Investments: Assets, Equities, and Bonds - Essay Example

Efficient Markets

Introduction

Efficient market describes a market with big numbers of each individual and rational profit maximizing competing with one another to determine market values of each security. More so, each profit maximisers rational and individuals ties to predict future market values of each security where information becomes available to each participant. Therefore, in efficient market, actual price of a security determines the value of its intrinsic value at any time. Additionally, efficient market hypothesis markets describe the prices of stocks as well as the rational that fully reflect the available information (Fama, 1970, 383-417). But, according to behavioral finance this kind of efficient market cannot explain the observed anomalies. On the other hand, market anomalies describe the abnormality in smooth pattern of stock market as described by OpenUniversity (2016,n.p).

Thesis Statement: Investors should use efficient market hypothesis to gain important information on stocks to gain a competitive advantage.

Efficient market hypothesis remains one of the important paradigms of traditional finance theories. More so, efficient market refer to a market with big numbers of each individual and rational profit maximizing competing with one another to determine market values of each security. Additionally, the relevant information gets distributed investors. There exists three levels of market efficiency which includes weak form, semi-strong, as well as strong form as described by Ellerbroek (2015, 4-8). Firstly, weak form of market efficiency gets reflected in the recent stock prices as the stock prices move randomly while the prices become independent of one another. Therefore, in weak form market efficiency, no participant can predict the future of past information. Additionally, the prices reflect the entire past price as well as volume of data.

More so, the prices form the past changes unrelated to future changes in price. Also, in weak market efficiency, the implications for technical analysis that rely on the past history of prices fail to form a basis for future price changes. However, the market adjusts and incorporates the information full and fast on the basis of fundamental analysis or private information. Additionally, the violation of weak market efficiency result in violation of strong as well as semi-strong market efficiency forms since they build on each other to achieve the appropriate progress. Also, some violations of weak efficient market analysis include trading rules, calendar effects, technical strategies as well as autocorrelation anomalies. Moreover, weak form evidence gets tested by statistical tests for independence of stock price changes. If the tests show that independence exist, then trends in price changes do not exists. Another test includes specific trading rules after transaction costs.

Secondly, in semi-strong market efficiency, the current stock reflects past information as well as publicly information available. Therefore, no participants can derive any profits on the basis of fundamental analysis. Fundamental analysis describes the process of determining the intrinsic value of a stocked through analyzing attributes of a firm as well as the financial statements. More so, after the announcements of the new public information, the participants cannot act the new information and expect to earn risk on the adjusted returns. Additionally, semi-strong efficient market encompasses weak from efficient market as a subset. In contrary, semi-strong efficient market form gets tested by event analysis. In contrary, anomalies that violate the semi-strong form market efficiency entails the small firm effects, stocks with large dividends, value stock as well as performance of mutual funds. Additionally, the tests for semi-strong market efficiency includes the event studies, stock splits as well as accounting changes, announcements as well as initial public offerings as discussed by Silver, T. (2011, n.p).

Thirdly, in strong form efficient market, the prices reflect all the available information from the private, current as well as past sources. Additionally, no group of investors can earn abnormal rates of the return of participants using private as well as public information. More so, strong form efficient market encompasses the semi-strong as well as the weak forms of subsets. On the other hand, there exist some keys to testing the validity of the three form of market efficiency. One, for the efficient market not to exhibit abnormal returns, it must get achieved consistently as well as for an extended period of time over which excess returns get earned. Two, economically efficient markets states that assets should get priced so that the participants can fail to exploit discrepancies and earn abnormal returns transaction costs. In contrary, the tests performed on strong form market efficiency includes insider transactions which need to get reported publicly and test performance of groups with access to non-public information.

Anomalies refer to an abnormal or strange occurrence. More so, in technical terms, anomalies describe deviation from normal order conditions and it applies to any unexpected phenomena or fundamental fact. Therefore, anomalies reflect an inefficient market. Anomalies fall into three categories such as technical anomalies, calendar or seasonal anomalies and fundamental anomalies as described by (George & Elton, 2011, 10-22).

Fundamental Anomalies

According to Karz, (2010,n.p), fundamental analysis includes small cap effects as well as value anomalies. Under fundamental analysis, we have the following techniques.

Technical Anomalies

Technical analysis includes a number of analyzing strategies that forecast future prices of stocks. More so, it analyzes the future prices based on useful past information as well as past prices. Additionally, it uses approaches such as moving averages as well as resistance support. According to Bodie et al. (2007, 50), weak form efficient market prices reflected the past information and technical analysis does not apply. More so, the strategy relies on objective trading rules to establish when to sell or buy. However, some anomalies deviate from the findings of the following studies as described in the following table as described by (Farooq, 2012, 8).

Technical Anomaly

Description

Articles

Trading range break

Trading range break describes a technical analysis approach based on support level as well as resistance. The investor develops a signal when the prices reach the local maximum or resistance level. When an investor decides to sell under pressure, the pressure could lead to the break of the resistance level. Therefore, the break lead to a buying signal which gets created when prices reach the minimum price level or the support level. Therefore, the technical analysis argues that selling should take place when prices fall below trough while buying takes place when prices fall raise above last peak.

Josef (1992)

Brock (1992)

Moving Averages

In this approach, selling stock takes place when short period averages fall below the long period averages while buying takes place when short period averages rise over long period averages.

Josef (1992)

Brock (1992)

Testing of semi-strong form hypothesis is described below.

Event studies tests

Strategies and studies to predict future rates of returns using public information include cross-section distribution, series analysis of returns as well as the price for each stock as discussed by George & Elton (2001, 20-40). Examining the rate of price adjustment to particular important economic events is based on event studies. Additionally, a corollary approach tests the possibility of investing in security after the public announcement of an important activity as well as experience abnormal rates of return. Therefore, it’s impossible for investors to get risk-adjusted returns by investing after the public announcement of any relevant information as well as paying normal transaction costs. Therefore, to carry out the above tests, one needs to adjust the security’s rates of return for the rates of return of the period considered. To calculate the abnormal rate return one should subtract the market return from return for the individual security as follows. ARit = Rit-Rmt

ARit represents the abnormal rate of return during period t on security i

Rit represents the rate of return during period t on security i

Rmt represents the rate of return on a market index during period t

Another calculation entails using the expected rate of return on the sock instead of the market rate of return as follows.

The abnormal rate of return

ARit = Rit - E(Rit)

Where E(Rit) represents the rate of return during period t for stock i based on the stock’s normal relationship with the market as well as the market rate of return. For instance, the stock is 20% more volatile than the market; the market has a 10% rate of return. Therefore, one would expect the stock to the experience of 12% rate of return. More so, one would expect that if the return on the stock is 5%, then the expected abnormal rate of return would be -7%.

Therefore, both tests emphasize on the analysis of abnormal rates of return that deviate from long-term expectations. Additionally, the tests get adjusted for market rates of return as well as stock’s specific risks attributes during the period as discussed by Schultz (2003, 483-518)

Time series tests

Time series tests are based on the best efficient market estimates of future rates of return that will run the historical rates of returns. More so, the tests predict any public information that will provide a proof of best estimates of return for long or short term purposes. However, the studies prove that there exists a limited success in predicting short time returns while it shows analysis of long-term returns success.

Quarterly earning studies

Quarterly earnings studies try to answer the question of the possibility of predicting future. Returns for stock based on a publicly available quarterly earnings reports. Some

Standardized Unexpected Earnings (SUE) is used to normalize the difference between

Expected as well as actual earnings by the standard deviation of the regression estimate

used to derive expected earnings (Fama & French 1993, 50−56. )

SUEt = (Reported EPSt - Predicted EPSt) / (Standard Error of Estimate of Regression Equation)

Some authors associate Big SUEs with abnormal stock price moves. More so, they discovered that fifty-one percent of the price adjustment occurred after the earnings got announced.

Predicting cross-sectional returns

Studies establish the types of public information available to predict the future returns through the following ways. One, price earnings ratios and returns that overvalue the high growth of price earning stocks while it gives less value to the price earning stocks. Two, the size affects the low price earnings stock that had higher returns and low risks. Three, book value –market value ratio reveals a positive between the book value of a firm’s equity as well as returns to the market value of the equity.

Results from the studies

The results from the above studies entail the following. One, corporate events reveals that prices change in relation to the direction of the event if there exists a real economic impact. Two, unexpected world events and economic news argues that markets adjust to the global events quickly. Three, initial public offerings show that initial public offering is priced at sixteen percent meaning they seem underpriced. Four, exchange listings show that a firm’s increase in value does not get affected by the potential increase in the liquidity and exposure to a national exchange. Five, split stock studies reveal that stock splits on its own do not affect the returns as they fail to add to a company’s value. Therefore, event studies support that semi-strong form of efficient market as observed by Raj & Kumari (2006, 235-146).

Performance of Mutual Funds in the broader stock market

The performance of Mutual Funds in relation to the broader stock market remains the most important test of semi-strong market efficiency. Intelligent security analysts, as well as portfolio managers, run the mutual funds. More so, the professional use the most appropriate fundamental analysis tool. Additionally, the results from the performance evaluation of old mutual funds against a buy and hold approach tends to be highly dependent on the method used to calculate return risks hence difficult. Also, the mutual funds performance range between less than or equal to one of a buy and hold approach after the mutual funds expenses, as well as transaction costs, are included. Wall Street Journal runs a dart test that revealed that the eighteen analysts ended up with a higher portfolio value. Additionally, the analysts’ picks got below the dartboard approach.

Therefore, mutual funds fail to earn excess risks adjusted return because of market efficiency. However, mutual risks fail to achieve the required success due to the following reasons. Firstly, the analysts fail to conduct unbiased research, fails to give attention to details hence displays a eutrophic behavior in recommending the stock. Secondly, the investigators come from reputable careers which pay more than the mutual fund managers to make investments decisions. Therefore, most professionals prefer to stay in their careers instead of becoming mutual funds managers or salesmen. Thirdly, the management fails to give the relevant income statements, as well as balance sheets, result in poor accounting practices among the corporations. Therefore, it seems difficult to determine the primary cause of average performance of mutual result from the mutual fund efficiency or the mutual fund mediocrity. Additionally, the mutual fund fails to consistently outperform a buy and hold strategies as discussed by Ellerbroek, (2015,5-7).

In conclusion, investors should use the efficient market hypothesis to gain important information on stocks to gain a competitive advantage in the market. When investors get into a position to identify the appropriate information on time, they adjust the stocks prices to the new information. As a result, the investor gains a competitive advantage in the market. The weak form of market efficiency gets reflected in the recent stock prices as the stock prices move randomly while the prices become independent of one another. The violation of weak market efficiency results in a violation of strong as well as semi-strong market efficiency forms since they build on each other to achieve the appropriate progress. Also, some violations of weak efficient market analysis include trading rules, calendar effects, technical strategies as well as autocorrelation anomalies. Semi-strong market efficiency, the current stock reflects past information as well as publicly information available. Therefore, no participants can derive any profits on the basis of fundamental analysis. In contrary, anomalies that violate the semi-strong form market efficiency entails the small firm effects, stocks with significant dividends, value stock as well as the performance of mutual funds. Finally, strong form efficient market, the prices reflect all the available information from the private, current as well as past sources. Additionally, no group of investors can earn abnormal rates of the return of participants using private as well as public information. More so, strong form efficient market encompasses the semi-strong as well as the weak forms of subsets.