Predictability of Excess Stock Returns - Coursework Example

EVALUATE THE EMPIRICAL EVIDENCE ON THE PREDICTABILITY OF EXCESS STOCK RETURNS USING TECHNICAL ANALYSIS Name University Name City, State Date of Submission Evaluate the Empirical Evidence on the Predictability of Excess Stock Returns Using Technical Analysis Part A Thoroughly evaluate the empirical evidence on the predictability of excess stock returns using technical analysis The stock market has enormous return abilities. It also has huge risks that may lead to losses. The development of the market and the application of different means of analysis provide an investor with options on the market and ideas on the market effects of different actions of the stakeholders of the stock especially the management to provide a picture of the results the stock posts. The analysis of a stock involves use of predictions to estimate the possible direction of stock using publically available information on a counter. Through these, technical analysis may reveal factors that would help the predictions further predict closer to the performance. There exist two means of evaluating a stock to make investment decisions. These include fundamental analysis and technical analysis. Fundamental analysis deals with studying the company in details and making the characteristics that make its value identified for decision-making. Technical analysis on the other hand looks at the factors of supply and demand. Technical analysis considers the application of the study on the market factors of the company, their effects on the price and factors of demand and supply. Technicians pay attention to the prices of the market and make predictions based on their understanding of the effect that information may have on the stock. They depend on the market efficiency hypothesis in making their decisions. To obtain a full view of market inefficiency, one needs to obtain returns over a long span to evaluate a company’s performance since stock prices changes slowly as per information provided (Fama, 1997, p.284). The changes sometimes close to zero providing no effect unless huge funds are invested in the counter to provide the power of quantity. The market of technical analysis depends on the market anomalies though may not provide a good picture of the actual market position. The use of information to determine the ability of the stock to provide massive returns to the investors is tricky and may at times provide misleading information to the investors. The use of a different approach to technical analysis that considers the studying of the model that describes the cash flows of the firm discounted by pricing aspects may deliver a positive correlation between the current returns expected and the past returns that the firm made (Johnson, 2002, p.585). Understanding this and applying it in the analysis to top up on the market and price study of the technical analysts would provide confident answers to predicting a stock’s performance hence massive returns for the investors. Considering recent growth changes in the firm would also provide a good place to predict performance. Firms with a positive growth rate always feature in the good performers while those whose growth rate is negative feature in firms that perform poorly. The lack of this information would lead to the use of other information available that may include growth rate levels and end of period expected returns. Most people that employ technical analysis are market speculators that only wait for a small piece of information to affect the stock and they pump in large sums of money to rip huge returns. Using the above, the technical analysts may make good predictions on the changes in the prices of the stock and gain millions from it. These huge returns come with a huge risk that may affect the investors. A company with a poor value normally referred to as a shell may influence the stock market based on demand and supply hence attracting experienced speculators. In such a case, they pump huge money into the stock mop up the supply and create a picture of demand through limited supply. These are held for some time and when any good information that may affect the price coupled with the demand appears, it adds to their benefits and they makes sells at good prices. In such a scenario, excess profits materialize. These continue until the demand is saturated again and the stock is in many hands that the prices fall again. Here the price will remain low and crafty speculators get into the market again to mop up the stock balances. The trend continues until the company management restructures well enough to introduce fundamentals that will make the stock valuable to many and hence stabilizing the stock movement. At this point, the real long-term investors come in to buy more shares and the company’s performance pushes the stock price further up. Efficient market hypothesis (EMH) indicates to a market in which the stock market reads overreaction and overconfidence of the stock investors. The EMH bases on assumptions that capital markets prove efficient and information about a stock spreads quickly affecting is price (Malkiel, 2011, p.59). The author further suggests that price changes within the stock market at times may reflect a “random walk” that many financial analysts indicate to mean normal price changes. The market self-correcting belief rate among the factors that contributed to the financial crisis based on the readings on EMH. The presence of a perfectly efficient market is impossible based on the fact that the stock prices may not reflect all the information available about the stock. Many technical analysts base more on the stock prices due to their simplicity to use and have led to numerous research involvements in measuring market efficiency. A number of tests have featured that help people apply in measuring the returns of a stock and making predictions. These include the automatic variance ratio test, automatic portmanteau test, a generalized spectral test, and test statistics that aid in measuring the degree of return predictability that a stock indicates (Kim, Shamsuddin & Lim, 2011, p.871). Applying any of these provides a reasonable framework that technical analysts may employ to predict successfully excess stock returns. Technical analysis has the ability to help investors rip huge returns from the stock market if applied well but also leads to much work and constant study of the stock price shifts, demand and supply factors that may not prove easy. Application of fundamental analysis provides better confidence in investors and aids those interested in investing long term in a counter. Part B Critically evaluate whether return predictability is a good test of market efficiency. Return predictability is not a good test of market efficiency. Markets may prove efficient to stocks or inefficient based on the way the analysts look at them. Returns predictability as used by many analysts to advice investors looks at what would affect the prices and lead to a better change that will result into returns rather than considering the factors that measure the efficiency of the market. The technical analysts look at the momentum of the stock that reflects on the previous returns and the future returns guiding investors based on such information. Though these may lead to massive returns, they may not necessarily indicate the market efficiency. If the markets were efficient as per the EMH, then the prices of the stocks would indicate the actual information on the market and the stock predictions would prove simpler. Consideration of returns and value for the stock provides the investors with an accurate understanding of the stock though do not provide them with an accurate summary of an efficient market (Asness, Moskowitz & Pedersen, 2013, p.930). Predicting returns covers the understanding of the factors that drive the prices and the markets. Many that believe in market efficiencies believe that the prices that the securities indicate hold the intrinsic value of the stock. It is normally stated “efficient capital markets have no memory” indicating to the volatile nature of the markets (DeBondt & Thaler, 1989, p.189). The statement means that the stock markets are not as predictable as many believe. If the stock market prices were predictable, many investors would keep track of the stock and invest when the prices go low knowing when they get high and they sell to make huge returns. A number of unpredictable factors make the market difficult. These include uncertainties that affect markets or even normal market changes that affect the stock prices. A number of theories explain these earning aspects of companies ranging from general theory developed by Keynes and the theory of investment value. These theories relate with the actual gains that the company makes. Keynes theory explains that the prices of the stock depend on the daily fluctuations of the profits that the company makes while the theory of investment value indicate that the prices in the current market are considered affected by the current earning power of the company. The theory by Williams further suggests the ignoring factor that many technical analysts forget that is of the long run dividend powers to pay that also may have a hand in providing the market prices. Companies that issue dividend tend to have price fluctuations that only feature during the time the company is about to announce its results for a period with payable dividends hence affecting the market differently. These all indicate to the returns inability to reflect an efficient market. Returns only indicate the gains that the investors make on the counters in the market and little on the efficient market. The consideration of an efficient market would provide an easily predictable market that would indicate easy to investors and hence taking away the beauty of the stock market that lies in its unpredictable nature. Reference List Asness, C., Moskowitz, T., & Pedersen, l. (2013) Values and Momentum Everywhere, Journal of Finance, Vol. 68, No. 3,pp929-985. DeBondt, W. & Thaler R. (1989) Anomalies: A Mean-Reverting Walk Down Wall Street, Journal of Economic Perspectives, Vol. 3, No. 1, pp 189-202. Fama, E. (1998) Market Efficiency, long-term returns, and behavioral finance, Journal of Financial Economics, Vol. 49, pp283-306. Johnson, T. (2002) Rational Momentum Effects, Journal of Finance, Vol. 57, No. 2, pp.585-608. Kim, J., Shamsuddin, A., & Lim, K. (2011) Stock Return Predictability and the Adaptive Markets Hypothesis: Evidence from Century-Long U.S. Data, Journal of Empirical Finance, Vol. 18, No. 5, pp. 868-879. Malkiel, B. (2003) The efficient Market Hypothesis and its Critics, Journal of Economic Perspectives, Vol. 17, No. 1, pp 59-82 Read More