Régimen aplicable

The CAPM theory provides the basis for many applications within the financial sector and to a lesser degree, in the resource sector and is worth briefly reviewing for later discussion in this thesis. The model is based on determining a company’s cost of equity capital by estimating the difference in a company’s share price return with the return of the overall market using historical data. Reilly (1985) refers to it as an equilibrium asset pricing model.

The model segregates the expected or required rate of return on an equity investment into a risk-free rate such as a Government bond plus a risk premium reflecting the additional risk required by investors firstly, to invest in the stock market (above the risk free rate) and secondly for the non-diversifiable risk of a particular company specific risks. This can be summarised as:

Rj = Rf + BBj(Rm – Rf)

Therefore if:

Rj = expected return on stock j

Rm = expected return on a well-diversified portfolio of shares (such as

the whole stock market)

BBj = ‘Beta factor’ or relative volatility of the return on stock j compared to the market average

It is evident that adjusts the market risk premium above the risk free rate for the risk or volatility of returns of the specific company being assessed.

)

( _{m f}

j R R

B −

In determining a risk-adjusted rate for an investment, Hull (2008) recommends:

1. Take a sample of companies whose main line of business is the same as that of the project being contemplated.

2. Calculate the betas of the companies and average them to obtain a proxy beta for the project.

3. Set the required rate of return equal to the risk-free rate plus the proxy beta times the excess returns of the market portfolio over the risk-free rate.

While the CAPM has a long history, there several shortcomings relevant to the resource sector which are worth highlighting and hence this thesis has investigated alternative pricing mechanisms using probability weighted changes in company value. The short comings discussed here are the relevance of the risk-free rate, beta (alpha) relationships given the commodity price leverage of resource companies, and embedded option value.

2.2.1.1 Risk-free Rate

Long-term Government bond yields (say 10 year, or even longer timeframes in the US) are often used as a risk-free rate in the model. In the resource sector, they often provide the best approximation of the life span of a resource project. Reilly (1985) points out that historically ‘risk-free’ type rates have been volatile and as evident in the current economic environment, it reflects the contrasting forces of Governments seeking to fund their various economic stimulus packages following the Global Financial Crisis.

Under CAPM the premise is that unless an investment compensates the risk with a higher return, an investor will always chose the least risky return and hence a deemed ‘risk-free’ government bond. However, to segregate out the risk-free rate may not always be the case as:

• Investors may allocate a proportion of their investments to the resource sector under diversification strategies irrespective of expected returns. In the most basic case, an index fund will hold stocks in a weighting corresponding to their weightings in an index. The promise of investment returns to investors is the ‘market return’.

• Other investors may not view risk-free rate as additive in their expected investment return. Rather it is likely to be viewed as an absolute minimum expected return to encourage investment so that it reflects an ‘all or nothing’ parameter. Also in the case of investing in resource companies, a multiple of the risk-free rate is usually a prerequisite for encouraging investment on a stock by stock basis.

The latter point is a subtle one but as outlined in Chapter 4, it means that the risk-free rate can be excluded from modelling the movement in a resource share prices as it will be inherent in a probability weighted value change causing the share price movement.

However, the first point could explain variation in the equity risk premium, which appears to have declined over time.

In the US, Kaplan and Ruback (1995) estimated a mean implied market equity risk premium of 7.78 percent from the inversion of cash flow analysis of a sample of highly leveraged transactions and state that this is comparable to historic arithmetic average market equity risk premia derived elsewhere. Bruce et al (1986) state that data from the Sydney Stock Exchange indicated an average risk premium of 6.5 percent pa to the Commonwealth bond rate was earned during the 1973-1983 period by this market. Officer (1992) stated that for over 100 years the equity risk premium has averaged approximately 8 percent in Australia although around this time there are indications that the premium had reduced.

In the author’s experience over the last 10 years and while working at three

investment banks, market analysts have lowered their equity risk premium from 6 per cent in the early 1990’s to around 4 per cent in the late 1990’s for valuing Australian companies. A 6 per cent equity risk premium was a ‘market standard’ for many years and based on the work of Officer (1992), Warren et al (2000) advised equity research analysts at one investment bank that an equity risk premium of 4 percent was now appropriate with supporting research on estimating historical excess returns as well as the premium implied from current market pricing.

The recent trends in lowering the equity risk premium has been reactionary as NPV valuation methods have failed to correlate with equity prices and analysts have struggled to justify recommendations based on fundamental valuations. Lowering the equity risk premium (as completely moving away from WACC discount rates) has been a partial solution but this thesis will argue that the issue relates to the market focusing on different valuation techniques at different times and NPV valuations become less relevant during bull markets (see Section 1.6.6).

2.2.1.2 Beta and Alpha Indices

Recalling, theβ index is a measure of the sensitivity of a particular share price relative to changes in the return on the market portfolio. It is estimated by using the co-variance of the share return with the return of the market index, standardised (divided) by the variance of the market return, i.e.

= j

β covariance (j,market)/variance (market)

Factors expected to influence the beta of a company include:

• The non-diversifiable (systematic) risk component of a company’s activities, for example, higher risk resource companies versus retailers.

• Gearing. Theoretically, a higher geared company will have a greater beta due to the excess earnings over interest costs in a growing economy and

• Sensitivity of the company’s revenue to the economic or business cycle with a higher beta often reflecting greater earnings leverage to the movement in a cycle.

The beta relationship of a particular share to the market is a fundamental element of the CAPM as it is deemed that the beta index explains the total difference in the returns of a stock relative to the market, i.e. the individual risk premium of a share equals the market premium timesβ . While this ability has been called into question on many occasions (see Rubinstein 2006, Mehrling 2005, Campbell and

Vuolteenaho, 2004; Vuolteenaho 2002; French 2003, Markowitz 1999, Fama and French 1992) it is the relationship between resource stocks and commodity prices that is important to this thesis. The reader will appreciate that β will constantly change given periods when Australian growth doesn’t match world growth and the performance of individual commodity prices doesn’t match the relative performance of the commodity complex as a whole. Hence, this thesis would argue that a constant such as β would be expected to change frequently– perhaps more frequently than traditionally assumed with CAPM.

The lack of accountability for this frequency (and CAPM in general) could be evident in alpha (α) - a coefficient measuring the portion of an investment's return arising from specific (nonmarket) risk. It is distinct from the amount of return caused by volatility, which is measured byβ discussed above. For example, if a stock has aβ of 1.5, it would be expected to gain a maximum of 15 percent when the index gains 10 percent. If, however, the stock actually gains 20 percent, the excess return above 15 percent represents the stock's alpha

(http://www.allbusiness.com/glossaries).

2.2.1.3 Embedded Option Value

One problem with the traditional NPV approach is that many projects contain embedded options. In resource companies this may reflect opportunities to expand existing plant, the potential to discover new resources through future exploration programs and also participate in more favourable commodity prices in the future. Typical NPV corporate valuations of projects are likely to include sensitivity analysis around a base case or use Monte Carlo simulations to highlight this variability.

In M&A activity this embedded option value is evident in the valuation range often provided in Independent Expert’s reports with an upside case assuming a number of positive factors or the occurrence of events not in the low case. However, the presence of operational and other parameters underpinning the low case are necessary to allow the embedded option value to be able to attain the high case.

Before continuing the discussion on embedded or real options, this thesis briefly reviews traditional option theory. As noted in Chapter 1, resource companies offer investors earnings, cash flow and resource/reserve value leverage to volatile

commodity prices, where movements or expectations of imminent movements in the underlying commodity price can lead to enhanced movements in their share prices. On a first assessment, this could been attributed to option value but there are a number of factors that suggest this is not the case and this thesis argues that share price movements relate to probability weighted valuation changes (see Chapter 4) although there is no doubt resource companies have embedded options. In the following discussion, the reader should contemplate whether the market is using a sophisticated option pricing techniques to value, for example, the additional value created by a potential expansion of a plant to a resource company or alternatively, simply the probability weighted value of this occurrence. Empirical observation would indicate the latter and in the author’s experience option pricing is only prevalent in option markets where traders are using option pricing models to derive expected option values.