LITERATURE REVIEW
2.2 Review of Theoretical Models
2.2.1 Stock Market Returns
and Wessels, 2010).
According to Allen, Brealey and Myers (2011), they claimed thata market is deemed to be efficient when the market is impossible to have a return that is higher than the market.
Market efficiency can be categorized into three stages, which are c, semi-strongform of market efficiency and strong forms of market efficiency,with the conditions of all available information is reflected in the stock price.
In weak form of market efficiency, stock prices reflect thefundamental information that relates to the historical stock price movements.There are lower possibilities for investors to make abnormal profit or return in the market as all the historical information is available and circulating in the market. Hence, surplusprofit might not be available if the market is in the status of weakly-efficient.
Semi-strongly efficient stock market prices reflect the fundamental information about historical stock prices as well as the current available information that is circulating in public. Current information could be proposal of merger and acquisitions, announcements of dividend pay-outs and others.
Strongly efficient market will reflect all possible informationregardless they are circulating in public or not. Strongly efficient market implies thatmispriced stocks are not feasible and it is not possible to have the opportunities to earn excess returnbecause trading on insider information has no contribution anymore (Malkiel, 2011).
However,some researchers did claim that it is still possible to have strongly efficient market as insider trading is not legal in the market (Schwert, 2003).
In an efficient market, apart from reflecting the insider and public
information on the stock prices, it is also related to other assumptions and financial models. Firstly, market efficiency will also be affected by the rationality of market players or investors. In fact,not all the trading is based on rational analysis but just an assumption made buy the investors.Nevertheless,there is argument claimed that this should not bring impacts to the stock prices as the probability of random trading is interrelated (Shleifer, 2000).
According to Goedhart et el., (2010), theystated that investors can be categorized into 3 group, which are traders, intrinsic value investorsand mechanical investors. The dissimilarity among them is the concept or basis of their investment or trading decision. Traders are using technical analysis, intrinsic value investors are using fundamental analysis and mechanical traders perform trades according to rules.
2.2.1.2 Random Walk Theory
The Random Walk Theory finds its origin in the early works of Bachelier back in 1900. Extended and translated into English by Cootner in 1964 this theory submits that stocks at the end of a certain time period largely show future prices. These seem to be generated by a random process and show independent (Gaussian or normal standard) distributions. Other chartist theories however share the common assumption that history repeats itself and therefore historical stock price behaviours can be used to predict a share’s price.
Brownian motion to build a mathematical model to explain price fluctuations on the stock market. Even though both tried to justify this theory empirically, they felt short as they only used cross-sectional data. In 1962, Moore analyzed eight shares from the U.S. Stock market (NYSE). They observed an approximately normal distribution;
however they acknowledged that most of the distributions were leptokurtic which weakens their findings. To provide more reliable facts, Fama et al, (1965) analyzed the whole Dow-Jones Industrial Average index (30 stocks).
The efficiency of information also plays a major role within this research area. If any information is distributed or accessible to/from each investor there would not be any fluctuation or variation in stock prices. Only when new information is created the market reacts (Fama et al, 1965). If the market (buyers and sellers) knows about a company`s future, this would already be reflected in the current stock price. As information is processed in different ways and there is existing disagreement about a company’s intrinsic value stock prices fluctuate randomly. Fama et al, (1965) calls it the market’s “noise” and forms a fundament for short-term behavioral models like the one of Barberis. According to Fama et al, (1965) this does not contradict the long-term market efficiency but underlines its power. One of the best established investment strategies, the long-term focused buy and hold approach, is based on this idea.
2.2.1.3 Modern Portfolio Model
In 1952, Harry Markowitz developed Modern portfolio model (MPT)
(Fabozzi, Gupta and Markowitz, 2002). Markowitz claims that the largest challenge for an investor is to discover the perfect combination of risky assets,stocks, in regards to expected return and variance of return.
A basic concept for perfect combination of stocks will be a portfolio that will generate highest return will not be generated with the portfolio with the lowest risk (variance). This concept assumes that greater expected return of a portfolio happens when investorsare likely to beargreater risk. In contrary, risk-averse investorswill be able to minimize the variance in exchange to a lower expected return.
Generally, MPT assumes that if investors are risk averse, they will only focus ononce off investment return when they are doing portfolios selection (Fama and French, 2003). Fama et al (2003) has confirmedthatholding constant expected return will minimize variance and holding constant variance will maximize expected return. Market participants can simplyformtheirfavored portfolio based on the formulation of an efficient frontier, depending on their risk appetites.
2.3.1.4 Capital Asset Pricing Model (CAPM)
Capital Asset Pricing Model (CAPM) is developed after HarryMarkowitz’s Modern Portfolio model (Fama et al, 2003). It supposes that investmentopportunity set is ageneral knowledge- prices reflection to the fresh informationso as to fall along the new trading
several market professionals in security markets.
CAPM adopted the assets pricing theory ofJohn Linther and William Sharpe (Fama et al, 2003). It is attractedby its pleasing predictions and simple logic about how risk measurement or assessment is done on the linkages between the risk and expected return.
Generally, the idea and concept behind this model is where market participants to be compensated in two approaches, which are time value of risk and money. Risk free rate (rf) is representing the time value of money and compensates the investors for their investments over a period of time. Additionally, time value for risk is representing the risk and calculates the amount of money that investors need to contribute for taking extra risks. This is calculated by taking a risk measure (beta) that compares the returns of the asset to the market for a certain period of time as well as to the market premium (Rm-rf).