Month: September 2020

Security market line (SML) is the representation of the capital asset pricing model. It displays the expected rate of return of an individual security as a function of systematic, non-diversifiable risk. The risk of an individual risky security reflects the volatility of the return from security rather than the return of the market portfolio. The risk in these individual risky securities reflects the systematic risk.

Formula

The Y-intercept of the SML is equal to the risk-free interest rate. The slope of the SML is equal to the market risk premium and reflects the risk return tradeoff at a given time:

E(R_i) = R_F + β_i × (E(R_M) – R_F)

Where:

E(Ri) is an expected return on security

E(RM) is an expected return on market portfolio M

β is a nondiversifiable or systematic risk

RM is a market rate of return

Rf is a risk-free rate

When used in portfolio management, the SML represents the investment’s opportunity cost (investing in a combination of the market portfolio and the risk-free asset). All the correctly priced securities are plotted on the SML. The assets above the line are undervalued because for a given amount of risk (beta), they yield a higher return. The assets below the line are overvalued because for a given amount of risk, they yield a lower return. In a market in perfect equilibrium, all securities would fall on the SML.

There is a question about what the SML looks like when beta is negative. A rational investor will accept these assets even though they yield sub-risk-free returns, because they will provide “recession insurance” as part of a well-diversified portfolio. Therefore, the SML continues in a straight line whether beta is positive or negative. A different way of thinking about this is that the absolute value of beta represents the amount of risk associated with the asset, while the sign explains when the risk occur.

SML Graph

The x-axis of the SML graph is represented by the beta, and the y-axis is represented by the expected return. The value of the risk-free rate is the beginning of the line.

• The zero-beta security will have the expected return equal to the risk-free rate. The expected return of zero-beta portfolio also equals the risk-free rate.
• The slope of the security market line is determined by the market risk premium (RPM), which is the difference between the expected market return and the risk-free rate. The higher the market risk premium, the steeper the slope and vice versa.
• The SML is not fixed and can change the slope and y-axis intersection over time. It depends on changes in interest rates, risk-return trade-off.
• If the beta coefficient of the given security changes over time, its position on the line will also change.

The shift of SML can also occur when key economical fundamental factors change, such as a change in the expected inflation rate, GDP, or unemployment rate.

Basic Principles of the portfolio investment process are given below:

1. It is the portfolio that matters:

Individual securities are important only to the extent that they affect the aggregate portfolio. For example, a security’s risk should not be based on the uncertainty of a single security’s return but, instead, on its contribution to the uncertainty of the total portfolio’s return.

In addition, assets such as a person’s career or home should be considered together with the security portfolio. In short, all decisions should focus on the impact the decision will have on the aggregate portfolio of all assets held.

2. Larger expected portfolio returns come only with larger portfolio risk:

The most important portfolio decision is the amount of risk which is acceptable, which is determined by the asset allocation within the security portfolio.

This is not an easy decision, since it requires that we have some idea of the risks and expected returns available on many different classes of assets. Nonetheless, the risk/return level of the aggregate portfolio should be the first decision any investor makes.

3. The risk associated with a security type depends on when the investment will be liquidated:

A person who plans to sell in one year will find equity returns to be more risky than a person who plans to sell in 10 years.

Alternatively, the person who plans to sell in 10 years will find one year maturity bonds to be more risky than the person who plans to sell in one year. Risk is reduced by selecting securities with a payoff close to when the portfolio is to be liquidated.

4. Diversification works:

Diversification across various securities will reduce a portfolio’s risk. If such broad diversification results in an expected portfolio return or risk level which is lower (or higher) than desired, then borrowing (or lending) can be used to achieve the desired level.

5. Each portfolio should be tailored to the particular needs of its owner:

People have varying tax rates, knowledge, transaction costs, etc. Individuals who are in a high marginal tax bracket should stress portfolio strategies which increase after-tax returns. Individuals who lack strong knowledge of investment alternatives should hire professionals to provide needed counseling.

Large pension portfolios should pursue strategies which will reduce brokerage fees associated with moving capital between equity and non-equity managers (for example, by using options on futures). In short, portfolio strategy should be molded to the unique needs and characteristics of the portfolio’s owner.

6. Competition for abnormal returns is extensive:

A large number of people are continuously using a large variety of techniques in an attempt to obtain abnormal returns larger than should be expected given a security’s risk.

Securities which are believed to be undervalued are bought until the price rises to a proper level, and securities which are believed to be overvalued are sold until the price falls to a proper level.

If the actions of these speculators are truly effective, security prices will adjust instantaneously to new information the efficient market theory (EMT) will be correct.

The extent to which EMT is correct as well as the extent to which one has unique information determiners whether a passive “investment” strategy or an active “speculative” strategy should be used.

In finance, technical analysis is an analysis methodology for forecasting the direction of prices through the study of past market data, primarily price and volume. Behavioral economics and quantitative analysis use many of the same tools of technical analysis, which, being an aspect of active management, stands in contradiction to much of modern portfolio theory. The efficacy of both technical and fundamental analysis is disputed by the efficient-market hypothesis, which states that stock market prices are essentially unpredictable, and research on technical analysis has produced mixed results.

Fundamental analysts examine earnings, dividends, assets, quality, ratio, new products, research and the like. Technicians employ many methods, tools and techniques as well, one of which is the use of charts. Using charts, technical analysts seek to identify price patterns and market trends in financial markets and attempt to exploit those patterns.

Technicians using charts search for archetypal price chart patterns, such as the well-known head and shoulder or double top/bottom reversal patterns, study technical indicators, moving averages and look for forms such as lines of support, resistance, channels and more obscure formations such as flags, pennants, balance days and cup and handle patterns.

Technical analysts also widely use market indicators of many sorts, some of which are mathematical transformations of price, often including up and down volume, advance/decline data and other inputs. These indicators are used to help assess whether an asset is trending, and if it is, the probability of its direction and of continuation. Technicians also look for relationships between price/volume indices and market indicators. Examples include the moving average, relative strength index and MACD. Other avenues of study include correlations between changes in Options (implied volatility) and put/call ratios with price. Also important are sentiment indicators such as Put/Call ratios, bull/bear ratios, short interest, Implied Volatility, etc.

There are many techniques in technical analysis. Adherents of different techniques (for example: Candlestick analysis, the oldest form of technical analysis developed by a Japanese grain trader; Harmonics; Dow theory; and Elliott wave theory) may ignore the other approaches, yet many traders combine elements from more than one technique. Some technical analysts use subjective judgment to decide which pattern(s) a particular instrument reflects at a given time and what the interpretation of that pattern should be. Others employ a strictly mechanical or systematic approach to pattern identification and interpretation.

Contrasting with technical analysis is fundamental analysis, the study of economic factors that influence the way investors price financial markets. Technical analysis holds that prices already reflect all the underlying fundamental factors. Uncovering the trends is what technical indicators are designed to do, although neither technical nor fundamental indicators are perfect. Some traders use technical or fundamental analysis exclusively, while others use both types to make trading decisions.

Principles

A core principle of technical analysis is that a market’s price reflects all relevant information impacting that market. A technical analyst therefore looks at the history of a security or commodity’s trading pattern rather than external drivers such as economic, fundamental and news events. It is believed that price action tends to repeat itself due to the collective, patterned behavior of investors. Hence technical analysis focuses on identifiable price trends and conditions.

Characteristics

Technical analysis employs models and trading rules based on price and volume transformations, such as the relative strength index, moving averages, regressions, inter-market and intra-market price correlations, business cycles, stock market cycles or, classically, through recognition of chart patterns.

Technical analysis stands in contrast to the fundamental analysis approach to security and stock analysis. In the fundamental equation M = P/E technical analysis is the examination of M (multiple). Multiple encompasses the psychology generally abounding, i.e. the extent of willingness to buy/sell. Also in M is the ability to pay as, for instance, a spent-out bull can’t make the market go higher and a well-heeled bear won’t. Technical analysis analyzes price, volume, psychology, money flow and other market information, whereas fundamental analysis looks at the facts of the company, market, currency or commodity. Most large brokerages, trading groups, or financial institutions will typically have both a technical analysis and fundamental analysis team.

In the 1960s and 1970s it was widely dismissed by academics. In a recent review, Irwin and Park reported that 56 of 95 modern studies found that it produces positive results but noted that many of the positive results were rendered dubious by issues such as data snooping, so that the evidence in support of technical analysis was inconclusive; it is still considered by many academics to be pseudoscience. Academics such as Eugene Fama say the evidence for technical analysis is sparse and is inconsistent with the weak form of the efficient-market hypothesis. Users hold that even if technical analysis cannot predict the future, it helps to identify trends, tendencies, and trading opportunities.

While some isolated studies have indicated that technical trading rules might lead to consistent returns in the period prior to 1987, most academic work has focused on the nature of the anomalous position of the foreign exchange market. It is speculated that this anomaly is due to central bank intervention, which obviously technical analysis is not designed to predict. Recent research suggests that combining various trading signals into a Combined Signal Approach may be able to increase profitability and reduce dependence on any single rule.

In security selection process, a traditional approach of Economic Industry Company analysis is employed. EIC analysis is the abbreviation of economic, industry and company. The person conducting EIC analysis examines the conditions in the entire economy and then ascertains the most attractive industries in the light of the economic conditions. At last the most attractive companies within the attractive industries are pointed out by the analyst.

EIC Analysis of a Company

Below are the further details of the components of EIC analysis, which analyst always consider before choosing or reaching any decision about any business.

• Economic Analysis
• Industry Analysis
• Company Analysis

Economic Analysis:

Every common stock is susceptible to the market risk. This feature of almost all types of common stock indicates their combined movement with the fluctuations in the economic conditions towards the improvement or deterioration.

Stock prices react favorably to the low inflation, earnings growth, a better balance of trade, increasing gross national product and other positive macroeconomic news. Indications that unemployment is rising, inflation is picking up or earnings estimates are being revised downward will negatively affect the stock prices. This relationship is reasonably reliable that the US economy is better represented by the Standard & Poor 500 stock index, which is famous market indicator. The stock market will forecast an economic boom or recession properly from the signs in front of average citizen. The Federal bank of New York has conducted a research that describes that the slope of the yield curve is the perfect indicator of the economic growth more than three months out. Recession is indicated by negative slope while positive slope is considered as good one.

The implications of market risk should be clear to the investor. When there is recession in the economy, the prices of stocks moves downward. All the companies suffer the effects of recession despite of the fact that these are high performing companies or low performing ones. Similarly the stock prices are positively affected by the boom period of the economy.

Industry Analysis:

It is clear there is certain level of market risk faced by every stock and the stock price decline during recession in the economy. Another point to be remembered is that the defensive kind of stock is affected less by the recession as compared to the cyclical category of stock. In the industry analysis, such industries are highlighted that can stand well in front of adverse economic conditions.

In 1980, Michael Porter proposed a standard approach to industry analysis which is referred to as competitive analysis frame work. Threats of new entrants evaluate the expected reaction of current competitors to new competitors and obstacles to entry into the industry. In certain industries it is quite difficult for new company to compete successfully.

For example new producers in the automobile industry face difficulty in competing the established companies, like General Motors and Ford etc. There are certain other industries where the entry of new company is easier like financial planning industry. No extraordinary efforts are required in such kind of industries to establish any new company. The growth in the industry is slowed down through the rivalry among the current competitors. Profits of the company are reduced when it tries to cover more market share because under existing rivalry the company has to invest a large portion of its earnings in this enhancing market share. The industry where the rivalry is friendly or modest among competitors provides greater opportunity for product differentiation & increased profits. The intense competition is favorable for the customer but not good for the producer of the product. In case of airline industry there are common fare price wars among the competitors. When one airline company reduces its price then the other must also adjust its price accordingly in order to retain the existing customers.

Another threat faced by company in industry is the treat of substitutes which prevents the companies to enhance the price of their products. When there is much increase in the price of particular product, then the consumer simply switches to other alternative product which has lower price. For example there are two different video games named Sega and Nintendo. These games competes each other directly in the market. If the price of Nintendo is enhanced then the new video game customers are switch toward the Sage which has relatively lower price. The investor conducting industry analysis should focus the level of risk of product substitution which seriously affects the future growth of company.

Another aspect of the industry analysis is the bargaining power of buyers which can greatly influence the large percentage of sales of seller. In this condition the profit margins are lower. Concessions are necessary to be offered by the seller because it is not affordable for him to lose customer. For example there is ship building company and the US Navy is its main customer. Only two to three ships are produced by the company every year and so it is very harmful for the firm to lose the Navy contract. On the other hand in case of departmental store, there is large number of customers and so the bargaining power of customers is low. In this business, losing one or two customers will not much affect the sales or profitability of the retail store.

The only capital intensive industry should not be focused. There are other industries that are not capital intensive like consultants required in retail computer store. There is need that is present which force the computer technician to solve the problems of the computer systems of people. In recent year, consumers are usually more sophisticated in area of personal computers. So they are better guided and they try to make their own decisions in the needs of software and hardware aspects. In fact they possess high power when they contact the sales staff.    

The bargaining power of suppliers has also substantial influence over the profitability of the company. The supplies for manufacturing products are required by the company and it does not have sufficient control over the costs. It is not possible for the company to increase the price of its finished products in order to cover the increased costs due to the presence of powerful buyer groups in market of substitute products. So while conducing industry analysis, the presence of powerful suppliers should be considered as negative for the company.

The above considerations of industry structure should be analyzed by the investor in order to make an estimate about the future trends of the industry in the light of the economic conditions. When potential industry is identified then comes the final step of EIC analysis which is narrower relating to companies only.

Company Analysis:

In company analysis different companies are considered and evaluated from the selected industry so that most attractive company can be identified. Company analysis is also referred to as security analysis in which stock picking activity is done. Different analysts have different approaches of conducting company analysis like

• Value Approach to Investing
• Growth Approach to Investing

Additionally in company analysis, the financial ratios of the companies are analyzed in order to ascertain the category of stock as value stock or growth stock. These ratios include price to book ratio and price-earnings ratio. Other ratios like return on equity etc. can also be analyzed to ascertain the potential company for making investment.

Advantages:

Fundamental analysis is good for long-term investments based on long-term trends, very long-term. The ability to identify and predict long-term economic, demographic, technological or consumer trends can benefit patient investors who pick the right industry groups or companies.

Sound fundamental analysis will help identify companies that represent a good value. Some of the most legendary investors think long-term and value. Graham and Dodd, Warren Buffett and John Neff are seen as the champions of value investing. Fundamental analysis can help uncover companies with valuable assets, a strong balance sheet, stable earnings, and staying power.

One of the most obvious, but less tangible, rewards of fundamental analysis is the development of a thorough understanding of the business. After such painstaking research and analysis, an investor will be familiar with the key revenue and profit drivers behind a company. Earnings and earnings expectations can be potent drivers of equity prices. Even some technicians will agree to that. A good understanding can help investors avoid companies that are prone to shortfalls and identify those that continue to deliver. In addition to understanding the business, fundamental analysis allows investors to develop an understanding of the key value drivers and companies within an industry. A stock’s price is heavily influenced by its industry group. By studying these groups, investors can better position themselves to identify opportunities that are high-risk (tech), low- risk (utilities), growth oriented (computer), value driven (oil), non-cyclical (consumer staples), cyclical (transportation) or income-oriented (high yield).

Stocks move as a group. By understanding a company’s business, investors can better position themselves to categorize stocks within their relevant industry group. Business can change rapidly and with it the revenue mix of a company. This happened to many of the pure Internet retailers, which were not really Internet companies, but plain retailers. Knowing a company’s business and being able to place it in a group can make a huge difference in relative valuations.

Disadvantages:

The main disadvantage for me is that if used on its own, fundamental analysis (FA) doesn’t take into consideration the “herd mentality” phenomenon. In the long run, the price per share (PPS) of companies is driven by their earnings, i.e., the profit they’re yielding. In the short term, the momentum can be quite influential on the PPS; I’m sure you’ve noticed that some stock are considered market darlings and, to a certain degree, it doesn’t matter what their quarterly results are; people keep on buying. The same applies for companies that, all of a sudden, fall out of favor for whatever reason, genuine or not. They keep getting hammered regardless of the results the company pumps out, until one day it reverses. FA doesn’t consider this irrational behavior.

Fundamental analysis may offer excellent insights, but it can be extraordinarily time-consuming. Time-consuming models often produce valuations that are contradictory to the current price prevailing on Wall Street. When this happens, the analyst basically claims that the whole street has got it wrong. This is not to say that there are not misunderstood companies out there, but it is quite brash to imply that the market price, and hence Wall Street, is wrong.

Valuation techniques vary depending on the industry group and specifics of each company. For this reason, a different technique and model is required for different industries and different companies. This can get quite time-consuming, which can limit the amount of research that can be performed.

Fair value is based on assumptions. Any changes to growth or multiplier assumptions can greatly alter the ultimate valuation. Fundamental analysts are generally aware of this and use sensitivity analysis to present a base-case valuation, a best-case valuation and a worst-case valuation. However, even on a worst-case valuation, most models are almost always bullish, the only question is how much so.

The majority of the information that goes into the analysis comes from the company itself. Companies employ investor relations managers specifically to handle the analyst community and release information. As Mark Twain said, “there are lies, damn lies, and statistics.” When it comes to massaging the data or spinning the announcement, CFOs and investor relations managers are professionals. Only buy-side analysts tend to venture past the company statistics. Buy-side analysts work for mutual funds and money managers. They read the reports written by the sell-side analysts who work for the big brokers (CIBC, Merrill Lynch, Robertson Stephens, CS First Boston, Paine Weber, DLJ to name a few). These brokers are also involved in underwriting and investment banking for the companies. Even though there are restrictions in place to prevent a conflict of interest, brokers have an ongoing relationship with the company under analysis. When reading these reports, it is important to take into consideration any biases a sell-side analyst may have. The buy-side analyst, on the other hand, is analyzing the company purely from an investment standpoint for a portfolio manager. If there is a relationship with the company, it is usually on different terms. In some cases this may be as a large shareholder.

When market valuations extend beyond historical norms, there is pressure to adjust growth and multiplier assumptions to compensate. If Wall Street values a stock at 50 times earnings and the current assumption is 30 times, the analyst would be pressured to revise this assumption higher. There is an old Wall Street adage: the value of any asset (stock) is only what someone is willing to pay for it (current price). Just as stock prices fluctuate, so too do growth and multiplier assumptions. Are we to believe Wall Street and the stock price or the analyst and market assumptions? It used to be that free cash flow or earnings were used with a multiplier to arrive at a fair value. In 1999, the S&P 500 typically sold for 28 times free cash flow. However, because so many companies were and are losing money, it has become popular to value a business as a multiple of its revenues. This would seem to be OK, except that the multiple was higher than the PE of many stocks! Some companies were considered bargains at 30 times revenues.

To conclude, fundamental analysis can be valuable, but it should be approached with caution. If you are reading research written by a sell-side analyst, it is important to be familiar with the analyst behind the report. We all have personal biases, and every analyst has some sort of bias. There is nothing wrong with this, and the research can still be of great value. Learn what the ratings mean and the track record of an analyst before jumping off the deep end. Corporate statements and press releases offer good information, but they should be read with a healthy degree of skepticism to separate the facts from the spin. Press releases don’t happen by accident; they are an important PR tool for companies. Investors should become skilled readers to weed out the important information and ignore the hype.

An oscillator is a technical analysis indicator that varies over time within a band (above and below a center line, or between set levels). Oscillators are used to discover short-term overbought or oversold conditions.

Oscillators are indicators that are used when viewing charts that are ranging (non-trending) to determine overbought or oversold conditions. Moving averages (MA) and trends are extremely important when studying the direction of a stock. A technician will use oscillators when the charts are not showing a definite trend in either direction. Oscillators are most beneficial when a company’s stock is either in a horizontal or sideways trading pattern or has not been able to establish a definite trend in a choppy market.

When the stock is in either an overbought or oversold situation, the true value of the oscillator is exposed. For example, a chartist can use oscillators to see when the stock is running out of steam on the upside the point at which the stock moves into an overbought situation. This simply means that the buying volume has been diminishing for a number of trading days, which means traders will then start to sell their shares. Conversely, when a stock has been sold by a greater number of investors for a consistent period of time, the stock will enter an oversold situation.

Oscillators are another group of tools used to identify overbought or oversold market conditions. They are also based on prices but are scaled in such a way that they “oscillate” around a certain value or between high and low values. For oscillators extreme high values indicate overbought markets while extreme low values indicate oversold markets.

Oscillators are perhaps most useful in identifying convergence and divergence. Convergence happens when the oscillator confirms the same pattern as the price movement. Divergence occurs when the oscillator contradicts the price pattern.

For the exam you need to know four different types of oscillators:

• Rate of Change (ROC) Oscillator
• Relative Strength Index (RSI)
• Moving Average Convergence/Divergence (MACD)
• Stochastic Oscillator

Rate of Change (ROC) Oscillator

ROC shows the percentage difference between the current price and the price n periods ago. In other words it measures the percentage change in price over a given period. The higher the percentage change in price the higher the ROC. Note the ROC oscillates around zero. When the price goes up, ROC goes down and vice versa.  Traders will often buy if the oscillator goes from negative to positive in an uptrend, or sell when it goes from positive to negative in a downtrend. If it crosses zero in the opposite direction of the trend it is usually ignored.

Relative Strength Index (RSI)

RSI measures the relative strength of a security against itself.  It is scaled to oscillate between 0 and 100 with high values (> 70) showing an overbought market and low values (< 30) showing an oversold market.

• RSI > 70, Sell Signal
• RSI < 30, Buy Signal

Moving Average Convergence/Divergence (MACD)

MACD (pronounced Mac-Dee) is an exponential moving average that shows the difference between short and long term moving averages. The MACD signal line itself then oscillates around zero (but is not bounded).

MACD can signal convergence or divergence as well as overbought and oversold conditions. Points where the MACD line crosses the ‘signal’ line can be used as trading signals. As you might have guessed, the shorter-term average crossing above the longer term line shows upside momentum increasing and is thus a bullish signal.

Stochastic Oscillators

The stochastic oscillator measures the relationship between the closing, high, and low prices and is also used to identify overbought and oversold markets. It is usually calculated using a 14 day period and always ranges between 0-100%.  In an uptrend the closing price tends to be near the high price of the period and a downtrend is marked by the low and closing prices being close together. Generally a buy signal occurs if the oscillator crosses above the 20% level and a sell signal is triggered if it crosses below the 80% level.

Sentiment Indicators (Non-Price Signals)

Sentiment indicators can include polls/surveys of market participants or, more commonly, calculated statistical indices. We’ll rip through the ones in the curriculum, again much of this is in the weeds and unlikely to show up with any significance on the exam.

Put/Call Ratio:

This is a contrarian indicator. The higher (lower) the ratio the more bearish (bullish) the signal. However if the ratio is skewed to one extreme or the other things are different. For example an extremely high ratio demonstrates excessively negative sentiment and the price is likely to rise.

Volatility Index (VIX): Calculated by the Chicago Board Options Exchange, the VIX measures options volatility. A high or rising VIX is a bearish sign, however, market participants use the VIX as a contrarian schedule.

Margin Debt – Increases in margin debt outstanding indicate increasing bullishness amongst investors.

Short interest ratio: Short interest is the number of shares investors have borrowed and sold short. The short interest ratio is that number divided by the average trading volume. A high short interest ratio indicates traders expect prices to decline, however, it also means at some point there will be greater buying demand as the traders have to cover their shorts (if this happens in the short term it can result in a short squeeze)

Flow of Funds Indicators: Indicate the relative supply and demand in the market. One particularly useful ratio is the arms index or short-term trading index.

The TRIN measures funds flowing into advancing and decreasing stocks. A ratio close to one suggests an even distribution, a ratio greater than one means more money is flowing into declining stocks. Spikes upwards have historically corresponded to large daily losses.

Other flow of funds indicators include the aforementioned margin debt, the mutual fund cash position (ratio of cash to total assets). Traders use this as a contrarian indicator. When cash balances increase there is future buying demand and traders expect the markets to rise.

New Equity Issuances: IPOs etc. A lagging indicator thought to coincide with market peaks since an IPO becomes more attractive to the business owners as prices rise.

Asset allocation refers to an investment strategy in which individuals divide their investment portfolios between different diverse asset classes to minimize investment risks. The asset classes fall into three broad categories: equities, fixed-income, and cash and equivalents. Anything outside these three categories (e.g., real estate, commodities, and art) is often referred to as alternative assets.

Asset allocation is the implementation of an investment strategy that attempts to balance risk versus reward by adjusting the percentage of each asset in an investment portfolio according to the investor’s risk tolerance, goals and investment time frame. The focus is on the characteristics of the overall portfolio. Such a strategy contrasts with an approach that focuses on individual assets.

Factors Affecting Asset Allocation Decision

An investors’ portfolio distribution is influenced by factors such as personal goals, level of risk tolerance, and investment horizon.

1. Goals factors

Goals factors are individual aspirations to achieve a given level of return or saving for a particular reason or desire. Therefore, different goals affect how a person invests and risks.

2. Risk tolerance

Risk tolerance refers to how much an individual is willing and able to lose a given amount of their original investment in anticipation of getting a higher return in the future. For example, risk-averse investors withhold their portfolio in favor of more secure assets. On the contrary, more aggressive investors risk most of their investments in anticipation of higher returns. Learn more about risk and return.

3. Time horizon

The time horizon factor depends on the duration an investor is going to invest. Most of the time, it depends on the goal of the investment. Similarly, different time horizons entail different risk tolerance. For example, a long-time investment strategy may prompt an investor to invest in a more volatile or higher risk portfolio since the dynamics of the economy are uncertain and may change in favor of the investor. However, investors with short-term goals may not invest in riskier portfolios.

Allocation strategy

There are several types of asset allocation strategies based on investment goals, risk tolerance, time frames and diversification. The most common forms of asset allocation are: strategic, dynamic, tactical, and core-satellite.

Strategic asset allocation

The primary goal of strategic asset allocation is to create an asset mix that seeks to provide the optimal balance between expected risk and return for a long-term investment horizon. Generally speaking, strategic asset allocation strategies are agnostic to economic environments, i.e., they do not change their allocation postures relative to changing market or economic conditions.

Dynamic asset allocation

Dynamic asset allocation is similar to strategic asset allocation in that portfolios are built by allocating to an asset mix that seeks to provide the optimal balance between expected risk and return for a long-term investment horizon. Like strategic allocation strategies, dynamic strategies largely retain exposure to their original asset classes; however, unlike strategic strategies, dynamic asset allocation portfolios will adjust their postures over time relative to changes in the economic environment.

Tactical asset allocation

Tactical asset allocation is a strategy in which an investor takes a more active approach that tries to position a portfolio into those assets, sectors, or individual stocks that show the most potential for perceived gains. While an original asset mix is formulated much like strategic and dynamic portfolio, tactical strategies are often traded more actively and are free to move entirely in and out of their core asset classes.

Core-satellite asset allocation

Core-satellite allocation strategies generally contain a ‘core’ strategic element making up the most significant portion of the portfolio, while applying a dynamic or tactical ‘satellite’ strategy that makes up a smaller part of the portfolio. In this way, core-satellite allocation strategies are a hybrid of the strategic and dynamic/tactical allocation strategies mentioned above.

Problems with asset allocation

There are various reasons why asset allocation fails to work.

• Investor behavior is inherently biased. Even though investor chooses an asset allocation, implementation is a challenge.
• Investors agree to asset allocation, but after some good returns, they decide that they really wanted more risk.
• Investors agree to asset allocation, but after some bad returns, they decide that they really wanted less risk.
• Investors’ risk tolerance is not knowable ahead of time.
• Security selection within asset classes will not necessarily produce a risk profile equal to the asset class.
• The long-run behavior of asset classes does not guarantee their shorter-term behavior.

A strategy used by investors to manage risk. By spreading your money across different assets and sectors, the thinking is that if one area experiences turbulence, the others should balance it out. It’s the opposite of placing all your eggs in one basket.

The term often crops up during periods of economic turbulence, when there’s a lot of uncertainty in financial markets. Rather than leaving themselves exposed to stock market swings, investors might look to spread their money across other assets like bonds and commodities too.

All investments carry some degree of risk and, as a result, you can’t avoid it completely. But the good news is that risk diversification can at least help you to avoid over-exposing yourself to one particular area.

Diversifying your investments doesn’t simply mean spreading your money across different assets. Instead, you can also spread it between companies of varying sizes, different sectors, and a range of geographic regions.

Risk diversification can also be important in the business world. For example, rather than specialising in a single area, a company may choose to expand into new products and sectors.

Diversification is the art of entering product markets different from those in which the firm is currently engaged in. It is helpful to divide diversification into ‘related’ diversification and ‘unrelated’ diversification.

Diversification is venerable rule of investment which suggests “Don’t put all your eggs in one basket”, spreading risk across a number of securities.

Diversification may take the form of unit, industry, maturity, geography, type of security and management. Through diversification of investments, an investor can reduce investment risks.

Investment of funds, say, Rs. 1 lakh evenly among as many as 20 different securities is more diversified than if the same amount is deployed evenly across 7 securities. This sort of security diversification is naive in the sense that it does not factor in the covariance between security returns.

The portfolio comprising 20 securities could represent stocks of one industry only and have returns which are positively correlated and high portfolio returns variability. On the other hand, the 7-stock portfolio might represent a number of different industries where returns might show low correlation and, hence, low portfolio returns variability.

Meaningful diversification is one which involves holding of stocks of more than one industry so that risks of losses occurring in one industry are counterbalanced by gains from the other industry. Investing in global financial markets can achieve greater diversification than investing in securities from a single country. This is for the fact that the economic cycles of different countries hardly synchronize and as such a weak economy in one country may be offset by a strong economy in another.

Fig. 5.2 portrays meaningful diversification. It may be noted from the figure that the returns overtime for Security X are cyclical in that they move in tandem with the economic fluctuations. In case of Security Y returns are moderately counter cyclical. Thus, the returns for these two securities are negatively correlated.

If equal amounts are invested in both securities, the dispersion of returns, up, on the portfolio of investments will be less because some of each individual security’s variability is offsetting. Thus, the gains of diversification of investment portfolio, in the form of risk minimization, can be derived if the securities are not perfectly and positively correlated.

A related diversification is one in which the two involved businesses have meaningful commonalties, which provide the potential to generate economies of scale or synergies based upon the exchange of skills or resources. In a related diversification the resulting combined business should be able to achieve improved ROI because of increased revenues, decreased costs, or reduced investment, which are attributable to the commonalties.

An important issue in any diversification decision is whether, in fact, there is a real and meaningful area of commonality that will benefit the ultimate ROI. If such a meaningful commonality is lacking, the diversification may still be justifiable, but the rationale will need to be different.

Related diversification

1. Exchanging skill and resources

Related diversification provides the potential to attain synergies by the exchanged or sharing of skills or resources. One business unit must have skills or resources that are ‘exportable’ to another company or business unit. Thus, a first condition for successful related diversification is to identify skills or resources that are exportable or that are needed and can be ‘imported!

The second condition is to find a partner or business unit that can either provide or use them. The third is to ascertain whether the organizational integration needed to accomplish the exchange is feasible. Skills or resources that can be usefully imported or exported can take a variety of forms.

2. Brand name

One commonly found resource that is exportable is a strong established brand name like Coca-Cola, Microsoft, Pepsi, Puma, BMW, or Nivea.

3. Marketing skills

Usually a firm will either possess or lack a strong skill in marketing for a particular market. Thus, a frequent motive to diversify is to export or import a marketing talent. The typical case in this regard is the introduction of Microsoft products into the People’s Republic of China (PRC). PRC was moving from the socialistic pattern of society to market economy.

During the 1990s, urbanization started increasing and a shift was seen from agriculture to the service sector. Agriculture, science and technology, industry and defence were targeted for modernization. Richard Fade, vice-president in charge of Microsoft’s Far-east operations, pondered Microsoft’s planned introduction of products into China.

In the Chinese computer hardware industry of 36 domestic vendors accounted for 82 per cent of the units of domestically manufactured PCs. In the software industry, State Owned Enterprises (SOEs) dominated the market. Since, the SOEs were answerable to the government, all their revenues accrued directly to national government.

The following are the key tasks that need to be done while localizing:

(i) The local character sets need to be supported.

(ii) The interface needs to be translated in a form that is familiar to the local user.

(iii) All documents should be in local language.

(iv) Configure the software so that it can support locally available software and hardware.

(v) Provide local customer service.

Microsoft in 1984 signed its first OEM agreement in Taiwan, home of over 3,000 PC systems and component manufacturers, before opening an office in 1989. Five years later Microsoft opened an office in China. It was estimated that 95 per cent of PCs had the English version of Microsoft DOS installed together with one of the many Chinese shells.

Microsoft had worked with SV earlier on a smaller project and so it agreed to work with them on P-DOS project. Based on their earlier experience, it was understood that it was very difficult to parcel out a particular major software localization task to one SV and hence opted for a ‘consortia’ of SVs and set UP a product development centre. This eventually paid the company a ‘prize reward’ by limiting other competitors in the market.

4. Service

A small company can often create or enter a market area and do well with an innovative product. As the market matures, however, the necessity for a strong service organization becomes important. The smaller firm might then consider joining forces with a larger firm which has a service organization that can be adapted to the involved product. Typical example is the Bluetooth technology of Blackberry.

5. R&D and product development

A firm may be highly skilled at R&D and new product development, but it may lack skills in either marketing or production. Godrej is marketing the mosquito repellent Good knight and mango juice Jumpin, which are typical products of small entrepreneurs. Sun silk shampoo of HUL is manufactured in SSI units of Pondicherry.

6. Exploiting excess capacity

One type of resources that is often easily exchanged is excess capacity. Bottling plants of SDC (Soft Drink Concentrates) are now widely engaged in bottling fresh juices of orange, apple, mango, pineapple, grapes, tender coconut and lemon juice for MNCs Pepsi and Coke in India.

7. Achieving economies of scale

Related diversification can sometimes provide economies of scale. Two smaller consumer product firms, for example, may not be able to afford an effective sales force, new product development or testing programme, or warehousing and logistics systems. However, the two firms together may be able to operate at an efficient level. Similarly, two firms when combined may be able to justify an expensive piece of automated production equipment.

8. Risks of related diversification

Even related diversification can be risky. There are three major problems. First, relatedness and potential synergy simply don’t exist. Strategists delude themselves that there is a synergistic justification not on the basis of judgement supported by a thorough external and self-analysis, but by manipulating semantics.

Second, potential synergy may exist but is never realized because of implementation problems. This happens when the diversification move involves integrating two organizations that have fundamental differences and/or because one of the two organizations lacks the ability or motivation to undertake necessary programmes to make the diversification work.

Third, possible violations of antitrust laws in the west and MRTP (Monopolies and Restrictive Trade Practice) law in India create an additional risk when an acquisition or merger is involved. Ironically, as the degree of relatedness and the synergy potential increase so does the possibility of an antitrust or MRTP problem. Jet Airways and Sahara deal is a typical example.

Jet Airways has extended its service to the mass market under Jet Lite. Similarly, Kingfisher acquired Air Deccan and symbolically kept the Kingfisher logo in the wings and POS outlets in the country, which includes all post offices and petrol pumps.

Unrelated Diversification

Unrelated diversification lacks commonality in markets, distribution channels, production technology, and R&D thrust to provide the opportunity for synergy through the exchange or sharing of assets or skills. Reliance entered into retailing by allocating Rs25, 000 crore in a phased manner is a typical example.

1. Manage and allocate cash flow

Unrelated diversification can balance the cash flows of SBU entities. A firm, which has many SBUs that merit investment might buy or merge with a cash cow to provide a source of cash. The acquisition of the cash cow may reduce the need to raise debt or equity over time, although if the cash cow is acquired, resources will need to be expected.

Typical example is Kingfisher Airlines, where the chairman and CEO Vijay Mallya himself routed the surplus cash from this liquor business to give the ‘Fly the good times’ experience to Indian aviation. So there’s KF Fun TV with seven channels (lifestyle, entertainment, sports, English premium, toon (cartoon), flight guide and view from the top channels, and KF Radio with 10 channels chartbusters and hindi pop, hindi retro (the golden oldies), Hindi Easy Listening, ghazals, english pop, english retro (an earful of vintage), Easy Listening (Honey trenched notes that remind the listener that world is still a wonderful place), Club (dance floor) Jazz and Blues and Lounge (lie back in the lap of lounge with the soothing notes of lounge music) supported with state of the art aircraft and technology for in-flight, catering. The reservation system is a remarkable attempt to reposition the image of the Indian industry.

2. Entering business areas with high ROI prospects

A basic diversification motivation is to improve ROI by moving into business areas with high ROI prospects. One approach is to enter high growth business areas. According to life style consumption study by Edelweiss Securities, organized retail trade in India is now finding its feet. Its share in the total retail pie is set to increase from the current 2 per cent to about 10 per cent by 2010. This will translate into approximately Rs1, 400 billion of retail trade by 2010 (Figure 8.19).

The study further says retail space is expected to increase from 10 million sq. ft. in 2002 to 80 million sq. ft. in 2010. Retail space development in leading centres will provide high impetus to retail growth as about 38 per cent of India’s high income households live in the top five cities (Mumbai, Delhi, Kolkata, Chennai and Bangalore), and an additional 28 per cent stay in mid-sized cities.

Significant growth in organized retailing during the next three years is expected in the metros and mini-metros through better performance of the existing stores, as well as opening of new stores. From 25 operational malls in 2003, the country is expecting over 600 malls by 2010. Accordingly Videocon Industries spotted organized retailing as the bright spot for future investments to the tune of Rs25, 000 crore by 2010.

3. Obtaining a ‘bargain’ price for a business

Another way to improve the ROI is to acquire a business at a ‘bargain’ price so the involved investment is low and the associated ROI is therefore high.

4. The potential to restructure a firm

Allen, Oliver, and Schwallie, three Booz Allen acquisition specialists have suggested another possibility: that an acquisition can provide the basis for a restructuring of the acquired firm, the acquiring firm, or both.

5. Reducing risk

The reduction of risk can be another motivation for unrelated diversification. The heavy reliance upon a single product line can stimulate a diversification move. Reducing risk can also lead to entering into businesses that will counter or reduce the cyclical nature of the existing earnings.

6. Risks of unrelated diversification

The very concept of an unrelated business, where by definition there is no possibility to improve that business through synergy, suggests risk and difficulty. Many knowledgeable people have made blanket statements warning against unrelated diversification. Peter Drucker claims that all successful diversification requires a common core or unity represented by common markets, technology, or production processes. He states that without such a unity, diversification can never work; financial ties alone are insufficient.

The beta (β) of an investment security (i.e. a stock) is a measurement of its volatility of returns relative to the entire market. It is used as a measure of risk and is an integral part of the Capital Asset Pricing Model (CAPM). A company with a higher beta has greater risk and also greater expected returns.

The beta coefficient can be interpreted as follows:

• β =1 exactly as volatile as the market
• β >1 more volatile than the market
• β <1>0 less volatile than the market
• β =0 uncorrelated to the market
• β <0 negatively correlated to the market

Examples of beta

High β: A company with a β that’s greater than 1 is more volatile than the market. For example, a high-risk technology company with a β of 1.75 would have returned 175% of what the market return in a given period (typically measured weekly).

Low β: A company with a β that’s lower than 1 is less volatile than the whole market. As an example, consider an electric utility company with a β of 0.45, which would have returned only 45% of what the market returned in a given period.

Negative β: A company with a negative β is negatively correlated to the returns of the market. For an example, a gold company with a β of -0.2, which would have returned -2% when the market was up 10%.

Equity Beta and Asset Beta

Levered beta, also known as equity beta or stock beta, is the volatility of returns for a stock taking into account the impact of the company’s leverage from its capital structure. It compares the volatility (risk) of a levered company to the risk of the market.

Levered beta includes both business risk and the risk that comes from taking on debt. It is also commonly referred to as “equity beta” because it is the volatility of an equity based on its capital structure.

Asset beta, or unlevered beta, on the other hand, only shows the risk of an unlevered company relative to the market. It includes business risk but does not include leverage risk.

Project Beta

For simplicity throughout previous chapters we have used a general beta factor (b) applicable to the overall systemic risk of portfolios, securities and projects. But now our analysis is becoming more focused, precise notation and definitions are necessary to discriminate between systemic business and financial risk. Table 7.1 summarizes the beta measures that we shall be using for future reference and also highlights a number of problems.

b = total systematic risk, which relates portfolio, security and project risk to market risk.

b = the business risk of a specific project (project risk) for investment appraisal.

bf = the published equity beta for a company that incorporates business risk and systematic financial risk if the firm is geared.

bA = the overall business risk of a firm’s assets (projects). It also equals a company’s

deleveraged published beta (bf) which measures business risk free from financial risk.

bD = the beta value of debt (which obviously equals zero if it is risk-free).

bf„ and bfG are the respective equity betas for similar all-share and geared companies.

When an all-equity company is considering a new project with the same level of risk as its current portfolio of investments, total systematic risk equals business risk, such that:

When a company is funded by a combination of debt and equity, this series of equalities must be modified to incorporate a premium for systematic financial risk. As we shall discover, the equity beta (bE) will be a geared beta reflecting business risk plus financial risk, which measures shareholder exposure to debt in their firm’s capital structure. Thus, the equity beta of an all-share company is always lower than that for a geared firm with the same business risk.

Irrespective of a gearing problem, Table 7.1 reveals a further weakness of the CAPM. A company’s asset beta (bA) should produce a discount rate that is appropriate for evaluating projects with the same overall risk as the company itself. But what if a new project does not reflect the average risk of the company’s assets? Then the use of bA is no more likely to produce a correct investment decision than the use of a WACC calculation.

To illustrate the point, Figure 7.1 graphs the Security Market Line (SML) to show the required return on a project for different beta factors, with a company’s WACC. The use of the overall cost of capital to evaluate projects whose risk differs from the company’s average will be sub-optimal where the IRR of the project is in either of the two shaded sections. To calculate the correct CAPM discount rate using Equation (45), we must determine the project beta.

Figure 7.1: The SML, WACC and Project Betas

The company’s average beta, shown in the diagram, provides a measure of risk for the firm’s overall returns compared with that of the market. However, management’s investment decision is whether or not to invest in a project. So, like the WACC, if the project involves diversification away from the firm’s core activities, we must use a beta coefficient appropriate to that class of investment. The situation is similar to a stock market investor considering whether to purchase the shares of the company. The individual would need to evaluate the share’s return by using the market beta in the CAPM.

Even if diversification is not contemplated, the project’s beta factor may not conform to the average for the firm’s assets. For example, the investment proposal may exhibit high operational gearing (the proportion of fixed to variable costs) in which case the project’s beta will exceed the average for existing operations.

A serious conflict (the agency problem) can also arise for those companies producing few products, or worse still a single product, particularly if management approach their capital budgeting decisions based on self-interest and short-termism, rather than shareholder preferences. Shareholders with well-diversified corporate holdings who dominate such companies may prefer to see projects with high risk (high beta coefficients) to balance their own portfolios. Such a strategy may carry the very real threat of bankruptcy but in the event may have very little impact their overall returns. For corporate management, the firm’s employees and its suppliers, however, the policy may be economic suicide.

Fortunately, if a beta is required to validate the CAPM for project appraisal, help is at hand. Management can obtain factors for companies operating in similar areas to the proposed project by subscribing to the many commercial services that regularly publish beta coefficients for a large number of companies, world wide. Their listings also include stock exchange classifications for industry betas. These are calculated by taking the market average for quoted companies in the same industry. Research reveals that the measurement errors of individual betas cancel out when industry betas are used. Moreover, the larger the number of comparable beta constituents, the more reliable the industry factor.

So, if management wish to obtain an estimate for a project’s beta, it can identify the industry in which the project falls, and use that industry’s beta as the project’s beta. This approach is particularly suitable for highly diversified and divisionalised companies because their WACC or market beta would be of little relevance as a discount rate for its divisional operations.

As an alternative to stock market data, management can also estimate a project’s beta from first principles by calculating its F-value.

The F-value of a project is rather like a beta factor in that it measures the variability of a project’s performance, relative to the performance of an entity for which a beta value exists.

The entity could be the industry in which the project falls, the firm undertaking the project, or a division within the firm that is responsible for the project.

A project’s F-value is defined as follows:

As a result, we can obtain an estimate of a project’s beta through one of three routes:

Portfolio Beta

Calculating the volatility, or beta, of your stock portfolio is probably easier than you think. A beta of 1 means that a portfolio’s volatility matches up exactly with the markets. A higher beta indicates great volatility, and a lower beta indicates less volatility. To do it, you’ll need to know the percentage of your portfolio by individual stock and the beta for each of those stocks.

The first step is to multiply the percentage of your portfolio and the beta for each individual stock. Once that is done, simply add up the results and you’ll have your portfolio beta.

This method is a simple weighted average calculation. It’s an easy way to quickly assess your entire portfolio’s volatility. It only works though if the individual stock’s betas are calculated correctly and comparably. Using a six month time period to calculate one stocks beta and a six year period to calculate the other will give you a much different result than using the same time period across the board. Likewise, it’s wise to use the same index for each individual stock’s beta so that your portfolio beta will have consistency with that index as well. For most portfolios, the S&P 500 is a reasonable index to start with.

It’s not required to use the same time period and index for each stock, but it is important to understand how differences in each individual stock’s beta will impact the result for your entire portfolio.