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Arbitrage Pricing Theory (APT) is a multi-factor model which offers greater breadth than CAPM and is further discussed in Chapter 4. Reilly (1985) states that the APT contends that the expected return of an asset can be modelled as a linear function of a number of factors which are deemed to influence share price returns. Each factor has a specific beta-coefficient. He notes that arbitrage pricing theory has three main assumptions:

1. Capital markets are perfectly competitive; including the ability of investors to short sell shares (Peirson et al, 1990)

2. Investors always prefer more wealth to less wealth with certainty (risk aversion described earlier)

3. The stochastic process generating asset returns can be represented as a K factor model.

The K factor model is of the form:

.... + + + + +

= r epsgrowth management oilprice

R_i α_i β _m γ δ ξ

Where =

i

R the return on asset i during a specified time period

i

α = a constant, specific to asset i =

m

r

β expected returns based on the sensitivity of changes in the share price to changes in the market.

These are followed by a series of factors which are deemed to influence the share price, for example γepsgrowth, where γ quantifies changes in the share price to

changes in earnings per share (eps) growth such that if γ =0.6and eps growth accelerates by 10 per cent, then the share price would be expected to rise by 6 per cent. Factors included in this equation are typically focussed on broad economic variables such as industrial production, oil prices, inflation and wage growth but can include company specific factors.

The arbitrage concept applies in the sense that if the price of the asset is not in line with the model estimate at the end of a specific period, then arbitrage opportunities will bring the share price back into line with the model forecast.

Peirson et al (1990) presents the theory in its simplest case where the return on a particular security, i, can be described by the abbreviated equation.

i i i i F F e R =α +β ( − )+ Where i

α = a constant, specific to asset i

i

β = a measure of the ‘sensitivity’ of returns on asset i to ‘factor’ F

F = a risk ‘factor’ which explains returns

F= the expected value of F

i

e = an error term which has an expected value of zero and is specific to asset i

In this case using the risk ‘factor’ as F, the equation specifies that unanticipated variations in F will cause returns to change. If, as ‘expected’ F = Fand = 0 then

=

i

e

i

R α_i. Therefore α_i is the expected return on asset i. Importantly, it is changes in

F from expectations that lead to a change in expected returns. In terms of , Roll and Ross (1980) describe this as a noise term, i.e., an unsystematic risk component idiosyncratic to the i asset. It is assumed to reflect the random influence of

information that is unrelated to other assets.

i

e

ik k i i i R =λ₀ +λ₁β₁ +λ₂β₂ +....+λ β Where = i

R expected return on asset i =

0

λ the expected return on an asset with zero systematic risk; can be inferred as risk free rate

= j

λ the risk premium for the jth factor; j=1,….k

= ij

β assets i’s sensitivity measure for the jth risk factor; j=1,….k

Roll and Ross (1980) believe APT offers a testable alternative to CAPM while Peirson et al (1990) note that the CAPM equation is really a special case of a single factor arbitrage pricing equation, the factor being the returns on the market portfolio. Nevertheless, this thesis would concur that APT offers a higher degree of

sophistication which is more likely to cope with share price behaviour than CAPM and its single comparison to market portfolio returns.

Lastly, value-at-risk (VaR) is a category of risk metrics (c.f. risk measure which is the process to estimate a risk metric) that describes probabilistically the market risk of a trading portfolio (www.riskglossary.com). This incorporates assessing

probability distributions for various influences on a portfolio and is akin to a modified version of arbitrage pricing theory. The use of VaR has increased dramatically and applied to a broad range of assets, for example, BHP Billiton’s operating cash flow at risk (McCarthy, 2006) to investment bank currency trading positions or derivatives. This thesis views a probabilistic approach to share

valuations and subsequent movements in share prices as a logical explanation based on empiricism and analysis outlined later in this thesis.

2.3 Efficient Market Hypothesis – Aspects and Phenomena

Research on the performance of bidders and targets in mergers and acquisitions are discussed later in this Chapter (see Section 2.7.4) but generally fall into two

categories (Brailsford and Knights, 1998). The first category of studies deals with an examination of the effects of takeovers on share prices. The standard test involves the application of event study methodology which estimates the risk-adjusted

abnormal returns on ordinary equity shares before and after the takeover event. The second category of studies focus on changes in reported accounting numbers following a takeover and profitability ratios are often analysed.

Brailsford and Knights, (1998) note that the arguments for the use of share prices stem from an underlying assumption about market efficiency and in a competitive market, prices should reflect an unbiased consensus about the value of information. The market efficiency cited is informational efficiency and forms the basis for the Efficient Market Hypothesis (EMH). The EMH states that asset prices in financial markets should reflect all available information; as a consequence, prices should always be consistent with ‘fundamentals’ (Beechey et al, 2000).

This section reviews the broad concepts of informational efficiency as its concepts are applicable in the analysis of share price movements and to special circumstances such as post announcement drift and price bubbles which are important to aspects of this research. Critics of EMH cite these circumstances as reflecting aspects of behavioural economics or behaviour finance with some justification although the shortcomings of the EMH are sometimes interpreted as simply misinterpretations of the model itself (Beechey et al, 2000).

2.3.1 Informational Efficiency

While Copeland et al, (1996) view market efficiency as equivalent to informational efficiency; in essence it is the assumption of an immediate response of the market to incorporate all relevant and publicly available information into a company’s share price. The implications as outlined by Peirson et al, (1990) are that share prices ‘fully reflect’ all available information and hence, implies that ‘mispricing’ opportunities are not available to investors. Indeed, the Securities Institute of Australia (1998) comments that a significant task of a security analyst/portfolio manager is trying to forecast the events that might cause latent ‘value’ to be crystallised in a company’s share price (events it describes as ‘catalysts for value’) but then EMH is theoretically expected to incorporate a probability weighted value for these outcomes.

Peirson et al (1990) comment that there are logistical constraints to the dissemination information in the market and not all investors will simultaneously hear the latest

news which may be material to a company’s share price. This can lead to the creation of excess returns as well as by trading market over-reaction and under-reaction biased price reactions to new information. Both these cases highlight that

information impounding into share prices may not be immediate as hypothesised by the EMH.

Fama (1970) classified informational market efficiency into three forms which reflect available sources of information:

1. Weak form efficiency. This implies that the information contained in the past sequence of prices of a security is fully reflected in the current market price of that security;

2. Semi-strong form efficiency. This implies that all publicly available information is fully reflected in a security’s current market price;

3. Strong form efficiency. This implies that all information, whether public or private, is fully reflected in a security’s current market price.

Weak form is consistent with the Markov property of stock pricing discussed earlier (Hull 2008) while each successive form is cumulative with weak form efficiency implicit in semi-strong efficiency and so forth. Peirson et al (1990) state that an implication of strong form efficiency is that an investor cannot earn abnormal returns from having inside information. Hence, strong-form efficiency is unlikely to be widespread although there is ample evidence that it is lacking in the resources sector where increased trading volumes occur in the days leading to a material

announcement by a company. Nevertheless most research is directed at supporting or discrediting EMH at a semi-strong efficiency level.

Semi-strong-form market efficiency requires that security prices adjust instantaneously and without bias to the public announcement of information.

Therefore abnormal returns should not be received from a subsequent analysis of this information and tests of the semi-strong form of the EMH analyse whether there are any post-announcement abnormal returns associated with the public release of information (Peirson et al, 1990). These tests can be part of event studies as discussed later in Section 2.3.2.

Beechey et al, (2000) have reviewed a considerable amount of empirical research devoted to testing whether financial markets are efficient under the predictions of the EMH. Table 7 summarises some EMH predictions and the empirical evidence relating to each prediction from their selective survey.

Table 7. Predictions of the Efficient Market Hypothesis.

From Beechey et al, (2000)

As expected, Table 7 highlights mixed levels of support. There are also other areas where potential post-announcement abnormal returns or beta adjustments used to explain share price returns are called into question. These include post-

announcement drift, price bubbles, the size effect or small-firm effect and the dividend-yield effect discussed in the next sections.

Empirical evidence from the author’s experience supports the contention that it is information that is ‘not yet in the market’ that will instigate investment or divestment

by certain portfolio managers, particularly in North America. Therefore the assumption that information is factored in the market implies that all facets of that information are ‘factored’ into the share price immediately following the

announcement. In fact there are observable situations when material company

announcements that would normally affect a companies share price are released after market one day (particularly on a Friday) and while the share price has not moved, investors reading the announcement on the following day do not invest as there is an assumption that the new information is indeed already factored into the share price. The question is whether this financial behaviour creates a self-fulfilling relationship in line with the EMH.

While there is certainly empirical evidence that supports EMH, there are many cases in the author’s experience where it is not supported. These fall into three categories:

• The logistical time for information to disseminate across market participants is certainly not instantaneous and depends on a variety of factors including the importance of the company within the market, the attention directed to it by market participants, additional media used for dissemination, timing of announcement, etc.

• Certain information is complex and may take hours or days to determine a valuation impact and the timeframe for this analysis is likely to be variable. • Historically many portfolio managers in Australia will invest at least one day

after an announcement given the time required for the sector analyst to present the recommendation to an investment committee seeking investment approval.

Overall, the concept of a share price rapidly moving towards a price that reflects additional value emerging from an announcement is not unrealistic. However, it is unrealistic to assume that the full value of every announcement is always

‘impounded’ instantaneously in the share price at the time of the announcement. Interestingly, Roll (1986) believes his hubris hypothesis whereby management in bidding companies pay too much in mergers and takeovers is consistent with strong- form market efficiency while in the Australian context and around that time, Walter (1984) found evidence in Australian takeovers for semi-strong efficiency.