Finance&Business

Jan 14 2020

Emh stock price




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Emh stock price-2.3.2 EFFICIENT MARKET HYPOTHESIS (EMH) Efficient market is closely related to (the absence of) arbitrage. It might be defined as simply an ideal market without arbitrage, but there is much



2.3.2 EFFICIENT MARKET HYPOTHESIS (EMH)

Efficient market is closely related to (the absence of) arbitrage. It

might be defined as simply an ideal market without arbitrage, but there

is much more to it than that. Let us first ask what actually causes price

to change. The share price of a company may change due to its new

earnings report, due to new prognosis of the company performance, or

due to a new outlook for the industry trend. Macroeconomic and

political events, or simply gossip about a company’s management,

can also affect the stock price. All these events imply that new information

becomes available to markets. The Efficient Market Theory

states that financial markets are efficient because they instantly reflect

all new relevant information in asset prices. Efficient Market Hypothesis

(EMH) proposes the way to evaluate market efficiency. For

example, an investor in an efficient market should not expect earnings

above the market return while using technical analysis or fundamental

Three forms of EMH are discerned in modern economic literature.

In the ‘‘weak’’ form of EMH, current prices reflect all information on

past prices. Then the technical analysis seems to be helpless. In the

‘‘strong’’ form, prices instantly reflect not only public but also private

(insider) information. This implies that the fundamental analysis

(which is what the investment analysts do) is not useful either. The

compromise between the strong and weak forms yields the ‘‘semistrong’’

form of EMH according to which prices reflect all publicly

available information and the investment analysts play important role

in defining fair prices.

Two notions are important for EMH. The first notion is the

random walk, which will be formally defined in Section 5.1. In short,

market prices follow the random walk if their variations are random

and independent. Another notion is rational investors who immediately

incorporate new information into fair prices. The evolution of

the EMH paradigm, starting with Bachelier’s pioneering work on

random price behavior back in 1900 to the formal definition of

EMH by Fama in 1965 to the rigorous statistical analysis by Lo

and MacKinlay in the late 1980s, is well publicized [9–13]. If prices

follow the random walk, this is the sufficient condition for EMH.

However, as we shall discuss further, the pragmatic notion of market efficiency does not necessarily require prices to follow the random

Criticism ofEMHhas been conducted along two avenues. First, the

thorough theoretical analysis has resulted in rejection of the random

walk hypothesis for the weekly U.S. market returns during 1962–1986

[12]. Interestingly, similar analysis for the period of 1986–1996 shows

that the returns conform more closely to the random walk. As the

authors of this research, Lo and MacKinlay, suggest, one possible

reason for this trend is that several investment firms had implemented

statistical arbitrage trading strategies5 based on the market inefficiencies

that were revealed in early research. Execution of these strategies

could possibly eliminate some of the arbitrage opportunities.

Another reason for questioning EMH is that the notions of ‘‘fair

price’’ and ‘‘rational investors’’ do not stand criticism in the light of

the financial market booms and crashes. The ‘‘irrational exuberance’’

in 1999–2000 can hardly be attributed to rational behavior [10]. In

fact, empirical research in the new field ‘‘behavioral finance’’ demonstrates

that investor behavior often differs from rationality [14, 15].

Overconfidence, indecisiveness, overreaction, and a willingness to

gamble are among the psychological traits that do not fit rational

behavior. A widely popularized example of irrational human behavior

was described by Kahneman and Tversky [16]. While conducting

experiments with volunteers, they asked participants to make choices

in two different situations. First, participants with $1000 were given a

choice between: (a) gambling with a 50% chance of gaining $1000 and

a 50% chance of gaining nothing, or (b) a sure gain of $500. In the

second situation, participants with $2000 were given a choice between:

(a) a 50% chance of losing $1000 and a 50% of losing nothing,

and (b) a sure loss of $500. Thus, the option (b) in both situations

guaranteed a gain of $1500. Yet, the majority of participants chose

option (b) in the first situation and option (a) in the second one.

Hence, participants preferred sure yet smaller gains but were willing

to gamble in order to avoid sure loss.

Perhaps Keynes’ explanation that ‘‘animal spirits’’ govern investor

behavior is an exaggeration. Yet investors cannot be reduced to

completely rational machines either. Moreover, actions of different

investors, while seemingly rational, may significantly vary. In part,

this may be caused by different perceptions of market events and

trends (heterogeneous beliefs). In addition, investors may have different

resources for acquiring and processing new information. As a

result, the notion of so-called bounded rationality has become popular

in modern economic literature (see also Section 12.2).

Still the advocates of EMH do not give up. Malkiel offers the

following argument in the section ‘‘What do wemean by saying markets

are efficient’’ of his book ‘‘A Random Walk down Wall Street’’ [9]:

‘‘No one person or institution has yet to provide a long-term,

consistent record of finding risk-adjusted individual stock

trading opportunities, particularly if they pay taxes and

incur transactions costs.’’

Thus, polemics on EMH changes the discussion from whether

prices follow the random walk to the practical ability to consistently

‘‘beat the market.’’

Whatever experts say, the search of ideas yielding excess returns

never ends. In terms of the quantification level, three main directions

in the investment strategies may be discerned. First, there are qualitative

receipts such as ‘‘Dogs of the Dow’’ (buying 10 stocks of the Dow

Jones Industrial Average with highest dividend yield), ‘‘January

Effect’’ (stock returns are particularly high during the first two January

weeks), and others. These ideas are arguably not a reliable profit

Then there are relatively simple patterns of technical analysis, such as

‘‘channel,’’ ‘‘head and shoulders,’’ and so on (see, e.g., [7]). There has

been ongoing academic discussion on whether technical analysis is able

to yield persistent excess returns (see, e.g., [17–19] and references

therein). Finally, there are trading strategies based on sophisticated

statistical arbitrage. While several trading firms that employ these strategies

have proven to be profitable in some periods, little is known about

persistent efficiency of their proprietary strategies. Recent trends indicate

that some statistical arbitrage opportunities may be fading [20].

Nevertheless, one may expect that modern, extremely volatile markets

will always provide new occasions for aggressive arbitrageurs.

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