Accounting Dissertations – Accounting Finance Risk
Financial theory describes risk assessment as one of the most important part in an investment decision making process. However, for a risk to be known, it is important for investors to interpret information flowing on the market. This study aims to examine the association between accounting information and the market risk over time. It also evaluates how far the beta value and accounting variables can be useful for investors in Mauritius.
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Beta estimates are calculated using Capital asset pricing model and accounting risk variables are derived from theoretical foundations and prior empirical findings. The relationship between the financial ratios and the level of systematic risk is obtained by regressing the variation in the beta against changes in the accounting variable.
The empirical evidence shows that beta is valid on the Stock Exchange of Mauritius (SEM). However, the power of beta is relatively low in capturing the systematic risk. This finding is in line with Campbell (1995) who obtained similar observation for emerging equity market and with Bundoo (2000) who noted same result. Finally the result shows that a strong association exist between accounting variables and market risk and it also observed that this relationship is consistent over time. Accounting variables like growth rate, debt ratio, asset size, liquidity, profit margin and accounting beta are able to capture market risk where beta generally provides a high explanatory power of systematic risk. The findings contradict the some of the association between the market risk measures and accounting risk measure obtained Beaver et al (1979).
- 1 1 Introduction
- 2 1.1 Problem Statement
- 3 1.2 Aims and objectives
- 4 1.3 Organisation of this paper
- 5 2 Literature review
- 6 2.1 Risk
- 7 2.1.1 Systematic and unsystematic risks
- 8 2.2 The Capital asset pricing model
- 9 2.2.1 Empirical review of Capital asset pricing model
- 10 2.2.2 Critics against Capital asset pricing model
- 11 2.2.3 The ongoing debate on the applicability of Capital asset pricing model
- 12 2.3 Accounting variables as a measure of systematic risk
- 13 2.3.1 Usefulness of accounting variables
- 14 2.3.2 Theoretical and empirical review of the relationship between individual accounting variable and systematic risk.
- 15 Dividend Payout
- 16 Growth rate
- 17 Asset Size
- 18 Accounting beta
- 19 Earning Variance
- 20 Profit Margin
- 21 Leverage ratio
- 22 Liquidity ratio
- 23 Interest Cover Ratio
- 24 2.3.3 Empirical review on the association between accounting risk variable and systematic risk
- 25 2.4 Stock Exchange of Mauritius- Empirical review
- 26 3 Research Methodology
- 27 3.1 Population and Sampling
- 28 3.2 Methodology
- 29 3.2.1 Market Measure of Systematic Risk
- 30 188.8.131.52 Return of Individual Securities
- 31 184.108.40.206 Market Return
- 32 220.127.116.11 Risk Free Rate.
- 33 (3.3)
- 34 3.2.2 Accounting measures of systematic risk
- 35 3.3 Expected outcome
- 36 3.4 Statistical Software Used
- 37 4 Data analysis and findings
- 38 4.1 Return on the Stock Exchange of Mauritius
- 39 4.2 Return of the SEM-7
- 40 4.3 Systematic Risk
- 41 4.3.1 Reliability of beta
- 42 4.3.2 Beta of the Listed Companies
- 43 4.4 Association between the Systematic Risk and Accounting variable
- 44 4.4.1 Relationship over different time interval
- 45 Table 4.6: The association over different time interval
- 46 4.4.2 Association between the Systematic Risk and Accounting variable
- 47 Table 4.7: The association between systematic risk and accounting risk variables
- 48 Accounting Variable
- 49 18.104.22.168 Significant accounting variables
- 50 22.214.171.124 Non significant accounting variables
- 51 5 Conclusion
The growth experienced in the Stock Exchange of Mauritius (SEM) during the years 1989 to 2007 was with no precedence. Stock prices of quoted companies on the SEM boomed, causing a high influx of capital which caused the market to rise to its peak with a net market capitalisation of MUR 173 billion in the end of the financial year 2007. Local investors who had investments in fixed deposits from local commercial banks shifted some of their investments to the SEM, with view of higher return. But Stock prices started to fall soon after the end of the month of February 2008 and within a year the SEMDEX reached a position which was a low as the values experienced in September 2006.
While this fall was largely attributed to the morose international situation, as a result of the international financial crisis; there is also the question whether the SEM effectively capture risk which is inherent by companies quoted and how far investors in Mauritius used the publish financial information to evaluate and predict the level of risk in the operating environment.
Financial markets serve a key purpose in an economy by allocating productive resources among various areas so as to enable an efficient resource allocation, across different firms, investors assess the security and market expected prospects and risks and form a portfolio of investments based on their assessment. Security analysis usually involves an evaluation of the financial position and performance obtained from the financial statements published periodically by companies. In an efficient financial market the share prices is expected change to the fair value of the firm as new information flows into the market.
Financial theory describes risk assessment as one of the most important part in an investment decision making process. The return of a stock is often considered to be narrowly related with the risk which the investor is taking while holding that stock. This makes the generally accepted principle that the higher is the risk in investing in an asset, the higher should be the asset’s expected return. This implies that there is a positive correlation between risk and expected return in holding a stock.
1.1 Problem Statement
The analysis of stocks return is intricately linked with the analysis of risk. Empirical studies carried by Graham et al (2001) has shown that the Capital Asset Pricing Model (CAPM), (an asset pricing tool which uses risk as a basis to calculate assets return) is used, by more than seventy five percent of the chief financial officers, as primary tools in the portfolio selection process. However some authors in the capital markets literature (Campbell (1995) and Chan et al (1991)) have argued that in the case of emerging stock exchanges the CAPM is inapplicable and beta is not significant.
However, for a risk to be known, it is important for investors to interpret information flowing to the market. Fama (1963) described three generic forms of market efficiency based on the market reaction to inflow of information. Markets which react to all past information are said to be in its weak form, those markets which react to all past and publicly available information are referred to as semi-strong efficient markets and those which react to all past, public and private information are considered as strongly efficient markets. A study made by Bundoo (2008) showed that Stock Exchange of Mauritius (SEM) has the characteristics of a market in its weak form. This implies that the SEM effectively responds to past information. Yet there is absence of empirical research which evaluates whether market return and risk are effectively pictured through accounting ratios.
1.2 Aims and objectives
This paper aims at analysing the share prices in the SEM and key accounting ratios to evaluate the financial position, performance of a sample of companies quoted across various economic sectors of the SEM with the view of answering the above question. It also seeks to test whether investors can trust beta in their decision-making process on the SEM.
The paper also aims at:
understanding the relationship between the financial ratios, market return and risk; estimating the level of systematic for different business segment where financial market information is not available; and to guide investment in measuring the systematic in private and non listed companies in Mauritius.
1.3 Organisation of this paper
The paper is organised as follows: Chapter 2 provides a summary of literatures concerning risk measures, accounting tools and market-based models to measure the performance and risk; It also surveys the empirical researches on the SEM and similar markets; Chapter 3 develops the models which are to be used in the analysis of the relationship between systematic risk and accounting ratios; It also outline the methodology and sample data which is used in the analysis; Chapter 4 presents the key findings from the study and Chapter 5 concludes the paper.
2 Literature review
Risk and return of a firm are the two most important factors in the development of financial strategy for both individual investors and firms. Risk is inherently multi-dimensional and as such it has multiple characteristics which may be classified as financial and non financial. These characteristics make up the risk profile of a security, which is generally observed as changing with time and at different levels of a market. These changes in turn, impact on the return of the investors either by creating value or destroying the initial value before the investment.
Modern financial theories have proposed different models which are founded on sound theoretical analysis which can be used to estimate the different degree of riskiness of a particular security. These risk measures are then used in valuation models to estimate the return which an investor, with a defined risk attitude, can expect from an investment. As described in chapter 1, above, the applicability of such financial theories remain untested in many emerging markets.
This chapter reviews the financial models which are commonly used by practitioners for estimating of the risk of stocks and stock market and their corresponding returns. It also summarises the main financial ratios which are used to analyse the financial risk, financial performance and the value of the firm. Finally a summary of the accounting tools and market-based models to measure return is also presented.
It has always been difficult for practitioners to reach a consensus on the definition of risk. Moles (2004), nevertheless, provides a simple definition which is taken in this paper as basis for risk measurement. He defines risk as “the chance (or probability) of a deviation from an anticipated outcome”. With this definition it is implied that risk is made up of at least these 3 elements:
1. probability: which means that risk can be quantified and expressed as a parameter, number of value;
2. deviation from anticipated outcome: which is extent to which the actual result may deviate from that which is expected;
3. anticipated outcome: this means that it is the consequence of the actual results deviating from the expected results that leads to risk. Newbold et al (2003) states that probability can be measured using past data by considering the proportion of times that an event occurred. For the case of an investor the anticipated event would be the financial return which he or she can expect by holding an asset. The measurement of the deviation from the anticipated return is normally done using the standard deviation of returns generated by an asset with regard to the expected return.
2.1.1 Systematic and unsystematic risks
The deviation from the anticipated return is caused by is explained by 2 levels of risk: systematic risk and unsystematic risk. The sum of these two main categories of risk is the total risk to which an investor is exposed to.
Systematic risk is associated with overall movements in the general market or economy and therefore is often referred to as the market risk. The market risk is the component of the total risk that cannot be eliminated through portfolio diversification.
Unsystematic risk which is a component of the portfolio risk that can be eliminated by increasing the portfolio size, the reason being that risks that are specific to an individual security such as business or financial risk can be eliminated by constructing a well-diversified portfolio.
2.2 The Capital asset pricing model
Markowitz (1952) constructed a mean-variance model to observe the trade-off between risks and return. The model mathematically proved that return can be maximised, while minimising the overall risk, by holding a diversified portfolio. The idea was based on the concept that securities that are inversely correlated or having coefficients which are less than one. Such negative or low correlation coefficient results in a low covariance between securities in the portfolio. The low covariance implies a comparatively low level risk. However, Sing et al, (2001) observed that the model ignore the general risk-averse attitude of most investors.
The Capital Asset Pricing Model (CAPM), developed by Sharpe (1964), is based on the framework set out by Markowitz (1952) which considers that investors invest their money in a portfolio of assets. The CAPM states that the return which a risk averse can expect from investing in a risky asset is a risk premium over the risk free rate. The formula 1 below states the formula which can be used to calculate the expected return.
E(Ri) = Rf + i ( E(Rm) – Rf ) (2.1)
E(Ri) – expected rate return of stock I;
i – relative risk of share I;
E(Rm) – expected rate return of the market portfolio; and
Rf – risk-free interest rate.
Sharpe (1964) and Lintner (1965) explained that the correct measure of risk of an asset is its beta factor, a standardised measure of the systematic risk and that the risk premium per unit of riskiness is the same across all assets.
CAPM has been developed by considering some assumptions such as normal distribution of assets return, perfect divisibility of assets and return, the existence of a risk free rate, perfect market conditions, inter alia, which might not exist in the real world. Despite the fact that most of the above assumptions are neither valid nor fulfilled, the CAPM has become an important tool in finance. It is widely used by finance practitioners for assessment of cost of capital, portfolio performance, portfolio diversification, valuing investments and choosing portfolio strategy among others.
The β factor in the equation 2.1 measures the volatility of the specific asset with regard to the volatility in the market, that is, the market risk. Mathematically it is expressed as in equation 2, below:
systematic_riskasset = covariance of the asset and that of the market
market_risk is the volatility in the market portfolio, it is measured by the standard deviation of prices of the market portfolio.