Tuesday, February 4, 2020
Calendar effects (seasonalities). January Effect , The Day of the Week Literature review
Calendar effects (seasonalities). January Effect , The Day of the Week Effect, The Holiday Effect - Literature review Example Literature Review For the day of the week effect in stock market returns, Gibbons & Hess (1981), Fama (1991), (Grossman and Stiglitz 1980)), French (1980)), Lakonishok and Levi (1982)), Rogalski (1984)) and Keim and Stambaugh (1984)), Harris (2002), Lakonishok and Smidt (1988), Allen and Karjalainen (1993) have exhibited the impression of this phenomenon. However, according to Kenourgios & Samitas (2008) latest global level studies indicate that this market irregularity is loosing its sheen to the extent of showing no symptoms of visibility or its effect has considerably reduced in developed stock markets since it was first registered in the 1980s (e.g., Chang et al., 1993; Schwert, 2001; Steeley, 2001; Kohers et al., 2004; Hui, 2005)). Generally, it is taken for granted that the apportioning of stock returns is the same for all days of a week but it is not that crucial an assumption for achieving market equilibrium. Empirical research indicates unequal stock returns on different day s of the week, particularly weekend effects on Monday returns. It could be because Mondayââ¬â¢s return is computed over three in stead of one day causing the mean and variance to be higher than other days, which could be approximately three times higher. Although Fama (1965)) has compared daily mean returns but he has found Mondayââ¬â¢s difference on stock returns to be 20% more than other daily returns, which is similar to what other researchers have focussed on (Gibbons & Hess, 1981). Background At the ground level, the theory of efficient capital markets is the same i.e. the theory of competitive equilibrium used on asset markets. It is based on the Ricardian principle of comparative advantage. The same notion in financial markets is applied with the only assumption of getting competitive advantage because of the gaps in information, not ââ¬Å"fully reflectedâ⬠in prices, thus, setting the basis for profitable trading rules (LeRoy, 1989). Fama (1991) has reviewed mark et efficiency literature by selecting the relevant research in the previous 20 years. He has taken the market efficiency hypothesis, which simply means that security prices are totally predictable as based on given information. It works on the assumption that information and the trading costs are mostly 0 (Grossman and Stiglitz 1980)). Another assumption of the efficiency hypothesis is that prices indicate information to the level where marginal benefits of accruing profits on the basis of information are less than the marginal cost (Jensen 1978)). There is so much opaqueness that one cannot measure market efficiency due to various versions of market efficiency to be reflected by going back on any type of efficiency hypothesis within the given information and the trading costs. There are other models that present a straightforward approach towards this issue. French (1980) also tested two models on stock returns as based on calendar time hypothesis and trading time hypothesis for a period between 1953 and 1977 for daily returns on Standards & Poorââ¬â¢s composite portfolio not matching with the models, indicating positive average return for the four days while negative return for Monday. Harris (2002) has studied weekly and intra-day designs in stock returns by employing transaction data for large and smaller firms. Findings indicate negative Monday close-to-close returns from the Friday close to Monday open for larger firms while for small firms it happens majorly the same for the whole of Monday trading.
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