Efficient Market Hypothesis - Case Study Example

Trying to make superior trading returns using technical analysis or fundamental analysis of shares is self-defeating Introduction Efficient Market Hypothesis (EMH) holds that stocks or shares trade at their fair value thus preventing buyers and sellers from gaining unduly from market inefficiency. In other words since the market functions efficiently investors cannot buy undervalued shares or sell overvalued shares. Thus if any investor desires to earn higher returns he has to buy much riskier shares or bonds. Ordinary shares carry then least amount of risk and therefore the least amount of return. However investors are using technical analysis and fundamental analysis when they are taking their investment decisions to gain trade returns. In fact investors can predict the future stock prices, based on the past stock prices and even by analyzing financial information such as company earnings and asset values. This paper would examine the relationship between EMH and the future predictions of stock prices based on technical and fundamental analysis. When stocks rose by high percentages the analysts could say that it was due to the efficacy of stock markets and therefore the positive rally reflected the true performance of the company. Efficient markets do exist in theory (Dobbins, & Witt, 1979). For example according to financial theory there are efficient stock markets that especially don't permit market manipulation by investors. However the practical scenario negates this proposition very often. For instance the rally of the stock could be attributed partially to the equity issue and not to the efficiency of the markets. Analysis According to many financial economists that future stock/share prices are partially predictable on the basis of past stock price patterns as well as some fundamental valuation metrics. Further economists pointed that these predictable patterns lead investors to earn excess returns with reference to excess risk adjusted rates. The following three problems explain why excessive reliance on fundamental financial analysis isn't going to benefit the investor or shareholder. (a). Asset substitution problem As and when debt to equity ratio increases investors tend to substitute new assets through new investment thus relatively increasing debt in place of equity. Assuming that investing is riskier, there is still a fairer chance of success against failure thus obliging both debt-holders and share holders to condone such risky investment decisions on the part of management (Campbell, 1987). Successful investments on shares lead to cumulative share holder benefits while unsuccessful ones lead to cumulative debt-holder woes. (b). Underinvestment problem Investors would not hesitate to reject investment in shares with positive Net Present Value (NPV) because they would not be bothered to increase the value of the firm any more than to allow the accrual of benefits associated with riskier debt to debt-holders themselves rather than to share holders. (c). Free cash flow problem Finally there is the problem of free cash flow. In the absence of free cash flow benefits accruing to investors, the management has a tendency to reduce the value of the firm through prodigal behavior, such as granting bonuses and higher salaries. Therefore higher levels of leverage would act as a preventive factor of such behavior and ensure discipline. 2. Overall analysis Next there is the problem of taxes. When corporate taxes are considered the firm is entitled to interest expense deduction which enables it to increase value of its assets. According to Modigliani and Miller (1963) the tax exemption allows the firm to reduce the leverage-based premium in the cost associated with raising the equity capital. Subsequently Miller added personal taxes to the equation. Some authors go a long way to discuss the most efficient ways in managing systematic risk, unsystematic risk and total risk and include a reference to "financial regulatory mechanisms, responsibility in the decision making structure and the chain of command and legitimacy". Regulatory regimes seeking to control financial markets are little too stringent at times though, regulators themselves do not feel that such 'strictness' is out of place. Financial stability is sought to be ensured through regulatory measures in the interest of the general public. Systematic risk is defined as holistic risk affecting the entire portfolio of assets across all segments of the market. In other words risk is more likely to spread through the whole financial system or the market thus causing a total collapse. In fact the ripple effects would be felt beyond the national borders of the country as well. Such systemic instability in the entire financial system cannot be overcome with specific small solutions. Thus there is a universal characteristic associated with this kind of risk. In the first place systematic risk cannot be avoided through diversification strategy. Diversification allows risk to be spread over a number of assets in the portfolio across a number of markets, thus attenuating the risk factor. However there is abatement or mitigation of systematic risk through hedging. Individual investment decisions concerning risk mitigation are inevitably focused on the capital adequacy rules. Concurrent decisions to mitigate risk and maintain capital adequacy are nothing new in the investment sphere. Sharpe ratio is used to calculate the amount of systematic risk: Here the performance evaluation is based on risk-adjusted measures. Now the question "is the return adequate compensation for the risk'" has to be answered by working out the returns given the risk involved. The following explanations are used to work it out. The Sharpe ratio enables the adjustment of returns on investments to be conclusive with respect to risk-free returns and the degree of volatility of an investment. Rp = Average return on the portfolio Rf = Average risk free rate Sp = Standard deviation of portfolio return (total risk). While Sharpe ratio is useful in determining adjusted risk and performance of a portfolio, there are other measures as well that have to be used in order to determine the level of risk accurately. Treynor ratio: rp = Average return on the portfolio rf = Average risk free rate 'p = Beta of portfolio (systematic risk) Treynor ratio is used to measure returns that are in excess of what could have been made on risk-free investment. For example Treasury Bills are less risky than other volatility-prone assets. That's why it's sometimes called reward-to-volatility ratio. It uses systematic risk. Thus higher the Treynor ratio, the higher the returns made on investments. However it is not like Sharpe ratio which is a measure of the excess return and does not help much. Next there is the Jensen's Alpha, a measure that calculates the excess returns above the security market line as done in the capital asset pricing model (CAPM). CAPM also uses beta as a multiplier to determine the total value of returns. Jensen's Alpha is a risk adjusted portfolio performance metric. It's calculated by using a regression technique to determine the performance of a given portfolio of a manager tested against a benchmark. On the other hand unsystematic (un-systemic) risk refers to a risk inherent in a particular industry or market that falters due to a specifically divergent variable. Unsystematic risk (or residual risk or diversifiable risk) can be overcome by resorting to diversification of one's portfolio (Lo, 2005). Since unsystematic risk is specific to a particular market or market segment, diversification helps investors either to reduce risk or totally cancel out depending on the relative offsetting effect of less risky investments. Unsystematic risk essentially presupposes the existence of a remedial measure without resorting to hedging which can be uncertain for a number of reasons. In the first place hedging is carried out with the intention of obviating systematic risk which occurs as the result of an exogenous variable going astray. In the case of unsystematic risk exogenous variables are assumed to behave in the predictable way (Lehmann, 1990). Thus forecasts are reliable to the extent that the individual potential investor does not feel the need to shuffle the basket of investments. Fund managers whose instincts the investor relies on, do not feel obliged to advice clients on the contrary decisions. In fact such advice depends not only the instincts of fund managers but also statistical forecasts. As the portfolio is more diversified unsystematic risk moves closer to zero. Accounting risk, financial risk and economic risk are all part and parcel of unsystematic risk. They signify the very nature of risk. For instance a financial risk might involve mistakes in cash flow forecasts thus leading to liquidity problems. These residual risks do not have a big impact on the whole system. The systemic imperviousness stands out as the most credible security against risk. But nevertheless the degree of this imperviousness is determined by a number of other factors that are inherent to the system itself. Calculations involve the same process as above. However, CAPM is often used to measure an individual security or a portfolio. Additionally the security market line (SML) is used to measure the reward-to-risk ratio of a security in relation to the total market as shown below. Finally total risk is the sum total of systematic risk and unsystematic risk. While the choice of the individual investor between different types of securities or investment instruments matters here, there is the need for the investor to make some decisive decisions involving which risk out of systematic and unsystematic risks to be reduced vis-'-vis the other. The following graph illustrates the hypothetical scenario of a company which invests in a given portfolio of securities. The red line is the Security Market Line. the horizontal axis shows the betas of all companies in the market the vertical axis shows the required rates of return, as a percentage Assuming that the risk free rate is 5%, and the overall stock market will produce a rate of return of 12.5% next year the following would give a clearer picture of fundamental financial ratio analysis. The imaginary investor/shareholder/company has a beta of 1.7. This result is obtained by substituting a few sample betas into the CAPM equation as follows. Ks = Krf + B (Km - Krf). Security Beta (It's a measure of risk) Rate of Return 'Risk Free' 0.0 5.00% Overall Stock Market 1.0 12.50% Utopia Company 1.7 17.75% Source: www.teachmefinance.com This figure and hypothetical data can be applied to understand all three types of risks. Conclusion In the conclusion it must be noted that technical and fundamental analysis of shares with reference to EMH might change the final outcomes such as trade returns to a greater extent. Assuming a constant rise in the rate of inflation, it would benefit from cumulative growth in share value if the current forecasts were to remain steady. However even if the current forecasts were a little out of line, there would still be a steady cash flow return because an opportunity cost per annum ensures a considerable setting off of risk associated with such unforeseeable outcomes. Despite financial market volatility investments and cash flow forecasts perform predictably well in accordance with agents' behaviour and sentiments. Thus there is a highly plausible scenario of positive financial outcomes (Fama, & Blume, 1966). Finally the decision to invest in shares based on EMH would have a positive impact on company finances depending on the cash flow variances. Continuous positive variances would enhance the company financial performance over the period under consideration, assuming other variables such as external debt remains constant over the period. REFERENCES 01. Campbell, JY 1987, 'Stock Returns and the Term Structure', Journal of Financial Economics, vol. 18, pp. 373-400. 02. Dobbins, R & Witt, SF 1979, 'Some Implications of the Efficient Market Hypothesis', Managerial Finance, vol. 5, no. 1, pp. 65 - 79. 03. Fama, EF & Blume, ME 1966, 'Filter Rules and Stock Market Trading', Journal of Business', vol. 39, pp. 226-41. 04. Farmer, D & Lo, A 1999, 'Frontiers of finance: evolution and efficient markets', Proceedings of the National Academy of Sciences, vol. 96, pp.9991-2. 04. Lehmann, B 1990, 'Fads, martingales, and market efficiency', Quarterly Journal of Economics, vol .105, pp. 1-28. 05. Lo, A 2005, 'Reconciling efficient markets with behavioral finance: the adaptive markets hypothesis', Journal of Investment Consulting, vol.7, pp.21-44. Read More