Achieving Better Returns In Your Portfolio
Research, Not Intuition
Successful portfolios are based on research and reasonable expectations, not intuition. Illogical investors attempt to guess which manager, stock or asset class will have tomorrow's best performance. That's why so many have consistently failed. Successful, rational investors excel because of a clear methodology, and, of course, discipline. What type of investor are you? What type of investor do you want to be?
See: Stock-Picking Strategies
Asset allocation deals with how investors divide their portfolio among three major asset categories: cash, bonds and stocks. The asset-allocation decision, otherwise known as investment policy, is arguably the most important determinant of a portfolio's long-term return. A study by landmark Brinson, Hood and Beebower, "Determinants of Portfolio Performance" (1986, 1991) argues that investment policy accounts for 94% of the variation in returns in a portfolio, leaving market timing and stock selection to account for only 6%. (For more information, see Five Things To Know About Asset Allocation and 6 Asset Allocation Strategies That Work.).
An overwhelming amount of evidence shows that there is little advantage in attempting either to time markets or select individual equities. Such efforts instead result in additional cost, additional risk and lower returns over time.
Risk and Reward
Risk and reward are related. An investor must be induced by a potential investment return in order to give up a risk-free alternative like a Treasury bill. The same holds true for small company stock. Wouldn't you demand a greater potential return to buy a fledgling, unknown company instead of Microsoft? It's a no-brainer. There's more risk involved in the transaction, so you should demand to get paid more, right?
A pioneering study by renowned academics, Eugene Fama and Ken French, suggests that three risk factors: market (beta), size (market capitalization) and price (book/market value) dimensions explain 96% of historical equity performance. This model goes further than CAPM to include the fact that two particular types of stocks outperform markets on a regular basis: value stocks (high book/market value) and small caps. Although it is not clear as to why this is so, this pattern nonetheless persists in multiple time frames and every global market where we can assemble data. Below is historical data showing that between 1960 and 2004, small value (small-cap, high book/market value) stocks outperformed both the market (S&P 500) and large-value stocks. What this implies is that historically, small-value "just happens" to deliver higher returns and higher volatility than the stock market as a whole. (To learn more, see How is the value of the S&P 500 calculated?)
The Fama-French three-factor model allows investors to calculate the way portfolios take different types of risk and to calculate their expected returns. The following exhibit shows how portfolios are plotted using their risk exposures. The vertical and horizontal axes represent the exposures to value and small-cap stocks. Portfolios exposed to size risk (small-cap stocks) plot along the vertical (size) axis; and those that take risk on distressed companies (value stocks) plot on the horizontal (value) axis. Since all equity portfolios assume a market risk (beta), no additional axis is needed. Market risk is represented just below the intersection of the axes, and anything above the line is excess return above the market.
Fama and French aren't particular about why book/market value measures risk, although they and others have suggested some possible reasons. For example, high book/market values could mean a stock is distressed, temporarily selling low because future earnings look doubtful, which implies that value stocks are more risky than average - exactly the opposite of what a traditional business analyst would tell you. The business analyst would say high book/market values indicate a buying opportunity since the stock looks cheap relative to its intrinsic value. Regardless of the reasoning, there is one thing that you should take away from the three-risk-factor model - history has shown that small value stocks tend to have higher returns and higher volatility than the stock market as a whole. Thus, by carefully managing the amount of some small value stocks in your portfolio, you can achieve above-average returns. (To learn more, see How To Avoid Closing Options Below Intrinsic Value.)
Asset classes have unique cycles. When growth is doing well, value may not do as well and vice versa. In some years, small and value stocks may outperform the market; in others they may underperform. It takes resilience and psychological preparedness to endure the times they underperform. Remember, investing in small and value stocks should augment the bottom line in the long run, but investors should understand that their portfolio will not identically track the market every single year (and that's OK).
Deciding on the degree to which your portfolio should be based on the three risk factors is the challenge for the investor. Tilting toward small and value stocks will help you reach above global market returns, but portfolio risk must be tempered by adding other assets with low correlations (e.g., bonds, international stocks, international small stocks and international small value stocks).
The Bottom Line
So, what have you learned? Investors can structure portfolios that deliver above global market index returns by designing a strategic portfolio tilt. Fundamental theories like asset allocation and the three-factor model can have a dramatic impact on the way you invest.
Remember, designing a portfolio that favors small and value companies over pure market risk should deliver higher expected returns over extended periods of time. These benefits can be reliably captured by passive strategies (like index funds) that do not rely on either individual stock selection or market timing. As with many things in life, a little strategic planning goes a long way.
The Capital Asset Pricing Model (CAPM)
The Capital Asset Pricing Model (CAPM)
No matter how much we diversify our investments, it's impossible to get rid of all the risk. As investors, we deserve a rate of return that compensates us for taking on risk. The capital asset pricing model
(CAPM) helps us to calculate investment risk and what return on
investment we should expect. Here we look at the formula behind the
model, the evidence for and against the accuracy of CAPM, and what CAPM
means to the average investor.
Birth of a Model
The capital asset pricing model was the work of financial economist (and, later, Nobel laureate in economics) William Sharpe, set out in his 1970 book "Portfolio Theory And Capital Markets." His model starts with the idea that individual investment contains two types of risk:
- Systematic Risk - These are market risks that cannot be diversified away. Interest rates, recessions and wars are examples of systematic risks.
- Unsystematic Risk - Also known as "specific risk," this risk is specific to individual stocks and can be diversified away as the investor increases the number of stocks in his or her portfolio. In more technical terms, it represents the component of a stock's return that is not correlated with general market moves.
Sharpe found that the return on an individual stock, or a portfolio of stocks, should equal its cost of capital. The standard formula remains the CAPM, which describes the relationship between risk and expected return.
Here is the formula:
CAPM's starting point is the risk-free rate - typically a 10-year government bond yield. To this is added a premium that equity investors demand to compensate them for the extra risk they accept. This equity market premium consists of the expected return from the market as a whole less the risk-free rate of return. The equity risk premium is multiplied by a coefficient that Sharpe called "beta."
More than 50% of retirement age individuals to not have enough savings
According to CAPM, beta is the only relevant measure of a stock's risk. It measures a stock's relative volatility - that is, it shows how much the price of a particular stock jumps up and down compared with how much the stock market as a whole jumps up and down. If a share price moves exactly in line with the market, then the stock's beta is 1. A stock with a beta of 1.5 would rise by 15% if the market rose by 10%, and fall by 15% if the market fell by 10%. (For further reading, see Beta: Gauging Price Fluctuations and Beta: Know The Risk.)
Beta is found by statistical analysis of individual, daily share price returns, in comparison with the market's daily returns over precisely the same period. In their classic 1972 study titled "The Capital Asset Pricing Model: Some Empirical Tests," financial economists Fischer Black, Michael C. Jensen and Myron Scholes confirmed a linear relationship between the financial returns of stock portfolios and their betas. They studied the price movements of the stocks on the New York Stock Exchange between 1931 and 1965.
Beta, compared with the equity risk premium, shows the amount of compensation equity investors need for taking on additional risk. If the stock's beta is 2.0, the risk-free rate is 3% and the market rate of return is 7%, the market's excess return is 4% (7% - 3%). Accordingly, the stock's excess return is 8% (2 X 4%, multiplying market return by the beta), and the stock's total required return is 11% (8% + 3%, the stock's excess return plus the risk-free rate).
What this shows is that a riskier investment should earn a premium over the risk-free rate - the amount over the risk-free rate is calculated by the equity market premium multiplied by its beta. In other words, it's possible, by knowing the individual parts of the CAPM, to gauge whether or not the current price of a stock is consistent with its likely return - that is, whether or not the investment is a bargain or too expensive.
What CAPM Means for You
This model presents a very simple theory that delivers a simple result. The theory says that the only reason an investor should earn more, on average, by investing in one stock rather than another is that one stock is riskier. Not surprisingly, the model has come to dominate modern financial theory. But does it really work?
It's not entirely clear. The big sticking point is beta. When professors Eugene Fama and Kenneth French looked at share returns on the New York Stock Exchange, the American Stock Exchange and Nasdaq between 1963 and 1990, they found that differences in betas over that lengthy period did not explain the performance of different stocks. The linear relationship between beta and individual stock returns also breaks down over shorter periods of time. These findings seem to suggest that CAPM may be wrong.
While some studies raise doubts about CAPM's validity, the model is still widely used in the investment community. Although it is difficult to predict from beta how individual stocks might react to particular movements, investors can probably safely deduce that a portfolio of high-beta stocks will move more than the market in either direction, and a portfolio of low-beta stocks will move less than the market.
This is important for investors - especially fund managers - because they may be unwilling to or prevented from holding cash if they feel that the market is likely to fall. If so, they can hold low-beta stocks instead. Investors can tailor a portfolio to their specific risk-return requirements, aiming to hold securities with betas in excess of 1 while the market is rising, and securities with betas of less than 1 when the market is falling.
Not surprisingly, CAPM contributed to the rise in use of indexing - assembling a portfolio of shares to mimic a particular market - by risk averse investors. This is largely due to CAPM's message that it is only possible to earn higher returns than those of the market as a whole by taking on higher risk (beta). (To learn more, see The Lowdown On Index Funds.)
The capital asset pricing model is by no means a perfect theory. But the spirit of CAPM is correct. It provides a usable measure of risk that helps investors determine what return they deserve for putting their money at risk. To learn more, see Achieving Better Returns In Your Portfolio.
Value At Risk (VAR)
Value At Risk (VAR)
A statistical technique used to measure and quantify the level of financial risk within a firm or investment portfolio over a specific time frame. Value at risk is used by risk managers in order to measure and control the level of risk which the firm undertakes. The risk manager's job is to ensure that risks are not taken beyond the level at which the firm can absorb the losses of a probable worst outcome.
Value at Risk is measured in three variables: the amount of potential loss, the probability of that amount of loss, and the time frame. For example, a financial firm may determine that it has a 5% one month value at risk of $100 million. This means that there is a 5% chance that the firm could lose more than $100 million in any given month. Therefore, a $100 million loss should be expected to occur once every 20 months.
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