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Three Forms of Markets Efficiency - Assignment Example

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The paper "Three Forms of Markets Efficiency" is a good example of a marketing assignment. Efficient frontier represents the ideal portfolios that offer the best-expected return for a given risk level. It can also be used to describe the lowest risk for a specified expected return. Consequently, portfolios that fall under the efficient frontier are considered suboptimal since they do not result in enough return for the given risk level…
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Short Answer Questions Date Institutional Affiliation Q1: Efficient frontier Efficient frontier represents the ideal portfolios that offer the best expected return for a given risk level. It can also be used to describe the lowest risk for a specified of expected return. Consequently, portfolios that fall under the efficient frontier are considered suboptimal since they do not result in enough return for the given risk level. at the same time, those that fall to the right of the efficient frontier are also termed as suboptimal since they translate to a higher risk level for the rate of return under consideration (Boubaker, & Sghaier, 2013). Below is a representation of the efficient frontier: Fig: Sketch of efficient frontier Q2: three forms of markets efficiency Weak form The weak form market efficiency is anchored on the history of price sequence. The weak form theory postulates that stock prices are already a reflection of the entire information that could be extracted through the examination of market trading data like the performance of past prices, the volume of trade, or the short interest. In essence, the theory holds that it is not possible to detect mispriced securities in an effort to conquer the market through past price analysis. According to the weak form, changes in the price of stock follow a random walk and are impossible to forecast on the basis of available past stock performances. Therefore, one cannot be able to benefit from the use of information that was known to everyone else (Yadirichukwu & Ogochukwu, 2014). Semi-strong form The semi-strong form holds that the prevailing prices fully takes into account all the information available to the public. In this hypothesis, public information does not only include past prices, but also all the information included in a company’s financial statements, dividend information, declared merger plans, earnings, the performance of other competing businesses etc. The public information is not restricted to financial data. In fact it could include critical data on the company’s quality management and patents held (Rizvi et al., 2014). Strong form The strong form maintains that stock prices actually reflect the totality of information relevant to the company, including information held only by the core players in the operations of the company that have custody of plans and policies. Beyond the semi-strong form of market efficiency, the strong form maintains that no one should benefit from the use of company’s information not available to the public. For instance, the management team should not benefit from inside information by purchasing company shares a few minutes after they resolved to pursue what could be an important acquisition (Rizvi et al., 2014). Q3: Analysis of beta = 1.3 The single index model is also referred to as the market model. The model analyses the portfolio risk of a given investment by considering the sensitivity of the security against the adjustments of the portfolio market return. As … states, the beta value is an indication of the response of the market return according to the changes of security return. It represents the sensitivity of the security return with regard to the changes in the overall market returns. That is, it indicates the level of risk of a given security, when the security is held in a sufficiently diversified portfolio (Mandal, 2013). In an analysis on the performance of several companies during a study, Krueger & Rahbar (1995) found out that those that revealed a beta value less that 0.71 had earned a return that was only 20% lower than those with beta values greater than 1.40. In this study, Krueger & Rahbar (1995) further found that beta had an explanatory power of 0.86, showing that it was not only random that beta and the return showed a positive relationship. From that analysis, it can be postulated that a beta of 1.3 represents a strong performance of the security return compared with the market. Since beta is simply the gradient of the graph of security return against the market return, the value of 1.3 signifies a strong security return performance for the investment compared to the overall performance of the market. Q4. Description of terms in relation to future contracts: Marking to market Once the futures contract has been secured, the changes to the spot exchange rates result in subsequent changes in the price of the these contracts. These adjustments lead to daily losses or gains that are ultimately subtracted from or added to the overall margin account owned by the contract holder. Therefore, through the marking to market process, the value of the assets that are covered by the futures contracts are determined before they are converted. In essence, the marking to market process conveniently brings the futures contract signed on the price of the previous day to a close before opening it once again on the prices of the current day that expires with the day’s settlement price. The process effectively prevents the accumulation of losses beyond the limit to which they can be afforded by the losing party (Chinn & Coibion, 2014). Convergence of price When the date of delivery of a futures contract is still many months into the future, the contract will be trading at a premium compared to the spot price of the commodity in question on the delivery date. As time passes and the delivery date gets closer, the price of the contract will continue to depreciate in value and in the ideal case, its value will be the same as that of the spot price on the delivery date. Convergence is said to occur when the price of a future contract shifts towards the spot price of the cash commodity in question as the delivery date comes closer (Garcia, Irwin, & Smith, 2015). Basis risk This is the financial risk that an offsetting investment in a hedging strategy is not likely to experience changes in price in an entirely opposing manner compared to other investments. The imperfection in the correlation of the two investments leads to the likelihood of an profit or loss in a hedging strategy thereby increasing the risk of the position. Question 5 The standard deviation directly affects the required rate of return since the higher the standard deviation implies that there is a higher likelihood that the return is not going to be expected, and this makes the portfolio riskier and hence the company should change their investment. On the other hand, the CAPM is market risk and not individual risk and indicates the correlation between the projected return and risk (Pamane & Vikpossi, 2014). Below is the CAPM equation. This equation indicates the correlation between the return and risk. Sensitivity of the stock to the market is measured using beta. Therefore, the required rate of return on a stock has correlation to the requisite rate of return on the stock market through beta. If we assume that the beta of the company is constant, the rise in the risk of the market is likely to increase the requisite rate of return on the market and hence elevate the requisite rate of return for the company (Pamane & Vikpossi, 2014). References Boubaker, H., & Sghaier, N. (2013). Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach. Journal of Banking & Finance, 37(2), 361-377. Chinn, M. D., & Coibion, O. (2014). The predictive content of commodity futures. Journal of Futures Markets, 34(7), 607-636. Garcia, P., Irwin, S. H., & Smith, A. (2015). Futures market failure?. American Journal of Agricultural Economics, 97(1), 40-64. Krueger, T.M. & Rahbar, M.H. (1995). Explanation of industry returns using the Variable beta model and lagged variable beta model. Journal Of Financial And Strategic Decisions, 8(2): 35 – 45 Mandal, N. (2013). Sharpe’s single index model and its application to construct optimal portfolio: an empirical study. Great Lakes Herald, 7(1): 1 – 60 Rizvi, S. A. R., Dewandaru, G., Bacha, O. I., & Masih, M. (2014). An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA. Physica A: Statistical Mechanics and its Applications, 407, 86-99. Yadirichukwu, E. & Ogochukwu, O.J. (2014). Evaluation of the weak form of efficient market hypothesis: Empirical evidence from Nigeria. International Journal of Development and Sustainability, 3(5): 1199 – 1244 Pamane K & Vikpossi E. (2014). An Analysis of the Relationship between Risk and Expected Return in the BRVM Stock Exchange: Test of the CAPM. Research in World Economy. Vol. 5, No. 1, pp:13-28. Read More
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