more generic fund management may refer to all forms of
institutional investment as well as investment management for private investors. Investment
managers who specialize in advisory or discretionary management on behalf of (normally wealthy)
private investors may often refer to their services as wealth management or portfolio management
often within the context of so-called "private banking".
The provision of 'investment management services' includes elements of financial statement analysis,
asset selection, stock selection, plan implementation and ongoing monitoring of investments.
Investment management is a large and important global industry in its own right responsible for
caretaking of trillions of yuan, dollars, euro, pounds and yen. Coming under the remit of financial
services many of the world's largest companies are at least in part investment managers and employ
millions of staff and create billions in revenue.
Fund manager (or investment adviser in the United States) refers to both a firm that provides
investment management services and an individual who directs fund management decisions.
Industry scope
The business of investment management has several facets, including the employment of
professional fund managers, research (of individual assets and asset classes), dealing, settlement,
marketing, internal auditing, and the preparation of reports for clients. The largest financial fund
managers are firms that exhibit all the complexity their size demands. Apart from the people who bring
in the money (marketers) and the people who direct investment (the fund managers), there are
compliance staff (to ensure accord with legislative and regulatory constraints), internal auditors of
various kinds (to examine internal systems and controls), financial controllers (to account for the
institutions' own money and costs), computer experts, and "back office" employees (to track and
record transactions and fund valuations for up to thousands of clients per institution).
[edit]Key problems of running such businesses
Key problems include:
revenue is directly linked to market valuations, so a major fall in asset prices causes a precipitous
above-average fund performance is difficult to sustain, and clients may not be patient during times
of poor performance;
successful fund managers are expensive and may be headhunted by competitors;
above-average fund performance appears to be dependent on the unique skills of the fund
manager; however, clients are loath to stake their investments on the ability of a few individuals-
they would rather see firm-wide success, attributable to a single philosophy and internal
discipline;
analysts who generate above-average returns often become sufficiently wealthy that they avoid
corporate employment in favor of managing their personal portfolios.
[edit]Representing the owners of shares
Institutions often control huge shareholdings. In most cases they are acting as fiduciary agents rather
than principals (direct owners). The owners of shares theoretically have great power to alter the
companies they own via the voting rights the shares carry and the consequent ability to pressure
managements, and if necessary out-vote them at annual and other meetings.
In practice, the ultimate owners of shares often do not exercise the power they collectively hold
(because the owners are many, each with small holdings); financial institutions (as agents) sometimes
do. There is a general belief that shareholders - in this case, the institutions acting as agents—could
and should exercise more active influence over the companies in which they hold shares (e.g., to hold
managers to account, to ensure Boards effective functioning). Such action would add a pressure
group to those (the regulators and the Board) overseeing management.
However there is the problem of how the institution should exercise this power. One way is for the
institution to decide, the other is for the institution to poll its beneficiaries. Assuming that the institution
polls, should it then: (i) Vote the entire holding as directed by the majority of votes cast? (ii) Split the
vote (where this is allowed) according to the proportions of the vote? (iii) Or respect the abstainers
and only vote the respondents' holdings?
The price signals generated by large active managers holding or not holding the stock may contribute
to management change. For example, this is the case when a large active manager sells his position
in a company, leading to (possibly) a decline in the stock price, but more importantly a loss of
confidence by the markets in the management of the company, thus precipitating changes in the
management team.
Some institutions have been more vocal and active in pursuing such matters; for instance, some firms
believe that there are investment advantages to accumulating substantial minority shareholdings (i.e.
10% or more) and putting pressure on management to implement significant changes in the business.
In some cases, institutions with minority holdings work together to force management change.
Perhaps more frequent is the sustained pressure that large institutions bring to bear on management
teams through persuasive discourse and PR. On the other hand, some of the largest investment
managers—such as BlackRock and Vanguard—advocate simply owning every company, reducing
the incentive to influence management teams. A reason for this last strategy is that the investment
manager prefers a closer, more open and honest relationship with a company's management team
than would exist if they exercised control; allowing them to make a better investment decision.
The national context in which shareholder representation considerations are set is variable and
important. The USA is a litigious society and shareholders use the law as a lever to pressure
management teams. In Japan it is traditional for shareholders to be low in the 'pecking order,' which
often allows management and labor to ignore the rights of the ultimate owners. Whereas US firms
generally cater to shareholders, Japanese businesses generally exhibit a stakeholder mentality, in
which they seek consensus amongst all interested parties (against a background of strong unions and
labour legislation).
[edit]Size of the global fund management industry
Conventional assets under management of the global fund management industry fell 19% in 2008, to
$61.6 trillion. Pension assets accounted for $24.0 trillion of the total, with $18.9 trillion invested in
mutual funds and $18.7 trillion in insurance funds. Together with alternative assets (sovereign wealth
funds, hedge funds, private equity funds and exchange traded funds) and funds of wealthy individuals,
assets of the global fund management industry totalled around $90 trillion at the end of 2008, a fall of
17% on the previous year. The decline in 2008 followed five successive years of growth during which
assets under management more than doubled. Falls on equity markets, poor investment performance,
reduced inflow of new funds, and investor redemptions, all contributed to the fall in assets in 2008.
The decline reported in US dollars was also exacerbated by the strengthening of the US dollar during
the particular year.
The US remained by far the biggest source of funds, accounting for over a half of conventional assets
under management in 2008 or over $30 trillion. The UK was the second largest centre in the world
and by far the largest in Europe with around 9% of the global total.[1]
[edit]Philosophy, process and people
The 3-P's (Philosophy, Process and People) are often used to describe the reasons why the manager
is able to produce above average results.
Philosophy refers to the over-arching beliefs of the investment organization. For example: (i)
Does the manager buy growth or value shares (and why)? (ii) Do they believe in market timing
(and on what evidence)? (iii) Do they rely on external research or do they employ a team of
researchers? It is helpful if any and all of such fundamental beliefs are supported by proof-
statements.
Process refers to the way in which the overall philosophy is implemented. For example: (i) Which
universe of assets is explored before particular assets are chosen as suitable investments? (ii)
How does the manager decide what to buy and when? (iii) How does the manager decide what to
sell and when? (iv) Who takes the decisions and are they taken by committee? (v) What controls
are in place to ensure that a rogue fund (one very different from others and from what is intended)
cannot arise?
People refers to the staff, especially the fund managers. The questions are, Who are they? How
are they selected? How old are they? Who reports to whom? How deep is the team (and do all
the members understand the philosophy and process they are supposed to be using)? And most
important of all, How long has the team been working together? This last question is vital because
whatever performance record was presented at the outset of the relationship with the client may
or may not relate to (have been produced by) a team that is still in place. If the team has changed
greatly (high staff turnover or changes to the team), then arguably the performance record is
completely unrelated to the existing team (of fund managers).
[edit]Investment managers and portfolio structures
At the heart of the investment management industry are the managers who invest and divest client
investments.
A certified company investment advisor should conduct an assessment of each client's individual
needs and risk profile. The advisor then recommends appropriate investments.
[edit]Asset allocation
The different asset class definitions are widely debated, but four common divisions
are stocks, bonds, real-estate and commodities. The exercise of allocating funds among these assets
(and among individual securities within each asset class) is what investment management firms are
paid for. Asset classes exhibit different market dynamics, and different interaction effects; thus, the
allocation of money among asset classes will have a significant effect on the performance of the fund.
Some research suggests that allocation among asset classes has more predictive power than the
choice of individual holdings in determining portfolio return. Arguably, the skill of a successful
investment manager resides in constructing the asset allocation, and separately the individual
holdings, so as to outperform certain benchmarks (e.g., the peer group of competing funds, bond and
stock indices)...
[edit]Long-term returns
It is important to look at the evidence on the long-term returns to different assets, and to holding
period returns (the returns that accrue on average over different lengths of investment). For example,
over very long holding periods (eg. 10+ years) in most countries, equities have generated higher
returns than bonds, and bonds have generated higher returns than cash. According to financial
theory, this is because equities are riskier (more volatile) than bonds which are themselves more risky
than cash.
[edit]Diversification
Against the background of the asset allocation, fund managers consider the degree
of diversification that makes sense for a given client (given its risk preferences) and construct a list of
planned holdings accordingly. The list will indicate what percentage of the fund should be invested in
each particular stock or bond. The theory of portfolio diversification was originated by Markowitz (and
many others) and effective diversification requires management of the correlation between the asset
returns and the liability returns, issues internal to the portfolio (individual holdings volatility), and cross-
correlations between the returns.
[edit]Investment styles
There are a range of different styles of fund management that the institution can implement. For
example, growth, value, market neutral, small capitalisation, indexed, etc. Each of these approaches
has its distinctive features, adherents and, in any particular financial environment, distinctive risk
characteristics. For example, there is evidence that growth styles (buying rapidly growing earnings)
are especially effective when the companies able to generate such growth are scarce; conversely,
when such growth is plentiful, then there is evidence that value styles tend to outperform the indices
particularly successfully.
[edit]Performance measurement
Fund performance is the acid test of fund management, and in the institutional context accurate
measurement is a necessity. For that purpose, institutions measure the performance of each fund
(and usually for internal purposes components of each fund) under their management, and
performance is also measured by external firms that specialize in performance measurement. The
leading performance measurement firms (e.g. Frank Russell in the USA or BI-SAM [1] in Europe)
compile aggregate industry data, e.g., showing how funds in general performed against given indices
and peer groups over various time periods.
In a typical case (let us say an equity fund), then the calculation would be made (as far as the client is
concerned) every quarter and would show a percentage change compared with the prior quarter (e.g.,
+4.6% total return in US dollars). This figure would be compared with other similar funds managed
within the institution (for purposes of monitoring internal controls), with performance data for peer
group funds, and with relevant indices (where available) or tailor-made performance benchmarks
where appropriate. The specialist performance measurement firms calculate quartile and decile data
and close attention would be paid to the (percentile) ranking of any fund.
Generally speaking, it is probably appropriate for an investment firm to persuade its clients to assess
performance over longer periods (e.g., 3 to 5 years) to smooth out very short term fluctuations in
performance and the influence of the business cycle. This can be difficult however and, industry wide,
there is a serious preoccupation with short-term numbers and the effect on the relationship with
clients (and resultant business risks for the institutions).
An enduring problem is whether to measure before-tax or after-tax performance. After-tax
measurement represents the benefit to the investor, but investors' tax positions may vary. Before-tax
measurement can be misleading, especially in regimens that tax realised capital gains (and not
unrealised). It is thus possible that successful active managers (measured before tax) may produce
miserable after-tax results. One possible solution is to report the after-tax position of some standard
taxpayer.
[edit]Risk-adjusted performance measurement
Performance measurement should not be reduced to the evaluation of fund returns alone, but must
also integrate other fund elements that would be of interest to investors, such as the measure of risk
taken. Several other aspects are also part of performance measurement: evaluating if managers have
succeeded in reaching their objective, i.e. if their return was sufficiently high to reward the risks taken;
how they compare to their peers; and finally whether the portfolio management results were due to
luck or the manager’s skill. The need to answer all these questions has led to the development of
more sophisticated performance measures, many of which originate in modern portfolio theory.
Modern portfolio theory established the quantitative link that exists between portfolio risk and return.
The Capital Asset Pricing Model (CAPM) developed by Sharpe (1964) highlighted the notion of
rewarding risk and produced the first performance indicators, be they risk-adjusted ratios (Sharpe
ratio, information ratio) or differential returns compared to benchmarks (alphas). The Sharpe ratio is
the simplest and best known performance measure. It measures the return of a portfolio in excess of
the risk-free rate, compared to the total risk of the portfolio. This measure is said to be absolute, as it
does not refer to any benchmark, avoiding drawbacks related to a poor choice of benchmark.
Meanwhile, it does not allow the separation of the performance of the market in which the portfolio is
invested from that of the manager. The information ratio is a more general form of the Sharpe ratio in
which the risk-free asset is replaced by a benchmark portfolio. This measure is relative, as it
evaluates portfolio performance in reference to a benchmark, making the result strongly dependent on
this benchmark choice.
Portfolio alpha is obtained by measuring the difference between the return of the portfolio and that of
a benchmark portfolio. This measure appears to be the only reliable performance measure to evaluate
active management. In fact, we have to distinguish between normal returns, provided by the fair
reward for portfolio exposure to different risks, and obtained through passive management, from
abnormal performance (or outperformance) due to the manager’s skill, whether through market timing
or stock picking. The first component is related to allocation and style investment choices, which may
not be under the sole control of the manager, and depends on the economic context, while the second
component is an evaluation of the success of the manager’s decisions. Only the latter, measured by
alpha, allows the evaluation of the manager’s true performance.
Portfolio normal return may be evaluated using factor models. The first model, proposed by Jensen
(1968), relies on the CAPM and explains portfolio normal returns with the market index as the only
factor. It quickly becomes clear, however, that one factor is not enough to explain the returns and that
other factors have to be considered. Multi-factor models were developed as an alternative to
the CAPM, allowing a better description of portfolio risks and an accurate evaluation of managers’
performance. For example, Fama and French (1993) have highlighted two important factors that
characterise a company's risk in addition to market risk. These factors are the book-to-market ratio
and the company's size as measured by its market capitalisation. Fama and French therefore
proposed three-factor model to describe portfolio normal returns (Fama-French three-factor model).
Carhart (1997) proposed to add momentum as a fourth factor to allow the persistence of the returns to
be taken into account. Also of interest for performance measurement is Sharpe’s (1992) style analysis
model, in which factors are style indices. This model allows a custom benchmark for each portfolio to
be developed, using the linear combination of style indices that best replicate portfolio style allocation,
and leads to an accurate evaluation of portfolio alpha.
[edit]Education or certification
Increasingly, international business schools are incorporating the subject into their course outlines
and some have formulated the title of 'Investment Management' or 'Asset Management' conferred as
specialist bachelors degrees (e.g. Cass Business School, London). Due to global cross-recognition
agreements with the 2 major accrediting agencies AACSB and ACBSPwhich accredit over 560 of the
best business school programs, the Certification of MFP Master Financial Planner Professional from
the American Academy of Financial Management is available to AACSB and ACBSP business school
graduates with finance or financial services-related concentrations. For people with aspirations to
become an investment manager, further education may be needed beyond a bachelors in business,
finance, or economics. A graduate degree or an investment qualification such as the Chartered
Financial Analystdesignation (CFA) or the Certified Financial Markets Practitioner (CFMP) Exam by
the Management Laboratory may help in having a career in investment management.[citation needed]
There is no evidence that any particular qualification enhances the most desirable characteristic of an
investment manager, that is the ability to select investments that result in an above average (risk
weighted) long-term performance[citation needed]. The industry has a tradition of seeking out, employing
and generously rewarding such people without reference to any formal qualifications[citation needed].
IT portfolio management is the application of systematic management to large classes of items managed by enterprise Information Technology (IT) capabilities. Examples of IT portfolios would be planned initiatives, projects, and ongoing IT services (such as application support). The promise of IT portfolio management is the quantification of previously mysterious IT efforts, enabling measurement and objective evaluation of investment scenarios.
Overview
Debates exist on the best way to measure value of IT investment. As pointed out by Jeffery and
Leliveld (2004) [1], companies have spent billions of dollars on IT investments and yet the headlines of
Agile Project Management approaches based on the principles of human interaction management are
founded on a process view of human collaboration. This contrasts sharply with the traditional
approach. In the agile software development or flexible product developmentapproach, the project is
seen as a series of relatively small tasks conceived and executed as the situation demands in an
adaptive manner, rather than as a completely pre-planned process.
[edit]Processes
This section relies largely or entirely upon a single source. Please help improve this articleby introducing appropriate citations to additional sources. (August 2010)
Traditionally, project management includes a number of elements: four to five process groups, and a
control system. Regardless of the methodology or terminology used, the same basic project
management processes will be used.
The project development stages[19]
Major process groups generally include:
Initiation
Planning or development
Production or execution
Monitoring and controlling
Closing
In project environments with a significant exploratory element (e.g., Research and development),
these stages may be supplemented with decision points (go/no go decisions) at which the project's
continuation is debated and decided. An example is the Stage-Gate model.
The complexity of PPM and other approaches to IT projects (e.g., treating them as a capital
investment) may render them not suitable for smaller or younger organizations. An obvious reason for
this is that a few IT projects doesn't make for much of a portfolio selection. Other reasons include the
cost of doing PPM—the data collection, the analysis, the documentation, the education, and the
change to decision-making processes.
Modern portfolio theoryFrom Wikipedia, the free encyclopedia
Modern portfolio theory (MPT) is a theory of investment which attempts to maximize portfolio
expected return for a given amount of portfolio risk, or equivalently minimize risk for a given level of
expected return, by carefully choosing the proportions of various assets. Although MPT is widely used in
practice in the financial industry and several of its creators won a Nobel prize for the theory, in recent years
the basic assumptions of MPT have been widely challenged by fields such as behavioral economics .
MPT is a mathematical formulation of the concept of diversification in investing, with the aim of selecting a
collection of investment assets that has collectively lower risk than any individual asset. That this is
possible can be seen intuitively because different types of assets often change in value in opposite ways.
For example, when prices in the stock market fall, prices in the bond market often increase, and vice
versa[citation needed]. A collection of both types of assets can therefore have lower overall risk than either
individually. But diversification lowers risk even if assets' returns are not negatively correlated—indeed,
even if they are positively correlated.
More technically, MPT models an asset's return as a normally distributed (or more generally as
an elliptically distributed random variable), defines risk as the standard deviation of return, and models a
portfolio as a weighted combination of assets so that the return of a portfolio is the weighted combination of
the assets' returns. By combining different assets whose returns are not perfectly positively correlated,
MPT seeks to reduce the total variance of the portfolio return. MPT also assumes that investors
are rational and markets are efficient.
MPT was developed in the 1950s through the early 1970s and was considered an important advance in the
mathematical modeling of finance. Since then, many theoretical and practicalcriticisms have been leveled
against it. These include the fact that financial returns do not follow a Gaussian distribution or indeed any
symmetric distribution, and that correlations between asset classes are not fixed but can vary depending on
external events (especially in crises). Further, there is growing evidence that investors are not rational and
markets are notefficient.[1][2]
Concept
The fundamental concept behind MPT is that the assets in an investment portfolio cannot be selected individually, each on their own merits. Rather, it is important to consider how each asset changes in price relative to how every other asset in the portfolio changes in price.
Investing is a tradeoff between risk and expected return. In general, assets with higher expected returns are riskier. For a given amount of risk, MPT describes how to select a portfolio with the highest possible expected return. Or, for a given expected return, MPT explains how to select a portfolio with the lowest possible risk (the targeted expected return cannot be more than the highest-returning available security, of course, unless negative holdings of assets are possible.)[3]
MPT is therefore a form of diversification. Under certain assumptions and for specific quantitative definitions of risk and return, MPT explains how to find the best possible diversification strategy.
[edit]History
Harry Markowitz introduced MPT in a 1952 article[4] and a 1959 book.[5] See also[3].
[edit]Mathematical model
In some sense the mathematical derivation below is MPT, although the basic concepts behind the model have also been very influential.[3]
This section develops the "classic" MPT model. There have been many extensions since.
[edit]Risk and expected return
MPT assumes that investors are risk averse, meaning that given two portfolios that offer the same expected return, investors will prefer the less risky one. Thus, an investor will take on increased risk only if compensated by higher expected returns. Conversely, an investor who wants higher expected returns must accept more risk. The exact trade-off will be the same for all investors, but different investors will evaluate the trade-off differently based on individual risk aversion characteristics. The implication is that a rational investor will not invest in a portfolio if a second portfolio exists with a more favorable risk-expected return profile – i.e., if for that level of risk an alternative portfolio exists which has better expected returns.
Note that the theory uses standard deviation of return as a proxy for risk. There are problems with this, however; see criticism.
Under the model:
Portfolio return is the proportion-weighted combination of the constituent assets' returns.
Portfolio volatility is a function of the correlations ρij of the component assets, for all asset pairs (i, j).
where Rp is the return on the portfolio, Ri is the return on asset i and wi is the weighting of component asset i (that is, the share of asset i in the portfolio).
Portfolio return variance:
where ρij is the correlation coefficient between the returns on assets i and j. Alternatively the expression can be written as:
,
where ρij = 1 for i=j.
Portfolio return volatility (standard deviation):
For a two asset portfolio:
Portfolio return:
Portfolio variance:
For a three asset portfolio:
Portfolio return:
Portfolio variance:
[edit]Diversification
An investor can reduce portfolio risk simply by holding combinations of instruments which are not
perfectly positively correlated (correlation coefficient )). In other words, investors can reduce their exposure to individual asset risk by holding a diversified portfolio of assets. Diversification may allow for the same portfolio expected return with reduced risk.
If all the asset pairs have correlations of 0—they are perfectly uncorrelated—the portfolio's return variance is the sum over all assets of the square of the fraction held in the asset times the asset's return variance (and the portfolio standard deviation is the square root of this sum).
[edit]The efficient frontier with no risk-free asset
Efficient Frontier. The hyperbola is sometimes referred to as the 'Markowitz Bullet', and is the efficient frontier if no risk-free asset is available.
As shown in this graph, every possible combination of the risky assets, without including any holdings of the risk-free asset, can be plotted in risk-expected return space, and the collection of all such possible portfolios defines a region in this space. The left boundary of this region is a hyperbola,[6] and the upper edge of this region is the efficient frontier in the absence of a risk-free asset (sometimes called "the Markowitz bullet"). Combinations along this upper edge represent portfolios (including no holdings of the risk-free asset) for which there is lowest risk for a given level of expected return. Equivalently, a portfolio lying on the efficient frontier represents the combination offering the best possible expected return for given risk level.
Matrices are preferred for calculations of the efficient frontier. In matrix form, for a given "risk
tolerance" , the efficient frontier is found by minimizing the following expression:
wTΣw − q * RTw
where
w is a vector of portfolio weights and
∑ wi = 1.
i
(The weights can be negative, which means investors can short a security.);
Σ is the covariance matrix for the returns on the assets in the portfolio;
is a "risk tolerance" factor, where 0 results in the portfolio with minimal risk and results in the portfolio infinitely far out the frontier with both expected return and risk unbounded; and
R is a vector of expected returns.
wTΣw is the variance of portfolio return.
RTw is the expected return on the portfolio.
The above optimization finds the point on the frontier at which the inverse of the slope of the frontier would be q if portfolio return variance instead of standard deviation were plotted horizontally. The frontier in its entirely is parametric on q.
Many software packages, including Microsoft Excel, MATLAB, Mathematica and R, provide optimization routines suitable for the above problem.
An alternative approach to specifying the efficient frontier is to do so parametrically on expected portfolio return RTw. This version of the problem requires that we minimize
wTΣw
subject to
RTw = μ
for parameter μ. This problem is easily solved using a Lagrange multiplier.
[edit]The two mutual fund theorem
One key result of the above analysis is the two mutual fund theorem.[6] This theorem states that any portfolio on the efficient frontier can be generated by holding a combination of any two given portfolios on the frontier; the latter two given portfolios are the "mutual funds" in the theorem's name. So in the absence of a risk-free asset, an investor can achieve any desired efficient portfolio even if all that is accessible is a pair of efficient mutual funds. If the location of the desired portfolio on the frontier is between the locations of the two mutual funds, both mutual funds will be held in positive quantities. If the desired portfolio is outside the range spanned by the two mutual funds, then one of the mutual funds must be sold short (held in negative quantity) while the size of the investment in the other mutual fund must be greater than the amount available for investment (the excess being funded by the borrowing from the other fund).
[edit]The risk-free asset and the capital allocation line
Main article: Capital allocation line
The risk-free asset is the (hypothetical) asset which pays a risk-free rate. In practice, short-term government securities (such as US treasury bills) are used as a risk-free asset, because they pay a fixed rate of interest and have exceptionally low default risk. The risk-free asset has zero variance in returns (hence is risk-free); it is also uncorrelated with any other asset (by definition, since its
variance is zero). As a result, when it is combined with any other asset, or portfolio of assets, the change in return is linearly related to the change in risk as the proportions in the combination vary.
When a risk-free asset is introduced, the half-line shown in the figure is the new efficient frontier. It is tangent to the hyperbola at the pure risky portfolio with the highest Sharpe ratio. Its horizontal intercept represents a portfolio with 100% of holdings in the risk-free asset; the tangency with the hyperbola represents a portfolio with no risk-free holdings and 100% of assets held in the portfolio occurring at the tangency point; points between those points are portfolios containing positive amounts of both the risky tangency portfolio and the risk-free asset; and points on the half-line beyond the tangency point are leveraged portfolios involving negative holdings of the risk-free asset (the latter has been sold short—in other words, the investor has borrowed at the risk-free rate) and an amount invested in the tangency portfolio equal to more the 100% of the investor's initial capital. This efficient half-line is called the capital allocation line (CAL), and its formula can be shown to be
In this formula P is the sub-portfolio of risky assets at the tangency with the Markowitz bullet, F is the risk-free asset, and C is a combination of portfolios P and F.
By the diagram, the introduction of the risk-free asset as a possible component of the portfolio has improved the range of risk-expected return combinations available, because everywhere except at the tangency portfolio the half-line gives a higher expected return than the hyperbola does at every possible risk level. The fact that all points on the linear efficient locus can be achieved by a combination of holdings of the risk-free asset and the tangency portfolio is known as the one mutual fund theorem,[6] where the mutual fund referred to is the tangency portfolio.
[edit]Asset pricing using MPT
The above analysis describes optimal behavior of an individual investor. Asset pricing theory builds on this analysis in the following way. Since everyone holds the risky assets in identical proportions to each other—namely in the proportions given by the tangency portfolio—in market equilibrium the risky assets' prices, and therefore their expected returns, will adjust so that the ratios in the tangecy portfolio are the same as the ratios in which the risky assets are supplied to the market. Thus relative supplies will equal relative demands. MPT derives the required expected return for a correctly priced asset in this context.
[edit]Systematic risk and specific risk
Specific risk is the risk associated with individual assets - within a portfolio these risks can be reduced through diversification (specific risks "cancel out"). Specific risk is also called diversifiable, unique, unsystematic, or idiosyncratic risk. Systematic risk (a.k.a. portfolio risk or market risk) refers to the risk common to all securities - except for selling short as noted below, systematic risk cannot be diversified away (within one market). Within the market portfolio, asset specific risk will be diversified away to the extent possible. Systematic risk is therefore equated with the risk (standard deviation) of the market portfolio.
Since a security will be purchased only if it improves the risk-expected return characteristics of the market portfolio, the relevant measure of the risk of a security is the risk it adds to the market portfolio, and not its risk in isolation. In this context, the volatility of the asset, and its correlation with the market portfolio, are historically observed and are therefore given. (There are several approaches to asset pricing that attempt to price assets by modelling the stochastic properties of the moments of assets' returns - these are broadly referred to as conditional asset pricing models.)
Systematic risks within one market can be managed through a strategy of using both long and short positions within one portfolio, creating a "market neutral" portfolio.
[edit]Capital asset pricing model
Main article: Capital Asset Pricing Model
The asset return depends on the amount paid for the asset today. The price paid must ensure that the market portfolio's risk / return characteristics improve when the asset is added to it. The CAPM is a model which derives the theoretical required expected return (i.e., discount rate) for an asset in a market, given the risk-free rate available to investors and the risk of the market as a whole. The CAPM is usually expressed:
β, Beta, is the measure of asset sensitivity to a movement in the overall market; Beta is usually found via regression on historical data. Betas exceeding one signify more than average "riskiness" in the sense of the asset's contribution to overall portfolio risk; betas below one indicate a lower than average risk contribution.
is the market premium, the expected excess return of the market portfolio's expected return over the risk-free rate.
This equation can be statistically estimated using the following regression equation:
where αi is called the asset's alpha , βi is the asset's beta coefficient and SCL is the Securities Characteristics Line.
Once an asset's expected return, E(Ri), is calculated using CAPM, the future cash flows of the asset can be discounted to their present value using this rate to establish the correct price for the asset. A riskier stock will have a higher beta and will be discounted at a higher rate; less sensitive stocks will have lower betas and be discounted at a lower rate. In theory, an asset is correctly priced when its observed price is the same as its value calculated using the CAPM derived discount rate. If the observed price is higher than the valuation, then the asset is overvalued; it is undervalued for a too low price.
(1) The incremental impact on risk and expected return when an additional risky asset, a, is added to the market portfolio, m, follows from the formulae for a two-asset portfolio. These results are used to derive the asset-appropriate discount rate.
Market portfolio's risk =
Hence, risk added to portfolio =
but since the weight of the asset will be relatively low,
i.e. additional risk =
Market portfolio's expected return =
Hence additional expected return =
(2) If an asset, a, is correctly priced, the improvement in its risk-to-expected return ratio achieved by adding it to the market portfolio, m, will at least match the gains of spending that money on an increased stake in the market portfolio. The assumption is that the investor will purchase the asset
with funds borrowed at the risk-free rate,Rf; this is rational if .
Thus:
i.e. :
i.e. :
is the “beta”, β -- the covariance between the asset's return and the market's return divided by the variance of the market return— i.e. the sensitivity of the asset price to movement in the market portfolio's value.
[edit]Criticism
Despite its theoretical importance, some people question whether MPT is an ideal investing strategy, because its model of financial markets does not match the real world in many ways.
[edit]Assumptions
The mathematical framework of MPT makes many assumptions about investors and markets. Some are explicit in the equations, such as the use of Normal distributions to model returns. Others are implicit, such as the neglect of taxes and transaction fees. None of these assumptions are entirely true, and each of them compromises MPT to some degree.
Asset returns are (jointly) normally distributed random variables. In fact, it is frequently observed that returns in equity and other markets are not normally distributed. Large swings (3 to 6 standard deviations from the mean) occur in the market far more frequently than the normal distribution assumption would predict.[7] While the model can also be justified by assuming any return distribution which is jointly elliptical [8] [9] , all the joint elliptical distributions are symmetrical whereas asset returns empirically are not.
Correlations between assets are fixed and constant forever. Correlations depend on systemic relationships between the underlying assets, and change when these relationships change. Examples include one country declaring war on another, or a general market crash. During times of financial crisis all assets tend to become positively correlated, because they all move (down) together. In other words, MPT breaks down precisely when investors are most in need of protection from risk.
All investors aim to maximize economic utility (in other words, to make as much money as possible, regardless of any other considerations). This is a key assumption of the efficient market hypothesis, upon which MPT relies.
All investors are rational and risk-averse. This is another assumption of the efficient market hypothesis, but we now know from behavioral economics that market participants are not rational. It does not allow for "herd behavior" or investors who will accept lower returns for higher risk. Casino gamblers clearly pay for risk, and it is possible that some stock traders will pay for risk as well.
All investors have access to the same information at the same time. This also comes from the efficient market hypothesis. In fact, real markets contain information asymmetry,insider trading, and those who are simply better informed than others.
Investors have an accurate conception of possible returns, i.e., the probability beliefs of investors match the true distribution of returns. A different possibility is that investors' expectations are biased, causing market prices to be informationally inefficient. This possibility is studied in the field of behavioral finance, which uses psychological assumptions to provide alternatives to the CAPM such as the overconfidence-based asset pricing model of Kent Daniel, David Hirshleifer, and Avanidhar Subrahmanyam (2001).[10]
There are no taxes or transaction costs. Real financial products are subject both to taxes and transaction costs (such as broker fees), and taking these into account will alter the composition of the optimum portfolio. These assumptions can be relaxed with more complicated versions of the model.[citation needed]
All investors are price takers, i.e., their actions do not influence prices. In reality, sufficiently large sales or purchases of individual assets can shift market prices for that asset and others (via cross-elasticity of demand.) An investor may not even be able to assemble the theoretically optimal portfolio if the market moves too much while they are buying the required securities.
Any investor can lend and borrow an unlimited amount at the risk free rate of interest. In reality, every investor has a credit limit.
All securities can be divided into parcels of any size. In reality, fractional shares usually cannot be bought or sold, and some assets have minimum orders sizes.
More complex versions of MPT can take into account a more sophisticated model of the world (such as one with non-normal distributions and taxes) but all mathematical models of finance still rely on many unrealistic premises.
[edit]MPT does not really model the market
The risk, return, and correlation measures used by MPT are based on expected values, which means that they are mathematical statements about the future (the expected value of returns is explicit in the above equations, and implicit in the definitions of variance and covariance.) In practice investors must substitute predictions based on historical measurements of asset return and volatility for these values in the equations. Very often such expected values fail to take account of new circumstances which did not exist when the historical data were generated.
More fundamentally, investors are stuck with estimating key parameters from past market data because MPT attempts to model risk in terms of the likelihood of losses, but says nothing about why those losses might occur. The risk measurements used are probabilistic in nature, not structural. This is a major difference as compared to many engineering approaches torisk management.
Options theory and MPT have at least one important conceptual difference from the probabilistic risk assessment done by nuclear power [plants]. A PRA is what economists would call a structural model. The components of a system and their relationships are modeled in Monte Carlo simulations. If valve X fails, it causes a loss of back pressure on pump Y, causing a drop in flow to vessel Z, and so on.
But in the Black-Scholes equation and MPT, there is no attempt to explain an underlying structure to price changes. Various outcomes are simply given probabilities. And, unlike the PRA, if there is no history of a particular system-level event like a liquidity crisis, there is no way to compute the odds of it. If nuclear engineers ran risk management this way, they would never be able to compute the odds of a meltdown at a particular plant until several similar events occurred in the same reactor design.
—Douglas W. Hubbard, 'The Failure of Risk Management', p. 67, John Wiley & Sons, 2009. ISBN 978-0-470-38795-5
Essentially, the mathematics of MPT view the markets as a collection of dice. By examining past market data we can develop hypotheses about how the dice are weighted, but this isn't helpful if the markets are actually dependent upon a much bigger and more complicated chaotic system -- the world. For this reason, accurate structural models of real financial markets are unlikely to be forthcoming because they would essentially be structural models of the entire world. Nonetheless there is growing awareness of the concept of systemic risk in financial markets, which should lead to more sophisticated market models.
Mathematical risk measurements are also useful only to the degree that they reflect investors' true concerns -- there is no point minimizing a variable that nobody cares about in practice. MPT uses the mathematical concept of variance to quantify risk, and this might be justified under the assumption
of elliptically distributed returns such as normally distributed returns, but for general return distributions other risk measures (like coherent risk measures) might better reflect investors' true preferences.
In particular, variance is a symmetric measure that counts abnormally high returns as just as risky as abnormally low returns. Some would argue that, in reality, investors are only concerned about losses, and do not care about the dispersion or tightness of above-average returns. According to this view, our intuitive concept of risk is fundamentally asymmetric in nature.
MPT does not account for the social, environmental, strategic, or personal dimensions of investment decisions. It only attempts to maximize risk-adjusted returns, without regard to other consequences. In a narrow sense, its complete reliance on asset prices makes it vulnerable to all the standard market failures such as those arising from information asymmetry,externalities, and public goods. It also rewards corporate fraud and dishonest accounting. More broadly, a firm may have strategic or social goals that shape its investment decisions, and an individual investor might have personal goals. In either case, information other than historical returns is relevant.
See also socially-responsible investing, fundamental analysis.
[edit]Extensions
Since MPT's introduction in 1952, many attempts have been made to improve the model, especially by using more realistic assumptions.
Post-modern portfolio theory extends MPT by adopting non-normally distributed, asymmetric measures of risk. This helps with some of these problems, but not others.
Black-Litterman model optimization is an extension of unconstrained Markowitz optimization which incorporates relative and absolute `views' on inputs of risk and returns.
[edit]Other Applications
[edit]Applications to project portfolios and other "non-financial" assets
Some experts apply MPT to portfolios of projects and other assets besides financial instruments.[11] When MPT is applied outside of traditional financial portfolios, some differences between the different types of portfolios must be considered.
1. The assets in financial portfolios are, for practical purposes, continuously divisible while portfolios of projects like new software development are "lumpy". For example, while we can compute that the optimal portfolio position for 3 stocks is, say, 44%, 35%, 21%, the optimal position for an IT portfolio may not allow us to simply change the amount spent on a project. IT projects might be all or nothing or, at least, have logical units that cannot be separated. A portfolio optimization method would have to take the discrete nature of some IT projects into account.
2. The assets of financial portfolios are liquid can be assessed or re-assessed at any point in time while opportunities for new projects may be limited and may appear in limited windows of time and projects that have already been initiated cannot be abandoned
without the loss of the sunk costs (i.e., there is little or no recovery/salvage value of a half-complete IT project).
Neither of these necessarily eliminate the possibility of using MPT and such portfolios. They simply indicate the need to run the optimization with an additional set of mathematically-expressed constraints that would not normally apply to financial portfolios.
Furthermore, some of the simplest elements of Modern Portfolio Theory are applicable to virtually any kind of portfolio. The concept of capturing the risk tolerance of an investor by documenting how much risk is acceptable for a given return could be and is applied to a variety of decision analysis problems. MPT, however, uses historical variance as a measure of risk and portfolios of assets like IT projects don't usually have an "historical variance" for a new piece of software. In this case, the MPT investment boundary can be expressed in more general terms like "chance of an ROI less than cost of capital" or "chance of losing more than half of the investment". When risk is put in terms of uncertainty about forecasts and possible losses then the concept is transferable to various types of investment.[11]
[edit]Application to other disciplines
In the 1970s, concepts from Modern Portfolio Theory found their way into the field of regional science. In a series of seminal works, Michael Conroy modeled the labor force in the economy using portfolio-theoretic methods to examine growth and variability in the labor force. This was followed by a long literature on the relationship between economic growth and volatility.[12]
More recently, modern portfolio theory has been used to model the self-concept in social psychology. When the self attributes comprising the self-concept constitute a well-diversified portfolio, then psychological outcomes at the level of the individual such as mood and self-esteem should be more stable than when the self-concept is undiversified. This prediction has been confirmed in studies involving human subjects.[13]
Recently, modern portfolio theory has been applied to modelling the uncertainty and correlation between documents in information retrieval. Given a query, the aim is to maximize the overall relevance of a ranked list of documents and at the same time minimize the overall uncertainty of the ranked list [1].
[edit]Comparison with arbitrage pricing theory
The SML and CAPM are often contrasted with the arbitrage pricing theory (APT), which holds that the expected return of a financial asset can be modeled as a linear function of variousmacro-economic factors, where sensitivity to changes in each factor is represented by a factor specific beta coefficient.
The APT is less restrictive in its assumptions: it allows for an explanatory (as opposed to statistical) model of asset returns, and assumes that each investor will hold a unique portfolio with its own particular array of betas, as opposed to the identical "market portfolio". Unlike the CAPM, the APT, however, does not itself reveal the identity of its priced factors - the number and nature of these factors is likely to change over time and between economies.
The impact of the risk event is assessed on a scale of 0 to 5, where 0 and 5 represent the minimum
and maximum possible impact of an occurrence of a risk (usually in terms of financial losses).
The probability of occurrence is likewise assessed on a scale from 0 to 5, where 0 represents a zero
probability of the risk event actually occurring while 5 represents a 100% probability of occurrence.
The Composite Index thus can take values ranging from 0 through 25, and this range is usually
arbitrarily divided into three sub-ranges. The overall risk assessment is then Low, Medium or High,
depending on the sub-range containing the calculated value of the Composite Index. For instance, the
three sub-ranges could be defined as 0 to 8, 9 to 16 and 17 to 25.
Note that the probability of risk occurrence is difficult to estimate since the past data on frequencies
are not readily available, as mentioned above.
Likewise, the impact of the risk is not easy to estimate since it is often difficult to estimate the potential
financial loss in the event of risk occurrence.
Further, both the above factors can change in magnitude depending on the adequacy of risk
avoidance and prevention measures taken and due to changes in the external business environment.
Hence it is absolutely necessary to periodically re-assess risks and intensify/relax mitigation
measures as necessary.
[edit]Risk Options
This section needs additional citations for verification.Please help improve this article by adding reliable references. Unsourced material may be challenged and removed. (August 2010)
Risk mitigation measures are usually formulated according to one or more of the following major risk
options, which are:
1. Design a new business process with adequate built-in risk control and containment measures from
the start.
2. Periodically re-assess risks that are accepted in ongoing processes as a normal feature of business
operations and modify mitigation measures.
3. Transfer risks to an external agency (e.g. an insurance company)
4. Avoid risks altogether (e.g. by closing down a particular high-risk business area)
Later research[citation needed] has shown that the financial benefits of risk management are less dependent
on the formula used but are more dependent on the frequency and how risk assessment is performed.
In business it is imperative to be able to present the findings of risk assessments in financial terms.
Robert Courtney Jr. (IBM, 1970) proposed a formula for presenting risks in financial terms.[8] The
Courtney formula was accepted as the official risk analysis method for the US governmental