Topic 3: Risk and Return Part II

The importance of financial markets

Financial markets allow companies, governments and individuals to increase their utility. Savers can invest in financial assets so that they can defer consumption and earn a return to compensate them for doing so. Borrowers have better access to capital that is available so they can invest in productive assets. Financial markets also provide us with information about the returns that are required for various levels of risk.

In Topic 2, you learnt the foundation knowledge about risk and return. In Topic 3, you will continue to build on your knowledge of risk and return. More specifically, in this topic, you will learn the following concepts:

Concept 1: Portfolio diversification

Concept 2: Systematic vs unsystematic risk

Concept 3: The capital asset pricing model (CAPM) and the security market line (SML).

Concept 4: Capital Market Line (CML) and efficient portfolios

Concept 1: Portfolio diversification

Meaning of Diversification

Portfolio diversification means investing in several different asset classes or sectors. It does not mean holding a lot of assets. For example, if you own 50 real-estate shares, you are not diversified. However, if you own 50 shares that span 20 different industries, then you are diversified.

What is the principle of diversification?

The purpose of diversification is to substantially reduce the variability of returns without an equivalent reduction in expected returns. This reduction in risk arises because worse than expected returns from one asset are offset by better-than-expected returns from another. However, there is a minimum level of risk that cannot be diversified away and that is the systematic portion.

The degree of gain from diversification (risk reduction) increases as the correlation between the rates of return on two securities decreases:

  • r = +1: Perfectively positive correlated. No risk reduction.
  • 0 < r < 1: Less than perfectively positive correlated. Some risk reduction.
  • r = < 0: Negatively correlated. More risk reduction

Diversification with multiple assets

The more assets we incorporate into the portfolio, the greater the diversification benefits are. The key is the correlation between each pair of assets in the portfolio. For a diversified portfolio, the variance of the individual assets contributes little to the risk of the portfolio. The risk depends largely on the covariances between the returns on the assets.

Diversifiable risk

This is the risk that can be eliminated by combining assets into a portfolio. This is also known as unsystematic, unique or asset-specific risk. If you hold only one asset, or assets in the same industry, then you are exposing yourself to risk that you could diversify away.

Concept 2: Systematic vs unsystematic risk

In order to distinguish between systematic and unsystematic risk, you need to understand the concept of total risk.

Total risk = Systematic risk + Unsystematic risk

The standard deviation of returns is a measure of total risk. For well-diversified portfolios, unsystematic risk is very small. Consequently, the total risk for a diversified portfolio is essentially equivalent to the systematic risk

Systematic risk

One of the fundamental concept of finance is that there is a reward for bearing risk. This means there is no reward for bearing risk unnecessarily. In other words, there is no reward for bearing unsystematic risk.

The expected return on a risky asset depends only on that asset’s systematic risk since unsystematic risk can be diversified away. One simple way investors can achieve diversification is by investing in mutual funds and ETFs.

Measuring systematic risk

How do we measure systematic risk? We use the beta coefficient.

2.13 Asset’s beta (systematic Risk) [latex]\beta_i=\frac{Cov(R_i,R_m)}{{\sigma_M}^2}[/latex] or [latex]\beta_i=\frac{\rho_{i,M}\times\sigma_i}{\sigma_M}[/latex]

Note: i denotes specific asset/stock

What does beta tell us?

  • A beta of 1 implies the asset has the same systematic risk as the overall market (AORD index)
  • A beta < 1 implies the asset has less systematic risk than the overall market
  • A beta > 1 implies the asset has more systematic risk than the overall market

Total vs systematic risk

Consider the following information:

Security Standard Deviation Beta
CCC 25% 1.50
KKK 30% 0.97
  • Which security has more total risk?
  • Which security has more systematic risk?
  • Which security should have the higher expected return?

Portfolio betas

Consider our previous example with the following four securities.

Security Weight Beta
CCC 0.133 1.685
KKK 0.2 0.195
NNN 0.267 1.161
BBB 0.4 1.434

What is the portfolio beta?

2.16 Portfolio beta [latex]\beta_{n\ Asset\ portfolio}=\sum_{i=1}^{n}{(w_i\times\beta_i)}[/latex]

Beta = 0.133(1.685) + 0.2(0.195) +0.267(1.161) + 0.4(1.434) = 1.147

Portfolio performance appraisal

Investors need a way to measure the performance of their portfolio. You need to measure the portfolio risk and then measure the performance against a benchmark with the same risk. Portfolio performance may differ from the benchmark due to:

  • asset allocation
  • market timing
  • security selection
  • random influences.

Portfolio performance measures

Simple benchmark index is the most common approach. Another approach is to compare to closest index.

Sharpe ratio

[latex]Sharpe\ ratio=\ \frac{\overline{r_p}-\overline{r_f}}{\overline{\sigma_p}}[/latex]

The Sharpe ratio measures excess return per unit of total risk.

where

[latex]\overline{r_p}[/latex] = the average portfolio return
[latex]\overline{r_f}[/latex] = the average risk-free rate of return
[latex]\overline{\sigma_p}[/latex] = the standard deviation of the returns on the portfolio.

Compare the Sharpe ratio of the portfolio to the Sharpe ratio of the benchmark.

Treynor ratio

[latex]Treynor\ ratio=\ \frac{\overline{r_p}-\overline{r_f}}{\overline{\beta_p}}[/latex]

The Treynor ratio measures excess return per unit of systematic risk.

where

[latex]\overline{\beta_p}[/latex] = an estimate of the portfolios’ systematic risk

Compare the Treynor ratio of the portfolio to the Treynor ratio of the benchmark.

Beta and the risk premium

Recall the definition of risk premium. It is Expected return – Risk-free rate.

The higher the beta, the greater the risk premium should be. Can we define the relationship between the risk premium and beta so that we can estimate the expected return? Yes, you can.

Concept 3: The capital asset pricing model (CAPM) and the security market line (SML).

The pricing of risky assets

What determines the expected rate of return on an individual asset? Risky assets will be priced such that there is a relationship between returns and systematic risk. Investors need to be sufficiently compensated for taking on the risks associated with the investment.

What determines the expected rate of return on an individual asset?

Risky assets will be priced such that there is a relationship between returns and systematic risk. Investors need to be sufficiently compensated for taking on the risks associated with the investment.

The capital market will only reward investors for bearing risk that cannot be eliminated by diversification. Unsystematic risk can be diversified away, so the capital market will not reward investors for taking this type of firm specific risk.

However, CAPM states the reward for bearing systematic risk is a higher expected return, consistent with the idea of higher risk requires higher return.

In equilibrium, the expected return on a risky asset i (or an inefficient portfolio), is given by the security market line:

[latex]E\left(R_i\right)=R_f+\left(\frac{E\left(R_M\right)-R_f}{\sigma_M^2}\right)Cov(R_i,R_M)[/latex]

The covariance term is the only explanatory factor in the equation that is specific to asset i.

As Cov(Ri,RM) is the risk of an asset held as part of the market portfolio, and s2M is the risk of the market portfolio, beta (bi) measures the risk of i relative to the risk of the market as a whole.

We can thus write the SML as the CAPM equation:

2.15 CAPM/SML [latex]{E(R}_i)=R_f+\beta_i\left[{E(R}_m\right)-R_f][/latex]

Note: i denotes specific asset/stock

Implementation of the CAPM

The three components of the CAPM are Rf, Bi and E(RM). They can be obtained as follows:

  • Rf  = the yield of the government security with the same term as the proposed project
  • Bi  = source time series data on the rates of return on shares and market portfolio; use market model to estimate beta
  • E(RM) = two ways to calculate, either calculate the average return in share market index over a long period of time and deduct Rf or estimate market risk premium directly over a long period of time.

Tests of the CAPM

Early empirical evidence was supportive of CAPM. Roll’s critique (1977) states that the market portfolio (theoretically all assets in the economy) is unobservable in practice. Tests of the CAPM can only determine whether the market portfolio used is efficient. Factors other than beta were shown to explain returns. However, CAPM is a useful tool when thinking about asset returns.

Fama–French three-factor model

Fama and French (1992) provide evidence on factors that explain asset returns — no support for CAPM; support for firm size, leverage, P–E, BV/MV, though not definitive. Fama and French (1995) leads to the most common three-factor model: Includes the CAPM market factor, a small minus large portfolio factor (SML) and a high minus low market to book portfolio (HML). Empirical evidence of Fama-French three-factor can be found from the following website:

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

This model is supported by Australian data. While the three-factor model is empirically robust, it suffers from difficult economic interpretation. Why do company size and BV/MV explain asset returns? The three-factor model is now very common in empirical research. Carhart (1997) added a fourth factor called momentum. The momentum factor is based on the finding that the companies that have had high (low) returns in the past 3–12 months have high (low) returns in the next 3–12 months.

Concept 4: Capital Market Line (CML) and efficient portfolios

The set of all feasible portfolios that can be constructed from a given set of risky assets.

Graph of the efficiency frontier

Image: Markowitz frontier (Public Domain) – CAL is Capital Allocation Line.

Investor will try to secure a portfolio on the efficient frontier. The efficient frontier is determined on the basis of dominance. A portfolio is efficient if:

  • no other portfolio has a higher return for the same risk, or
  • no other portfolio has a lower risk for the same return.

Investors are a diverse group and, therefore, each investor may prefer a different point along the efficient frontier.

An efficient frontier is a graph that shows the trade-off between risk and return for a set of investments. The efficient frontier is constructed by plotting the expected return of each investment against its standard deviation, which is a measure of its volatility or risk. The efficient frontier represents the set of portfolios that offer the highest expected return for a given level of risk, or the lowest risk for a given level of expected return. Portfolios that lie on the efficient frontier are considered to be “efficient” because they provide the maximum possible return for a given level of risk, or the minimum possible risk for a given level of return.

In financial analysis, the efficient frontier is often represented as a curve on a two-dimensional graph, with expected return on the y-axis and standard deviation on the x-axis. The curve starts at the point with the lowest standard deviation and rises to the point with the highest expected return. The portfolios that lie on the efficient frontier are those that maximize expected return for a given level of risk, or minimize risk for a given level of expected return.

The capital market line

Combining the efficient frontier with preferences, investors choose an optimal portfolio. This can be enhanced by introducing a risk-free asset: The opportunity set for investors is expanded and results in a new efficient frontier—capital market line (CML).

The CML represents the efficient set of all portfolios that provides the investor with the best possible investment opportunities when a risk-free asset is available. The CML links the risk-free asset with the optimal risky portfolio (M). Investors can then vary the riskiness of their portfolio investment by changing weights in the risk-free asset and portfolio M. This changes their return according to the CML:

2.14 Capital Market Line (CML) [latex]E\left(R_P\right)=R_f+(\frac{E\left(R_m\right)-R_f}{\sigma_M})\sigma_P[/latex]

Appendix:

Expected vs unexpected returns

Realised returns are generally not equal to expected returns. The realised return has the expected component and the unexpected component. At any point in time, the unexpected return can be either positive or negative. Over time, the average of the unexpected return component is zero.

Announcements and news

Announcements and news contain both an expected component and a surprise component. It is the surprise component that affects a share’s price and therefore its return. This is obvious when you watch how share prices move when an unexpected announcement is made or earnings are different than anticipated.

Efficient markets

Efficient markets are a result of investors trading on the unexpected portion of announcements. The easier it is to trade on surprises, the more efficient markets should be. Efficient markets involve random price changes because you cannot predict surprises.

Efficient capital markets:

In efficient capital markets, share prices are in equilibrium or are ‘fairly’ priced. If this is true, then you should not be able to earn ‘abnormal’ or ‘excess’ returns. Efficient markets do not imply that investors cannot earn a positive return in the share market. They can return based on the systematic risk of the asset.

Reaction of share price to new information in efficient and inefficient markets

What makes markets efficient?

There are many investors do research in the capital market. As new information comes to market, this information is analysed and trades are made based on this information. Therefore, prices should reflect all available public information. If investors stop researching shares, then the market will not be efficient. One consequence of the wider availability of information and lower transaction costs is that the market will be more volatile. It is easier to trade on ‘small’ news instead of just big events. It is also important to remember that not all available information is reliable. It’s important to still do the research and not jump on everything that crosses the news wire.

Common misconceptions about the efficient market

Efficient markets do not mean that you cannot make money. They do mean that, on average, you will earn a return that is appropriate for the risk undertaken. There is not a bias in prices that can be exploited to earn excess returns. Market efficiency will not protect you from wrong choices if you do not diversify. You still do not want to ‘put all your eggs in one basket’.

Claims of superior performance in share picking are very common and often hard to verify. However, if markets are semi-strong form efficient, the ability to consistently earn excess returns is unlikely.

Even the experts get confused about the meaning of capital market efficiency. Consider the following quote from a column in Forbes magazine: ‘Popular delusion three: Markets are efficient. The efficient market hypothesis, or EMH, would do credit to medieval alchemists and is about as scientific as their efforts to turn base metals into gold.’ The writer is definitely not a proponent of EMH. Now consider this quote: ‘The truth is nobody can consistently predict the ups and downs of the market.’ This statement is clearly consistent with the EMH. Ironically, the same person wrote both statements in the same column with exactly nine lines of type separating them.

Strong form efficiency

In strong form of efficiency prices reflect all information, including public and private. If the market is strong form efficient, then investors could not earn abnormal returns regardless of the information they possessed

Empirical evidence indicates that markets are not strong form efficient and that insiders could earn abnormal returns. 

Semi-strong form efficiency

Prices reflect all publicly available information including trading information, annual reports, press releases, etc. If the market is semi-strong form efficient, then investors cannot earn abnormal returns by trading on public information. Implies that fundamental analysis will not lead to abnormal returns

Empirical evidence suggests that some shares are semi-strong form efficient, but not all. Larger, more closely followed shares are more likely to be semi-strong form efficient. Small, more thinly traded shares may not be semi-strong form efficient, but liquidity costs may wipe out any abnormal returns that are available.

Weak form efficiency

Prices reflect all past market information such as price and volume. If the market is weak form efficient, then investors cannot earn abnormal returns by trading on market information. Implies that technical analysis will not lead to abnormal returns. Empirical evidence indicates that markets are generally weak form efficient. Just because technical analysis shouldn’t lead to abnormal returns, that doesn’t mean that you won’t earn fair returns using it—efficient markets imply that you will. There are also many technical trading rules that have never been empirically tested; so it is possible that one of them might lead to abnormal returns. But if it is well publicised, then any abnormal returns that were available will soon evaporate.

References:

  • Peirson, G., Brown, R., Easton, S. A., Howard, P., & Pinder, S. (2015). Business finance (Twelfth edition). McGraw-Hill Education.
  • Ross, S. A., Trayler, R., Hambusch, G., Koh, C., Glover, K., Westerfield, R., & Jordan, B. (2021). Fundamentals of corporate finance (Eighth edition.). McGraw-Hill Education (Australia) Pty Limited.
  • Parrino, R., Au Yong, H. H., Dempsey, M. J., Ekanayake, S., Kidwell, D. S., Kofoed, J., Morkel-Kingsbury, N., & Murray, J. (2014). Fundamentals of corporate finance (Second edition.). John Wiley and Sons Australia, Ltd.

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