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The efficient market hypothesis (EHM), which was developed from Eugene Fama’s Ph.D. dissertation, claims that, in a liquid market and at any given time, provision prices completely reflect all valid information. In addition, there are five effects, or market anomalies, that have implications for the efficient market hypothesis: post-earnings-announcement price drift effect, P/E effect, momentum effect, book-to-market effect, and small-firm effect. Both EMH and the five effects have a great influence on the performance of professional managers; thus, they should be reviewed in details.

The efficient market hypothesis has three degrees: weak, semi-strong, and strong. These degrees address the insertion of non-public data in market prices. The theory claims that, since marketing is efficient and current rates reflect all data, attempts to exceed the market are at most a game of eventuality rather than one of mastery.

The weak form of efficient market hypothesis supposes that current stock rates completely reflect all currently available valid market data. It claims that past rates and volume data are not connected with the future directing of security rates. It implies that excess returns cannot be obtained with the help of technical analysis.

The semi-strong form of efficient market hypothesis supposes that current stock rates react rapidly to the release of all new public data. It claims that security rates include accessible market and non-market public information. It implies that excess returns cannot be obtained with the help of fundamental analysis.

The strong form of efficient market hypothesis supposes that current stock rates completely reflect all public and private data. It claims that market, non-market, and inside data include the assurance rates and that no one has monopolistic admission to relevant data. It supposes a perfect market and assumes that excess returns are not possible to obtain consistently.

Two basic rules comprise the EMH. First, the efficient market hypothesis states that public data get reflected in asset rates immediately. Information that has to affect the future rates of any fiscal instrument will be referred to the asset rates today.

If a pharmaceutical organization now selling at $10 per share gets approbation for a new medicine that will provide the organization a value of $20 the next day, the price will grow to $20 instantly, not slowly over time. Due to the reason that acquisition of the stock with a rate below $20 will concede an immediate income, one can wait for market members to bid the rates up to $20 without delay.

Naturally, it is possible that the complete effect of the new data is not instantly obvious to all market members. In addition to this, it is likely that the exemplary sales and income cannot be prognosticated with any accuracy and that the worth of the discovery is susceptible to a wide variety of ratings. Some of the market members can vastly undervalue the importance of the newly approved medicine, while others can greatly overrate it.

Consequently, in a number of cases, the market can underreact to an auspicious part of news. However, in other cases, the market can overreact, and this is still far from clear whether regular overreaction or underreaction to news represents an arbitrage possibility, promising dealers extraordinary, risk-adjusted, and easy gains. It is this aspect of efficient market hypothesis that implies the second, and more basic, rule of the hypothesis: in an effective market, it is impossible to get above average income without taking on above common risk. For this statement, the five effects should be considered.

The overreaction hypothesis is a particular anomaly in the effective market. It has been observed by De Bondt and Thaler (1985). Their study indicates that, as a rule, the stock market overreacts to unsuspected events such as income announcements that are above its expectations. After this, they demonstrate that shares that experience the highest (or lowest) income in response to the case tend to underperform (or overperform) in the following period, thus “correcting” its mistake. The observers hypothesise that the cause of the overreaction is the market’s ineffective response to the income information. Similar conduct was observed by Brooks and Buckmaster (1980) who noticed that income deviated from a random walk after testing extremes and tended to return to the permanent mean.

An anomaly contrary to the overreaction assumption, which is called the under-reaction anomaly, has also been observed. It is described as the slow response of market members to new data such as income announcements, which constitute a first under-reaction that is corrected since the accumulative share returns tend to go adrift in the same direction as the initial income response for an essential period after the annunciation has been made (Ball & Brown, 1968; Choi & Kim, 2001; Hong & Stein, 1999). Therefore, the accumulative stock returns of organizations that announce their income higher (or lower) than expected tend to drift upwards (or downwards) for a period of time after the data has been given a public access. The phenomenon of under-reaction is commonly known as the post-earnings announcement drift anomaly.

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A basic rule of efficient markets is that any new information has to be reflected in stock prices almost immediately and the regulations should be fair regarding the new data received. Predictable samples, such as market under-reactions and overreactions and their respective following corrections, should not exist in an efficient market.

P/E effect is a phenomenon that occurs frequently and in which portfolios created by shares with low price-to-earnings rates make greater overall income than portfolios created by shares where the rates are higher in relation to the income per share. Portfolios comprising low P/E stocks frequently outperform portfolios including high P/E stocks. There is a hypothesis based on the fund asset pricing pattern and other patterns relating risk to refunds, stating that the reason for this is the greater risk of low P/E shares, and thus potentially greater refunds. In other words, when two stocks have the same refunds, then the one with the lower P/E rates is riskier; otherwise, the P/E ratio would be the same. It would be a very surprising and bothering conclusion, because analysis of P/E rates is such a simple process. Even though it can be possible to earn exceeding returns with the help of hard work and much discernment, it seems hardly probable that such a simplistic method is enough to generate exceeding returns.

In 1993, Jegadeesh and Titman gave a new point of view to the EMH by documenting that, over an interjacent period of three to twelve months, past winners, as a rule, continue to perform better than past losers. In other words, they showed the existence of momentum in share prices, meaning that shares with strong past efficiency continue to do well, while shares with poor past efficiency maintain poor performance. Considering the article by Jegadeesh and Titman (1993), numerous researchers have documented the momentum effect across various markets and time periods. Nevertheless, it still seems hard to explain why it happens. In fact, the observed momentum in share prices is mentioned as one of the most confusing anomalies in finance.

Some types of momentum have been documented in the literature, including industry momentum, income momentum, and price momentum. In a word, industry momentum is the anomaly when industries with high past efficiency continue to outperform industries with low past efficiency. Income momentum focuses on return driftings following good or bad income announcements, meaning that good announcement shares will outperform bad announcement shares in the post-announcement phase. And the last one, price momentum, is related to the phenomenon where shares with solid past returns continue to outperform stocks with poor past returns.

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In one word, momentum is related to positive autocorrelation in stock rates, where rates are drifting either up or down. In contrast, average reversion refers to the phenomenon where share prices expose negative autocorrelation, and therefore, after some period of deviation, return to their basic values. Consequently, both of the phenomena obviously conflict with the EMH and the Random Walk Model by pointing that it is possible to forecast the direction of future stock shares and thus identify lucrative market strategies, they also seem to conflict with each other. Concerning momentum, relational strength strategies, being strategies that purchase past winners and sell past losers, would appear lucrative. Nevertheless, in the case of average reversion, contrarian strategics, being strategics that purchase past losers and sell past winners, would be preferable. Ultimately, even though the momentum strategics can be realised by both private and institutional depositors, the strategics in the empirical sector is implemented in the way that seems most feasible and easiest to the private depositors.

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The next effect is the book-to-market one. It is one of the oldest effects that has been observed on fiscal markets. It compares book value of an organization to price of the shares - reverse of P/B ratio. The bigger the book-to-market rates are, the cheaper is the examined company. Book-to-Market was not even regarded as a market anomaly at the start of the 20th century when Ben Graham famously promoted its using. The rates lost some of their popularity when the EMT and CAPM became major Wall Street theories, but it regained its position after a few studies demonstrated the rationality of their use. This phenomenon is well-described in the classic Fama and French research paper (1993). Low value effect portfolios comprise long shares with the highest Book-to-Market rates and short shares with the lowest Book-to-Market rates. Nevertheless, the low value effect had essential declines with more than 50% drops in the 1930s. Value agent is still a solid performance supporter in long only portfolios. The only explanation is that depositors overreact to increasing aspects for rising stocks, and value stocks are thus undervalued. In accordance with some academics, the coefficient of market worth to book worth itself is a risk criterion, and thus, the larger refunds generated by poor MV/BV stocks are merely a compensation for the risk. Poor MV/BV stocks are frequently those experiencing some fiscal distress.

The following effect is a small-firm effect. It is the theory that holds that smaller organizations, or those firms with a small market plowback, outperform the larger firms. The theory also states that smaller firms have a greater amount of growth opportunities than larger firms. Moreover, small cap firms tend to have a more changeable business environment, and the correction of issues – for example, the correction of a funding shortage – may lead to a large cost appreciation. Ultimately, small cap shares tend to have lower share prices, which means that cost appreciations tend to be larger than those that are among large cap shares.

The concept of earning a premium for investments in smaller firms has been around since at least the early eighties, and probably even earlier. Over this time, the small-cap effect has become a significant reason for investors. It builds a key element for pricing shares by way of factor patterns, defines in part how capital is categorized, and, naturally, leads to the innovation and widespread using of small-cap capital.

However, seizing, finding, and even measuring the size reward – as being distinct from the market – have represented a problem for investors and investigators. Since its being discovered, the size effect has come under severe scrutiny, being challenged on plenty of fronts. Many people regard the historical record of the SCE being more sporadic and weaker than other effects, such as momentum and value, for example. More noticeably, size has had a durable weak period in the USA after its being documented and published. It has since been even more fragile internationally, enduring long time of poor efficiency and being focused on extreme, less-liquid microcap shares, with almost all of the information of a size premium being concentrated on merely one month, January.

Along with a steadier economic and statistical imporatance, the small-firm effect also gets far more successful when focused on quality. It is stable in relation to time and strong in regard to other criteria of size, which are not based on market funding (for instance, book value of equity; book value of assets; setting and equipment; and number of workers). Moreoevr, it is consistent across industries and regions, and even renewed in months other than January, while, at the same time, lowering the enormous and anomalous return in January. The long list of protests to the small-firm effect is removed one by one, when concntrating on quality/junk. The normal size effect, as it is commonly referred to in the literature, is experiencing a strong crosswind from poor-quality small stocks. Once the crosswind is removed, concentrating instead on quality-neutral shares, the small-share premium becomes strong. In its standard form, the small-firm effect is weak, approximating to the possibility of non-existent. Once settled for quality exhibition, it is real and effective.

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As it has been mentioned, the most confusing anomalies are small-firm, price-earnings, momentum, and market-to-book anomalies. Fama and French (1993) argue that anomalies referred to the CAPM are seized by the three-factor pattern. They base their pattern on the fact that medium surplus portfolio returns are perceptible to three factors that include: (1) surplus market portfolio return, (2) the variety between the surplus return on a portfolio of small shares and the surplus return on a portfolio of big share, and (3) the variety between the surplus return on a portfolio of high-book-to-market shares and the surplus return on a portfolio of low-book-to-market shares (high minus low, HML).

The pattern fits two additional risk agents tomarke the CAPM in order to show the return changes better and cure the anomalies of the CAPM. Fama and French (1996) state that the pattern captures a lot of the variations in the cross-section of medium stock returns and consumes most of the anomalies, which have bothered the CAPM. In the same research, they argue that the experiential success of their pattern shows that it is an equilibrium pricing pattern, a three-factor version of intertemporal CAPM or Ross’ arbitrage pricing theory.


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All in all, it should be emphasized that all of these factors and effects have a great impact on managers’ work. Naturally, there are exceptions, such as Peter Lynch, Warren Buffet, or John Templeton, but, as a rule, most managers do not choose anything better than the passive strategy. Consequently, if one wants to achieve a great goal in such sphere as investment, it is vital to learn the efficient market hypothesis as well as the five effects.



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